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Characterization and Simulation of Material Distribution
and Fiber Orientation in Sandwich Injection Molded Parts
Von der Fakultät für Maschinenbau der
Technischen Universität Chemnitz
genehmigte
Dissertation
zur Erlangung des akademischen Grades
Doktor-Ingenieur (Dr.-Ing.)
vorgelegt
von M. Eng. Somjate Patcharaphun
geboren am 25.12.1972 in Bangkok, Thailand
Gutachter: Prof. Dr.-Ing. G. Mennig
Prof. Dr.-Ing. J. Wortberg
Prof. Dr.-Ing. Habil. B. Wielage
Tag der Einreichung: 21.05.2006
Tag der Verteidigung: 29.10.2006
URL: http://archiv.tu-chemnitz.de/pub/2006/0184
ISBN: 3-939382-04-3 (978-3-939382-04-1)
Bibliographic Description
Author: Patcharaphun, Somjate
Topic: Characterization and Simulation of Material Distribution and Fiber Orientation in
Sandwich Injection Molded Parts
A Dissertation submitted to the Faculty of Mechanical Engineering, Institute of Mechanical and
Plastics Engineering, Chemnitz University of Technology, 2006.
133 Pages, 69 Figures, 14 Tables, 144 References
Abstract
In this work, the material distribution, structure of fiber orientation and fiber attrition in
sandwich and push-pull injection molded short fiber composites are investigated, regarding the
effect of fiber content and processing parameters, given its direct relevance to mechanical
properties. The prediction of the tensile strength of conventional, sandwich and push-pull
injection molded short fiber composites are derived by an analytical method of modified rule of
mixtures as a function of the area fraction between skin and core layers. The effects of fiber
length and fiber orientation on the tensile strength are studied in detail. Modeling of the
specialized injection molding processes have been developed and performed with the simulation
program in order to predict the material distribution and the fiber orientation state. The second-
order orientation tensor ( ) approach is used to describe and calculate the local fiber
orientation state. The accuracy of the model prediction is verified by comparing with
corresponding experimental measurements to gain a further basic understanding of the melt flow
induced fiber orientation during sandwich and push-pull injection molding processes.
11a
Key words: Sandwich injection molding, Push-Pull injection molding, Fiber orientation
distribution, Fiber length distribution, Material distribution, Mechanical properties, Numerical
simulation.
Acknowledgements
This work is based on research conducted between March 2003 and April 2006 at the Institute of
Mechanical and Plastics Engineering at the University of Chemnitz. A number of people have
contributed to the completion of this thesis, and deserve to be thanked.
First and foremost, I would like to express my sincere gratitude to my supervisor, Prof. Dr.-Ing.
Günter Mennig for his invaluable guidance and encouragement throughout my studies. His
support during my pursuit of the doctor degree will always be appreciated.
Special thanks to Dr.-Ing. Hannes Michael for his kindness and encouragement. I enjoyed the
many hours of lively exchanges (technical or not) that we had and look forward to future
collaborations.
I would like to express my thanks to Dipl.-Ing. Helmut Püschner, and other colleagues at the
laboratory, who provided invaluable support concerning the experimental part. Thanks also go to
M.Tech. Kaushik Banik, M.Sc. Bin Zhang, Loic Bouteruche and Anne Hewitson, for interesting
discussions, many valuable experimental data, and great friendships.
I wish to extend my thanks to TARGOR GmbH, BUNA GmbH, BASF AG, and BAYER GmbH,
Germany for the cost free supply of materials. Financial support from the Faculty of Engineering,
Kasetsart University, Thailand is gratefully acknowledged.
Most importantly, my deepest thanks go to my parents, my sisters, and my wife for their
dedication and inspiration that enabled me to reach this milestone in my life. Thank you for
keeping me afloat when I was down and thank you, by always being there when I needed you,
for reminding me of the goodness of life.
Chemnitz, 2006 Somjate Patcharaphun
Contents
Acknowledgements
Bibliographic Description
Nomenclature V 1. Introduction 1
1.1 Conventional injection molding process 1
1.2 Two-component injection molding process 3
1.2.1 Co-injection (Sandwich) molding 3
1.2.2 Gas- and Water-assisted injection molding 5
1.2.3 Overmolding 7
1.3 Specialized injection molding techniques for enhancing
properties of thermoplastics and composites 7
1.3.1 Multiple live-feed injection molding 8
1.3.2 Push-pull processing 9
1.3.3 Sequential injection molding 10
1.4 Simulation of the injection molding and specialized processes 11
1.4.1 Simulation of the conventional injection molding process 11
1.4.2 Simulation of some specialized injection molding processes 13
1.5 Research objectives 15
1.6 Outline of the thesis 16
Contents II
2. Molding of Short Fiber Reinforced Composites 17
2.1 Rheology of short fiber composites 18
2.2 Microstructure of injection molded short fiber composites 20
2.2.1 Fiber orientation 20
2.2.2 Fiber attrition during molding 21
2.3 Mechanical properties 23
2.4 Predictive methods of tensile strength for short fiber composites 25
2.4.1 Modified rule of mixtures (MROM) 26
2.4.2 Area fraction method 28
3. Modeling of the Injection Molding Process 34
3.1 Governing equations 34
3.2 Predicting fiber orientation 37
3.2.1 Characterizing orientation 38
3.2.2 Flow-induced fiber orientation 40
3.2.3 Numerical simulation of fiber orientation for injection molding 42
4. Experimental and Simulation Procedures 43
4.1 Materials and processing conditions 43
4.1.1 Sandwich injection molding 43
4.1.2 Push-pull injection molding 46
4.2 Microstructure analyses 48
4.3.1 Skin/core material distribution 48
4.3.2 Fiber orientation analysis 49
4.3.3 Fiber length analysis (Fiber attrition) 51
4.3 Mechanical testing 52
4.4 Process simulation 53
4.4.1 Pre-processing 53
Contents
III
4.4.2 Simulation approach 55
4.4.2.1 Simulation of skin/core material distribution
in sandwich injection molding 55
4.4.2.2 Simulation of 3-D fiber orientation distribution
in sandwich and push-pull injection moldings 56
5. Experimental Results and Discussion 61
5.1 Comparison between conventional and sandwich injection moldings 61
5.1.1 Fiber orientation distribution 61
5.1.2 Fiber length distribution (Fiber attrition) 66
5.1.3 Mechanical properties 68
5.2 Comparison between conventional and push-pull injection moldings 70
5.2.1 Geometry of weldlines 70
5.2.2 Fiber orientation in weldline areas 71
5.2.3 Effects of holding pressure difference and fiber concentration
on penetration length of weldline 76
5.2.4 Fiber length distribution in weldline areas 79
5.2.5 Weldline strength 82
5.3 Prediction of tensile strength for short fiber reinforced composites 84
6. Comparison between Simulation and Experiment 89
6.1 Sandwich injection molding 89
6.1.1 Effect of skin/core volume fraction on the skin/core
material distribution 89
6.1.2 Effect of processing parameters on the skin/core material
distribution 92
6.1.2.1 Effect of skin and core melt temperatures 92
6.1.2.2 Effect of skin and core injection flow rates 94
6.1.2.3 Effect of mold temperature 98
Contents IV
6.1.3 Effect of glass fiber content on the skin/core material distribution 99
6.1.4 Case study 101
6.2 Simulation of fiber orientation in sandwich injection molding 104
6.3 Simulation of fiber orientation in push-pull injection molding 111
7. Conclusions 115
8. References 119
9. Curriculum Vitae 137
Nomenclature
Symbol Meaning Unit
----------------------------------------------------------------------------------------------------------------
CUσ Ultimate strength of the composite MPa
fσ Ultimate strength of the fiber MPa
fV Volume fraction of the fiber -
mV Volume fraction of the matrix -
mσ Stress developed in the matrix MPa
0f Fiber orientation efficiency factor -
lf Fiber length efficiency factor -
na Proportion of fibers making an angle nϕ with
respect to the applied load or flow direction -
l Fiber length mμ
cl Critical fiber length mμ
d Diameter of fiber mμ
τ Interfacial shear strength between fiber and matrix MPa
mτ Shear strength of the matrix MPa
CF Total load sustained by the composite N
LF Load carried by longitudinal fibers N
TF Load carried by transverse (or random) fibers N
C
L
AA Area fraction between the skin region and the
cross-sectional area of specimen -
Nomenclature
VI
Symbol Meaning Unit
----------------------------------------------------------------------------------------------------------------
C
T
AA Area fraction between the core region and the
cross-sectional area of specimen -
ULσ Ultimate tensile strength of the skin material MPa
UTσ Ultimate tensile strength of the core material MPa
skinf0 Fiber orientation efficiency factors for the skin layer -
coref0 Fiber orientation efficiency factors for the core layer -
skinA Cross-sectional area of skin material 2mm
coreA Cross-sectional area of core material 2mm
ρ Density 3/ mkg
P Pressure Pa
pC Specific heat at constant volume 11.. −− KkgJ
T Temperature °C
v Specific volume kgm /3
•
S Rate of heat generation due to chemical reaction 3/ mW
u Velocity vector -
g Body force vector -
q Heat flux vector -
∇ Gradient operator -
tDD Substantial derivative -
τ Extra stress tensor -
η Non-Newtonian viscosity sPa.
γ& Strain rate tensor -
k Heat conduction coefficient -
I Identity matrix -
α Compressibility coefficient -
Nomenclature
VII
Symbol Meaning Unit
----------------------------------------------------------------------------------------------------------------
β Thermal expansion coefficient -
gh Melt-mold heat transfer coefficient -
( )φθψ , Orientation distribution function -
ija Second order orientation tensor -
ijkla Fourth order orientation tensor -
λ Shape factor of particle -
er Aspect ratio of the ellipsoid -
IC Fiber interaction coefficient -
bδ Thickness fraction of the core material -
0Lxi Measured distance ratio between length of
measurement and total length of specimen -
iϕ Angle between the individual fiber and the local
flow direction °
iNϕ Number of fibers with a certain angle to the local
flow direction -
lΔ% Percent difference between the number average
fiber length inside the granules and the overall glass
fiber length inside the molded part %
Gl Average fiber length inside the granules mμ
jl Local fiber length inside the individual layers of
sectioned part mμ
1. Introduction
1.1 Conventional injection molding process
Injection molding process is one of the most widely used operations in the polymer
processing industry. It is characterized by high production rate, high automation, and accurate
dimensional precision. Products ranging from as small as plastic gears to as large as
automobile bumpers can be injection molded. Injection molding process is accomplished in
an injection molding machine (Figure 1.1) which basically consists of two essential
components; the injection unit and the clamping unit. The function of the former is to melt
the polymer and inject it into the mold cavity, whereas the clamping unit holds the mold,
opens and closes it automatically, and ejects the finished products.
Figure 1.1 Schematic drawing of a typical injection molding machine. [1]
Introduction 2
The most common type of injection molding machine is the in-line reciprocating screw type.
The screw both rotates and undergoes axial reciprocating motion. When the screw rotates, it
acts like a screw extruder, melting and pumping the polymer. When it moves axially, it acts
like an injection plunger, pushing the polymer melt into the mold cavity. The screw is
generally driven by a hydraulic motor and its axial motion is activated and controlled by
hydraulic system. The raw material is supplied to the injection molding machine through the
feed hopper, which is located on top of the injection unit. The screw takes in the material and
conveys it to the screw tip. On its way, the plastic passes through heated barrel zones, while
the rotation of the screw results in a continuous rearrangement of the plastic material in the
flights of the screw. Shear and heating from the barrel wall cause a largely homogeneous
heating of the material. The conveying action of the screw builds up the pressure in front of
the tip. This pressure pushes back the screw. As soon as there is enough supply of melt in
front of the screw, the screw moves forward to inject the molten material into the mold cavity.
The injection molding process can be subdivided into four stages: (a) injection, (b) packing,
(c) cooling, and (d) ejection. The cycle begins when the mold closes, followed by the
injection of the polymer into the mold cavity. Once the cavity is completely filled, a holding
pressure is maintained to compensate for material shrinkage. As soon as the gate is
completely frozen, no more material can be injected and, the packing pressure is released and
the screw turns, feeding the next shot to the front of the screw. When the part is sufficiently
cool, the mold opens and the part can be taken out for further cooling to the ambient
temperature.
Introduction
3
1.2 Two-component injection molding processes
During the past two decades, numerous attempts have been made to develop injection
molding process to produce products with special design features and properties. Two
component injection molding being an alternative process derived from conventional
injection molding has created a new era for additional applications, more design freedom, and
special structural features. These efforts have resulted in a number of processes, including:
• Co-injection (Sandwich) molding
• Gas- and Water-assisted injection molding (GAIM and WAIM)
• Overmolding
• Further two-component injection methods e.g. Insert molding and Rotating mold
techniques are beyond the scope of this section
1.2.1 Co-injection (Sandwich) molding
Sandwich injection molding is an extension of the standard injection molding technology
which allows for two components to be sequentially injected into the mold in order to
fabricate products with a layered structure. This processing technology was first invented by
Garner and Oxley of ICI [2]. Figure 1.2 shows a schematic principle of the sandwich
injection molding process. The formation of the skin and the core structure can be explained
by the molding process. A given percentage of the skin material is first injected into the
cavity to form the skin layer. As the fastest material in the center of the flow reaches the flow
front, it splits to the outer wall of the mold and freezes forming a frozen layer or skin layer.
This is called “Fountain flow” as schematically illustrated in Figure 1.3. Prior to the skin
material’s reaching the end of the cavity, the second material is injected to form the core.
This core material develops a second flow front pushing the skin material ahead of it until the
cavity is nearly filled and finally a much smaller amount of the skin material is injected to
seal the gate. The last injection of skin material is important to clean all core material out of
the gate area and ensure that no core material will be injected into the next part during the
initial skin material injection.
Introduction 4
A
B B
B
A
A
B
(1) (2)
(3) (4)
A
Figure 1.2 The sandwich injection molding process works by first injecting the skin material
(1, 2) then switching to the core material (3). A small amount of skin material can seal the
gate to purge the core material away from the sprue (4).
Mold Wall
Fountain Flow
Skin MaterialCore Material
Solidified Skin Layer
Solidified Skin Layer
Wal
l Thi
ckne
ss
Melt Front
Flow Direction
Figure 1.3 Schematic of polymer melt flow profile across the thickness during sandwich
injection molding process.
Introduction
5
The resulting skin/core geometry of sandwich molded parts provides a number of advantages
because the different material properties can be incorporated into the same part, as
demonstrated in Figure 1.4. It is often desirable for the skin material to have a superior
appearance, while the strength and rigidity of the part is strongly dependent upon the core
material [3-5]. Typically, the core material will be less costly than the skin material, which
can yield potential cost savings. This is often achieved by using recycled material as the core.
Sandwich injection also exploits to use a foam core. In this case, large parts with hard and
glossy surfaces can be molded without the need for high clamping forces since shrinkage is
compensated by the expansion of the core material. In applications, where thin-walled
products are more suitable, low weight, high stiffness products with reinforcing ribs can be
molded economically [6-7].
Skin material
Core material Skin material
Core material
Figure 1.4 Sandwich injection moldings. [5]
1.2.2 Gas and Water-assisted injection molding
Gas-assisted injection molding (GAIM) is an important variant of the traditional technology
for injection molding of thermoplastics. In the simplest terms, gas-assisted molding process
begins like any conventional injection molding process with the injection of polymer melt
into a cavity. Only a partial volume of melt is injected and a short shot is purposely produced
(see Figure 1.5). At the end of the polymer injection stage, compressed gas, usually nitrogen
(due to its relative inertness and availability) is injected through the central core of the melt
similar to sandwich injection molding. The gas drives the molten polymer further into the
mold, until it is filled completely. The penetrating gas, acting now as the core material, leaves
Introduction 6
a polymer layer at the mold wall, yielding a product with a polymer skin and a hollow core.
The gas can either be injected through a needle in the nozzle, or directly into the mold
through separate gas injection needles. After the mold has been entirely filled, gas is used to
transmit the packing pressure to the polymer that is being cooled. Any shrinkage of the
polymer material near the gas channel is compensated for by an enlargement of the gas core.
Once all polymer material has solidified, the gas pressure is released. The product is then
further cooled until it has retained sufficient rigidity to be ejected from the mold. The most
important characteristic of GAIM is the fact that the pressure drop in the gas core is
negligibly small compared to the pressure drop in an equivalent molten polymer.
Consequently, the pressure can be considered constant throughout the gas core, which
accounts for most of the advantages of GAIM, such as reduction of raw material, weight of
product, cycle time, clamping force, sink marks and residual stresses, and enhancement of
design possibilities [1, 8-10].
P = 0P = 0
(1) (2)(2)
(3) (4)
Vented cavityVented cavity
Figure 1.5 Schematic showing the various stages of the gas assisted injection molding process:
(1) Melt injection; (2) Gas injection; (3) Packing phase; (4) Part ejection. [8]
Water-assisted injection molding (WAIM) appears at the beginning of the 70s but its real
development started at the Institute für Kunststoffverarbeitung (IKV), a plastic processing
development center in Germany, in 1998. This process is similar to GAIM except that it uses
water instead of nitrogen. The aim of developing WAIM is to reduce cooling cycle times in
the production of hollow or partly hollow parts [11].
Introduction
7
1.2.3 Overmolding
The overmolding process is a versatile and increasingly popular injection molding process
that provides increased design flexibility for making multi-color or multi-functional products
at reduced cost. This technique permits one-step joining of two or more polymers (e.g.
rigid/flexible or rigid/rigid) into parts, which do not require any further finishing operations
[12-13]. Besides the economical advantages, the process offers the possibility of obtaining a
broad range of mechanical properties of the end products [14-15]. The typical applications of
the overmolding process are the combination of multi-colored areas within one part and the
soft-touch applications (e.g. handles). For instance, two-component plastic parts can be
produced by a two-component injection molding machine, which introduces sequentially
different polymers into a special mold through separate runner systems. After molding the
preform of the first component, the cavity part for the second component is activated by
removing a metal core (core back mold) or opening the mold and transporting the preform
into a second cavity (e.g. rotating mold base). The second polymer is then delivered by the
second injection unit into the newly formed cavity through its independent runner system and
the final part is ejected after packing and cooling phases. This method is sometimes referred
to as in-mold assembly, since the resulting part effectively acts as an assembly of two
materials rather than as a layered structure.
1.3 Specialized injection molding techniques for enhancing properties of
thermoplastics and composites
Defects such as weldlines, sink marks, and warpage are caused by melt fronts collision,
unbalanced flow, uneven cooling and non-uniform internal stress. Varying the processing
parameters can result in the modification of the molded part outlook, physical and mechanical
properties [1, 8, 16]. The modifications, however, are often slight and not quantified, and they
also rely upon the expertise of the operator who uses his experience and art to determine the
processing parameters. During the last decade, several techniques have been developed using
different approaches in order to improve the molding properties, e.g. weldline strength, by
controlling the melt flow pattern of the polymer as it is being shaped [17-19]. This concept
has been applied to a wide range of thermoplastic matrix composites especially with glass-
Introduction 8
fiber reinforced thermoplastics [20-25]. There have been many such improvements, but three
in particular stand out. The first, multiple live-feed injection molding, auxiliary equipment is
incorporated into the standard molding machine. For two others, push-pull processing and
sequential injection molding, require special molding machine and modified tooling for
optimal success.
1.3.1 Multiple live-feed injection molding
The multiple live-feed injection molding process, is also known as Shear Controlled
Orientation Injection Molding (SCORIM), developed at Brunel University, and licensed by
British Technology Group [26]. This process achieves significant improvement and control
over part properties by using a special injection head that splits the melt flow in the mold into
two streams (see Figure 1.6). Once the mold is filled or during the packing stage, the multi-
live feed system’s hydraulic pistons begin moving forward and backward in an alternating
fashion. As one live feed piston pushes downward, it forces melt through the runner and
cavity up into the second live feed cylinder. The process then reverses, and the melt flows in
the opposite direction. The principle advantages of the process are; enhanced and controlled
orientation of fiber or flake fillers, significant reduction of weldline effects and controlled
modification of the microstructure of injection molded unfilled plastics, especially in liquid
crystal polymers (LCPs) [20-21, 27].
Wel
dlin
eW
eldl
ine
Conventional injection unit
Hydraulic cylinders and pistons
Runner system
Multiple live-feedprocessing head
Figure 1.6 Schematic of the multiple live-feed injection molding process. [8]
Introduction
9
1.3.2 Push-pull processing
The push-pull injection molding process is a melt oscillation technique, which is very similar
to SCROIM. It was originally unveiled by Klöckner Ferromatik Desma at the K’89 show. As
shown in Figure 1.7, the push-pull injection molding system includes two injection units and
a two gate mold. The cavity is firstly filled simultaneously by the melt from both the units via
the two separate gates. After the two melt fronts meet, the weldline is formed and the filling
phase is subsequently switched to the holding phase. The material solidifies starting at the
cavity wall but there is still molten core and then the first push-pull stroke begins. The control
software program allows the definition of several holding pressures for one stroke from either
the first or the second injection unit. From one of the injection units, polymer melt is pressed
into the cavity resulting in the molten core being pushed through the gate back into the other
injection unit and thus the geometry of weldline is deformed to a tongue shape. As the
material flows back and forth through the mold, molecular orientation is continuously created
and subsequently frozen in as the material solidifies from the outer layers toward the hot core.
By keeping the molten polymer in laminar motion during solidification, the molded parts
acquire an oriented structure throughout the volume. If the mold is complex and the melt has
to flow around obstacles, the motion will create better mixing in the area behind the obstacles
and reduce the weakening effect of the weldline by dispersing them throughout the part and
eliminates void, cracks, and micro-porosities in large cross-section molding. The number of
strokes can be selected by taking into account the part’s thickness. When all the strokes are
completed, cooling phase follows. As the thickness of frozen layer increases with the number
of strokes within the holding time, the total cycle time is not notably increased as compared
to conventional injection molding [23].
Secondary injection unitPrimary injection unit
Primary runner Overflow runner
Multigated mold
Figure 1.7 Schematic principle of push-pull injection molding process. [8]
Introduction 10
1.3.3 Sequential injection molding
Sequential injection molding is an increasingly used manufacturing processing technique
presenting the advantages over traditional injection molding. The process is generally used in
large parts, which are difficult to pack from one central area. Sequential valve gating is used
to control the filling of parts and each valve gate is independently opened and closed at a pre-
determined event (time, screw position, cavity pressure, etc.) providing complete control of
cavity fill. This technique can minimize the pressure loss in the system and also can be used
to control the location of weldline, as illustrated in Figure 1.8, in order to ensure that the
weld is positioned away from the critical area, and thus improving the product’s performance
[24, 25].
Resultant Part
a) Classical Weldline
b) Middle Disturbance
c) Side Disturbance
Figure 1.8 Schematic illustration of sequential injection molding (experimental mold,
developed at TU Chemnitz): Filling study by sequentially opening and closing the valve gates.
[24, 25]
Introduction
11
1.4 Simulation of the injection molding and specialized processes
1.4.1 Simulation of the conventional injection molding process
There are several milestones in the history of Computer-Aided Engineering (CAE). The
analysis of mold filling in injection molding started with the work of Spencer and Gilmore
[28] in the early 1950’s. They employed an empirical equation for capillary flow and coupled
it with a quasi steady-state approximation to calculate the filling time. Since then, different
methods have been proposed to describe the molding cycle with varying degrees of
complexity. One-dimensional rectangular flow was proposed by Ballman et al. [29] and
Staub [30]. Harry and Parrot [31] considered a one-dimensional quasi-steady state flow
analysis coupled with an energy balance equation. Williams and Lord [32] made a significant
contribution by considering all the components of a one-dimensional non-isothermal flow. A
similar model was presented by Thienel and Menges [33] using a different solution technique.
In order to study a more representative one-dimensional flow, a number of analyses were
carried out on the radial filling of a center gated disc mold. Kamal and Kenig [34-35]
proposed an integrated mathematical treatment of the filling, packing, and cooling stages of
the injection molding cycle. Similar simulations were carried out by Berger and Gogos [36],
and Wu et al. [37]. However, it was not until the 1970’s when the development and
application of computer simulations to injection molding intensified. In particular, Stevenson
and co-workers [38] analyzed one-dimensional flow in a center-gated disc. Lord and
Williams [39] studied the one-dimensional filling behavior in rectangular cavity geometry.
Nunn and Fenner [40] modeled one-dimensional tubular flow of polymer melts, which was
later extended by Hieber et al. [41] to simulate the polymer flow in a non-circular tube under
non-isothermal condition.
The general characteristics of injection molding are that the part thickness is much smaller
than the overall part dimension and the polymer melts are highly viscous due to their long
molecular chain structure. As a result, the ratio of inertia force to the viscous forces (as
characterized by the dimensionless Reynolds number) is in the order of 10-3 -10-4. This makes
the Hele-Shaw flow formulation [42], which is based on the creeping-flow lubrication model,
an appropriate candidate for analyzing the flow in typical injection molded parts. In addition
to neglecting the fluid inertia, the Hele-Shaw flow formulation also omits calculation of the
Introduction 12
velocity component and thermal convection in the gapwise direction. Compared with heat
conduction in the gapwise direction, heat conduction in the planar directions is also neglected.
Other commonly adopted simplifications include neglecting the transverse flow at the melt
front region (the fountain flow behavior), viscous convection (drag force) and heat
conduction on the lateral wall surfaces, and mapping of gapwise solutions at the flow
junctions and where the wall thickness changes. Accordingly, the usage of computational
resources including computational storage and CPU time can be reduced considerably
compared with the case of a full three-dimensional simulation. In this approach, three-
dimensional geometry is represented with one-dimensional tubular elements and two-
dimensional triangular thin-shell elements for which the wall thickness is implicitly specified
as an attribute; i.e. a “mid-plane” mesh has to be created either from collapsed or from an
existing three-dimensional CAD design model. Those one- and two-dimensional elements are
numerically divided into several “layers” (typically 8-20) in the gapwise direction for details
of the variables under consideration. While the governing equations of mold filling and
packing are being solved by the finite-element method (FEM), finite-difference method
(FDM) is applied in the gapwise direction and the temporal domain. By doing so, the
transient behavior and variation of the variables in the gapwise direction can be captured.
Since the gapwise velocity component is not calculated and the mesh model only represents
the “shape” of the part geometry, the Hele-Shaw flow formulation is sometimes called 2.5-
dimensional (2.5-D) simulation. Although the governing equations and the geometry are
simplified, the Hele-Shaw flow model became the standard numerical framework for various
commercial software packages and research codes [43-45] and has been extended or
incorporated by other researchers [46-49] e.g. simulation of polymer melt flow during the
filling and packing phase, fiber orientation, shrinkage and warpage. However, the Hele-Shaw
flow formulation has its limitations owing to the inherent creeping-flow and thin-wall
assumptions. For example, the shell element employed in the Hele-Shaw model needs the
construction of the mid-plane, which is time-consuming [50]. Furthermore, it cannot
accurately model the three-dimensional flow behaviors, particularly important when molding
with fiber reinforced systems [51], within thick and complex geometries or at the melt fronts
(fountain flows), regions where the part thickness changes abruptly or separate melt fronts
meet (weldlines), and regions around special part features such as bosses, corners, and/or ribs
as compared to those obtained by the three-dimensional (3-D) simulation model [50, 52-54].
Introduction
13
The interest in 3-D simulation of injection molding has increased tremendously in the past
few years. Several commercial and research-oriented 3-D CAE simulation programs for
injection molding have been developed [52-53]. In particular, Hetu et al. [52] developed a 3-
D finite-element program for predicting the velocity and pressure fields governed by
generalized Stokes equations. In addition to the temperature field, they also solved the
position of flow fronts using the pseudo-concentration method. Zachert and Michaeli [53]
analyzed polymer flow at the region of a sudden thickness change during injection molding
using both a Hele-Shaw flow formulation and a 3-D approach. Chang and Yang [54]
developed the numerical simulation for 3-D mold filling based on an implicit finite-volume
method (FVM). Their work was later commercialized and extended to cover various stages in
injection molding and special molding processes. Pichelin and Coupez [55] analyzed the 3-D
mold filling of an incompressible fluid and the shape of the fountain flow front using an
implicit discontinuous Taylor-Galerkin scheme. Han et al. [56] predicted the fluid flow
advancements and pressure variation in the microchip encapsulation process using a 3-D
FEM based on a generalized Hele-Shaw formulation. By treating the polymer density as a
function of pressure and temperature, Haagh et al. [57] incorporated the compressibility of
the polymer melt in a 3-D mold filling process. Rajupalem et al. [58] and Talwar et al. [59]
used an equal-order velocity-pressure formulation to solve the Navier-Stokes equations in
their 3-D simulation of mold filling/packing phases.
1.4.2 Simulation of some specialized injection molding processes
Over recent years, as for the conventional injection molding, the numerical simulations of co-
injection, gas-assisted injection, SCORIM, and push-pull processing are mostly based on the
thin wall, Hele-Shaw approximation. Simulation of the sequential sandwich injection
molding process was first carried out by Turng and Wang [60] in order to predict the skin and
core melt front progression and the distribution of the two layers by calculating the residence
time of the particles that enter the mold cavity. Schlatter et al. [61-62] used a special transport
equation to characterize the displacement of the interface between skin and core for the
sequential injection of polymers. Visualization and simulation of the sandwich mold filling
process have been presented by Lee et al. [63-64]. They developed a simulation approach
based on the Hele-Shaw approximation and kinematics of interface to calculate the two-phase
flow and the interface evolution during filling in simultaneous sandwich molding. Jaroschek
[65] studied the distribution of the core material during the filling process of sandwich
Introduction 14
injection molding using multiple gates, a variation of cascade control, with specific valves
and standard hot runner manifolds. The experimental results were also compared with those
obtained by the Moldflow simulation package using a layered 2.5-D flow approach and FEM
grid representing the housing geometry (loudspeaker box). His findings suggest that it is
possible to use a double hot runner system that allows even large components to be produced
by sandwich molding using multiple gating in case where the simulation program provides
sufficient accuracy. Chen et al. [66-67] utilized an algorithm based on the control volume
finite-element method combined with a particle-tracing scheme using a dual-filling-parameter
technique to predict the advancements of both melt front and gas front during the gas-assisted
injection process. Gao et al. [68] also used this volume tracking technique with the Galerkin
Finite Element model to simulate the filling stage of the gas-assisted injection molding
process, particularly the gas penetration phenomenon involving the gas-polymer interaction.
Wang et al. [69] compared the experimental and simulation results of gas penetration in terms
of different shot sizes, delay time and gas pressure. They suggested that an improper
modeling can cause artificial fast cooling in the gas channels, which will hinder the gas
penetration in the numerical simulation. Pittman et al. [70] simulated the cooling and
solidification of polymer melt during SCORIM by using the one-dimensional transient model.
A non-Newtonian, temperature-dependent viscosity is used, together with temperature-
dependent thermal properties and latent heat of solidification. Recent work [71] investigates
the weldline strength and the fiber orientation in the weldline region of push-pull processed
parts, with respect to the number of push-pull strokes and the holding pressure differences
between both the injection units. The experimental results are also compared with those
obtained by the simulation package using a 2.5-D model (based on Hele-Shaw
approximation). A good agreement has been obtained between the predictions and the
measurements, thus showing the usefulness of the commercial software in helping the design
engineer to identify the location of weldline and fiber orientation state within the weldline
areas.
Initial work on the 3-D simulation of the gas-assisted injection molding process was done by
Khayat et al. [72] which used a boundary-element method (BEM). Their contribution reduces
to the analysis of isothermal, incompressible, Newtonian fluid flow in simple 3-D geometries.
Haagh et al. [73] presents a 3-D model based on the finite-element method and a pseudo-
concentration technique for tracking the flow interfaces. Ilinca et al. [74] used a pressure
stabilized Petrov-Galerkin method to solve the Navier-Strokes equations in their 3-D
Introduction
15
numerical model for gas-assisted injection molding. An additional pressure stabilization term
was included compared with the standard Galerkin method. The position of the polymer/air
interfaces was also tracked using the pseudo-concentration method. Ilinca et al. [75] also used
this numerical model to simulate 3-D numerical model to simulate 3-D co-injection molding.
The polymer/air and skin/core polymer interfaces were tracked by solving two additional
transport equations.
1.5 Research objectives
The main objective of this work is to investigate the capability of the sandwich injection
molding technique for enhancing the orientation of fibers within the molded parts. The
influences of glass fiber concentration and processing parameters on the material distribution,
fiber orientation and fiber attrition are examined. Additionally, one of the specialized
injection molding techniques – push-pull processing – is employed in order to improve the
fiber orientation within the weldline area. The effect of processing parameters including the
number of push-pull strokes and the holding pressure differences between both the injection
units have been studied. The degradation of the fiber length caused by the alternating shear
field is also investigated.
The prediction of the tensile strength of conventional, sandwich and push-pull injection
molded short fiber reinforced composites are derived by an analytical method of modified
rule of mixtures (MROM) as a function of the area fraction between skin and core layers. The
effects of fiber length and fiber orientation on the tensile strength of short fiber reinforced
composites are also studied in detail. This model provides the necessary information to
determine what fiber length distribution and what fiber orientation distribution are required to
achieve a desired composite strength.
Material distribution and fiber orientation structures of sandwich and push-pull processed
parts are predicted by the 2.5 and 3-D numerical analyses. The predictions solve the full
balance equations of mass, momentum, and energy for a generalized Newtonian fluid. The
second-order orientation tensor ( ) approach is used to describe and calculate the local
fiber orientation state. The accuracy of model predictions is extensively evaluated by
11a
Introduction 16
comparing with corresponding experimental measurements to gain a further basic
understanding of the relationship between the processing conditions, the fiber orientation
distribution and the properties of the final injection molded part.
1.6 Outline of the thesis
In Chapter 2 the fundamentals of rheology, general behavior and predictive methods for short
fiber reinforced composites are introduced. The influence of parameters on mechanical and
physical properties is described. The mathematical formulations used for the flow model and
the basics of fiber orientation prediction are summarized in Chapter 3. Chapter 4 details the
experimental procedures including materials, processing conditions, morphology observation
and measurement of mechanical properties. The process simulations of sandwich and push-
pull injection molding processes are also presented. In Chapter 5, the morphology
developments with different processing types are discussed. It provides the evidences of
mechanical properties, fiber orientation, and fiber length distribution within sandwich and
push-pull injection molded parts compared with those obtained using conventional injection
molding. In Chapter 6, predictions of the skin/core material distribution and fiber orientation
are compared with the experimental results. A number of simulations of sandwich and push-
pull injection molding in a dumbbell part are carried out in order to investigate the influence
of various parameters. Finally, the conclusions are presented in Chapter 7.
2. Molding of Short Fiber Reinforced
Composites
A short fiber composite consists of a polymer matrix reinforced by fibers of much smaller
length as compared with the overall dimensions of the fabricated structure. These reinforced
polymers have been developed to fill the mechanical property gap between the continuous
fiber laminates used as primary structures by the aircraft and aerospace industry and the neat
polymers used in low-load-bearing applications. Although short fiber composites do not
achieve the characteristic mechanical values which can be obtained with continuous fiber
laminates [76]. However, they can be processed with the same techniques used for unfilled
thermoplastics, e.g. injection molding of short fiber composites for the high volume
production purposes and the ability to be molded into complex shapes. Furthermore, their
intrinsic recyclability is rapidly being recognized as a strong driving force for their further
application [77]. The molding processes of short fiber composites requires the compounded
material to be heated and then forced to flow under the application of a high pressure in order
to conform to the shape of the mold cavity. If injection molding is the chosen fabrication
route, then the flow processes involved in mold filling can be very complex and result in a
marked orientation of the fibers in the final part. The microstructure and morphology that are
produced depend on how well the fibers are dispersed, the range of fiber lengths and
diameters, how the fibers interact with the mold walls and each other during flow, the heat
transfer in the mold, and the geometry of the mold. This in turn will have a major effect on
the anisotropy of the mechanical and physical properties of the injection molded component
[76].
Molding of Short Fiber Reinforced Composites
18
This chapter will introduce a short review of rheological properties and microstructure of
short fiber reinforced composites including the fiber attrition during processing operations.
Topics also include the mechanical properties and the predictive methods for short fiber
reinforced composites.
2.1 Rheology of short fiber composites
The rheological properties of short fiber composites may differ in detail from those of normal
unfilled polymers, but they are not considerably different. In practice the methodology for
measuring the basic flow properties of fiber filled melts follows closely that used for
characterizing the flow properties of unfilled materials. Indeed, the shear viscosity can be
measured using most of the normal techniques, i.e. cone and plate, capillary, dynamic
mechanical, etc. Detailed experimental techniques used for characterizing rheological
properties can be found elsewhere [78].
Much of the early work on the rheology of filled polymers was concerned with dilute
suspensions. The flow properties of such melts will differ significantly from those of filled
thermoplastics of commercial grades, where individual particles are in close proximity to
each other. Figure 2.1 shows a plot of log shear viscosity versus log shear rate for three
grades of polycarbonate, containing 0, 20 and 35 by weight of short glass fibers (%wt),
respectively. At low shear rates the presence of the fibers causes an appreciable increase in
viscosity, but it is noteworthy that the viscosity values for the three materials converge to a
very similar value at the higher shear rates. Essentially the same pattern of behavior is shown
by many other fiber reinforced grades of polymers [79]. The similarity in viscosity values at
high shear rates, for filled and unfilled polymers, is an important factor in explaining the
successful exploitation of these materials, since very little additional power will be required
to process the filled materials [80].
The basic rheological data for fiber filled polymers are derived from tests performed using
very simple geometries. In practice, however, the flow geometries occurring in technological
processing equipment will be very complex. The fiber orientation distribution (FOD) in a
molded part can be qualitatively interpreted through an appreciation of the fiber orientation
resulting from certain basic categories of flow:
Molding of Short Fiber Reinforced Composites
19
• Shear flow – as will occur in a straight tube or duct
• Convergent flow – in the simplest case this will occur when a fluid passes from a
wide to a narrow cross-section.
• Divergent flow (also referred to as extensional flow) – in the simplest case this will
occur when a fluid passes from a narrow to a wide cross-section.
Convergent flow leads to an alignment of fibers parallel to the flow direction. Divergent flow,
on the other hand, tends to orient the fibers orthogonally to the flow direction. Frequently,
this is observed as fiber filled melts pass from a narrow gate into the mold cavity.
1 10 100 1000 10000 10000010
100
1000
10000
Temp. = 306.7 oC
Visc
osity
(Pa.
s)
Shear Rate (1/s)
PC (Makrolon 2800) PC filled with 20 wt% short-glass-fiber (Makrolon 8020) PC filled with 35 wt% short-glass-fiber (Makrolon 8030)
Figure 2.1 Apparent viscosity versus shear rate for three polycarbonates containing different
amounts of short glass fibers. (Moldflow database)
Molding of Short Fiber Reinforced Composites
20
2.2 Microstructure of injection molded short fiber composites
2.2.1 Fiber orientation
As the fiber suspension flows into the mold, one must know the fiber orientation structure not
only to determine its rheological behavior but also to estimate its mechanical performance.
Flow and deformation of the suspension change the orientation of the fibers flowing in it.
These orientations are subsequently frozen in as the material solidifies and become a key
feature of the microstructure of the finished composite. If the fibers are randomly oriented,
the mechanical and physical properties will be isotropic. If the fibers are aligned in one
direction, the composite will be stiffer and stronger in that direction compared with any other
direction. The distribution of orientations in a molded part could be quite diverse. One region
may have random fiber orientation, while others may have preferred alignment in certain
directions.
In the injection molded short fiber composites, a characteristic layer structure is observed,
with the fibers oriented in quite different manners according to their location through the
thickness, as schematically demonstrated in Figure 2.2. These general features are apparent in
studies of fiber orientation distribution found in the literature [80-89]. In the skin region, the
fiber orientation is predominately parallel to the flow direction. This is due to, as the melt fills
the mold, there is fountain flow which initially orients the fibers perpendicular to the main
flow direction. Fountain flow causes the melt to be deposited on the mold wall with the
alignment direction parallel to the mold fill direction. Here it solidifies rapidly and this
alignment is retained in the solid article. Further behind the melt front, shear flow dominates
and produces fairly uniform levels of fiber alignment. The fiber orientation and the thickness
of this region are influenced by non-isothermal effects and by injection speed [80-81]. In
contrast, the core of the molding contains fibers mainly aligned perpendicular to the flow
direction due to a slower cooling rate and lower shearing.
Molding of Short Fiber Reinforced Composites
21
Core layer
Skin layer
Skin layer
Z
X Y (Flow direction)
Figure 2.2 Schematic diagram of molding indicating the fiber orientation in the skin and core
layers.
During the injection molding process of short fiber composites, the distribution of fiber
orientation is governed by a variety of factors. These include the type and/or shape [82, 90],
concentration of fibers [83-84], the gate designs and/or flow geometry [85-86]. The
processing conditions such as injection flow rate, injection pressure, and melt temperature
can also significantly alter the proportions of the oriented regions [87-88]. It has also been
shown that the mechanical and physical properties of injection molded short fiber composites
depend critically on the fiber orientation distribution in the final product [82-89].
2.2.2 Fiber attrition during molding
One of the major concerns in producing fiber reinforced parts by injection molding is fiber
breakage during processing. Many experiments have established the fact that the fibers get
damaged during processing and fiber length may be reduced by an order of magnitude [91-
93]. This reduction in length can potentially reduce the reinforcing efficiency of the fibers,
thus substantially reducing the mechanical properties of the composite [94-95]. The reduction
Molding of Short Fiber Reinforced Composites
22
in fiber length during compounding and molding can be explained by the three common
mechanisms including; fiber-flow, fiber-fiber and fiber-wall interactions.
• Fiber-flow interactions: most flows in injection molding process are a combination of
extensional and shear deformations. In a purely elongational flow, fibers tend to align along
the stretching direction and hence are under tension, fibers are rather unlikely to break under
this mode. However, in shear flows, fibers rotate across the streamlines and may bend to their
critical radius of curvature and buckle under viscous forces transmitted by the polymer melt.
• Fiber-fiber interactions in concentrated suspensions can cause fiber overlaps, which
will induce bending stresses in the fibers, resulting in breakage. The effect of fiber volume
fraction on breakage was studied by von Turkovic and Erwin [91], who found that glass
fibers in polystyrene had the identical length distribution at the exit of an extruder for volume
fractions ranging from 1 to 20%. Their results indicated that the fiber length was reduced by
an order of magnitude after processing and that the average final length was insensitive to
initial fiber length distribution.
• Fiber-wall interactions: in injection molding, the effect of mold and screw geometries
plays a crucial role in fiber length reduction. Wider mold channels have been shown to
reduce breakage [84-86]. Also, the gate region of the mold may be a key factor in fiber
degradation. Bailey and Rzepka [96] studied long fiber materials under various material and
processing conditions in a plunger molding machine, a conventional injection molding
machine, and an extruder. Mold configurations with a small gate and a generous gate were
studied. Fiber loadings from 30-60% were used. Their study showed that a larger gate
produced final fiber lengths with a mean of 0.99 mm, whereas a smaller gate had a mean
fiber length of only 0.49 mm. They also found that there was substantially more damage in
the skin region than in the core. This could be attributed to a high shear rate near the mold
surface coupled with fiber interactions with the mold wall.
Molding of Short Fiber Reinforced Composites
23
2.3 Mechanical properties
The general stress-strain curves observed in glass fiber reinforced thermoplastics are
illustrated in Figure 2.3. It is well known that the addition of glass fibers results in an
enhancement of the stiffness and strength of the composite [82-85, 89, 94-95]. It also can be
seen that both the stiffness and strength increase with fiber concentration. However, one very
important consequence of utilizing large volume fractions of fibers is that although stiffness
is increased significantly, there is not necessarily a pro rata change in strength [85, 89, 95].
Furthermore, the work to fracture decreases rapidly as the concentration of fibers is increased
[82-83, 85], i.e. the composite will only tolerate small impact energies.
As with all materials that are uniaxially oriented, the mechanical properties of a highly
aligned composite depend critically on the angle between the applied stress and fiber
orientation direction. Figure 2.3 also shows some experimental tensile strength data obtained
on moderately well-aligned composites of glass fiber in polypropylene. It can be seen that a
large composite strength is only obtained when the stress direction is close to the fiber
orientation axis. This sensitivity to angle becomes much more acute as the ratio of fiber
strength to matrix strength increases. The anisotropy in the mechanical properties has
important implications for the behavior of partially aligned short fiber composites. A cross-
section cut from a simple tensile test specimen, molded in short glass fiber reinforced
polycarbonate, reveals a complex fiber orientation distribution (see Figure 2.4). It is clear that
when a stress is applied to this bar many of the fibers will be at quite large angles with
respect to the stress direction. Overall, then the stiffness of the bar will be significantly less
than for fully aligned fibers.
Molding of Short Fiber Reinforced Composites
24
Te
nsile
stre
ss,
(M
Pa)
Strain, (%)
0
10
20
30
40
50
60
70
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
SFRPP30 parallel to flow directionSFRPP30 transverse to flow directionSFRPP40 parallel to flow directionSFRPP40 transverse to flow directionLFRPP30 parallel to flow directionLFRPP30 transverse to flow directionLFRPP40 parallel to flow directionLFRPP40 transverse to flow direction
ε
σ
Flowdirection
Figure 2.3 Typical stress-strain curves for glass fiber reinforced polypropylene at various
fiber volume fractions, fiber lengths, and testing locations. [89] (The description of
abbreviations is shown in section 4.1)
Another parameter of key importance in influencing the mechanical properties of composites
is the fiber length. As can be seen from Figure 2.3, when the stress is applied parallel to the
fiber axis in a uniaxially aligned fiber reinforced composite, the greatest stiffness and strength
occur when the fibers are very long compared with their diameter. With short fiber
composites, however, the fibers are usually of the order of half a millimeters in length so as
to enable the composites to be processed easily using, e.g. injection molding. In this case the
stiffness and strength of the composite will be lower [86, 89, 95]. Hence the strength of any
given injection molded composite part will depend critically on both the fiber length
distribution and fiber orientation distribution.
Molding of Short Fiber Reinforced Composites
25
Fiber orientationparallel to theflow direction
Fiber orientationparallel to theflow direction
Random-in-planealignment of fibers
FlowFlow directiondirection
Skin
laye
rC
ore
laye
rSk
in la
yer
Figure 2.4 Optical photomicrograph showing the fiber orientation pattern across the thickness
of tensile test bar.
2.4 Predictive methods of tensile strength for short fiber composites
Tensile strength is one important property of engineering materials. One of the basic
motivations for the use of composite materials as engineering materials is the high tensile
strength that can be achieved by incorporating high strength fibers into a matrix since the
fibers carry most of the load. Over the last decade, several theoretical models have been
proposed in order to predict the modulus and strength of short fiber composites. One is the
laminate analogy, which combines the micro-mechanics of joining different phases with the
macro-mechanics of lamination theory. The success of the laminate approximation is strongly
dependent upon the assumption of physical volume averaging combined with an ability to
estimate the properties of the individual plies, each of which contains uniaxially oriented
fibers. This approach has been used successfully to predict strength, modulus, stress-strain
behavior [97-98], and flexural stiffness [99]. The other major approach is the modified rule of
Molding of Short Fiber Reinforced Composites
26
mixtures (MROM), which has been mostly used to predict the modulus and strength of short
fiber composites by taking into consideration the effects of fiber length and orientation
distribution [100-103]. In general, all of the proposed methods have shown good agreement
with experimental results. Although the laminate and MROM methods are usually used to
estimate the strength for short fiber composites, the procedures to estimate the strength of
sandwich and push-pull injection molded parts have not been established.
In this section, therefore, the model used for predicting the ultimate tensile strength (UTS) of
sandwich and push-pull injection molded part will be introduced. This predictive method is
also based on a MROM as a function of the area fraction between skin and core layers (so
called area fraction method). The advantage of this method over the traditional method is that
the weldline strength of push-pull processed part and the UTS of sandwich injection molded
part, containing different fiber concentration between skin and core material, being able to
estimate. In order to take into account the influence of fiber length as well as fiber orientation,
the fiber orientation efficiency factor ( ) and fiber length efficiency factor ( ) also can be
accommodated.
0f lf
2.4.1 Modified rule of mixtures (MROM)
The modified rule of mixtures is often used to predict the tensile strength of short fiber
composites. The formula of MROM is given by
mmfflCU VVff σσσ += 0 (2.1)
where CUσ and fσ are the ultimate strength of the composite and fiber, respectively; and
denote the volume fraction of the fiber and matrix;
fV
mV mσ is the stress developed in the
matrix; and are the fiber orientation and fiber length efficiency factors, which depend
on various parameters such as fiber volume fraction and processing conditions, and are only
fitted empirically [95]. By using the Voigt average [79] and dividing the reinforcement into
groups of uniaxially aligned fibers, is determined by
0f lf
0f
∑=n
nnaf ϕ40 cos (2.2)
Molding of Short Fiber Reinforced Composites
27
where is the proportion of fibers making an angle na nϕ with respect to the applied load or
flow direction. The efficiency of fiber reinforcement for several situations is presented in
Table 2.1, this efficiency is taken to be unity for an oriented fiber composite in the alignment
direction, and zero perpendicular to it.
Table 2.1 Reinforcement efficiency of fiber reinforced composites for several fiber
orientations and at various directions of stress application. [79]
Reinforcement Efficiency, (f 0 )
Parallel to fibers 1Perpendicular to fibers 0
Fiber randomly and uniformly Any direction in the plane tributed within a specific plane of the fibers
ber randomly and uniformlytributed within three-
imensions in space
3/8
Any direction 1/5
Stress DirectionFiber Orientation
ibers parallel
dis
Fidis d
All F
If the fiber length ( is uniform, the fiber length efficiency factor can be obtained from )l
cl l
lf2
= for l < (2.3) cl
ll
f cl 2
1−= for l ≥ (2.4) cl
where the critical minimum fiber length. This critical length is given by cl
τ
σ2
dl f
c = (2.5)
where is the fiber diameter and d τ the interfacial shear strength between fiber and matrix.
In the case of a strong interfacial bond, τ is limited by the shear strength of the matrix ( )mτ .
Assuming isotropy of the matrix this results in
3mσ
τ = (2.6)
Molding of Short Fiber Reinforced Composites
28
If the fiber length is not uniform, the model can be given by
mmll i
cff
ll c
iffCU V
llVf
llV
fcii
σσσ
σ +⎥⎦
⎤⎢⎣
⎡⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎥
⎦
⎤⎢⎣
⎡= ∑∑
⟩⟨ 21
2 00 (2.7)
The first and second terms in this expression represent the contributions of the fiber length
being shorter and longer than , respectively. cl
As always one should be fully aware of all assumptions that lie behind any model, which in
this case are:
• Stress transfer across the interface increases linearly from the tips of the fiber inwards
to some maximum value
• No fiber-matrix deboding occurs
• The fiber orientation factor is independent of strain and is the same for all fiber
lengths
• The composite matrix properties are the same as the resin properties
• The fiber strength is known (which may also be different from a textbook value or
even a measurement on the fibers used to produce the test samples)
• τ is independent of loading angle
• Fiber diameter is monodisperse
2.4.2 Area fraction method
The deviation of this model to predict the tensile strength of short fiber composite can begin
by considering the total load sustained by the composite ( )CF is equal to the loads carried by
longitudinal fibers and transverse (or random) fibers, which was proposed by Akay and
Barkley [85], defined as
TLC FFF += (2.8)
Molding of Short Fiber Reinforced Composites
29
From the definition of stress ( AF σ= ) and the expression for , and in terms of
their respective stresses, the ultimate tensile strength of the composite (
CF LF TF
CUσ ) can be rewritten
as:
TUTLULCCU AAA σσσ += (2.9)
or ⎟⎟⎠
⎞⎜⎜⎝
⎛+⎟⎟
⎠
⎞⎜⎜⎝
⎛=
C
TUT
C
LULCU A
AAA
σσσ (2.10)
where C
L
AA
is the area fraction between the skin region and the cross-sectional area of
specimen; and C
T
AA
is the area fraction between the core region and the cross-sectional area of
specimen. The UTS of the skin region, ULσ , where the fibers near the part surface are
generally aligned in the flow direction or tensile axis, is given by:
mmll i
cff
ll c
iffUL V
llVf
llV
fci
skin
i
skinσσ
σσ +⎥
⎦
⎤⎢⎣
⎡⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎥
⎦
⎤⎢⎣
⎡= ∑∑
⟩⟨ 21
2 00 (2.11)
The ultimate tensile strength of the core region, UTσ , where the fiber orientation is
predominately transverse or random to the flow direction, this equation can be written as:
mmll i
cff
ll c
iffUT V
llVf
llV
fci
core
i
coreσσ
σσ +⎥
⎦
⎤⎢⎣
⎡⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎥
⎦
⎤⎢⎣
⎡= ∑∑
⟩⟨ 21
2 00 (2.12)
Therefore, the UTS of short fiber reinforced composites ( UCσ ) with respect to the effects of
fiber length and fiber orientation can be evaluated with following equation:
Molding of Short Fiber Reinforced Composites
30
⎟⎟⎠
⎞⎜⎜⎝
⎛
⎥⎥⎦
⎤
⎢⎢⎣
⎡+⎟⎟
⎠
⎞⎜⎜⎝
⎛⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎟⎟
⎠
⎞⎜⎜⎝
⎛
+⎟⎟⎠
⎞⎜⎜⎝
⎛
⎥⎥⎦
⎤
⎢⎢⎣
⎡+⎟⎟
⎠
⎞⎜⎜⎝
⎛⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎟⎟
⎠
⎞⎜⎜⎝
⎛=
∑∑
∑∑
⟩⟨
⟩⟨
C
Tmm
ll i
cff
ll c
iff
C
Lmm
ll i
cff
ll c
iffCU
AAV
llVf
llV
f
AAV
llVf
llV
f
ci
core
ci
core
ci
skin
i
skin
σσσ
σσσ
σ
21
2
21
2
00
00
(2.13)
where and are the fiber orientation efficiency factors for the skin and core layers,
respectively. The schematic diagram of cross-sectional area for conventional injection
molded composites is depicted in Figure 2.5a.
skinf 0 core
f0
Equation (2.13) can be expressed in terms of the UTS for the sandwich injection moldings as
below:
⎟⎟⎠
⎞⎜⎜⎝
⎛
⎥⎥⎦
⎤
⎢⎢⎣
⎡+⎟⎟
⎠
⎞⎜⎜⎝
⎛⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎟⎟
⎠
⎞⎜⎜⎝
⎛
+⎟⎟⎠
⎞⎜⎜⎝
⎛
⎥⎥⎦
⎤
⎢⎢⎣
⎡+⎟⎟
⎠
⎞⎜⎜⎝
⎛⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎟⎟
⎠
⎞⎜⎜⎝
⎛=
∑∑
∑∑
⟩⟨
⟩⟨
C
coremm
ll i
cff
ll c
iff
C
skinmm
ll i
cff
ll c
iffCU
AAV
llVf
llV
f
AAV
llVf
llV
f
ci
core
ci
core
ci
skin
i
skin
σσσ
σσσ
σ
21
2
21
2
00
00
(2.14)
where and skinA coreA are the cross-sectional area of skin and core materials (see Figure 2.5b).
Equation (2.13) also can be employed for sandwich injection molded composites, containing
different fiber concentration between skin and core material (see Figure 2.5c). For example,
when the skin and core materials filled with 40 and 20 wt% of fiber, the expression can be
written as follows:
⎟⎟⎠
⎞⎜⎜⎝
⎛
⎥⎥⎦
⎤
⎢⎢⎣
⎡+⎟⎟
⎠
⎞⎜⎜⎝
⎛⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎟⎟
⎠
⎞⎜⎜⎝
⎛
+⎟⎟⎠
⎞⎜⎜⎝
⎛
⎥⎥⎦
⎤
⎢⎢⎣
⎡+⎟⎟
⎠
⎞⎜⎜⎝
⎛⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎟⎟
⎠
⎞⎜⎜⎝
⎛
+⎟⎟⎠
⎞⎜⎜⎝
⎛
⎥⎥⎦
⎤
⎢⎢⎣
⎡+⎟⎟
⎠
⎞⎜⎜⎝
⎛⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎟⎟
⎠
⎞⎜⎜⎝
⎛=
∑∑
∑∑
∑∑
⟩⟨
⟩⟨
⟩⟨
C
Tmm
ll i
cff
ll c
iff
C
coremm
ll i
cff
ll c
iff
C
skinmm
ll i
cff
ll c
iffCU
AAV
llVf
llV
f
AAV
llVf
llV
f
AAV
llVf
llV
f
ci
coresub
ci
coresub
ci
core
ci
core
ci
skin
i
skin
σσσ
σσσ
σσσ
σ
21
2
21
2
21
2
20.
20
.
20
20
40
40
00
00
00
(2.15)
Molding of Short Fiber Reinforced Composites
31
AL
AT
AC = AL + AT
Skin material
Core material
ASkin
ACore
AC = ASkin + ACore
Skin material
Core material
ASkin
ACore
AC = ASkin + ACore + AT
AT
(a)
(b)
(c)
Figure 2.5 Schematic illustration of cross-sectional area indicating the skin and core regions:
(a) Conventional injection molded short fiber composite, (b) Sandwich injection molded part,
and (c) Sandwich injection molded short fiber composite.
In addition, the prediction of weldline strength, WLσ , of short fiber reinforced composites for
conventional and push-pull injection moldings also can be calculated by rewriting the
Equation (2.13) as :
⎟⎟⎠
⎞⎜⎜⎝
⎛
⎥⎥⎦
⎤
⎢⎢⎣
⎡+⎟⎟
⎠
⎞⎜⎜⎝
⎛⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎟⎟
⎠
⎞⎜⎜⎝
⎛
+⎟⎟⎠
⎞⎜⎜⎝
⎛
⎥⎥⎦
⎤
⎢⎢⎣
⎡+⎟⎟
⎠
⎞⎜⎜⎝
⎛⎟⎟⎠
⎞⎜⎜⎝
⎛−+⎟⎟
⎠
⎞⎜⎜⎝
⎛=
∑∑
∑∑
⟩⟨
⟩⟨
C
Coremm
ll i
cff
ll c
iff
C
Skinmm
ll i
cff
ll c
iffWL
AAV
llVf
llV
f
AAV
llVf
llV
f
ci
core
ci
core
ci
skin
i
skin
σσσ
σσσ
σ
21
2
21
2
00
00
(2.16)
Molding of Short Fiber Reinforced Composites
32
where and are the cross-sectional areas where the fibers are aligned randomly and
perpendicular to the flow direction, respectively (see Figure 2.6). In the case of push-pull
injection molded composites, is the region with the predominant fiber orientation in the
flow direction.
skinA coreA
coreA
ACore
ASkin
ASkinAC ACore= +
ACoreACore
ASkinASkin
ASkinAC ACore= +ASkinASkinACAC ACoreACore= +
ASkin
ACore
ASkinAC ACore= +
ASkinASkin
ACoreACore
ASkinAC ACore= +ASkinASkinACAC ACoreACore= +
Conventional injection molded part
Push-pull injection molded part
Figure 2.6 Schematic illustration of cross-sectional area at the weldline position for
conventional and push-pull injection molded short fiber composites.
3. Modeling of the Injection Molding
Process
3.1 Governing equations
The polymer melt flow is governed by the three fundamental laws of physics, i.e. the
principles of conservation of mass, momentum, and energy, which are expressed as
Continuity: ( ) 0=⋅∇+∂∂ u
tρρ (3.1)
Momentum: gPtDuD ρτρ +⋅∇+−∇= (3.2)
Energy: ( )•
+∇+⋅∇⎥⎦
⎤⎢⎣
⎡∂∂
−⋅−∇= SuuTPTq
tDTDC
vp :τρ (3.3)
where ρ is the density, P is the pressure, is the specific heat at constant volume, pC T is
the temperature, v is the specific volume, is the rate of heat generation due to chemical
reaction, is the velocity vector,
•
S
u g is the body force vector, q is the heat flux vector, ∇ is
the gradient operator,tD
D is the substantial derivative, and τ is the extra stress tensor. To
equate the numbers of unknowns and equations, it requires additional relationships among the
variables, such as rheological constitutive equation, an equation of state for polymer, a
thermal constitutive equation and/or equations for cure and kinetics [45]. For example, the
Modeling of the Injection Molding Process 34
rheological constitutive equation of polymer melts is typically modeled by the generalized
Newtonian viscosity model:
γητ &2= (3.4)
with ( )[ ]Tuu ∇+∇=21γ& (3.5)
where η is the non-Newtonian viscosity, γ& is the strain rate tensor, and u is the velocity
vector.
Due to the typically large number of elements and nodes associated with 3-D simulation, it is
necessary to neglect less significant terms in the governing equations. Otherwise, the
computational time and memory requirement would become too excessive to justify for the
3-D simulation. For example, if the polymer melts are assumed to be incompressible during
filling, the conservation equations of mass and momentum in equations (3.1) and (3.2)
become the Navier-Stokes equations [57]:
0=⋅∇ u (3.6)
( ) gPtDuD ργηρ +⋅∇+−∇= &2 (3.7)
To take into account the effect of inertia on the polymer melt flows (e.g. branching flows or
jetting), the inertia term in the left-hand side of equation (3.3) may not be ignored [59].
Whether the body force (e.g. gravity) term, gρ , in the momentum equation can be neglected
depends on the geometry and material of the system [57]. If the inertia is negligible, the
Navier-Stokes equations can be further reduced to the Stokes equations:
( ) gP ργη +⋅∇+−∇= &20 (3.8)
Through the dimensional analysis (see [73]), the energy equation can be reduced to a simpler
form as:
Modeling of the Injection Molding Process
35
( ) γγηρ &&:2+∇⋅∇=⎟⎟⎠
⎞⎜⎜⎝
⎛∇⋅+
∂∂ TkTu
tTCp (3.9)
where is the heat conduction coefficient. k
After the entire cavity is completely filled, the pressure throughout the cavity increases
rapidly as additional polymer melt is packed into the cavity to compensate for the volumetric
shrinkage. During the packing stage, the melt compressibility can no longer be neglected.
Haagh et al. [73] used equation (3.1) as the governing equation to account for polymer
shrinkage in both filling and post-filling stages. Hetu et al. [52] employed the following
governing equations for the compressible flow during the packing stage. The compressibility
effects are included by incorporating the equation of state in the continuity equation.
⎟⎟⎠
⎞⎜⎜⎝
⎛∇⋅+
∂∂
−⎟⎟⎠
⎞⎜⎜⎝
⎛∇⋅+
∂∂
=⋅∇− TutTPu
tPu βα (3.10)
⎟⎠⎞
⎜⎝⎛ ⋅∇−⋅∇+−∇= uIP ηγη
3220 & (3.11)
( ) γγηβρ && :2+∇⋅∇+⎟⎟⎠
⎞⎜⎜⎝
⎛∇⋅+
∂∂
=⎟⎟⎠
⎞⎜⎜⎝
⎛∇⋅+
∂∂ TkPu
tPTTu
tTCp (3.12)
where I is the identity matrix, α is the compressibility coefficient, and β is the thermal
expansion coefficient. The density and the coefficients α and β can be simply calculated
from the equation of state [45].
After the gate freezes off, no more polymer melt enters the cavity and the cooling stage
begins. In this stage, the convection and dissipation terms in the energy equation can be
neglected since the velocity of a polymer melt in the cooling stage is almost zero [52].
Modeling of the Injection Molding Process 36
3.2 Predicting fiber orientation
As pointed out earlier, knowing an average fiber orientation direction for the complete part is
not sufficient because the local spatial orientation also plays an important role in determining
properties such as strength and toughness. Hence, considerable research has been done with
the intent of learning how to predict fiber orientation in injection molded parts. Mathematical
models have been developed and incorporated into simulations of injection molding with the
emphasis on predicting the influence of mold geometry, processing conditions, and material
properties on the final orientation pattern. Most recent works on the fiber orientation analysis
have their origin from Jeffery [104], who derived the equation of orientation change of an
ellipsoidal particle immersed in the homogeneous flow field based on hydrodynamics. This
equation is available only in a dilute suspension regime where the interaction between fibers
is negligible. In a non-dilute suspension regime, statistical consideration of the fiber
orientation is required to model the ensemble of interacting fiber particles. In this case, the
orientation distribution function is the only model that can describe the distribution of fiber
orientation completely.
For an efficient numerical simulation of the orientation state of fibers, Advani and Tucker
[105] reviewed the orientation tensor, which was originally introduced by Hand [106]. The
meaning of the orientation tensor is similar to the Fourier series of the orientation distribution
function. In this approach, only a few components are required to represent the state of
orientation at each spatial point. This advantage has made the orientation tensor, especially
the second order tensor, to be widely used in calculation of the fiber orientation [47, 107-108]
and material property prediction [109-111] in short fiber composites. The orientation tensor is
independent of the coordinate system, making it advantageous for numerical simulation and
evaluations of orientation. The only weakness of the orientation tensor approach is that a
closure approximation is required to close the governing equation which is the main reason
for causing errors between calculated and measured values. Hybrid closure approximation
proposed by Advani and Tucker [105, 112] has been considered in many applications.
Recently, several approaches have been introduced to propose more accurate closure
approximations [113-115].
Modeling of the Injection Molding Process
37
The following section will review the present state-of-the-art modeling of fiber orientation in
molding short fiber composites. Topics covered include characterizing orientation, fiber
orientation mechanics for a collection of fibers, closure approximation and incorporation of
these ideas in manufacturing process model for injection molding.
3.2.1 Characterizing orientation
A complete description of the distribution of fiber orientation begins by considering a single
fiber whose orientation can be represented by a unit vector p as shown in Figure 3.1.
Components of the vector p are described by angles θ and φ in spherical coordinates as
follows:
φθ cossin1 =p φθ sinsin2 =p θcos3 =p (3.13)
Describing the orientation of individual fibers is ineffective since the composites contain
numerous short fibers. Thus, the concept of probabilistic distribution was introduced to fully
describe the distribution of fiber orientation in three dimensions. The probability distribution
function for orientation, also known as the orientation distribution function, ( )φθψ , , is
defined as the probability of fiber lying between angles θ and θθ d+ , φ and φd . The
probability distribution function must satisfy two physical conditions. First, one end of the
fiber is indistinguishable from the other end, so ψ must be periodic:
( ) ( )πφθπψφθψ +−= ,, (3.14)
Second, every fiber must have some direction, so the integral over all possible directions or
the orientation space must be equal to unity:
( ) 1sin,2
0 0
=∫ ∫ φθθφθψππ
dd (3.15)
This is known as the normalization requirement. If the orientation statistics change with
position, ψ is a function of x , , y z in addition to θ and φ .
Modeling of the Injection Molding Process 38
p
2
1
3
θ
φ
p
2
1
3
θ
φ
Figure 3.1 Characterization of the fiber orientation in a coordinate system
The distribution function can be approximated by measuring the orientations of a large
number of fibers selected from a region where the distribution function is a complete and
unambiguous description of the fiber orientation state. However, this distribution function
depends not only upon the angles θ and φ but also upon spatial position. The resulting
approach would be highly computationally intensive with large storage requirement, making
it somewhat inappropriate for numerical simulation. For a more efficient method of
numerically simulating the orientation state of fiber, Advani and Tucker [105] used
orientation tensors. Such tensors are defined as the dyadic products of the unit vector p
averaged over all possible directions, with ψ as the weighting function. The definitions of
second ( ) and fourth ( ) order orientation tensors can be defined as: ija ijkla
( )dppppa jiij ψ∫= (3.16)
and ( )dppppppa lkjiijkl ψ∫= (3.17)
There are a number of physical interpretations of these tensors. They can be thought of as a
generalization of orientation parameters, as moments of the distribution function, or as a
series expansion of the distribution function. Advani and Tucker [105] provide a complete
review. They have shown that these tensors are free from a priori assumptions about the
Modeling of the Injection Molding Process
39
shape of the distribution function and can be readily transformed from one coordinate frame
of reference to another complying with the rules of tensor transformation, that is
jiij aa = (3.18)
The normalization condition such as Equation (3.15) implies that the trace of is unity: ija
1=iia (3.19)
The tensor description substitutes less number of scalar quantities for the distribution function
to describe orientation. For example, for planar orientation, only two of the four components
are independent. For the 3-D case, only five of the nine components are independent.
Viscosity and elastic stiffness are normally fourth-order tensors, and one would normally
require only a fourth-order orientation tensor to predict the effect of orientation on these
fourth-order properties [105]. By approximating the fourth-order tensor in term of second-
order tensors, it is possible to predict the effect of orientation on fourth-order properties using
just the second-order orientation tensor [112].
3.2.2 Flow-induced fiber orientation
Jeffery modeled accurately the motion of a single fiber immersed in a large body of
incompressible Newtonian fluid [104]. However, fibers in concentrated suspensions behave
somewhat differently. A number of researchers have observed fiber orientation in
concentrated suspensions [80-89, 96]. All of them reported fiber orientation behavior that is
qualitatively similar to single-fiber motion. In elongational flows, fibers align along the
direction of stretching, aligning with the streamlines in converging flows and normal to the
streamlines in diverging flows. Shear flows tend to orient fibers in the flow direction.
However, these researchers do not observe perfect alignment of fibers, which the theory
predicts. Fibers flowing in concentrated suspension are so close to each other that they not
only interact hydrodynamically but may physically collide with each other, causing more
erratic motion that violates Jeffery’s assumptions.
The dynamic behavior of a concentrated suspension is quite complex, as the rheology is
closely coupled with the fiber orientation structure. So far, a phenomenological model
Modeling of the Injection Molding Process 40
proposed by Folgar and Tucker has proven useful [116]. They model the interaction between
the fibers by introducing an additional term in the equation of motion for single-fiber motion.
This term is similar to a diffusive term, and the effective diffusivity is made proportional to
the strain rate, as interactions take place only when the suspension is deforming. A
dimensionless “interaction coefficient” term, typically of the order of 10IC -2, served to
match their experimental results [116-117]. The equation of motion can then be combined
with the equation that conserves fibers in the orientation space to produce the equation of
change for fiber orientation in terms of distribution function and orientation tensors [105,
116-117]. For example, the equation of change for the second-order tensor is given by:
( ) ( ) ijijIijklklkjikkjikkjikkjikij aCaaaaatD
aD322
21
21
−+−++−−= δγγγγλωω &&&& ( ) (3.20)
where ijδ is the unit tensor, j
i
i
jij x
vxv
∂∂
−∂
∂=ω and
j
i
i
jij x
vxv
∂∂
+∂
∂=γ& are the vorticity and the
rate of deformation tensors, respectively. A shape factor of particle is defined as ( )( )1
12
2
+
−=
e
e
rr
λ
where is the aspect ratio of the ellipsoid, is the experimental interaction coefficient
depending on the particle geometry and concentration, and
er IC
2ijij γγ
γ&&
& = is the effective shear
rate.
3.2.3 Numerical simulation of fiber orientation for injection molding
Over the last decade, several numerical techniques have been developed to determine the
fiber orientation in injection molded composites by using the generalized Hele-Shaw (GHS)
formulation [47, 108, 113, 118-122]. However, because of the simplifying assumptions used
in GHS flow model [42], the so-called 2.5-D model reaches its limits in the simulation of the
thick-walled moldings, complex geometrical configurations (such as bosses, corners, and
ribs), and at the melt front (fountain flow) regions. Therefore, the fully 3-D simulation model
should be able to generate complementary and more detailed information related to the flow
characteristics in injection molded parts than the one obtained when using a 2.5-D model.
This will be particularly important while molding with fiber reinforced systems.
4. Experimental and Simulation
Procedures
4.1 Materials and processing conditions
4.1.1 Sandwich injection molding
To investigate the influence of processing parameters and glass fiber content on the material
distribution in sandwich injection molding, the polystyrene (PS 165H), unfilled polycarbonate
(Makrolon 2800), and polycarbonate filled with 20 and 35 wt% short glass fiber (Makrolon
8020 and Makrolon 8345) were used. The materials were supplied in granular form by BASF
Chemical Co., Ltd. and BAYER GmbH, Germany, respectively. The sandwich injection
molded part (dumbbell shape) was carried out on an ARBURG ALLROUNDER two-
component injection molding machine (Model: 320S 500-350). The core materials were
colored prior to injection to facilitate the identification of the interface between skin and core
materials. All the specimens were molded after the machine had attained a steady state with
respect to the preset melt and mold temperatures. The selection of the variation range for each
injection parameter was based on the filling technique recommended by the material supplier
and ARBURG’s operating instructions [123]. The effects of the skin/core ratio, molding
parameters, and glass fiber content on the core thickness were varied on three levels, while
other variables were maintained at a constant level throughout this study. Table 4.1 and 4.2
summarize the materials and the various parameter settings. These four materials are
respectively designated as PS, PC, SFRPC20, and SFRPC35. The sandwich combinations
considered are PC/PC, PC/SFRPC20, PC/SFRPC35, SFRPC20/PC, and SFRPC35/PC. In this
nomenclature, the first constitutes the skin while the second designates the core.
Experimental and Simulation Procedures 42
Table 4.1 Material and variation of parameter settings used for investigating the effect of
processing conditions on the skin/core material distribution in sandwich injection molding.
Material Grade Supplier
Polystyrene PS 165 H BASF
1st-Plasticator (Skin) 2nd-Plasticator (Core)
N In
M
* T
ozzle temperature ( °C) 210 / 230 / 260 210 / 230 / 260jection flow rate (ccm / s) 9.25 / 18.5 / 37.0 6.5 / 13.5 / 27.0 / 54.0
* Injection volume (%by volume) 35 / 40 / 45 65 / 60 / 55
old temperature was set at 40 °CTotal cooling time = 40 sec.
otal volume of part = 37.0 ccm
Processing ConditionsSandwich Molding
Table 4.2 Materials and processing parameters used for investigation of the effect of mold
temperature and glass fiber content on the skin/core material distribution in sandwich injection
molding.
Skin Material Core Material (Skin/Core)
PC PC PC/PCPC PC+SGF 20 wt% PC/SFRPC20PC PC+SGF 35 wt% PC/SFRPC35
PC+SGF 20 wt% PC SFRPC20/PCPC+SGF 35 wt% PC SFRPC35/PC
1st-Plasticator (Skin) 2nd-Plasticator (Core)
NInj
ozzle temperature ( oC) 300 300ection flow rate (ccm/s) 14.95 16.65njection volume (% by volume) 50 50
old temperatures were set at 40 °C / 80 °C /120 °CTotal cooling time = 40 sec.
otal volume of part = 37.0 ccm
Sandwich Molding Sample Code
Processing ConditionsSandwich Molding
* I
M
* T
Experimental and Simulation Procedures
43
Polypropylene compounded with short glass fiber is one of the most commercially important
materials and exhibits the most significant development and growth. Therefore, to investigate
the effect of processing technique on the fiber orientation, fiber attrition and mechanical
properties, the unfilled polypropylene (PP-H 1100 L, supplied by TARGOR) and
polypropylene filled with 20 and 40 wt% short glass fiber (PP32G10-0 and PP34G10-9,
supplied by BUNA) were used. The test specimens were also molded on the same machine
which can be employed both for conventional injection molding and sandwich molding.
Injection speed and skin/core volume ratio were chosen as follows: the speed of the first
injection unit (skin material) was kept higher in order to achieve a good surface finish and to
prevent premature solidification of the melt, whereas lower speed was used for the second
injection unit (core material). The latter was done in order to assess the uniform core
extension along the flow direction without the breakthrough of the core material at the far end
of the bar [124-125]. Several settings were tried and those leading to an overall satisfying
quality with regard to visual properties were finally chosen. The mold temperature was 55 °C
and the five heating zones (from nozzle to feed zone) were set to 250 °C, 240 °C, 230 °C, 220
°C, and 210 °C, respectively. The materials and processing parameters used for single and
sandwich molding specimens, containing different short glass fiber contents between skin and
core materials, are given in Table 4.3 and 4.4.
Table 4.3 Materials used for investigation of the effect of processing technique on the fiber
orientation, fiber attrition, phase separation, and mechanical properties.
No. Sample Code
1 PP2 SFRPP203 SFRPP40
Sample CodeSkin Material Core Material (Skin/Core)
4 PP+SGF 20 wt% PP SFRPP20/PP5 PP PP+SGF 20 wt% PP/SFRPP206 PP+SGF 20 wt% PP+SGF 20 wt% SFRPP20/SFRPP207 PP+SGF 40 wt% PP SFRPP40/PP8 PP PP+SGF 40 wt% PP/SFRPP409 PP+SGF 40 wt% PP+SGF 20 wt% SFRPP40/SFRPP2010 PP+SGF 40 wt% PP+SGF 40 wt% SFRPP40/SFRPP40
Single Molding
Sandwich Molding
PP PP+SGF 20 wt% PP+SGF 40 wt%
Experimental and Simulation Procedures 44
Table 4.4 Processing conditions used for investigation of the effect of processing technique on
the fiber orientation, fiber attrition, phase separation, and mechanical properties of single and
sandwich injection moldings.
1st-Plasticator 2nd-Plasticator
Injection pressure (bar) 1000 1000 1000Holding pressure (bar) 800 - 800
Holding time (sec) 25 - 25Back pressure (bar) 20 20 20Cooling time (sec) 40 - 40
Injection flow rate (ccm/s) 18.5 18.5 8.8Screw speed (m/min) 12 12 12
Injection volume (ccm), (%) 37 (100%) 14.8 (40%) 22.2 (60%)
Sandwich MoldingProcessing Conditions Single Molding
4.1.2 Push-pull injection molding
Compared to the conventional injection molding process, the push-pull technique is different
in the way that the mold is fitted with at least two gates. The cavity is firstly filled
simultaneously by the melt from both the units via the two separate gates (see Figure 4.1).
After the two melt fronts meet, the weldline is formed and the filling phase is subsequently
switched to the holding phase. The material solidifies starting at the cavity wall but there is
still molten core and then the first push-pull stroke begins. The control software program
allows the definition of several holding pressures for one stroke from either the first or the
second injection unit. From one of the injection units, polymer melt is pressed into the cavity
resulting in the molten core being pushed through the gate back into the other injection unit
and thus the geometry of weldline is deformed to a tongue shape. One of these movements is
termed as push-pull 1 stroke. The number of strokes can be selected by taking into account
the part’s thickness. When all the strokes are completed, cooling phase follows. As the
thickness of frozen layer increases with the number of strokes within the holding time,
therefore the total cycle time is not notably increased as compared to conventional injection
molding [23].
Experimental and Simulation Procedures
45
MoldMold unitunit
First First plasticatorplasticator
Seco
nd
Seco
nd p
last
icat
orpl
astic
ator
Weldline
(b)(b) (c)(c)(a)(a)
Figure 4.1 Schematic principle of push-pull injection molding process (a) First step, (b)
Second step, and (c) Third step.
The materials used in this study were unfilled polycarbonate (Makrolon 2800) and
polycarbonate filled with 20 and 35 wt % short-glass-fiber (Makrolon 8020 and Makrolon
8345). The dumbbell-shaped specimens were injection molded on ARBURG two-component
injection molding machine. Besides the push-pull processing, conventional injection molding
was also carried out for reference purpose. The material injected from both the units was same
with an addition of a small amount of pigment in one of them to be used as a tracer material.
All the specimens were molded only after the machine had attained a steady state with respect
to the preset melt and mold temperatures. The processing parameters used for push-pull
molding are given in Tables 4.5 and 4.6, respectively.
Experimental and Simulation Procedures 46
Table 4.5 Processing conditions used in this study.
* T
Processing Conditions 1st-Plasticator 2nd-Plasticator
Nozzle temperature (oC) 300 300Injection speed (ccm/s) 30 30Injection pressure (bar) 1000 1000
* Injection volume (% by volume) 62.5 37.5
Total cooling time = 45 sec. Mold temperature = 100 oCotal volume of part = 24.0 ccm
Table 4.6 Parameter settings for push-pull 1, 2, and 3 strokes
Difference of Holding Difference of Holding Difference of Holding Holding Pressure Time Holding Pressure Time Holding Pressure Time
ΔP (bar) (sec) ΔP (bar) (sec) ΔP (bar) (sec)
PC / PC
120
120
Push-Pull 3 strokes
(# 1st / # 2nd)
Sample Code Push-Pull 1 stroke Push-Pull 2 strokes
70 4
4
5
54
70 5 4
120
220
220 4
120 4
5
4
120 4
5220
70 5
4
SFRPC20 / SFRPC20
SFRPC35 / SFRPC35
10
10
10
120
120
120
120
4.2 Microstructure analyses
4.2.1 Skin/core material distribution
For investigating the skin/core material distribution, tensile specimens were cut along the
flow direction through the middle at five different locations, as shown in Figure 4.2. The
sections were then mounted on a stage, after polishing with the help of a metallurgical
Experimental and Simulation Procedures
47
technique. The thickness fraction of the core material ( bδ ) was assessed by optical
microscopy (OLYMPUS model PMG3) and computer aided image analysis (a4i Analysis
version 5.1 and Image-Pro Plus). The measurements were taken at every 6 mm from the gate,
which corresponded to the measured distance ratio ( 0Lxi ) between length of measurement
and total length of specimen (170 mm).
170 mm
Flowdirection
6 mm
4 mm
bδ
Longitudinal area
Skin material
Core material
Figure 4.2 Location of sections for material distribution analysis [126].
4.2.2 Fiber orientation analysis
Polarized light microscopy and computer aided image analysis were also utilized in order to
investigate the fiber orientation distribution. For observing fiber orientation, tensile
specimens were cut parallel to the flow direction into various layers parallel at the middle of
specimen (or weldline position for push-pull molded part) as shown schematically in Figure
4.3. The sections were then polished using a metallurgical technique and mounted on a stage.
In the present case, 500 fibers per sample were measured, establishing histograms and
calculating the fiber orientation variation across only half the thickness of the sections
assuming the symmetry of flow. In order to determine planar fiber orientation in the skin and
Experimental and Simulation Procedures 48
core layers, the second order orientation tensor , introduced by Advani and Tucker [105],
was calculated using the following equation:
11a
∑=
=i
i
N
niN
aϕ
ϕϕ 1
211 cos1 (4.1)
where iϕ is the angle between the individual fibers and the local flow direction and is
the number of fibers with a certain angle
iNϕ
iϕ to the local flow direction. For perfect alignment
along the flow axis, the orientation average ( ) would be equal to 1, whereas when fibers are
randomly oriented to the flow direction it would be 0.5.
11a
X Y (Flow direction)
Z
Weldline Position
20 mm
Figure 4.3 Location of areas for fiber orientation analysis [23, 127].
Experimental and Simulation Procedures
49
4.2.3 Fiber length analysis (Fiber attrition)
For the investigation of fiber lengths within the skin and core layer, the tensile specimens
were cut into seven sections, as shown in Figure 4.4. For the separation of skin and core
materials microtome technique was employed. Short-glass-fibers were isolated from the
composite materials by using an incineration method, according to DIN EN 60. Magnified
fiber images were then digitized semi-automatically with the help of Image-Pro Plus software
running on a personal computer. The fiber length distribution (FLD) was determined by the
average fiber length which was calculated from a minimum of 500 length measurements on
fibers recovered from the incineration of the specimen sections. The percent difference
between the average fiber length inside the granules and the overall glass fiber length inside
the molded part ( ) was used to describe the results. For this purpose the following
equation was employed:
lΔ%
100% ×⎥⎦
⎤⎢⎣
⎡ −=Δ
G
Gj
lll
l (4.2)
with being the average fiber length inside the granules and the local fiber length inside
the individual layers (skin and core layers) of the sections of the parts.
Gl jl
1
2
4
3
6
7
5
25 mm25 mm
25 mm
25 mm
25 mm
25 mm
20 mm
170 mm
Figure 4.4 Location of sections for fiber length distribution analysis.
Experimental and Simulation Procedures 50
4.3 Mechanical testing
Geometry of tensile specimens is shown in Figure 4.5a, according to the recommendation of
DIN EN ISO 527-1/1A/5. Impact bars were obtained from the tensile bars by removing the
clamping parts; these rectangular specimens are of thickness 4 mm, width 10 mm and length 80
mm. A V-notch of 45o ± 1o and a root radius of 0.25 ± 0.05 mm were made by sawing with a
razor blade. The dimension of the Charpy V-notch impact specimen is illustrated in Figure
4.5b, referring to the standard of DIN EN ISO 179/1 e A.
Test specimen
Sprue
Gate
Runner
(a) (b)
Figure 4.5 (a) Dimensions of the injection molded specimen and (b) Geometry of Charpy V-
notch impact.
The molded tensile specimens were tested on Zwick 1464 mechanical tester at a crosshead
speed of 5 mm/min for a sample gage length of 50 mm. For each molding condition, five
dumbbell-shaped specimens were tested and the average values of the maximum tensile stress
were used for analysis. Charpy impact tests were conducted on a CEAST impact tester model
6545 using the specimens with a V-notch. The tests were carried out with impact energy of 1
Joule and a sample span length of 80 mm. The average values of notched Charpy impact
strength (kJ/m2) were obtained again from a group of five specimens.
Experimental and Simulation Procedures
51
4.4. Process simulation
4.4.1 Pre-processing
A simple simulation project can be subdivided into three sections. In the first stage, a model
is created, the boundary conditions are assigned and the calculation is set up. In the
subsequent processing step, the calculation algorithm is applied to the meshed model and
resulting files are automatically saved. This means that the results are not visible immediately.
When displaying results (post-processing), first one has to decide about which information
contained in the extensive result data should be presented. Then, the corresponding data can
be read from the result files and can be displayed graphically. Results from the first
calculation are interpreted. Then the decisions to modification of the part geometry or the
process parameters are made and a new calculation is performed. Additionally, the results
from an analysis can be the basis for the following simulation. For example the results from a
filling analysis are used as a basis for the packing analysis. A cooling analysis can be
attached to a packing analysis. Figure 4.6 shows the typical sequence performed when
simulating the injection molding process.
Open a new project
Create mold model Open / Createa part model
Mesh mold model Create and edit the mesh
If required createrunner system
Assign boundaryconditions
Set up analysis
PrePre--processingprocessing
Create report
Change partgeometry
Change boundaryconditions
Run analysis Create and display results
Are the resultsreasonable ?
Perform furtherAnalysis if
required
If yes
If no
Open a new project
Create mold model Open / Createa part model
Mesh mold model Create and edit the mesh
If required createrunner system
Assign boundaryconditions
Set up analysis
PrePre--processingprocessing
Create report
Change partgeometry
Change boundaryconditions
Run analysis Create and display results
Are the resultsreasonable ?
Perform furtherAnalysis if
required
If yes
If no
Figure 4.6 Typical sequence performed in injection molding simulation.
Experimental and Simulation Procedures 52
4.4.2 Simulation approach
4.4.2.1 Simulation of skin/core material distribution in sandwich injection molding
To investigate the effects of processing parameters and glass fiber content on the skin/core
material distribution, the commercial software package, Moldflow, has been utilized in order
to predict the flow behavior and thickness fraction of the core material in the sandwich
injection molding process. The midplane model was first created by a CAD program
(Solidwork) and was meshed by creating triangular elements on the surfaces (3517 nodes,
6296 elements) as demonstrated in Figure 4.7. In the present implementation for the
sandwich injection molding process, each polymer obeys the governing equations for
generalized Hele-Shaw flow of inelastic, non-Newtonian fluids under non-isothermal
conditions [44].
Injection Point
8.0006.7505.5004.2503.000
Mesh thickness (mm)
Figure 4.7 2.5-D mesh model used for the simulation of skin/core material distribution in
sandwich injection molding.
Experimental and Simulation Procedures
53
4.4.2.2 Simulation of 3-D fiber orientation distribution in sandwich and push-pull injection
moldings
At present, a commercial software package for 3-D simulation of two-component injection
molding including the fiber orientation analysis is not yet available. However, from the
process setting of this program (where the user can input the processing parameters i.e. an
injection location, selection of material, definition of mold and melt temperature) it is
possible to control the melt flow profile during the filling phase similar to the melt flow
development during sequential sandwich and push-pull injection molding processes. By
using only one material and controlling the ram speed profile during injection phase for
sandwich injection molding process [128] or utilizing the controlled valve gate with the hot
runner system for push-pull processing [129]. In this study, the 3-D models of sandwich and
push-pull processing have been developed and performed with the aid of Moldflow
simulation program in order to predict the 3-D fiber orientation distribution in the sandwich
and push-pull injection molded parts. First, the 3-D model was created by Solidwork program
and was then meshed by creating tetrahedral elements within the CAD model (see Figures 4.8
and 4.9). This mesh model was then simulated by using the 3-D finite element analysis,
which is based on fluid mechanics and heat transfer calculations. The material properties used
for computer simulation of skin/core material distribution in sandwich injection molding and
for predicting of 3-D fiber orientation distribution in sandwich and push-pull injection
moldings are summarized in Tables 4.7
Table 4.7 Material properties (Moldflow database).
Thermal Conductivity Specific Heat Glass Transition
(W / m °C) (J / kg °C) Temperature (°C)
PP + 40% Short Glass Fiber * Celstran PP-GF40 0.140 at 275 °C 2243 at 275 °C 138
PS PS 165H 0.155 at 230 °C 1975 at 230 °C 92
PC Makrolon 2800 0.173 at 300 °C 1700 at 300 °C 139
PC + 20% Short Glass Fiber Makrolon 8020 0.185 at 300 °C 1530 at 300 °C 150
PC + 35% Short Glass Fiber Makrolon 8345 0.209 at 300 °C 1400 at 300 °C 150
* The material properties of PP filled with 40% short glass fiber from TARGOR (PP34G10-9) are not available in Moldflow database
Materials Trade Name
Experimental and Simulation Procedures 54
Injection Point
Figure 4.8 3-D mesh model used for simulation of fiber orientation during sandwich injection
molding (59,798 nodes, 337,358 tetrahedral elements).
Figure 4.9 3-D mesh model used for simulation of fiber orientation during push-pull
processing (22,352 nodes, 119,355 tetrahedral elements).
Overflow Cavity # 1
Overflow Cavity # 2
Main Cavity
Injection Point
Valve Gate # 1
Valve Gate # 2
Valve Gate # 3
Valve Gate # 4
Hot Runner System
Experimental and Simulation Procedures
55
• Sandwich injection molding
The sandwich injection molding simulation was performed by injecting 40 % vol. of material
(Celstran 40 wt% GF) into the cavity with the injection flow rate of 18.5 ccm/s. After
approximately 1 second, the rest of material (60 %vol.) was then injected into the cavity with
a slower injection flow rate of 8.88 ccm/s until the end of the injection shot. The comparison
of simulation results between single and sandwich injection molding processes is shown in
Figure 4.10.
Single injection molding Sandwich injection molding
40 %vol. of material
Figure 4.10 Three-dimensional simulation results of the melt flow front during the filling
stage for single and sandwich injection moldings.
Experimental and Simulation Procedures 56
• Push-pull processing simulation
To simulate the conventional injection molded part with weldline, valve gates # 2 and # 3
were initially opened whereas valve gates # 1 and # 4 were closed. The simulation started
when the polymer melt was injected from the injection point and passed valve gates # 2 and #
3 into the main cavity and a weldline was formed by the merging of two melt fronts at the
middle of the part, as demonstrated in Figure 4.11a. After the main cavity had been
completely filled, the simulation was switched to the packing phase and the push-pull
processing could be simulated by alternatively opening and closing the valves as described
previously [71,129]. Figure 4.11b to 4.11d demonstrate the simulation results of the push-pull
process, for the number of push-pull 1, 2, and 3 strokes, respectively. In the case of the push-
pull 1 stroke, valve gate # 3 was closed after the main cavity had been filled and a weldline
had been produced and at the same time valve gate # 4 was opened. During this period,
depending on the setting time of the valve gate, the molten polymer flowed continuously
from the main cavity through valve gate # 4 into overflow cavity # 2. For the push-pull 2
strokes, after the first stroke was completed, valve gates # 2 and # 4 were closed and valve
gates # 1 and # 3 were activated. Then the polymer melt flowed in the reverse direction from
the main cavity through valve gate # 1 into overflow cavity # 1. In the case of the push-pull 3
strokes, the third stroke of the push-pull processing simulation started after the second stroke
was completed by closing valve gates # 1 and # 3 and opening valve gates # 2 and # 4. The
polymer melt was again pushed back through the corresponding cavity system.
Experimental and Simulation Procedures
57
Weldline Position
Valve Gate # 1
Valve Gate # 2Valve Gate # 3
Valve Gate # 4
Overflow Cavity # 2 Overflow Cavity # 1
Valve Gate # 1
Valve Gate # 2Valve Gate # 3
Valve Gate # 4
Overflow Cavity # 2 Overflow Cavity # 1
Push-Pull 1 stroke
Valve Gate # 1
Valve Gate # 2Valve Gate # 3
Valve Gate # 4
Overflow Cavity # 2 Overflow Cavity # 1
1st stroke 2nd stroke
Valve Gate # 1
Valve Gate # 2Valve Gate # 3
Valve Gate # 4
Overflow Cavity # 2 Overflow Cavity # 1
2nd stroke1st stroke
3rd stroke
(a) (b)
(c) (d)
Fill time (sec)
11.268.4435.6292.8140.000
Figure 4.11 Evolution of the melt flow front during the simulation: (a) Conventional injection
molding with weldline, (b) Push-pull injection molding 1 stroke, (c) Push-pull injection
molding 2 strokes, and (d) Push-pull injection molding 3 strokes.
Experimental and Simulation Procedures 58 Experimental and Simulation Procedures 58
5. Experimental Results and Discussion
5.1 Comparison between conventional and sandwich injection moldings
5.1.1 Fiber orientation distribution
As Figure 5.1a shows, it was found that there are a number of distinct regions within the
moldings with different fiber alignments. This has also been identified by several other
studies [17, 20, 47, 80-89,120]. The layer at the mold wall, referred to as the surface layer,
tends to have fibers randomly oriented or slightly flow aligned. This randomly oriented
region is caused by fountain flow near the melt front [113]. In particular, fibers from the core
region near the melt front move outward to the wall passing through the fountain flow region.
In the skin region, the fiber orientation is predominately parallel to the flow direction. This is
due to elongational forces arising during fountain flow at the front and to shear flow after the
front has passed. In contrast, a random in plane alignment of fibers is observed in the core
layer due to a slower cooling rate and lower shearing. Moreover, the micrographs clearly
reveal that voids are mostly located within the core layer. This observation has also been
reported in previous works [85, 96,130]. The presence of voids is mainly attributed to
shrinkage during the cooling stage of injection molding where the molten core undergoes
shrinkage away from the solidified skin layer [130]. Figure 5.2 shows the measured values
for the fiber orientation tensor ( 11a ) vs. the relative thickness (zi / h). From the measured
results obtained in this study, it is interesting to note that the core of the molding appears to
contain a random alignment of fibers ( 11a ≈ 0.5) rather than highly aligned transverse to the
flow direction ( 11a ≈ 0). The explanation for this would be related with the effect of geometry
such as a clamping part of tensile specimen (at the entrance region) where the converging
flow field is established. This can lead to a higher velocity gradient of the flowing melt along
the flow path, and thus resulting in an increase of the fiber orientation within the core layer. It
Experimental Results and Discussion 60
also can be observed that the 11a in the core region of SFRPP20 is higher than in the core of
SFRPP40. These results are in agreement with the work carried out by previous researchers
[83-85] in that an increase of the thickness of the core layer of injection molded short fiber
reinforced thermoplastics appears to be more pronounced as the glass fiber content increases.
Figure 5.1 Optical micrographs in the Z-Y plane of (a) single and (b) sandwich injection
moldings.
VoidsVoids
FlowFlow DirectionDirection
SFRPP20SFRPP20 SFRPP40SFRPP40
Skin Skin LayerLayer
CoreCore LayerLayer
SurfaceSurface LayerLayer
Y
Z(a)
SFRPP20/SFRPP20SFRPP20/SFRPP20 SFRPP40/SFRPP40SFRPP40/SFRPP40
FlowFlow DirectionDirectionY
Z
(b)
Experimental Results and Discussion
61
Figure 5.2 Variation of the 11a component of orientation tensor through the half thickness of
single and sandwich injection molded specimens.
Figure 5.1b shows the fiber orientation inside the skin and core layers of sandwich molded
specimens with different glass-fiber contents. For SFRPP20/SFRPP20 and
SFRPP40/SFRPP40, it can also be seen in Figure 5.2 that the values for 11a within the core
layer are higher than those obtained for single injection moldings. This can be due to two
possible reasons. Firstly, it can be the result of the melt flow front of the first injected
material (which will become the skin material) develops a parabolic velocity profile, near the
mold wall the fibers are generally aligned in the flow direction due to the high velocity
gradient. Prior to the skin material’s reaching the end of the cavity, the second material is
injected to form the core. This material develops a second flow front, pushing the skin
material ahead of it. As shown in Figure 5.3, the velocity at the center of the core material is
higher than that at the skin flow front, because the material injected first solidifies as it comes
into contact with the cold wall of the mold. The solidified skin material can act as a second
mold wall inside the mold cavity, narrowing of the flow channel. Thus the higher the velocity
gradient of core material, the higher is the fiber orientation in the core layer. Secondly, the
slower the injection speed of the second material during the filling stage, the higher the
thickness of the solidified skin layer restricting the cross-sectional area available for the
0.0 0.2 0.4 0.6 0.8 1.00.4
0.5
0.6
0.7
0.8
0.9
1.0
Surface Midplane
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Relative Thickness (zi / h)
Experimental Results
SFRPP20 SFRPP40 SFRPP20/SFRPP20 SFRPP40/SFRPP40
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Experimental Results and Discussion 62
flowing melt. This leads to a higher velocity gradient that tends to increase the fiber
orientation of the adjacent melt layer. These results are in agreement with the work carried
out by previous researchers [47, 81, 119] in that the fibers at the mid-plane become more
flow aligned and the thickness of the core region decreases with the thickness of the cold
boundary layer increasing.
Figure 5.3 Schematic of polymer melt flow profile and resulting fiber layer structure in
sandwich injection molded short fiber composites. [127]
FlowFlow DirectionDirection
FlowFlow DirectionDirection
PrimaryPrimary Skin Skin LayerLayer
CoreCore LayerLayer
SecondarySecondary Skin Skin LayerLayerTotal Skin Total Skin LayerLayer
PrimaryPrimary Skin Skin LayerLayer
CoreCore LayerLayer
Solidified Skin Layer
Skin Material
Mold WallMold Wall
Core Material
Velocity Profile of Skin Material
Velocity Profile of Core Material
FlowFlow DirectionDirection
Experimental Results and Discussion
63
The photomicrographs of longitudinal area of sandwich specimens are illustrated in Figures
5.4a through 5.4e. These pictures clearly indicate that the fibers are highly oriented parallel to
the local flow direction within the skin region, as presented in Figures 5.4a to 5.4c.
Furthermore, in the core region, the higher degree of fiber orientation and lesser voids
(Figures 5.4c-e) of sandwich molded parts are thought to be caused by the shape of the
velocity profile and the thickness of the frozen layer near the wall, as stated earlier.
Figure 5.4 Optical micrographs of longitudinal area (Z-Y plane) of sandwich injection
molded parts: (a) SFRPP20/PP, (b) SFRPP40/PP, (c) SFRPP40/SFRPP20, (d) PP/SFRPP20,
and (e) PP/SFRPP40.
SFRPP20SFRPP20 SFRPP40SFRPP40
SFRPP20SFRPP20
SFRPP40SFRPP40
PPPPPPPP
PPPP PPPP
SFRPP20SFRPP20 SFRPP40SFRPP40
(a) (b) (c)
(d) (e)
Y (Flow direction)
Z
Experimental Results and Discussion 64
5.1.2 Fiber length distribution (Fiber attrition)
Figure 5.5 shows the percent differences between the mean fiber length of the granules and
the overall glass fiber length inside the molded part ( lΔ% ). In all the cases, the fiber length
is much lower in the injection moldings than in the granules, which is due to the fact that
fiber length is always reduced to a limiting value depending on melt viscosity, the intensity of
the shear field and the residence time [91-92]. Furthermore, it is obvious that the mean fiber
length for each subdivision of tensile specimens decreases with the increase of the glass fiber
concentration. This has been observed by many authors [82, 87, 92, 94-95, 99, 102] who
mainly attribute a higher fiber concentration to a higher degree of fiber-fiber interaction and
increased fiber-wall contacts. Moreover, it can be seen that the fiber attrition inside the skin
layer of the injection moldings is higher than that in the core layers. Our experiments with
simple molded geometry showed that the reduction of fiber length for SFRPP20 is
approximately 10-15% in the core and about 20-25% in the skin layer. As pointed out by
previous researchers [83, 131], the fiber length is obviously higher within the core layer than
in the skin layer. This is due to the following mold filling characteristics. The core
component is filled with relatively low shear force compared to the skin component, where
the melt begins to solidify as soon as it comes into contact with the cold mold wall. Therefore,
less deformation is applied to the fibers at the center which results in a higher average fiber
length in the core region. For the higher fiber concentration, a higher degree of fiber
degradation inside the skin and core layers, which accounts for approximately 30% in the
core layer and 40-45% in the skin layer, can be observed. The occurrence of more
pronounced fiber length degradation for the higher fiber concentration is believed to arise
from an increased fiber-fiber interaction in the more viscous melt.
With respect to fiber attrition in the longitudinal direction of the bar, it can be noted that the
effects of different processing types and glass-fiber concentrations do not lead to significant
changes of fiber length. In all the cases, only insignificant differences between the
subdivisions were observable. Probably the effect of the simple mold geometry, used for this
investigation, on fiber length destruction is smaller than that of complicated mold geometry
[132]. Comparing the effect of sandwich and single injection molding processes on the fiber
length inside the skin region, only minor differences were observed. As mentioned earlier,
this is due to a higher shear rate near the mold surface and fiber interactions with the mold
wall. The effect of different processing types on fiber length, however, is more pronounced in
Experimental Results and Discussion
65
the core region. The fiber length distribution within the core layer of the sandwich molding
(SFRPP20/SFRPP20) is slightly lower than the values obtained for the single injection
molding (SFRPP20). For a higher fiber loading, the fiber length inside the core region of
SFRPP40 and SFRPP40/SFRPP40 becomes higher. This can not only be explained by the
narrower flow channel and the higher shear rate occurring during the sandwich molding
process, but also by the higher fiber loading itself, which results in more frequent fiber-fiber
interactions and, thus, higher fiber destruction in the core region of sandwich moldings.
Figure 5.5 Fiber attrition in the skin and core layers at various positions of tensile specimens:
(a) Single and sandwich molded parts containing 20 wt% short glass fibers and (b) Single and
sandwich molded parts containing 40 wt% short glass fibers.
5.1.3 Mechanical properties
Figure 5.6 illustrates the tensile and impact properties of sandwich molding specimens
containing different glass fiber concentrations within the skin and core materials in
comparison to those of single injection molding specimens. It is generally known that the
addition of glass fibers results in an enhancement of the tensile and impact properties [76, 82-
1 2 3 4 5 6 7-50
-40
-30
-20
-10
0-50
-40
-30
-20
-10
0
%Δ l
Position
SFRPP40 (Core layer) SFRPP40 (Skin layer) SFRPP40/SFRPP40 (Core layer) SFRPP40/SFRPP40 (Skin layer)
%Δ l SFRPP20 (Core layer) SFRPP20 (Skin layer) SFRPP20/SFRPP20 (Core layer) SFRPP20/SFRPP20 (Skinlayer) (a)
(b)
Experimental Results and Discussion 66
89, 95-96, 102-103]. The mechanical properties of PP co-injected with glass-fiber reinforced
PP are generally at an intermediate level between those of PP and glass-fiber reinforced PP
alone [133]. It is interesting to note that, for the sandwich injection moldings
(SFRPP20/SFRPP20 and SFRPP40/SFRPP40), the maximum tensile stress and impact
strength are higher than for the single injection moldings (SFRPP20 and SFRPP40). This
improvement of the mechanical properties is considered to be due to a higher degree of fiber
orientation within the core layer (the influence of voids is neglected since the area fraction
between the total area of voids and the cross-sectional area of the specimen is approximately
less than 0.25%). However, comparing the mechanical properties of sandwich molding and
single injection molding, it can be observed that the maximum tensile stress and the impact
strength of sandwich specimens are not as high as one might have expected. This is probably
due to the higher fiber attrition that occurs during sandwich molding process and this fiber
shortening can reduce the fiber reinforcing efficiency [134-136].
Figure 5.6 Maximum tensile stress and impact strength of conventional and sandwich
injection molded parts containing different glass fiber contents.
PP
SFRP
P20/
PP
SFRP
P40/
PP
PP/S
FRPP
20
PP/S
FRPP
40
SFRP
P20
SFRP
P20/
SFRP
P20
SFRP
P40/
SFRP
P20
SFRP
P40
SFRP
P40/
SFRP
P40
0
20
40
60
80
100
Max
imum
Ten
sile
Str
ess
(MPa
) Maximum Tensile Stress Impact Strength
0
2
4
6
8
10
12
14
Impa
ct S
tren
gth
(kJ/
m2 )
Experimental Results and Discussion
67
5.2 Comparison between conventional and push-pull injection moldings
5.2.1 Geometry of weldlines
Figure 5.7 shows the weldline geometries of conventional and push-pull processed specimens
for SFRPC35 / SFRPC35, which are molded at several holding pressure differences. In the
case of conventional injection molding process, a relatively straight weldline is produced
when the holding pressures on both sides are kept same. The geometry of weldline is
deformed to the tongue shape with difference in holding pressure. It has been found that the
position of the weldline at the mold surface does not change even when the pressure
difference is increased. The tongue-shaped weldlines can also be observed for SFRPC20 /
SFRPC20 and PC / PC in the same way. The geometry of weldline for push-pull 2 and 3
strokes processed specimens can be easily observed in the longitudinal area (Z-Y plane), (as
presented later in Figures 5.10 and 5.11).
Figure 5.7 Weldline geometry of SFRPPC35/SFRPC35.
ΔΔP = 0 barP = 0 bar
ΔΔP = 70 barP = 70 bar
ΔΔP = 120 barP = 120 bar
ΔΔP = 120 barP = 120 bar
ΔΔP = 220 barP = 220 bar
ΔΔP = 120 barP = 120 bar
WeldlineWeldlinePositionPosition
ConventionalConventional
PushPush--PullPull 1 1 strokestroke
PushPush--PullPull 1 1 strokestroke
PushPush--PullPull 1 1 strokestroke
PushPush--PullPull 2 2 strokesstrokes
PushPush--PullPull 3 3 strokesstrokes
Holding Holding PressurePressureDifferenceDifference ((ΔΔP)P)
Experimental Results and Discussion 68
5.2.2 Fiber Orientation in Weldline Areas
A typical result of fiber orientation in the weldline area is shown in Figure 5.8. As expected,
it can be seen that fiber orientation in the weldline region consists mainly of fibers which are
parallel to the weldline surface, i.e., perpendicular to the flow direction. This is associated
with the fountain flow phenomena at the melt flow front, as investigated by previous works
[137-142]. As one moves away from the weldline region, the orientation pattern is similar to
that observed in the non-welded specimens.
Figure 5.8 Optical micrographs showing the fiber orientation distribution in the weldline
region of the PC filled with 35 wt% of short-glass-fiber at the midplane location (X-Y plane).
Weldline region
Fountain flow at
the melt flow front
Experimental Results and Discussion
69
The micrographs of the weldline geometries and the fiber orientation pattern across the
thickness of the push-pull processed specimens are illustrated in Figures 5.9 - 5.11 and the
measured values of orientation tensor (a11) within weldline area are shown in Figure 5.12. It
has been found that in the surface layer of weldline position, the fibers still show
perpendicular alignment to the flow direction. This is due to the fact that the melt begins to
solidify as soon as it comes into contact with the cold mold wall. For the push-pull 1 stroke
and 2 strokes processed specimens, it can be clearly seen that the fibers within the weldline
region are highly aligned parallel to the local flow direction and the degree of fiber
orientation in the core layer of push-pull 1 stroke processed specimen increases with
increasing holding pressure difference (see Figure 5.12). However, in the case of the push-
pull 3-strokes processed sample, it should be noted that the third stroke of push-pull does not
produce any major changes in the fiber orientation within the weldline region, particularly in
the core layer, where the fibers are preferentially oriented perpendicular to the flow direction,
as presented in Figures 5.11a. This can be attributed to the heat transfer characteristic of
molten polymer, as reported by Moldflow database, where the thermal conductivity of the
unfilled PC (Makrolon 2800) was 0.173 W/m.K and 0.209 W/m.K for PC filled with 35 wt%
short-glass-fibers (see Table 4.7). In the case of PC filled with 35 wt% short-glass-fibers the
viscosity increases more rapidly and reaches its no-flow temperature sooner than for the
unfilled PC, and thus it could not be manipulated as much as the unfilled PC with the lower
thermal conductivity (see Figure 5.11b). Therefore, the molten core is expected to become
thinner during the push-pull process as – stroke by stroke – solidified layers deposit on the
mold wall, so that the resistance against the screw motion increases.
Experimental Results and Discussion 70
Figure 5.9 Optical micrographs showing the fiber orientation pattern across the thickness (Z-
Y plane) of the push-pull 1 stroke processed specimen.
1 2
3
44
12
34
5
5
Experimental Results and Discussion
71
Figure 5.10 Optical micrographs showing the fiber orientation pattern across the thickness
(Z-Y plane) of the push-pull 2 strokes processed specimen.
12
1st 2nd
1
2
Experimental Results and Discussion 72
Figure 5.11 (a) Optical micrographs showing the fiber orientation pattern across the thickness
(Z-Y plane) of the push-pull 3 strokes processed specimen and (b) Weldline geometry of
push-pull 3 strokes processed specimen for unfilled PC.
1st
3rd
Fiber alignment perpendicular to the flow direction
1st
3rd
(a)
(b)
Experimental Results and Discussion
73
Figure 5.12 Variation of the 11a component of orientation tensor through the half thickness of
conventional and push-pull processed specimens in the weldline area.
5.2.3 Effects of holding pressure difference and fiber concentration on penetration
length of weldline
The optical micrographs of penetration length of weldline for the unfilled PC and PC filled
with different glass-fiber contents (20 and 35 wt %) using various holding pressure
differences are shown in Figures 5.13 to 5.15. It can be seen that the higher the difference in
holding pressure, the longer is the penetration length of weldlines, as expected. However, it
should be noted that the relationship between the pressure difference and the penetration
length of weldline is not linear, (see Figure 5.16) suggesting that this increase in the
penetration length of weldline is not solely due to an increase in holding pressure differences,
but may involve some other parameters including the compressibility of molten polymer
during the holding stage and also the effect of pressure on the viscosity of melt, in that the
greater the pressure the higher the melt viscosity [143]. In comparing the penetration length
0.0 0.2 0.4 0.6 0.8 1.00.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Conventional Push-pull 1 stroke (ΔP = 70 bar) Push-pull 1 stroke (ΔP = 120 bar) Push-pull 1 stroke (ΔP = 220 bar) Push-pull 2 strokes (ΔP = 120 bar) Push-pull 3 strokes (ΔP = 120 bar)
Experimental results
MidplaneSurface
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Relative Thickness (zi / h)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Experimental Results and Discussion 74
of weldline for filled and unfilled PC, it can be observed that the higher the glass fiber
content added into the polymer melt, the shorter the penetration length of the weldline. For
the maximum holding pressure difference, it has been found that the maximum penetration
length of the unfilled PC melt is around 24-25 mm, while in the case of filled PC melt (20
and 35 wt%), it is around 16-18 mm away from the initial weldline position. The decrease in
penetration length of weldline in filled PC melt can be attributed to an increase in viscosity in
the flowing polymer melt [144]. This appears to contradict results of a previous work on the
filled and unfilled PC in which the shortest penetration length of weldline for unfilled PC was
reported [145].
Figure 5.13 Penetration length of weldline across the sample thickness of the molded part for
the unfilled PC at various holding pressure differences.
ΔP = 0 bar
ΔP = 70 bar
ΔP = 120 bar
ΔP = 220 bar
Penetration length of weldline
Experimental Results and Discussion
75
Figure 5.14 Penetration length of weldline across the sample thickness of the molded part for
the PC filled with 20 wt% short glass fibers at various holding pressure differences.
Figure 5.15 Penetration length of weldline across the sample thickness of the molded part for
the PC filled with 35 wt% short glass fibers at various holding pressure differences.
ΔP = 0 bar
ΔP = 70 bar
ΔP = 120 bar
ΔP = 220 bar
Penetration length of weldline
ΔP = 0 bar
ΔP = 70 bar
ΔP = 120 bar
ΔP = 220 bar
Penetration length of weldline
Experimental Results and Discussion 76
Figure 5.16 Relationship between the holding pressure difference and penetration length of
weldline for PC with various glass-fiber contents.
5.2.4 Fiber length distribution in weldline areas
The histogram representing the fiber length distribution for the granules of PC filled with 20
and 35 wt% short-glass-fibers (20G and 35G) is shown in Figure 5.17a. In general, it can be
seen that the higher the fiber loading, the shorter the fiber length, as has been reported by
many authors [82, 87, 92-95, 99]. A further fragmentation of fibers also occurred during
injection molding as presented in Figure 5.17b. Our experiments with simple geometry
showed that the reduction of fiber length is approximately 8-14 %. This is due to the high
shear rates during injection molding when the melt containing fibers has to pass through gates
which are primarily narrow channels of flow. Table 5.1 shows the percent differences
between the mean fiber length of the granules and the mean fiber length ( lΔ% ) within the
weldline area of conventional and push-pull processed parts. It has been found that the effects
of holding pressure difference and the number of push-pull strokes do not lead to significant
changes of fiber length. This may be due to the fact that fiber length is always reduced to a
0 50 100 150 200 2500
5
10
15
20
25Pe
netra
tion
Leng
th o
f Wel
dlin
e (m
m)
Difference of Holding Pressure, ΔP (bar)
PC / PC SFRPC20 / SFRPC20 SFRPC35 / SFRPC35
Experimental Results and Discussion
77
limiting value depending on melt viscosity, the intensity of the shear field and the residence
time [91-92] and thus the fibers can not undergo further fragmentation during push-pull
processing.
Figure 5.17 Histograms representing fiber length distribution (a) within PC granules
containing 20 and 35 wt% short glass fibers and (b) within injection molded article without
weldline.
0-25
25-5
050
-75
75-1
0012
5-15
015
0-17
517
5-20
020
0-22
522
5-25
025
0-27
527
5-30
030
0-32
532
5-35
035
0-37
537
5-40
040
0-42
542
5-45
045
0-47
547
5-50
050
0-52
552
5-55
055
0-57
557
5-60
062
5-65
065
0-67
567
5-70
070
0-72
5
0.00
0.05
0.10
0.15
0.20
0.25
0.30
Average aspect ratio (L/D) = 7.866
G35
Average aspect ratio (L/D) = 10.093μ = 172.209 μm
μ = 129.879 μm
Rel
ativ
e Fi
ber L
engt
h D
istr
ibut
ion
Fiber Length (μm)
G20
Fiber length (μm)
(a)
(b)
0-25
25-5
050
-75
75-1
0012
5-15
015
0-17
517
5-20
020
0-22
522
5-25
025
0-27
527
5-30
030
0-32
532
5-35
035
0-37
537
5-40
040
0-42
542
5-45
045
0-47
547
5-50
050
0-52
552
5-55
055
0-57
557
5-60
062
5-65
065
0-67
567
5-70
070
0-72
5
0.00
0.05
0.10
0.15
0.20
0.25
0.30
SFRPC35Average aspect ratio (L/D) = 7.088
μ = 114.586 μm
Average aspect ratio (L/D) = 9.691
μ = 151.416 μm
Rel
ativ
e Fi
ber L
engt
h D
istr
ibut
ion
Fiber length (μm)
SFRPC20
Fiber length (μm)
Experimental Results and Discussion 78
Table 5.1 Fiber length in the weldline area of conventional and push-pull processed parts.
Difference of Holding Average Fiber Average Aspect (# 1st / # 2nd) Pressure, ΔP (bar) Length (μm) Ratio (L/D)
70 157.028 10.183 8.815
120 150.395 9.703 12.667
220 152.689 9.821 11.335
70 116.802 6.913 10.069
120 112.120 7.159 13.673
220 116.223 6.966 10.514
Difference of Holding Average Fiber Average Aspect (# 1st / # 2nd) Pressure, ΔP (bar) Length (μm) Ratio (L/D)
Difference of Holding Average Fiber Average Aspect (# 1st / # 2nd) Pressure, ΔP (bar) Length (μm) Ratio (L/D)
SFRPC20 / SFRPC20
Push-Pull 2 strokes
Push-Pull 3 strokes
11.260SFRPC35 / SFRPC35 120 115.254 7.086
Sample Code
%Δ l
SFRPC20 / SFRPC20 120 148.754 9.744 13.620
10.412
SFRPC35 / SFRPC35 120 118.736 6.853 8.580
SFRPC20 / SFRPC20 120 154.278 10.143
SFRPC35 / SFRPC35
Sample Code
%Δ l
Sample Code Push-Pull 1 stroke
%Δ l
Experimental Results and Discussion
79
5.2.5 Weldline strength
The photographs of the samples broken during the tensile testing are illustrated in Figure 5.18.
In the case of SFRPC20/SFRPC20 and SFRPC35/SFRPC35, the tensile failure was brittle
without any neck formation and it occurred at the weldline position. The explanation for this
would be related to the existence of the perpendicular fiber alignment around the weldline
surface, which can be a source of stress concentration within the part surface and thus it
would be easy to break at this position when compared to another position away from the
weldline area. On the other hand, for the unfilled PC specimens, the failure was ductile with
necking initiated across the gauge length. This behavior is also in accordance with previous
observation [145].
Figure 5.18 Appearance of fractured specimens of SFRPC35 / SFRPC35.
The maximum tensile stresses of conventional and push-pull processed parts, for PC
containing different short-glass-fiber contents (0, 20, and 35 %wt) are shown in Figure 5.19.
For the unfilled PC, it is found that the presence of the weldline and the effect of push-pull
processing do not have any significant influence on the maximum tensile stress. While, in the
case of short glass fiber reinforced PC, the maximum tensile stress of the samples with
ΔΔP = 0 barP = 0 bar
ΔΔP = 70 barP = 70 bar
ΔΔP = 120 barP = 120 bar
ΔΔP = 120 barP = 120 bar
ΔΔP = 220 barP = 220 bar
ΔΔP = 120 barP = 120 bar
WeldlineWeldlinePositionPosition
ConventionalConventional
PushPush--PullPull 1 1 strokestroke
PushPush--PullPull 1 1 strokestroke
PushPush--PullPull 1 1 strokestroke
PushPush--PullPull 2 2 strokesstrokes
PushPush--PullPull 3 3 strokesstrokes
Holding Holding PressurePressureDifferenceDifference ((ΔΔP)P)
Experimental Results and Discussion 80
weldline is significantly lower than the values obtained for the samples without weldline.
Furthermore, the weldline strength of injection molded PC composites is found to decrease
with the content of reinforcing fibers in the composites. These behaviors are also in
accordance with previous investigations using different composite materials [71, 137-142,
145-146].
Figure 5.19 Maximum tensile stress of conventional and push-pull processed specimens
containing different glass fiber contents.
In comparing the weldline strength of injection molded parts produced by conventional and
push-pull techniques, it can be seen that the weldline strength of the push-pull 1 stroke
processed parts increases with increasing the holding pressure differences. In case of the
highest holding pressure difference (�P = 220 bar), the weldline strength is higher than that
of the conventional molding. In fact the differences are in the range of 40-45%. For the push-
pull 2 strokes processed part, it is also observed that the weldline strength is superior to the
one produced by the conventional injection molding (approximately 25-30 %). This increase
in the weldline strength is supposed to be caused by the higher degree of fiber orientation
PPP
1 st
roke
(Δ
P=70
bar
)
PPP
1 st
roke
(Δ
P=12
0 ba
r)
PPP
3 st
roke
s(Δ
P=12
0 ba
r)
With
out
Wel
dlin
e
PPP
1 st
roke
(ΔP=
220
bar)
PPP
2 st
roke
s (Δ
P=12
0 ba
r)
Wel
dlin
e
0
20
40
60
80
100
120
140
Max
imum
Ten
sile
Str
ess
(MPa
)
PC / PC SFRPC20 / SFRPC20 SFRPC35 / SFRPC35
0
20
40
60
80
100
120
140
Max
imum
Ten
sile
Str
ess
(MPa
)
PPP
1 st
roke
(Δ
P=70
bar
)
PPP
1 st
roke
(Δ
P=12
0 ba
r)
PPP
3 st
roke
s(Δ
P=12
0 ba
r)
With
out
Wel
dlin
e
PPP
1 st
roke
(ΔP=
220
bar)
PPP
2 st
roke
s (Δ
P=12
0 ba
r)
Wel
dlin
e
0
20
40
60
80
100
120
140
Max
imum
Ten
sile
Str
ess
(MPa
)
PC / PC SFRPC20 / SFRPC20 SFRPC35 / SFRPC35
0
20
40
60
80
100
120
140
Max
imum
Ten
sile
Str
ess
(MPa
)
Experimental Results and Discussion
81
along the flow direction within the weldline areas, as mentioned earlier. However, there is
only minor difference in weldline strength observed between push-pull 3 strokes and
conventional injection moldings (around 7-10%). This is due to the perpendicular fiber
alignment in weldline area particularly in the core layer of push-pull 3 strokes processed part,
as stated earlier.
5.3 Prediction of the tensile strength for short fiber reinforced composites
The purpose of developing a theoretical model is to explain and predict the experimental
results. Additionally, the theoretical model should also be able to be verified by the existing
experimental results. As described in the section 2.4.1, the critical fiber length ( cl ) and the
interfacial shear strength between fiber and matrix (τ ) can be calculated by Equations 2.5
and 2.6 for given composites system if the fiber length distribution, the fiber diameter ( d )
and the matrix strength ( mσ ) are given. The required parameters for predicting the strength of
short fiber reinforced composites are given in Tables 5.2 to 5.4. Since the fiber volume
fraction, the matrix strength and the area fraction between skin and core layer have been
given experimentally (the measured data of fiber orientation and length, glass fiber content of
granules and area fraction of skin and core layers are summarized in Appendices A to F),
then the predicted values of UTS for the conventional, sandwich and push-pull injection
molded composites can be estimated following Equations 2.13 to 2.16. The theoretically
calculated results, together with the experimentally determined UTS and weldline strength
are shown in Figures 5.20 to 5.22. It can be seen from Figure 5.20 that the model predictions
show a reasonable agreement with the experimental values, although there are still some
differences in both the cases. The calculated results indicate that the UTS increases with the
increase of fiber volume fraction and the UTS of PP sandwich injected with glass fiber
reinforced PP (PP/SFRPP and SFRPP/PP) are at an intermediate level between those of PP
and glass fiber reinforced PP alone. In addition the predicted results also show the UTS of
sandwich injection moldings are higher than that of single injection moldings. This is due to a
higher degree of fiber orientation within the core layer (or a higher area fraction of skin layer,
C
L
AA ) of sandwich injection molded composites, as mentioned in section 5.1.4, though the
Experimental Results and Discussion 82
fiber length within the core layer of the sandwich moldings are slightly lower than the values
obtained for the single injection moldings.
Figure 5.20 Comparison of experimental and theoretically calculated UTS results for
conventional and sandwich injection molded short glass fiber reinforced polypropylene.
SFR
PP20
/PP
PP/S
FRPP
20
SFR
PP20
SFR
PP20
/SFR
PP20
SFR
PP40
/PP
PP/S
FRPP
40
SFR
PP40
/SFR
PP20
SFR
PP40
SFR
PP40
/SFR
PP40
0
20
40
60
80
100
120
M
axim
um T
ensi
le S
tres
s (M
Pa)
Max
imum
Ten
sile
Str
ess
(MPa
)
Experimental Results Theoretically Calculated Results
0
20
40
60
80
100
120
Experimental Results and Discussion
83
SFR
PP20
/PP
PP/S
FRPP
20SF
RPP
20SF
RPP
20/S
FRPP
20SF
RPP
40/P
PPP
/SFR
PP40
SFR
PP40
/SFR
PP20
SFR
PP40
/SFR
PP40
SFR
PP40
σm
(M
Pa)
28.5
28.5
28.5
28.5
28.5
28.5
28.5
28.5
28.5
Mea
sure
men
tτ
(MPa
)16
.45
16.4
516
.45
16.4
516
.45
16.4
516
.45
16.4
516
.45
Cal
cula
ted
[79]
σf (M
Pa)
3450
3450
3450
3450
3450
3450
3450
3450
3450
[76]
d (μ
m)
1212
1212
1212
1212
12M
easu
rem
ent
l c (μ
m)
1258
.36
1258
.36
1258
.36
1258
.36
1258
.36
1258
.36
1258
.36
1258
.36
1258
.36
Cal
cula
ted
[79]
Vf
0.2
0.2
0.2
0.2
0.4
0.4
0.4/
0.2
0.4
0.4
Mea
sure
men
t
Vm
0.8
0.8
0.8
0.8
0.6
0.6
0.6/
0.8
0.6
0.6
Mea
sure
men
t
AL/A
C
__
0.91
30.
965
__
_0.
938
0.83
4M
easu
rem
ent
AT
/AC
_
0.04
0.08
70.
035
_0.
063
0.05
50.
062
0.16
6M
easu
rem
ent
AS
kin/A
C0.
440.
42_
_0.
410.
420.
42_
_M
easu
rem
ent
AC
ore/A
C0.
560.
54_
_0.
590.
517
0.52
5_
_M
easu
rem
ent
Para
met
ers
Sam
ples
Sour
ce
Tabl
e 5.
2 P
aram
eter
s us
ed in
the
theo
retic
al c
alcu
latio
n of
UTS
for
sing
le a
nd s
andw
ich
inje
ctio
n m
olde
d sh
ort g
lass
fibe
r
rein
forc
ed P
P c
ompo
site
s.
Experimental Results and Discussion 84
PPP
2 st
roke
sPP
P 3
stro
kes
With
out
( ΔP
= 70
bar
)( Δ
P =
120
bar)
( ΔP
= 22
0 ba
r)( Δ
P =
120
bar)
( ΔP
= 12
0 ba
r)W
eldl
ine
σm
(M
Pa)
60.3
360
.33
60.3
360
.33
60.3
360
.33
60.3
3M
easu
rem
ent
τ (M
Pa)
34.8
334
.83
34.8
334
.83
34.8
334
.83
34.8
3C
alcu
late
d [7
9]σ
f (M
Pa)
3450
3450
3450
3450
3450
3450
3450
[76]
d (μ
m)
1515
1515
1515
15M
easu
rem
ent
l c (μ
m)
742.
8974
2.89
742.
8974
2.89
742.
8974
2.89
742.
89C
alcu
late
d [7
9]
Vf
0.2
0.2
0.2
0.2
0.2
0.2
0.2
Mea
sure
men
t
Vm
0.8
0.8
0.8
0.8
0.8
0.8
0.8
Mea
sure
men
t
AS
kin/A
C
0.44
0.76
0.61
0.48
0.60
0.56
0.92
Mea
sure
men
t
AC
ore/A
C
0.56
0.24
0.39
0.52
0.40
0.44
0.08
Mea
sure
men
t
PPP
2 st
roke
sPP
P 3
stro
kes
With
out
( ΔP
= 70
bar
)( Δ
P =
120
bar)
( ΔP
= 22
0 ba
r)( Δ
P =
120
bar)
( ΔP
= 12
0 ba
r)W
eldl
ine
σm
(M
Pa)
60.3
360
.33
60.3
360
.33
60.3
360
.33
60.3
3M
easu
rem
ent
τ (M
Pa)
34.8
334
.83
34.8
334
.83
34.8
334
.83
34.8
3C
alcu
late
d [7
9]σ
f (M
Pa)
3450
3450
3450
3450
3450
3450
3450
[76]
d (μ
m)
1515
1515
1515
15M
easu
rem
ent
l c (μ
m)
742.
8974
2.89
742.
8974
2.89
742.
8974
2.89
742.
89C
alcu
late
d [7
9]
Vf
0.35
0.35
0.35
0.35
0.35
0.35
0.35
Mea
sure
men
t
Vm
0.65
0.65
0.65
0.65
0.65
0.65
0.65
Mea
sure
men
t
AS
kin/A
C
0.41
0.81
0.62
0.52
0.59
0.50
0.89
Mea
sure
men
t
AC
ore/A
C
0.59
0.19
0.38
0.48
0.41
0.50
0.11
Mea
sure
men
t
Para
met
ers
Sour
ceW
eldl
ine
SFR
PC20
/SFR
PC20
PPP
1 st
roke
Para
met
ers
SFR
PC35
/SFR
PC35
Sour
ceW
eldl
ine
PPP
1 st
roke
Tabl
e 5.
3 P
aram
eter
s us
ed in
the
theo
retic
al c
alcu
latio
n of
wel
dlin
e st
reng
th fo
r con
vent
iona
l and
pus
h-pu
ll in
ject
ion
mol
ded
shor
t gla
ss fi
ber r
einf
orce
d P
C c
ompo
site
s.
Experimental Results and Discussion
85
Table 5.4 Mean glass fiber length of injection molded composites.
A comparison between the experimental and predicted results of weldline strength for
conventional and push-pull injection molded short glass fiber reinforced PC composites are
illustrated in Figures 5.21 and 5.22. The predicted results are in satisfactory agreement with
the experiments in that the weldline strength of injection molded composites decreases with
the increase of the fiber volume fraction and the UTS of weldline-containing parts is very
much lower than the values obtained for the parts without weldline. Furthermore, it is evident
that the weldline strength increases with the increase of holding pressure difference (�P) and
the increasing of number of strokes does not have any significant influence on the UTS.
However, it should be noted that the predicted UTS results are still higher than the
experimental ones. The reasons for this are twofold; firstly, the parameters used in the
calculation ( fσ and τ ) are given by various independent methods from literature [76, 79].
The conditions of the tests may be different, which would lead to an error in the calculation.
It is observed in Equations 2.2 to 2.5 that all the orientation measures are independent of the
fiber strength. Only the fiber length efficiency factor ( lf ) depends on the fiber strength,
SFRPP20 (Skin layer) 333.04
SFRPP20 (Core layer) 375.65
SFRPP40 (Skin layer) 184.38 Conventional (Weldline) 151.416
SFRPP40 (Core layer) 232.22 Push-pull 1 stroke (ΔP = 70 bar) 157.028
Push-pull 1 stroke (ΔP = 120 bar) 150.395
Push-pull 1 stroke (ΔP = 220 bar) 152.689
Push-pull 2 strokes (ΔP = 120 bar) 154.278
SFRPP20/SFRPP20 (Skin layer) 332.73 Push-pull 3 strokes (ΔP = 120 bar) 148.754
SFRPP20/SFRPP20 (Core layer) 370.93 Conventional (Without Weldline) 151.416
SFRPP40/SFRPP40 (Skin layer) 183.15
SFRPP40/SFRPP40 (Core layer) 230.95
SFRPP20/PP (Skin layer) 344.05 Conventional (Weldline) 114.586
PP/SFRPP20 (Core layer) 379.81 Push-pull 1 stroke (ΔP = 70 bar) 116.802
SFRPP40/PP (Skin layer) 190.68 Push-pull 1 stroke (ΔP = 120 bar) 112.12
PP/SFRPP40 (Core layer) 224.24 Push-pull 1 stroke (ΔP = 220 bar) 116.223
SFRPP40/SFRPP20 (Skin layer) 193.19 Push-pull 2 strokes (ΔP = 120 bar) 118.736
SFRPP40/SFRPP20 (Core layer) 373.68 Push-pull 3 strokes (ΔP = 120 bar) 115.254
Conventional (Without Weldline) 114.586
SFRPC35/SFRPC35
μ
μ
Push-pull processed parts
SFRPC20/SFRPC20
Single moldings μ
Sandwich moldings μ
(μm)
(μm)
(μm)
(μm)
Experimental Results and Discussion 86
which is the value known with the least degree of accuracy. Therefore, if fσ is not known
with sufficient accuracy, the absolute value of lf may be inaccurate. Secondly, the errors
may arise due to the consideration of the uniform fiber alignment, flaw-free molding, and
both the longitudinal and transverse layers experience the same strain, whereas these
assumptions are difficult to obtain in thermoplastic composites.
Figure 5.21 Comparison of experimental and theoretically calculated weldline strength for
conventional and push-pull injection moldings with 20 %wt short glass fiber reinforced
polycarbonate.
0
20
40
60
80
100
120
140
Max
imum
Ten
sile
Str
ess
(MPa
)
Max
imum
Ten
sile
Str
ess
(MPa
)
Experimental Results for SFRPC20/SFRPC/20
Theoretically Calculated Results for SFRPC20/SFRPC20
0
20
40
60
80
100
120
140
PPP
1 st
roke
(Δ
P=70
bar
)
PPP
1 st
roke
(Δ
P=12
0 ba
r)
PPP
3 st
roke
s(Δ
P=12
0 ba
r)
With
out
Wel
dlin
e
PPP
1 st
roke
(ΔP=
220
bar)
PPP
2 st
roke
s (Δ
P=12
0 ba
r)
Wel
dlin
e
Experimental Results and Discussion
87
Figure 5.22 Comparison of experimental and theoretically calculated weldline strength for
conventional and push-pull injection moldings with 35 %wt short glass fiber reinforced
polycarbonate.
0
20
40
60
80
100
120
140
Max
imum
Ten
sile
Str
ess
(MPa
)
Max
imum
Ten
sile
Str
ess
(MPa
)
Experimental Results for SFRPC35/SFRPC35
Theoretically Calculated Results for SFRPC35/SFRPC35
0
20
40
60
80
100
120
140
PPP
1 st
roke
(Δ
P=70
bar
)
PPP
1 st
roke
(Δ
P=12
0 ba
r)
PPP
3 st
roke
s(Δ
P=12
0 ba
r)
With
out
Wel
dlin
e
PPP
1 st
roke
(ΔP=
220
bar)
PPP
2 st
roke
s (Δ
P=12
0 ba
r)
Wel
dlin
e
Experimental Results and Discussion 88
6. Comparison between Simulation and
Experiment
6.1 Sandwich injection molding
6.1.1 Effect of skin/core volume fraction on the skin/core material distribution
In sandwich injection molding, one of the major tasks is to find out the proper ratio between
the skin and the core materials which is needed to obtain an optimum skin/core sandwich
structure in the molded part. In this study, the virgin polystyrene (PS) was employed in order
to investigate the effect of processing parameters on the skin/core material distribution. In the
case of a simple mold geometry (dumbbell shaped parts), three volume fractions of the core
material (in terms of cavity volume percentage, vol.%), ranging from 55 to 65 vol.% were
injected with the melt temperature of 230 °C. The mold temperature was set at 40 °C and the
skin and core injection flow rates were kept at 18.5 and 27.0 ccm/s, respectively.
Figure 6.1 shows the experimental and numerical results of the effect of varying core volume
fractions on the skin/core material distribution. It is found that the core volume fraction of 60
vol.% produces sandwich injection molded parts without any defect, whereas the lowest core
volume fraction (55 vol.%) shows a large amount of skin material at the far end of the cavity
due to less penetration of the core melt along the flow direction. On the contrary, increasing
the core volume fraction from 60 to 65 vol.%, results in a breakthrough phenomenon because
the amount of skin material is too low and the core melt can easily catch up with the flow
front of the skin material, which generates a defective part and leads to the molding being
discarded.
Comparison between Simulation and Experiment 90
Figure 6.1 Influence of core volume fraction on the material distribution at the end of filling
process: (a) Experiment and (b) Simulation.
For purpose of comparison, a heat transfer coefficient (�) of 1,200 W/m2-K [147] is used in
this calculation and the wall thickness of the model is divided into 20 layers. It can be seen
from Figure 6.1b that the resemblance between numerical simulation and experiment is
strikingly good. Moreover, the prediction by simulation program is also in accordance with
the measured data obtained from the Image-Pro Plus Analysis software, as shown in Figure
6.2, which represents the thickness fraction of the core material at various positions along the
bar. However, it should be noted that the values for the thickness fraction of the core material
are slightly different in the simulation and the experimental results. The measured values are
higher than the predicted values. Following are some possible reasons for these discrepancies.
Firstly, the thermal conductivity of polymer (k) used in the calculations is assumed to be
constant [44]. However, it was found that this property varied considerably with temperature
BreakthroughBreakthrough of of corecore material material at at thethe end of end of thethe barbar
55 vol.% of Core Material
60 vol.% of Core Material
65 vol.% of Core Material
(a) Experimental Results
(b) Simulation Results
55 55 vol.%vol.% of of CoreCore MaterialMaterial
60 60 vol.%vol.% of of CoreCore MaterialMaterial
65 65 vol.%vol.% of of CoreCore MaterialMaterial
Distribution of polymer A and B
Polymer B
Polymer A
Thickness fraction, polymer B
0.96260.72200.48130.24070.000
Comparison between Simulation and Experiment
91
[148]. Secondly, the heat transfer coefficient between the polymer and the mold metal is
more significant for thin wall moldings. In this study, the calculated values of thickness
fraction were still lower than the measured ones, although the suggested value of 1,200
W/m2-K was employed in the simulation [147]. According to a recent measurement of the
heat transfer coefficient [149], it was found that this value is approximately 550 W/m2-K.
Thirdly, the errors may arise due to the use of dimensional analysis to simplify the governing
equations, which assumes the cavity to be thin and flat in that the ratio of cavity thickness to
cavity length is much lower than unity ( 1⟨⟨= LHδ ) [44]. Therefore, errors can occur in the
region containing out-of-plane flow, such as thick sections of the part, which cannot be
accurately modeled by 2.5-D analysis. Finally, the errors may arise due to the assumption of a
steady state and incompressibility of the fluid in the calculations, whereas these are difficult
to achieve during the processing of the polymeric materials.
Figure 6.2 Effect of core volume fraction on the thickness fraction of core material at various
positions of specimen: (a) Experiment and (b) Simulation.
0.0 0.2 0.4 0.6 0.8 1.00.00.10.20.30.40.50.60.70.80.91.0
0.00.10.20.30.40.50.60.70.80.91.0
Relative Cavity Length (xi / L0)
Simulation Results 55 vol.% of Core Material 60 vol.% of Core Material 65 vol.% of Core Material
Thic
knes
s Fr
actio
n of
Cor
e M
ater
ial (δ
/ b)
Experimental Results 55 vol.% of Core Material 60 vol.% of Core Material 65 vol.% of Core Material (a)
(b)
Breakthrough of Core Material
Comparison between Simulation and Experiment 92
6.1.2 Effect of processing parameters on the skin/core material distribution
6.1.2.1 Effect of skin and core melt temperatures
The effect of skin and core melt temperature on the thickness fraction of the core material is
shown in Figures 6.3 and 6.4. The injection flow rates of skin and core melt were set at 18.5
and 27.0 ccm/s, respectively, while the injection volumes of skin and core polymers were
kept at 40 and 60 vol.%, respectively. Experimental results are in good agreement with the
numerical simulation results. In Figures 6.3a and 6.4a, only the skin melt temperature is
varied and the core melt temperature is kept unchanged. It can be seen that an increase in the
skin melt temperature induces a decrease in skin thickness, which results in a thicker core
layer near the gate region and a larger amount of skin polymer in areas that are remote from
the gate. In turn, for the lower skin melt temperature, the thicker skin layer is formed near the
gate area. This can also lead to an increase in the penetration length of the core melt at the far
end of the cavity.
Figure 6.3 Influence of skin/core melt temperature on material distribution at the end of
filling process: (a) Effect of skin melt temperature and (b) Effect of core melt temperature.
Skin / Core = 210oC / 230oC
Skin / Core = 230oC / 230oC
Skin / Core = 260oC / 230oC
Skin / Core = 230oC / 210oC
Skin / Core = 230oC / 230oC
Skin / Core = 230oC / 260oC
Skin / Skin / CoreCore = 210= 210ooC / 230C / 230ooC C
Skin / Skin / CoreCore = 230= 230ooC / 230C / 230ooC C
Skin / Skin / CoreCore = 260= 260ooC / 230C / 230ooC C
Skin / Skin / CoreCore = 230= 230ooC / 230C / 230ooC C
Skin / Skin / CoreCore = 230= 230ooC / 210C / 210ooC C
Skin / Skin / CoreCore = 230= 230ooC / 260C / 260ooC C
Thickness fraction, polymer B
0.96260.72200.48130.24070.000
Experimental results Simulation results
(a)
(b)
Comparison between Simulation and Experiment
93
Figure 6.4 Comparison of predicted and experimental results: (a) Effect of skin melt
temperature and (b) Effect of core melt temperature on core thickness fraction of molded part
at various positions of tensile specimens.
0.0 0.2 0.4 0.6 0.8 1.00.00.10.20.30.40.50.60.70.80.91.0
0.00.10.20.30.40.50.60.70.80.91.0
Thic
knes
s Fr
actio
n of
Cor
e M
ater
ial (δ
/ b)
Relative Cavity Length (xi / L0)
Simulation Results Skin Temp./Core Temp. =230 / 210 oC Skin Temp./Core Temp. =230 / 230 oC Skin Temp./Core Temp. =230 / 260 oC
Experimental Results Skin Temp./Core Temp. = 230 / 210 oC Skin Temp./Core Temp. = 230 / 230 oC Skin Temp./Core Temp. = 230 / 260 oC
0.0 0.2 0.4 0.6 0.8 1.00.00.10.20.30.40.50.60.70.80.91.0
0.00.10.20.30.40.50.60.70.80.91.0
Relative Cavity Length (xi / L0)
Simulation Results Skin Temp./Core Temp. = 210 / 230 oC Skin Temp./Core Temp. = 230 / 230 oC Skin Temp./Core Temp. = 260 / 230 oC
Thic
knes
s Fr
actio
n of
Cor
e M
ater
ial (δ
/ b)
Experimental Results Skin Temp./Core Temp. = 210 / 230 oC Skin Temp./Core Temp. = 230 / 230 oC Skin Temp./Core Temp. = 260 / 230 oC
(a)
(b)
Comparison between Simulation and Experiment 94
The effect of the core melt temperature on material distribution is shown in Figures 6.3b and
6.4b. The results show that the effect of the core melt temperature on material distribution is
more pronounced than that of the skin melt temperature. The core layer near the gate region
is thicker when the core melt temperature is lower. In addition, when the core material is less
viscous, the core melt front advancement increases substantially. This can not only be
explained by the higher core melt temperature and lower core melt viscosity, but also by the
local rate of cooling at the mold center which is relatively slow when compared to that near
the mold wall, this can be explained by the low thermal conductivity of the polymer melt.
Both of the effects just mentioned can lead to the flow front of the core material stretching
easily which results in a reduction of the thickness of the core near the gate, while the core
thickness away from the gate is increased.
6.1.2.2 Effect of skin and core injection flow rates
Figures 6.5 and 6.6 show the effect of skin and core injection flow rate on the thickness
fraction of the core polymer at the end of the filling process. Both the skin and core melt
temperatures were set at 230 °C and the injection volume of skin and core polymers were 40
and 60 vol. %, respectively. It was found that the effect of the skin injection flow rate does
not lead to significant changes in the skin/core configuration of molded parts, as presented in
Figures 6.5a and 6.6a. In all the cases, only insignificant differences with regard to the
thickness fraction values for the core material can be noted between the measured positions.
Probably this can be attributed to the higher cooling rate at the mold wall, which has a greater
effect on the skin melt viscosity than the rise in temperature caused by shear heating. From
the simulation results, it can also be seen that the higher the skin injection flow rate, the lower
the thickness fraction of the skin layer near the gate. This is associated with the shear
thinning behavior of the polymer melt.
Comparison between Simulation and Experiment
95
Figure 6.5 Influence of skin/core injection flow rate on material distribution at the end of
filling process: (a) Effect of skin injection flow rate and (b) Effect of core injection flow rate.
54.0 54.0 ccm/sccm/s
27.0 27.0 ccm/sccm/s
13.5 13.5 ccm/sccm/s
6.5 6.5 ccm/sccm/s
Breakthrough of core material Breakthrough of core material at the end of the barat the end of the bar
CoreCore injectioninjection flowflow raterate
Distribution of polymer A and B
Polymer B
Polymer A
Skin / Core = 9.25 / 27.0 ccm/s
Skin / Core = 18.5 / 27.0 ccm/s
Skin / Core = 37.0 / 27.0 ccm/s
Skin / Core = 18.5 / 54.0 ccm/s
Skin / Core = 18.5 / 27.0 ccm/s
Skin / Core = 18.5 / 13.5 ccm/s
Skin / Core = 18.5 / 6.5 ccm/s
Skin Skin / / CoreCore = 9.25 = 9.25 / 27.0 / 27.0 ccm/sccm/s
Skin Skin / / CoreCore = 18.5 = 18.5 / 27.0 / 27.0 ccm/sccm/s
Skin Skin / / CoreCore = 37.0 = 37.0 / 27.0 / 27.0 ccm/sccm/s
Skin / Core = 18.5 / 54.0 ccm/s
Skin / Core = 18.5 / 27.0 ccm/s
Skin / Core = 18.5 / 13.5 ccm/s
Skin / Core = 18.5 / 6.5 ccm/s
Thickness fraction, polymer B
0.96260.72200.48130.24070.000
(a)
(b)
Experimental results Simulation results
Comparison between Simulation and Experiment 96
Figure 6.6 Comparison of predicted and experimental results: (a) Effect of skin injection flow
rate and (b) Effect of core injection flow rate on core thickness fraction of molded part at
various positions of tensile specimens.
0.0 0.2 0.4 0.6 0.8 1.00.00.10.20.30.40.50.60.70.80.91.0
0.00.10.20.30.40.50.60.70.80.91.0
Thic
knes
s Fr
actio
n of
Cor
e M
ater
ial (δ
/ b)
Relative Cavity Length (xi / L0)
Simulation Results Skin / Core Injection Flow Rate = 37.0 / 27.0 ccm/s Skin / Core Injection Flow Rate = 18.5 / 27.0 ccm/s Skin / Core Injection Flow Rate = 9.25 / 27.0 ccm/s
Experimental Results Skin / Core Injection Flow Rate = 37.0 / 27.0 ccm/s Skin / Core Injection Flow Rate = 18.5 / 27.0 ccm/s Skin / Core Injection Flow Rate = 9.25 / 27.0 ccm/s
0.0 0.2 0.4 0.6 0.8 1.00.00.10.20.30.40.50.60.70.80.91.0
0.00.10.20.30.40.50.60.70.80.91.0
Thic
knes
s Fr
actio
n of
Cor
e M
ater
ial (δ
/ b)
Relative Cavity Length (xi / L0)
Simulation Results Skin / Core Injection Flow Rate = 18.5 / 54.0 ccm/s Skin / Core Injection Flow Rate = 18.5 / 27.0 ccm/s Skin / Core Injection Flow Rate = 18.5 / 13.5 ccm/s Skin / Core Injection Flow Rate = 18.5 / 6.5 ccm/s
Experimental Results Skin / Core Injection Flow Rate = 18.5 / 54.0 ccm/s Skin / Core Injection Flow Rate = 18.5 / 27.0 ccm/s Skin / Core Injection Flow Rate = 18.5 / 13.5 ccm/s Skin / Core Injection Flow Rate = 18.5 / 6.5 ccm/s
(a)
(b)
Comparison between Simulation and Experiment
97
A variation of the core injection flow rate has a more significant effect on the material
distribution than a change in the skin injection flow rate, which is evident from Figures 6.5b
and 6.6b. A decrease in the core injection flow rate leads to a significant reduction of the core
thickness fraction near the gate region, while the penetration length of the core polymer
increases substantially and breakthrough occurs at the far end of the cavity. The reason for
this phenomenon can be related to the slower core injection flow rate, leading to the skin
polymer gaining more time to solidify against the mold wall, which results in a thicker
solidified skin layer close to the gate (see Figure 6.7). This can lead to an increase in the core
melt front advancement. In the case of breakthrough, the skin material does not reach the far
end of mold. Consequently, the core melt front catches up with the skin melt front and ends
up at the far end of the cavity. In contrast, the higher core injection flow rate results in a
higher thickness fraction of the core material near the gate leaving a large amount of skin
polymer at the end of the cavity. This can be explained by the fact that the faster the core
injection flow rate, the higher the shear rate near the mold wall; hence the shear thinning
behavior is more pronounced for the skin polymer.
Figure 6.7 Effect of core injection flow rate on thickness distribution of solidified skin
material.
Thicker solidified skin material GateGate
GateGate Thinner solidified skin material
Skin / Core injection flow rate = 18.5 / 6.5 ccm/s
Skin / Core injection flow rate = 18.5 / 54.0 ccm/s
Comparison between Simulation and Experiment 98
6.1.2.3 Effect of mold temperature
The effect of the mold temperature variation on the skin/core material distribution is shown in
Figure 6.8. In this study the unfilled PC was used for both the skin and core materials, which
were injected with the same melt temperature of 300 °C. The injection volume of core
material was kept at 50 vol.% and the injection flow rate of skin and core melt were
maintained at constant levels of 14.95 and 16.65 ccm/s, respectively. Both of experimental
and predicted results indicate that increasing mold temperature induces an increase in the
core thickness. This is due to the fact that higher mold temperature allows slower cooling of
the polymer melt, resulting in a thinner frozen layer of the skin material, i.e. higher thickness
fraction of core material. On the other hand, at the lower mold temperature, the thicker skin
layer is formed near the gate region. This can also lead to an increase in the penetration
length of the core melt front at the end of the cavity.
Figure 6.8 Effect of mold temperature on the thickness fraction of core material at various
positions of specimen: (a) Experiment and (b) Simulation.
0.0 0.2 0.4 0.6 0.8 1.00.00.10.20.30.40.50.60.70.80.91.00.00.10.20.30.40.50.60.70.80.91.0
Thic
knes
s Fr
actio
n of
Cor
e M
ater
ial (δ
/ b)
Relative Cavity Length (xi / L0)
Simulation Results Mold Temperature = 40oC Mold Temperature = 80oC Mold Temperature = 120oC
Experiental Results Mold Temperature = 40oC Mold Temperature = 80oC Mold Temperature = 120oC (a)
(b)
Comparison between Simulation and Experiment
99
6.1.3 Effect of glass fiber content on the skin/core material distribution
Figure 6.9 shows the effect of the glass fiber content within the skin material on the thickness
fraction of core material. In this investigation, the unfilled PC, PC filled with 20 and 35 wt%
were injected with the skin flow rate of 14.95 ccm/s and 16.65 ccm/s for the core material.
The mold and melt temperature were set at 300 °C and 80 °C, respectively. It can be seen that
the higher the glass fiber content in the skin material, the thicker the frozen layer of skin
material is formed. This can also be attributed to the heat transfer characteristic of molten
polymer, as mentioned in section 5.2.2, where the thermal conductivity of the PC filled with
35 wt% short-glass-fibers was higher than that of unfilled PC. Thus, the viscosity of PC filled
with 35 wt% short glass fibers increases more rapidly and solidifies sooner than for the
unfilled PC, resulting in the thicker solidified skin layer.
Figure 6.9 Effect of glass fiber content within the skin material on core thickness fraction of
molded part at various positions of tensile specimens: (a) Experiment and (b) Simulation.
0.0 0.2 0.4 0.6 0.8 1.00.00.10.20.30.40.50.60.70.80.91.0
0.00.10.20.30.40.50.60.70.80.91.0
Thic
knes
s Fr
actio
n of
Cor
e M
ater
ial (δ
/ b)
Relative Cavity Length (xi / L0)
Simulation results PC/PC SFRPC20/PC SFRPC35/PC
Experimental Results PC/PC SFRPC20/PC SFRPC35/PC (a)
(b)
Comparison between Simulation and Experiment 100
The effect of the glass fiber content within the core material on the thickness fraction of core
material can be observed further in Figure 6.10. The results indicate that the thickness
fraction of core material increases with increasing the glass fiber content. This is associated
with the higher the glass fiber content added into the polymer melt, the higher the viscosity of
the flowing polymer melt [78, 144]. The viscosity versus shear rate curve for three materials
(PC, SFRPC20, and SFRPC35) is shown in Figure 2.1.
Figure 6.10 Effect of glass fiber content within the core material on core thickness fraction of
molded part at various positions of tensile specimens: (a) Experiment and (b) Simulation.
0.0 0.2 0.4 0.6 0.8 1.00.00.10.20.30.40.50.60.70.80.91.0
0.00.10.20.30.40.50.60.70.80.91.0
Thic
knes
s Fr
actio
n of
Cor
e M
ater
ial (δ
/ b)
Relative Cavity Length (xi / L0)
Simulation Results PC/PC PC/SFRPC20 PC/SFRPC35
Experimental Results PC/PC PC/SFRPC20 PC/SFRPC35 (a)
(b)
Comparison between Simulation and Experiment
101
6.1.4 Case study
This experimental study deals with the sandwich injection of a housing part as illustrated in
Figure 6.11. In this case, the sandwich molding technology allows to combine a conductive
filled skin material with a cheaper unfilled or recycled core material based on the same
material for good skin-core adhesion. The industrial goal is to fill a cheaper or recycled
polymer in the core as much as possible and without breakthrough phenomenon. In this study,
the sequential injection was performed in the following steps, as described in section 1.2.1, a
given percentage of the skin material (PS, transparent) is first injected into the cavity,
followed by the injection of the core material (PS, blue color) and finally a much smaller
amount of the skin material is injected to seal the gate. The material and processing
parameters used for the computer prediction are given in Table 6.1 and the amounts of
injected material (in term of cavity volume percentage) are varied according to Table 6.2.
Figure 6.11 Housing and 2.5-D meshed model used in this study.
5.0004.1503.3002.4501.600
Mesh thickness (mm)
Comparison between Simulation and Experiment 102
Table 6.1 Material and processing conditions.
Table 6.2 Amount of injected material.
A comparison between the experimental and simulation results for the housing part is
illustrated in Figures 6.12 to 6.13. In Figure 6.12b the simulation result of the core material
distribution is given in terms of core thickness fraction. The blue area designates the area
which is only occupied by the skin material, while the yellow-green areas indicate the areas
occupied by both the skin and core materials. The simulation results of skin and core material
distribution for different injection volume percentage are given in Figure 6.13. In the case of
Run # 1 (A-B-A = 50-45-5 % by volume), the blue areas are the breakthrough areas as
predicted by the numerical simulation where the core component has broken through the skin
component and can be seen at the part surface, which would lead to discarding of molded part
(see Figure 6.13a). On the other hand, by slightly changing the content of skin and core
materials (Run # 2, A-B-A = 55-40-5 % by volume), it can be seen that the entire surface is
occupied by skin material (see Figure 6.13b). Finally, at the end of filling, one observes a
very good agreement between prediction and experiment.
1st-Plasticator 2nd-Plasticator 1st-Plasticator (Skin Material) (Core Material) (Skin Material)
1 50% 45% 5%2 55% 40.5% 4.5%
* Total volume of part = 30 ccm
Run #
Injection Volume (%by volume)
Material Grade SupplierPolystyrene PS 165 H BASF
1st-Plasticator 2nd-Plasticator (Skin Material) (Core Material)
Melt temperature ( oC ) 230 230Injection flow rate (ccm/s) 18.5 27Injection pressure (bar) 1000 1000Holding pressure (bar) _ 800Holding time (sec.) _ 25
Mold temperature = 40 oCTotal cooling time = 40 sec.
Processing ConditionsSandwich Molding
Comparison between Simulation and Experiment
103
Figure 6.12 Sandwich injection of a housing part: (a) Experimental and (b) Simulation results.
Figure 6.13 (a) Material distribution of skin and core polymers at the end of filling: Injection
volume of A-B-A = 50- 45-5 % (Run # 1).
The breakthrough of core material
Distribution of polymer A and B
Polymer B
Polymer A
Thickness fraction, polymer B
0.96260.72200.48130.24070.000
(a) (b)
Skin material
Skin material
Comparison between Simulation and Experiment 104
Figure 6.13 (b) Material distribution of skin and core polymers at the end of filling: Injection
volume of A-B-A = 55- 40-5 % (Run # 2).
6.2 Simulation of fiber orientation in sandwich injection molding
Comparison between 2.5-D and 3-D simulation of fiber orientation and measurement
In comparing the 2.5-D simulation results for the fiber orientation tensor ( 11a ) across the half
thickness for single and sandwich injection moldings, as depicted in Figure 6.14, there is no
significant discrepancy in both cases. Furthermore, as can be seen from Figure 6.15 the
predicted values of 11a obtained in 2.5-D model are not in accordance with the measurements.
The simulation results show the higher value of 11a within the core region compared to the
skin region, whilst the measured results show the lower value of 11a within the core layer.
This may be probably caused by some factors. Firstly, it can be associated with the effect of
geometry such a clamping part of tensile specimen where the converging flow field is
established. This can lead to a higher velocity gradient of the flowing melt along the flow
path, and thus resulting in an increase of the fiber orientation within the core layer, as
mentioned in section 5.1.1. Secondly, the errors may arise due to the use of dimensional
analysis to simplify the governing equations, which omits the calculation of velocity
No breakthrough
Distribution of polymer A and B
Polymer B
Polymer A
Comparison between Simulation and Experiment
105
component and thermal convection in the gap wise direction [44-45]. Finally, the Hele-Shaw
flow formulation also neglects the transverse flow at the melt front region (the fountain flow
behavior) which has a significant effect on the evolution of fiber orientation during injection
mold filling [150].
Figure 6.14 2.5-D simulation results for the orientation tensor ( 11a ) component at different
layers over the half thickness of single and sandwich injection molded parts.
Single Molding Sandwich Molding
Flow directionFlow directionFiber orientation tensor
Relative thickness = 0 (Surface)
Relative thickness = 1.000 (Midplane)
Relative thickness = 0.120
Relative thickness = 0.262
Relative thickness = 0.423
Relative thickness = 0.601
Relative thickness = 0.794
Relative thickness = 0 (Surface)
Relative thickness = 1.000 (Midplane)
Relative thickness = 0.120
Relative thickness = 0.262
Relative thickness = 0.423
Relative thickness = 0.601
Relative thickness = 0.794
Converging flow
Comparison between Simulation and Experiment 106
Figure 6.15 Comparison of the 2.5-D model prediction and measurement of fiber orientation
tensor ( 11a ) across the half thickness at the middle position of single and sandwich injection
moldings (tensile specimen) for PP filled with 20 wt% of short glass fiber.
The 2.5-D model of the rectangular bar (without clamping part) was used in order to neglect
the effect of converging channel. It can be seen from Figure 6.16 that the fiber orientation
predictions of the rectangular bar give a better qualitative agreement with the experimental
measurements for the orientation profiles as compared to that of the tensile geometry, in
which the values of 11a become lower in the core region. However, there is still no significant
difference in the predicted value of 11a between single and sandwich moldings and the
predicted values of 11a within the skin layer obtained from 2.5-D model are still
underestimated.
0.0 0.2 0.4 0.6 0.8 1.00.4
0.5
0.6
0.7
0.8
0.9
1.0
Midplane
Experimental Results
SFRPP20 SFRPP20/SFRPP20
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Relative Thickness (zi / h)
2.5-D Simulation Results
Single Molding Sandwich Molding
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Surface
Comparison between Simulation and Experiment
107
Figure 6.16 Comparison of the 2.5-D model prediction and measurement of fiber orientation
tensor ( 11a ) across the half thickness at the middle position of single and sandwich injection
moldings (rectangular specimen) for PP filled with 20 wt% of short glass fiber.
Figure 6.17 represents the 3-D simulation result of fiber orientation tensor ( 11a ) at the end of
filling for single injection molding process (injection flow rate of 18.5 ccm/s). It can be seen
that the predicted values of 11a agree reasonably well with the measurements. The simulation
results show the higher degree of fiber orientation in the skin layer as compared to the core
layer, where the fibers are oriented randomly to the flow direction ( 11a ≈ 0.5). This would be
associated with the effect of geometry i.e. a clamping part of tensile specimen, as stated
earlier. It is also indicated in Figure 6.18a that the calculated values of 11a within the core
region of SFRPP20 are higher than that of SFRPP40. This is due to an increase in the
viscosity of the polymer melt, which has more fiber content [78, 144]. The higher the
viscosity of polymer melts the narrower the shear zone during the filling phase, and thus
resulting in a lower degree of fiber orientation in the core region. Furthermore, from the 3-D
simulation results as illustrated in Figures 6.18b to 6.20, it is interesting to note that the
0.0 0.2 0.4 0.6 0.8 1.00.4
0.5
0.6
0.7
0.8
0.9
1.0
Experimental Results
SFRPP20 SFRPP20/SFRPP20
MidplaneSurface
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Relative Thickness (zi / h)
2.5-D Simulation Results
Single Molding Sandwich Molding
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Comparison between Simulation and Experiment 108
sandwich injection moldings show higher values of 11a within the core region as compared to
the single injection moldings. The change in the 11a values is thought to be caused by the
thicker solidified skin layer which develops during the flow of sandwich injection molded
short fiber composites, as mentioned in section 5.1.1. Therefore, the velocity profile of the
following core melt can be sharper and can cause the fibers in the core layer to be more
aligned in the flow direction.
Figure 6.17 3-D simulation result of fiber orientation tensor ( 11a ) for single injection molded
part.
Fiber orientation tensor (a11)
1.000
0.750
0.500
0.250
0.000
Comparison between Simulation and Experiment
109
Figure 6.18 Comparison of the 3-D model prediction and measurement of 11a across the half
thickness at the middle position: (a) single injection molded specimens for PP filled with 20
wt% and 40 wt% of short glass fiber (b) single and sandwich injection molded specimens for
PP filled with 40 wt% of short glass fiber.
0.0 0.2 0.4 0.6 0.8 1.00.4
0.5
0.6
0.7
0.8
0.9
1.0
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
3-D Simulation Results
Single molding Sandwich molding
Experimental Results
SFRPP40 SFRPP40/SFRPP40
MidplaneSurface
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Relative Thickness (zi / h)
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0.0 0.2 0.4 0.6 0.8 1.00.4
0.5
0.6
0.7
0.8
0.9
1.0
Single Injection Moldings
MidplaneSurface
Experimental Results
SFRPP20 SFRPP40
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Relative Thickness (zi / h)
3-D Simulation Results
SFRPP20 SFRPP40
0.4
0.5
0.6
0.7
0.8
0.9
1.0
(a)
(b)
Comparison between Simulation and Experiment 110
Figure 6.19 Comparison of the orientation tensor ( 11a ) component across the thickness for
single and sandwich injection moldings.
Figure 6.20 Comparison of the orientation tensor ( 11a ) component at the mid-plane layer (z =
2.0 mm) for single and sandwich injection moldings.
Flow direction
Flow direction
Single Injection Molding
Sandwich Injection Molding
Sandwich Injection Molding Single Injection Molding
Comparison between Simulation and Experiment
111
6.3 Simulation of fiber orientation in push-pull injection molding
Effect of holding pressure difference and the number of push-pull strokes on 3-D fiber
orientation in weldline areas
Figures 6.21 and 6.22 represent the 3-D simulation results of fiber orientation tensor ( 11a ) for
conventional and push-pull injection molding processes. In the case of conventional injection
molding with weldline, the predicted results indicate that the fibers near the part surface are
randomly oriented. Near the midplane of the part (core layer), the fibers are mainly aligned
perpendicular to the flow direction, which is caused by the fountain flow effect at the melt
front [137-142]. For the push-pull injection moldings, the simulation results show that not
only the degree of fiber orientation increases with increasing holding pressure differences,
but also an increase in the number of strokes does not produce any major changes in fiber
orientation within the weldline area compared to push-pull 1 stroke. These findings are also
in good agreement with previous experimental work concerning the fiber orientation
distribution within the weldline areas of push-pull processed parts. In addition, it can be seen
from Figure 6.22 that the predicted values of orientation tensor components ( 11a ) agree
reasonably well with corresponding experimental measurements. The predicted values of 11a
across the part thickness show the same tendency as the measured ones, although there is still
a slight discrepancy in both cases. One possible factor that may cause the differences between
calculation and measurement is the fiber-fiber interaction coefficient (CI). According to
previous findings [119-120, 122] concerning the comparison between the numerical and
experimental fiber orientation in injection molded part, it has been found that the fiber
orientation predictions are quite sensitive to this coefficient especially near the surfaces of the
part. They also suggested that CI = 0.01 gives a good agreement for the skin layer, whereas CI
= 0.001 is a better choice for the core layer.
Comparison between Simulation and Experiment 112
Figure 6.21 3-D Simulation results of fiber orientation tensor ( 11a ): (a) at midplane layer and
(b) across the part thickness of conventional and push-pull injection moldings, for PC with 35
wt% short glass fibers.
(b)
Push-Pull 1 stroke
Push-Pull 2 strokes
Push-Pull 3 strokesWeldlineWeldline
PushPush--PullPull 1 1 strokestroke
PushPush--PullPull 2 2 strokesstrokes
PushPush--PullPull 3 3 strokesstrokes
11stst
11stst 22ndnd
22ndnd11stst
33rdrd
Z
X
Y Z
X
(a)
WeldlineWeldline PositionPositionFlowFlow DirectionDirection FlowFlow DirectionDirection
PushPush--PullPull 1 1 strokestroke
PushPush--PullPull 2 2 strokesstrokes
PushPush--PullPull 3 3 strokesstrokes
1st
1st
1st
2nd
2nd
3rd
Comparison between Simulation and Experiment
113
0.0 0.2 0.4 0.6 0.8 1.00.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
MidplaneSurface
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Relative Thickness (zi / h)
Weldline Push-Pull 1 stroke (ΔP = 70 bar) Push-Pull 1 stroke (ΔP = 120 bar) Push-Pull 1 stroke (ΔP = 220 bar) Push-Pull 2 strokes (ΔP = 120 bar) Push-Pull 3 strokes (ΔP = 120 bar)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Figure 6.22 Predicted and measured values of 11a orientation tensor component across the
half thickness at the weldline position of conventional and push-pull injection moldings, for
PC with 35 wt% short glass fibers.
Simulation Results
Experimental Results
0.0 0.2 0.4 0.6 0.8 1.00.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
MidplaneSurface
Orie
ntat
ion
Tens
or C
ompo
nent
(a11
)
Relative Thickness (zi / h)
Weldline Push-Pull 1 stroke (ΔP = 70 bar) Push-Pull 1 stroke (ΔP = 120 bar) Push-Pull 1 stroke (ΔP = 220 bar) Push-Pull 2 strokes (ΔP = 120 bar) Push-Pull 3 strokes (ΔP = 120 bar)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Comparison between Simulation and Experiment 114
7. Conclusions
The present study was concentrated on investigating the capabilities of the sandwich and
push-pull injection molding processes to enhance the orientation of fibers and its effect on the
attrition of fiber length since these are critical to the mechanical performance of short fiber
composites. The accuracy of the model prediction was verified by comparing with the
corresponding experimental measurements. Results and conclusions obtained during this
study can be summarized as:
• A sandwich injection molding technique was employed to improve the mechanical
properties of short glass fiber reinforced thermoplastics (SFRTs) with respect to the fiber
orientation and fiber attrition within the skin and core layers. The results confirmed the
expected rise in the maximum tensile stress and impact strength as the concentration of the
short glass fibers was increased. The mechanical properties of sandwich injection moldings
were observed to be higher than those of single injection moldings, which can be attributed to
the higher fiber orientation within the core layer. The results obtained by analyzing the fiber
attrition inside the skin and core regions in the longitudinal direction of tensile specimens
showed that the degree of fiber degradation inside the skin layers was higher than in the core
layers. There were only minor differences in the skin region fiber length observed between
sandwich and single injection molding processes, this effect was more pronounced in the core
region and for the higher fiber concentration.
• A theoretical model derived by an analytical method of modified rule of mixtures
(MROM) as a function of the area fraction between skin and core layers has been introduced
to predict the ultimate tensile strength (UTS) of conventional, sandwich and push-pull
injection molded composites. The effects of fiber length, fiber orientation and fiber content
on the tensile strength of SFRTs were studied in detail. The present model was verified to
Conclusions 116
existing experimental results, and for all cases, the predictions showed satisfying agreement.
The differences between calculated and experimental data may result from some parameters
and assumptions made in the derivation of the equations, which would lead to errors in the
calculations.
• A push-pull injection molding technique was employed to enhance the weldline
strength of short glass fiber reinforced polycarbonate with respect to the fiber orientation and
the fiber length distribution in the weldline areas. The effects of processing parameters
including the number of push-pull strokes, holding pressure differences between both of the
injection units and the effect of glass fiber concentration have been studied. It was found that
the weldline strength of the push-pull 1 stroke processed parts increases with increasing
penetration length of weldline. An increase of the number of strokes did not produce any
major changes in the weldline strength compared to that of push-pull 1 stroke processed part.
The fiber attrition within the weldline area was not significantly affected by the holding
pressure difference and the number of push-pull strokes. An expected nonlinear relationship
between the holding pressure difference and the penetration length of weldline was also
observed, which can be associated with the rheological behavior and heat transfer
characteristics of polymer melt in the cavity.
• The effects of processing parameters and glass fiber concentration on the skin/core
material distribution in sandwich injection molded parts were investigated and extensively
verified against the predicted results performed by the commercial simulation package
(Moldflow). Both the simulated and the experimental results indicated that in order to obtain
an optimum encapsulated skin/core structure in the sandwich injection molded part, it is
necessary to select proper core volume fraction and processing parameters. The results
suggest that the most important processing parameter for controlling the breakthrough
phenomenon was the core injection flow rate, while the skin injection flow rate did not have
any significant influence on the thickness fraction of the core material. The thickness fraction
of core material increases with either an increase in mold temperature and skin melt
temperature or a decrease in core melt temperature. An increase in solidified thickness of skin
material or an increase in thickness fraction of core material, which has higher glass fiber
content can be associated with the heat transfer characteristic and the viscosity of molten
polymer. If a higher proportion of core material is needed for industrial purposes, either the
skin melt temperature or the core injection flow rate has to be increased, or the core melt
Conclusions
117
temperature has to be decreased. A good agreement between simulation and experimental
results indicate that the simulation program can be used as a valuable tool for the prediction
of melt flow behavior during sandwich injection process.
• Structure of fiber orientation in sandwich and push-pull injection molded short fiber
composites have been predicted by the 2.5-D and 3-D numerical analyses. The predictions
solve the full balance equations of mass, momentum, and energy for a generalized Newtonian
fluid. The second-order orientation tensor approach was used to describe and calculate the
local fiber orientation state. Changing the numerical values of orientation tensor ( 11a ) clearly
shows the difference in the capabilities of simulation model. The predicted results obtained
from the 2.5-D was found to be less accurate than that of 3-D model. This is due to the use of
dimensional analysis to simplify the governing equations, which omits the calculation of
velocity component and thermal convection in the gap wise direction. In addition, the Hele-
Shaw flow formulation also neglects the transverse flow at the melt front region (the fountain
flow behavior) which has a significant effect on the evolution of fiber orientation during
injection mold filling. For the 3-D model, the predicted and measured results of 11a were
found to be in a good agreement. However, slight discrepancies were observed at the center
and close to the mold wall which may result from the fiber-fiber interaction coefficient used
in the calculation.
Conclusions 118
8. References
[1] Donald V. Rosato and Dominick V. Rosato, Injection Molding Handbook: The
Complete Molding Operation Technology, Performance, Economics, Second Edition,
Chapman & Hall, New York, 1995.
[2] P.J. Garner and D.F. Oxley, British Patent, 1968, 156(1): 1156-1217.
[3] C. Donovan, K.S. Rabe, W.K. Mammel and H.A. Lord, Recycling plastic by two-shot
molding, Polymer Engineering and Science, 1975, 15(11): 774-780.
[4] W. Fillmann, Verarbeitung treibmittelhaltiger Thermoplaste nach dem
Mehrkomponentenspritzgießverfahren, Kunststoffe, 1977, 67(4): 206-216.
[5] J. MaRoskey, A new low cost co-injection system that reduced product costs, 30th
Annual Conference & Design Recognition of the SPI Structural Plastics Division
(Structural Plastic 2002), 14-16 April 2002, Michigan.
[6] E. Escales, Das ICI-Sandwich-Spritzgießverfahren, Kunststoffe, 1970, 60(11): 847-
852.
[7] H. Eckardt and S. Davies, An introduction to multi-component (sandwich) injection
molding, Plastic & Rubber International, 1979, 4(2): 72-74.
[8] R.A. Malloy, Plastic Part Design for Injection Molding: An Introduction, Hanser
Publishers, New York, 1994.
References
120
[9] K.C. Rush, Gas-assisted injection molding: The new age of plastic molding
technology, Society of Plastics Engineers Annual Technical Conference, Technical
Papers, 1989: 1014-1018.
[10] J. Avery, Gas-Assisted Injection Molding: Principle and Applications, Hanser
Publishers, New York, 2001.
[11] W. Michaeli, A. Brunswick and C. Kujat, Reducing cooling time with water-assisted
injection molding, Kunststoffe Plast Europe, 2000, 90(8): 25-28.
[12] E. Costalas and H. Krauss, Optimized bonding of composites in over-injection,
Kunststoffe Plast Europe, 1995, 85(11): 1887-1891.
[13] J. Rothe, Special injection molding methods, Kunststoffe Plast Europe, 1997, 87(11):
1564-1581.
[14] K. Kuhmann and G.W. Ehrenstein, The influence of flow condition and injection
parameters on the bond strength of compatible material combinations, Society of
Plastics Engineers Annual Technical Conference, Technical Papers, 1997: 451-428.
[15] D.B. Tachalamov and A.M. Cunha, Structure development and mechanical properties
of overmolded parts, Society of Plastics Engineers Annual Technical Conference,
Technical Papers, 2003: 725-729.
[16] A.W. Birley, B. Haworth and J. Batchelor, Physics of Plastics: Processing, Properties
and Materials Engineering, Hanser Publishers, New York, 1992.
[17] P.S. Alan and M.J. Bevis, Multiple live-feed injection molding, Plastic Rubber and
Composites Processing and Applications, 1987, 7(1): 3-10.
[18] H. Becker, G. Fischer and U. Müller, Gegentakt-Spritzgießen technischer Formteile,
Kunststoffe, 1993, 83(3): 165-169.
[19] F. Johannaber and W. Michaeli, Handbuch Spritzgießen, Hanser Verlag, 2001.
References 121
[20] P.J. Hine, R.A. Duckett, I.M. Ward, P.S. Alan and M.J. Bevis, A comparison of short
glass fiber reinforced polypropylene plates made by conventional injection molding
and using shear controlled injection molding, Polymer Composites, 1996, 17(3): 400-
407.
[21] R.L. Reis, A.M. Cunha and M.J. Bevis, Shear controlled orientation injection molding
of polymeric composites with enhanced properties, Society of Plastics Engineers
Annual Technical Conference, Technical Papers, 1998: 487-491.
[22] H.-C. Ludwig, G. Fischer and H. Becker, A quantitative comparison of morphology
and fiber orientation in push-pull processed and conventional injection molded parts,
Composites Science and Technology, 1995, 53(2): 235-239.
[23] S. Patcharaphun and G. Mennig, Investigation on weldline strength of short-glass-
fiber reinforced polycarbonate manufactured through push-pull-processing technique,
Journal of Reinforced Plastics and Composites, 2006, 25(4): 421-435.
[24] I. Kühnert, V. Stoll and G. Mennig, Sequential injection molding: The influence on
weldlines, The 21st annual meeting of the polymer processing society (PPS), Leipzig,
Germany, 19-23 June 2005, ISBN 3-86010-784-4.
[25] G. Mennig and I. Kühnert, Untersuchungen und Verbesserung der Bindenahtfestigkeit
von technischen Bauteilen aus kurzfaserverstärkten Thermoplasten,
Forschungsbericht des Forschungskuratoriums Maschinebau e.V., FKM-Heft 283,
AiF-Abschlussbericht 2004.
[26] P.S. Allan and M.J. Bevis, British Patent No. 2170-140-B, 1987.
[27] L. Wang, P.S. Alan and M.J. Bevis, Enhancement of internal weldline strength in
thermotropic liquid crystal polymer moldings, Plastic Rubber and Composites
Processing and Applications, 1995, 23(3): 139-150.
[28] R.S. Spencer and G.D. Gilmore, Some flow phenomena in the injection molding of
polystyrene, Journal of Colloid Science, 1951, 6(2): 118-132.
References
122
[29] R.L. Ballman, T. Schusman and H.L. Toor, Injection molding: Flow of a molten
polymer into a cold cavity, Industrial and Engineering Chemistry, 1959, 51(7): 847-
850.
[30] R.B. Staub, Effect of basic polymer properties on injection molding behavior, Society
of Plastics Engineers Annual Technical Conference, Technical Papers, 1961: 345-348.
[31] D.H. Harry and R.G. Parrot, Numerical simulation of injection molding filling,
Polymer Engineering and Science, 1970, 10(4): 209-214.
[32] G. Williams and H.A. Lord, Mold-filling studies for the injection molding of
thermoplastic materials. Part 1: The flow of plastic materials in hot- and cold-walled
circular channels, Polymer Engineering and Science, 1975, 15(8): 553-568.
[33] P. Thienel and G. Menges, Mathematical and experimental determination of
temperature, velocity, and pressure fields in flat molds during the filling process in
injection molding of thermoplastics, Polymer Engineering and Science, 1978, 18(4):
314-320.
[34] M.R. Kamal and S. Kenig, The injection molding of thermoplastics part 1:
Theoretical model, Polymer Engineering and Science, 1972, 12(4): 294-301.
[35] M.R. Kamal and S. Kenig, The injection molding of thermoplastics part 2:
Experimental test of model, Polymer Engineering and Science, 1972, 12(4): 302-308.
[36] J.L. Berger and C.G. Gogos, A numerical simulation of the cavity filling process with
PVC in injection molding, Polymer Engineering and Science, 1973, 13(2): 102-112.
[37] P.C. Wu, C.F. Huang and C.G. Gogos, Simulation of the mold-filling process,
Polymer Engineering and Science, 1974, 14(3): 223-230.
[38] J.F. Stevenson, A. Galskoy, K.K. Wang, I. Chen and D.H. Reber, Injection molding in
disk-shaped cavities, Polymer Engineering and Science, 1977, 17(9): 706-710.
References 123
[39] H.A. Lord and G. Williams, Mold-filling studies for the injection molding of
thermoplastic materials. Part 2: The transient flow of plastic materials in the cavities
of injection-molding dies, Polymer Engineering and Science, 1975, 15(8): 569-582.
[40] R.E. Nunn and R.T. Fenner, Flow and heat transfer in the nozzle of an injection
molding machine, Polymer Engineering and Science, 1977, 17(11): 811-818.
[41] C.A. Hieber, R.K. Upadhyay and A.I. Isayev, Non-isothermal polymer flow in non-
circular runners, Plastic Engineering, 1983, 39(3): 48.
[42] C.A. Hieber and S.F. Shen, A finite-element/finite-difference simulation of the
injection-molding filling process, Journal of non-Newtonian Fluid Mechanics, 1980,
7(1): 1-32.
[43] E.C. Bernhardt, Computer Aided Engineering for Injection Molding, Hanser
Publishers, New York, 1987.
[44] P. Kennedy, Flow Analysis of Injection Molds, Hanser Publishers, New York, 1995.
[45] C.L. Tucker, Computer Modeling for Polymer Processing, Hanser Publishers, New
York, 1995.
[46] H.H. Chiang, C.A. Hieber and K.K. Wang, A unfilled simulation of the filling and
post-filling stages in injection molding Part 1: Formulation, Polymer Engineering and
Science, 1991, 31(2): 116-124.
[47] M. Gupta and K. K. Wang, Fiber orientation and mechanical properties of short-fiber-
reinforced injection-molded composites: Simulated and experimental results, Polymer
Composites, 1993, 14(5): 367-382.
[48] H.H. Chiang, K. Himasekhar, N. Santhanam and K.K. Wang, Integrated simulation of
fluid-flow and heat-transfer in injection-molding for the prediction of shrinkage and
warpage, Journal of Engineering Materials and Technology: Transaction of the
ASME, 1993, 115(1): 37-47.
References
124
[49] J. Wortberg and G. Burmann, Computer design of hot-runner systems, Kunststoffe
1992, 82(2): 91-94.
[50] S. Roth, B. Küster and H. Sura, Practical comparison of simulation techniques: 2.5-D
or 3-D?, Plast Europe, 2004, 94(7): 65-67.
[51] B.E. VerWeyst, C.L. Tucker III, P.H. Foss and J.F. O’Gara, Fiber orientation in 3-D
injection molded features: Prediction and experiment, International Polymer
Processing, 1999, 14(4): 409-420.
[52] J.F. Hetu, D.M. Gao, A. Garcia-Rejon and G. Salloum, 3-D finite element method for
the simulation of the filling stage in injection molding, Polymer Engineering and
Science, 1998, 38(2): 223-236.
[53] J. Zachert and W. Michaeli, Simulation and analysis of three-dimensional polymer
flow in injection molding, Journal of Reinforced Plastics and Composites, 1998,
17(10): 955-962.
[54] R.Y. Chang and W.H. Yang, Numerical simulation of mold filling in injection
molding using a three-dimensional finite volume approach, International Journal for
Numerical Methods in Fluids, 2001, 37: 125-148.
[55] E. Pichelin and T. Coupez, Finite element solution of the 3-D mold filling problem for
viscous incompressible fluid, Computer Methods in Applied Mechanics and
Engineering, 1998, 163(1-4): 359-371.
[56] R. Han, L.H. Shi and M. Gupta, Three-dimensional simulation of microchip
encapsulation process, Polymer Engineering and Science, 2000, 40(3): 776-785.
[57] G.A.A.V. Haagh and F.N. Van de Vosse, Simulation of three-dimensional polymer
mold filling processes using a pseudo-concentration method, International Journal for
Numerical Methods in Fluids, 1998, 28(9): 1355-1369.
References 125
[58] V. Rajupalem, K. Talwar and C. Friedl, Three-dimensional simulation of the injection
molding process, Society of Plastics Engineers Annual Technical Conference,
Technical Papers, 1997: 670-673.
[59] K. Talwar, F. Costa, V. Rajupalem, L. Antanovski and C. Friedl, Three-dimensional
simulation of plastic injection molding, Society of Plastics Engineers Annual
Technical Conference, Technical Papers, 1998: 562-566.
[60] L.S. Turng and V.W. Wang, Simulation of co-injection and gas-assisted injection
molding, Society of Plastics Engineers Annual Technical Conference, Technical
Papers, 1991: 297-299.
[61] G. Schlatter, A. Davidoff, J.F. Agassant and M. Vincent, Numerical simulation of the
sandwich injection molding process, Society of Plastics Engineers Annual Technical
Conference, Technical Papers, 1995: 456-460.
[62] G. Schlatter, A. Davidoff, J.F. Agassant and M. Vincent, An unsteady multi-fluid
flow model: Application to sandwich injection molding process, Polymer Engineering
and Science, 1999, 39(1): 78-88.
[63] D.J. Lee, A.I. Isayev and J.L. White, Simultaneous sandwich injection molding:
Simulation and experiment, Society of Plastics Engineers Annual Technical
Conference, Technical Papers, 1998: 346-350.
[64] C.T. Li, D.J. Lee and A.I. Isayev, Interface and encapsulation in simultaneous co-
injection molding of disk: Two-dimensional simulation and experiment, Society of
Plastics Engineers Annual Technical Conference, Technical Papers, 2002: 465-469.
[65] C. Jaroschek, Passgenaue Verteilung des Kernmaterials, Kunststoffe 2004, 94(5): 68-
71.
[66] S.C. Chen, K.F. Hsu and K.S. Hsu, Analysis and experimental study of gas
penetration in gas-assisted injection-molded spiral tube, Journal of Applied Polymer
Science, 1995, 58(4): 793-799.
References
126
[67] S.C. Chen, K.F. Hsu and K.S. Hsu, Polymer melt flow and gas penetration in gas-
assisted injection molding of a thin part with gas channel design, International Journal
of Heat and Mass Transfer, 1996, 39(14): 3003-3019.
[68] D.M. Gao, K.T. Nguyen, R.A. Garcia and G. Salloum, Numerical modeling of the
mold filling stage in gas-assisted injection molding, International Polymer Processing,
1997, 12(3): 267-277.
[69] T.J. Wang, H.H. Chiang, X. Lu and F. Lihwa, Computer simulation and experimental
verification of gas-assisted injection molding, Journal of Injection Molding
Technology, 1998, 2(3): 120-127.
[70] J.F.T. Pittman, P. Aguirre and D. Ding, Development of a computer simulation of
SCORIM: In-mold shearing with cooling and solidification, International Polymer
Processing, 1996, 11(3): 248-256.
[71] R. Brunotte, I. Kühnert and G. Mennig, Einfluss von pulsierendem Nachdruck auf die
Festigkeit von Bindenähten, Tagungsband, TECHNOMER’03, 18, Fachtagung über
Verarbeitung und Anwendung von Polymeren, 13-15 November 2003, Chemnitz,
ISBN 3-00-012510-8.
[72] R.E. Khayat, A. Derdouri and L.P. Hebert, A 3-dimentional boundary-element
approach to gas-assisted injection molding, Journal of non-Newtonian Fluid
Mechanics, 1995, 57(2-3): 253-270.
[73] G.A.A.V. Haagh, H. Zuidema, F.N. Van de Vosse, G.W.M. Peters and H.E.H. Meijer,
Towards a 3-D finite element model for the gas-assisted injection process,
International Polymer Processing, 1997, 12(3): 207-215.
[74] F. Ilinca and J.F. Hetu, Three-dimensional finite element solution of gas-assisted
injection molding, International Journal for Numerical Methods in Engineering, 2002,
53(8): 2003-2017.
References 127
[75] F. Ilinca and J.F. Hetu, Three-dimensional simulation of multi-material injection
molding: Application to gas-assisted and co-injection molding, Polymer Engineering
and Science, 2003, 43(7): 1415-1427.
[76] S.M. Lee, Handbook of Composite Reinforcements, VCH Publishers, New York,
1992.
[77] D.W. Clegg, Recycling of polymer composites, Handbook of Polymer-Fiber
Composites, Polymer Science and Technology Series, Longman Scientific &
Technical, New York, 1994.
[78] F.N. Cogswell, Polymer Melt Rheology: A guide for industrial practice, George
Godwin, London, 1981.
[79] I.S. Miles and S. Rostami, Multicomponent Polymer Systems, Polymer Science and
Technology Sires, Longman Scientific & Technical, New York, 1992.
[80] P.F. Bright, R.J. Crowson and M.J. Folkes, Study of effect of injection speed on fiber
orientation in simple moldings of short glass fiber filled polypropylene, Journal of
Material Science, 1978, 13(11): 2497-2506.
[81] P. Gerard, J. Raine and J. Pabiot, Characterization of fiber and molecular orientations
and their interaction in composite injection molding, Journal of Reinforced Plastics
and Composites, 1998, 17(10): 922-934.
[82] S.Y. Fu, B. Lauke, E. Mäder, C.Y. Yue and X. Hu, Fracture resistance of short-glass-
fiber-reinforced and short-carbon-fiber-reinforced polypropylene under Charpy
impact load and its dependence on processing, Journal of Materials Processing
Technology, 1999, 89-90: 501-507.
[83] J. Karger-Kocsis and K. Friedrich, Fatigue crack propagation in short and long fibre-
reinforced injection-molded PA 6.6 composites, Composites, 1988, 19(2): 105-114.
References
128
[84] M. Akay and D. Barkley, Processing-structure-property interaction in injection
molded glass-fiber-reinforced polypropylene, Composite Structure, 1985, 3(3-4): 269-
293.
[85] M. Akay and D. Barkley, Fiber orientation and mechanical behavior in reinforced
thermoplastic injection moldings, Journal of Materials Science, 1991, 26(10): 2731-
2742.
[86] M. Pechulis and D. Vautour, The effect of thickness on the tensile and impact
properties of reinforced thermoplastics, Society of Plastics Engineers Annual
Technical Conference, Technical Papers, 1997: 1860-1864.
[87] P. Singh and M.R. Kamal, The effect of processing variables on microstructure of
injection molded short fiber reinforced polypropylene composites, Polymer
Composites, 1989, 10(5): 344-351.
[88] S.E. Barbosa and J.M. Kenny, Analysis of the relationship between processing
conditions fiber orientation-final properties in short fiber reinforced polypropylene,
Journal of Reinforced Plastic and Composites, 1999, 18(5): 413-420.
[89] P. Hess, Mechanischer Eigenschaftsvergleich von langglasfaserverstärkten
Thermoplasten mit kurzglasfaserverstärkten Kunststoffen, Diplomarbeit, Technische
Universität Chemnitz, 2004.
[90] S. Hashemi, K.J. Din and P. Low, Fracture behavior of glass bead-filled
poly(oxymethylene) injection moldings, Polymer Engineering and Science, 1996,
36(13): 1807-1820.
[91] R. von Turkovic and L. Erwin, Fiber fracture in reinforced thermoplastic processing,
Polymer Engineering and Science, 1983, 23(13): 743-749.
[92] V.B. Gupta, R.K. Mittal, P.K. Sharma, G. Mennig and J. Wolters, Some studies on
glass-fiber-reinforced polypropylene, Part 1: Reduction in fiber length during
processing, Polymer Composites, 1989, 10(1): 8-15.
References 129
[93] B. Franzen, C. Klason, J. Kubat and T. Kitano, Fiber degradation during processing of
short fiber reinforced thermoplastics, Composites, 1989, 20(1): 65-76.
[94] V.B. Gupta, R.K. Mittal, P.K. Sharma, G. Mennig and J. Wolters, Some studies on
glass-fiber-reinforced polypropylene, Part 2: Mechanical properties and their
dependence on fiber length, interfacial adhesion, and fiber dispersion, Polymer
Composites, 1989, 10(1): 16-27.
[95] J. Denault, T. Vu-Khanh and B. Foster, Tensile properties of injection molded long
fiber thermoplastic composites, Polymer Composites, 1989, 10(5): 313-321.
[96] R. Bailey and B. Rzepka, Fiber orientation mechanisms for injection molding of long
fiber composites, International Polymer Processing, 1991, 6(1): 35-41.
[97] J.C. Halpin and J.L. Kardos, Strength of discontinuous reinforced composites: Fiber
reinforced composites, Polymer Engineering and Science, 1978, 18(6): 496-504.
[98] J.L. Kardos and J.C. Halpin, Short predicting the strength and toughness of fiber
composites, Macromolecular Symposia, 1999, 147: 139-153.
[99] M. Xia, H. Hamada and Z. Maekawa, Flexural stiffness of injection molded glass
fiber reinforced thermoplastics, International Polymer Processing, 1995, 10(1): 74-81.
[100] H. Fukuda and T.W. Chou, A probabilitistic theory of the strength of short fiber
composites with variable fiber length and orientation, Journal of Materials Science,
1982, 17(4): 1003-1011.
[101] P.A. Templeton, Strength predictions of injection molding compounds, Journal of
Reinforced Plastics and Composites, 1990, 9(3): 210-225.
[102] S.Y. Fu and B. Lauke, Effects of fiber length and fiber orientation distributions on the
tensile strength of short fiber reinforced polymers, Composites Science and
Technology, 1996, 56(10): 1179-1190.
References
130
[103] J.L. Thomason, Micromechanical parameters from macromechanical measurements
on glass reinforced polypropylene, Composites Science and Technology, 2002, 62(10-
11): 1455-1468.
[104] G.B. Jeffery, The Motion of Ellipsoidal Particles Immersed in a Viscous Fluid,
Proceedings of the Royal Society of London A102, 1922: 161-179.
[105] S.G. Advani and C.L. Tucker III, The use of tensors to describe and predict fiber
orientation in short fiber composites, Journal of Rheology, 1987, 31(8): 751-784.
[106] G.L. Hand, A theory of anisotropic fluids, Journal of Fluid Mechanics, 1962, 13(1):
33-46.
[107] S.G. Advani and C.L. Tucker III, A numerical simulation of short fiber orientation in
compression molding, Polymer Composites, 1990, 11(3): 164-173.
[108] S.T. Chung and T.H. Kwon, Numerical simulation of fiber orientation in injection
molding of short fiber reinforced thermoplastics, Polymer Engineering and Science,
1995, 35(7): 604-618.
[109] P.D. Patel and D.C. Bogue, The effect of molecular orientation on the mechanical
properties of fiber filled amorphous polymers, Polymer Engineering and Science,
1981, 21(8): 449-456.
[110] C.W. Camacho, C.L. Tucker III, S. Yalvac and R.L. McGee, Stiffness and thermal
expansion predictions for hybrid short fiber composites, Polymer Composites, 1990,
11(4): 229-239.
[111] N.M. Neves, G. Isdell, A.S. Pouzada and P.C. Powell, On the effect of the fiber
orientation on the flexural stiffness of injection molded short fiber reinforced
polycarbonate plates, Polymer Composites, 1998, 19(5): 640-651.
[112] S.G. Advani and C.L. Tucker III, Closure approximations for 3-dimensional structure
tensors, Journal of Rheology, 1990, 34(3): 367-386.
References 131
[113] R.S. Bay and C.L. Tucker III, Fiber orientation in simple injection molding, Part 1:
Theory and numerical methods, and Part 2: Experimental results, Polymer
Composites, 1992, 13(4): 317-341.
[114] J.S. Cintra and C.L. Tucker III, Orthotropic closure approximations for flow-induced
fiber orientation, Journal of Rheology, 1995, 39(6): 1095-1122.
[115] K.H. Han and Y.T. Im, Modified hybrid closure approximation for predicting of flow-
induced fiber orientation, Journal of Rheology, 1999, 43(3): 569-589.
[116] F. Folgar and C.L. Tucker III, Orientation behavior of fibers in concentrated
suspensions, Journal of Reinforced Plastics and Composites, 1984, 3(2): 98-119.
[117] W.C. Jackson, S.G. Advani and C.L. Tucker III, Predicting the orientation of short
fibers in thin compression moldings, Journal of Composite Materials, 1986, 20(6):
539-557.
[118] M.R. Kamal and A.T. Mutel, The prediction of flow and orientation behavior of short
fiber reinforced melts in simple flow systems, Polymer Composites, 1989, 10(5): 337-
343.
[119] P.H. Foss, J.P. Harris, J.F. O’Gara, L.P. Inzinna, E.W. Liang, C.M. Dunbar, C.L.
Tucker III and K.F. Heitzmann, Prediction of fiber orientation and mechanical
properties using C-Mold and Abaqus, Society of Plastics Engineers Annual Technical
Conference, Technical Papers, 1996: 501-505.
[120] A. Larsen, Injection molding of short fiber reinforced thermoplastics in a center-gated
mold, Polymer Composites, 2000, 21(1): 51-64.
[121] N.M. Neves, A.J. Pontes and A.S. Pouzada, Experimental validation of morphology
simulation in glass fiber reinforced polycarbonate disc, Journal of Reinforced Plastics
and Composites, 2001, 20(6): 452-465.
References
132
[122] A.J. Pontes, N.M. Neves and A.S. Pouzada, The role of the interaction coefficient in
the prediction of the fiber orientation in planar injection moldings, Polymer
Composites, 2003, 24(3): 358-366.
[123] ARBURG GmbH + Co, A Brief Guide into Injection Molding, 1997.
[124] G. Schlatter, J.-F Agassant, A. Davidoff and M. Vincent, An unsteady multi-fluid
flow model: Application to sandwich injection molding process, Polymer Engineering
and Science, 1999, 39(1): 78-88.
[125] R. Seldezn, Co-injection molding: Effect of processing on material distribution and
mechanical properties of a sandwich molded plate, Polymer Engineering and Science,
2000, 40(5): 1165-1176.
[126] S. Patcharaphun and G. Mennig, Simulation and experimental investigations of
material distribution in the sandwich injection molding process, Polymer-Plastics
Technology and Engineering (in press).
[127] S. Patcharaphun and G. Mennig, Properties enhancement of short-glass-fiber
reinforced thermoplastics via sandwich injection molding technique, Polymer
Composites, 2005, 26(6): 823-831.
[128] S. Patcharaphun and G. Mennig, Three-Dimensional Simulation and Experimental
Investigations of Fiber Orientation in Sandwich Injection Molded Parts,
TECHNOMER’05, 19. Fachtagung über Verarbeitung und Anwendung von
Polymeren, November 2005, Chemnitz, Germany.
[129] S. Patcharaphun, B. Zhang and G. Mennig, Simulation of Three-Dimensional Fiber
Orientation in Weldline Areas during Push-Pull-Processing, Journal of Reinforced
Plastics and Composites (submitted).
[130] M. Akay and D. O’Regan, Generation of voids in fiber reinforced thermoplastic
injection moldings, Plastics, Rubber and Composites Processing and Applications,
1995, 24(2): 97-102.
References 133
[131] D. O’Regan and M. Akay, The distribution of fiber lengths in injection molded
polyamide composite components, Journal of Materials Processing Technology, 1996,
56(1-4): 282-291.
[132] M. Sanou, B. Chung and C. Cohen, Glass fiber-filled thermoplastics, Part 2: Cavity
filling and fiber orientation in injection molding, Polymer Engineering and Science,
1985, 25(16): 1008-1016.
[133] D.A. Messaoud, B. Sanschagrin and A. Derdouri, Co-injection molding: Effect of
processing on material distribution and mechanical properties of short-glass-fiber-
reinforced polypropylene test bar, Society of Plastics Engineers Annual Technical
Conference, Technical Papers, 2002: 645-648.
[134] P.A. Eriksson, A.C. Albertsson, P. Boydell, G. Prautzsch and J.-A.E. Manson,
Prediction of mechanical properties of recycled fiberglass reinforced polyamide 66,
Polymer Composites, 1996, 17(6): 830-839.
[135] S.R. Tremblay, P.G. Lafleur and A. Ait-Kadi, Effect of injection parameters on fiber
attrition and mechanical properties of polystyrene molded parts, Society of Plastics
Engineers Annual Technical Conference, Technical Papers, 1999: 432-436.
[136] U. Yilmazer and M. Cansever, Effect of processing conditions on the fiber length
distribution and mechanical properties of glass fiber reinforced nylon-6, Polymer
Composites, 2002, 23(1): 61-71.
[137] A. Savadori, A. Pelliconi and D. Romanini, Weldline resistance in polypropylene
composites, Plastics and Rubber Processing and Applications, 1983, 3(3) : 215-221.
[138] B. Fisa and M. Rahmani, Weldline strength in injection molded glass fiber-reinforced
polypropylene, Polymer Engineering and Science, 1991, 31(18): 1330-1336.
[139] B. Fisa, J. Dufour and T. Vu-Khanh, Weldline integrity of reinforced plastics: Effect
of filler shape, Polymer Composites, 1987, 8(6): 408-418.
References
134
[140] A. Vaxman, M. Narkis, A. Siegman and S. Kenig, Weld-line characteristics in short
fiber reinforced thermoplastics, Polymer Composites, 1991, 12(3): 161-168.
[141] V. M. Nadkarni and S. R. Ayodhya, The influence of knit-lines on the tensile
properties of fiber-glass reinforced thermoplastics, Polymer Engineering and Science,
1993, 33(6): 358-367.
[142] F. Meyer and I. Kühnert, Untersuchungen zur Bindenahtfestigkeit von technischen
Bauteilen aus kurzfaserverstärkten Thermoplasten, Forschungsbericht des
Forschungskuratoriums Maschinebau e.V., FKM-Heft 265, AiF-Abschlussbericht
2001.
[143] N. Sombatsompop, K. Liolios, M.H. Mohd Jamel and A.K. Wood, Techniques for
pressure-density-temperature measurements in polymer melts, Polymers & Polymer
Composites, 1997, 5(4): 259-264.
[144] J. Crown, M.J. Folkes and P.F. Bright, Rheology of short-glass-fiber reinforced
thermoplastics and it application to injection molding 1. Fiber motion and viscosity
measurement, Polymer Engineering and Science, 1980, 20(14): 925-933.
[145] K. Tomari, H. Takashima and H. Hamada, Improvement of weldline strength of fiber
reinforced polycarbonate injection molded articles using simultaneous composite
injection molding, Advances in Polymer Technology, 1995, 14(1): 25-34.
[146] A. Meddad and B. Fisa, Weldline strength in glass fiber reinforced polyamide 66,
Polymer Engineering and Science, 1995, 35(11): 893-901.
[147] K. Ainoya and O. Amano, Accuracy of filling analysis program, Society of Plastics
Engineers Annual Technical Conference, Technical Papers, 2001: 726-730.
[148] N. Sombatsompop and A. K. Wood, Measurement of thermal conductivity of
polymers using an improved Lee’s disc apparatus, Polymer Testing, 1997, 16(3): 203-
223.
References 135
[149] G. Mennig, K. Lunkwitz and D. Lehmann, Chemische Oberflächenmodifizierung
beim Spritzgießen und dessen Wechselwirkung mit dem Verarbeitungsverhalten,
DFG-Abschlussbericht, Technische Universität Chemnitz, 2005.
[150] K.-H. Han and Y.-T. Im, Numerical simulation of three-dimensional fiber orientation
in injection molding including fountain flow effect, Polymer Composites, 2002, 23(2):
222-238.
Curriculum Vitae
Personal data Name: Somjate Patcharaphun
Date of birth: 25 December 1972
Birthplace: Bangkok, Thailand
Nationality: Thai
Marital status: Married
Education 1979 – 1985 Primary school, Santa Cruz Suksa School, Bangkok, Thailand
1986 – 1990 Secondary school, Taweetapisek School, Bangkok, Thailand
1991 – 1994 Bachelor of Engineering (B.Eng.), Faculty of Engineering, King
Mongkut’s Institute of Technology Thonburi (KMITT), Bangkok,
Thailand
1998 – 2000 Master of Engineering (M.Eng.), School of Energy and Materials, King
Mongkut's University of Technology Thonburi (KMUTT), Bangkok,
Thailand
Professional experience 1994 – 1996 Project engineer, Isuzu Motor (Thailand) Co., Ltd.
1996 – 1997 Technical consultant and instructor, Italthai Development Co., Ltd.
1997 – 1998 Project engineer, Telecom Asia Co., Ltd.
since 2000 Lecturer, Department of Materials Engineering Faculty of Engineering,
Kasetsart University, Thailand.
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