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C-S.FR
PROLB : FROM LBM TO
CFD IN INDUSTRIAL
CONTEXT
HATEM TOUIL, CS SI LYON
2
WHAT IS PROLB ?
Accuracy
Competitive turnaround times
Easy setup
LBPhysics (Open Module)
Free and automated post-processing
CFD software based on the Lattice-Boltzmann method
ProLB : GENESIS OF THE SOFTWARE
2005-2008: MIMOSA project,
« Méthodes Innovantes pour la modélisation des sources acoustiques »
› ADEME project involving: Renault, Alstom, SNCF, Ecole Centrale de Lyon, UPMC and Ghanta
› Evaluate LBM approach using existing commercial proprietary software
› PhD thesis of S. Marié: 3D academic code (now associate professor at CNAM Paris)
Conclusions: LBM enables to predict correctly industrial applications but the soft used had a monopoly and
was very expensive.
2008-2009: Renault-CS effort propose a software demonstrator for automotive industry requirements
2009-2013: LaBS project
« Lattice Boltzmann Solver »
› FUI8 project , involving: Renault, CS, Airbus, ENS de Lyon and UPMC.
› Other partners: Matelys et Gantha
› Multi-scale and multi-resolution CFD software development
ProLB : GENESIS OF THE SOFTWARE .
2015-2018: CLIMB project
« ComputationaL methods with Intensive Multiphysics Boltzmann solver »
› BPI project, involving: CS, Renault, Airbus, Ecole Centrale de Lyon, UPMC and AMU (owners).
Partners: Matelys, Gantha, Onera, Univ. Paris Sud, Valeo.
› HPC performance optimization of LaBS
› CS provided with the commercial license : LaBS ProLB
2018-present: Albatros/OMEGA3 project
Airbus, Safran, Cerfacs, Ecole Centrale de Lyon and AMU
5
THEY USE PROLB
40+ users 10+ users
6
LATTICE-BOLTZMANN METHOD
Benefits of Lattice-Boltzmann method:
– Accuracy
– Low numerical dissipation
– Numerical efficiency
Lattice-Boltzmann method:
Transient
Low turnaround times
High accuracy
Lattice Boltzmann Method
Particle velocity discretization (finite discrete velocity set instead of
continuous particle velocity)
Space and time discretization of the discrete-velocity Boltzmann
equation
Lattice structure used in ProLB: D3Q19
Well suited for Unsteady Flow including
noise generation / propagation
7
FASTER TIME TO SOLUTION
Surface Mesh Input file *.labs
Pre-processing Solver Post-processing
PRE-PROCESSING :
•Surface mesh Loading (186 surfaces, 2,3M triangles)
•Problem setup
2h
•SOLVER :
•Volume mesh :
•200 M cells
•Simulated physical time :
•1,4 s
•480 processors
48h
POST-PROCESSING :
•Fully automated post-processing using scripts
•Hundreds of images generated
1h
Other softwares .stl
.nas
.xdmf
.case
Example for a usual drag coefficient calculation :
8
PROLB GUI: LBPRE
Modern, user friendly Graphical User
Interface
Easy setup
Easy template creation using user
variables
Fully-scriptable
Setup 3D display Setup tree
9
PROLB SOLVER: LBSOLVER
High-fidelity, transient simulations
Competitive turnaround times
Fully automated volume mesh generation
Advanced features: Rotating mesh
Results surface mesh refinement (Optimal Surface Refinement)
Advanced automatic initialization (2 Step-Refinement)
LES (SISM) + Wall Law, DNS
Porous media model
Absorbing regions to damp wave reflections at the
boundaries of the fluid domain
Direct advanced outputs (Monitors, Root Mean Square,
Average, Y+, Min value, Max value , …)
Moving mesh
Porous medium
10
PROLB MESH
Fully automated volume mesh generation, based only on Lowest case mesh cell size
Refinement level number
Rotating domain definition
Cartesian / Octree mesh
Immersed boundary conditions
Parallel (multi-core) volume mesh
User Input
exclusion
exclusion
Refinement
exclusion
Refinement
11
PROLB MESH
Mesh example of a high-speed train
(200m)
Mesh Size Cores CPU mesh
generation time
375 420 289 nodes 768 1 hour
Locomotive representation Locomotive mesh representation
12
POST-PROCESSING
Python scripts for common automotive applications using Paraview (batch
and interactive): Aerodynamics
Aeroacoustics
Export file formats: XDMF (HDF5)
Ensight Gold (.case)
Tecplot
13
POST-PROCESSING
2D streamlines Iso Cpi + 2D streamlines Iso Cpi Projected streamlines
14
POST-PROCESSING
Surface iso Cp Velocity planes along
the vehicle
3D streamlines around the
side mirror and A pillar Pressure levels – Thirds:
80 Hz
MODELS
16
Large Eddy Simulations in LBM
Discrete velocities Boltzmann equation:
where is the BGK* collision model
Relaxation time (towards equilibrium)
LBM with Boussinesq hypothesis turbulence like models
𝜈𝑒𝑓𝑓 = 𝜈 + 𝜈𝑡𝑢𝑟𝑏 (SISM** model)
*
**
D3Q19 Lattice
17
Wall modeled Large Eddy Simulations in ProLB
Classical law of the wall for // flows
Curvature effect* ( )
*
18
Wall modeled Large Eddy Simulations in ProLB
Adverse pressure gradient effect*
Characteristic velocity:
Pressure gradient – friction velocitity /ratio:
Law of the wall*:
With
*
APPLICATIONS
20
AERODYNAMICS SIMULATION – DRAG COEFFICIENT CALCULATION
Good
accuracy
Exp.
Calculation
21
AERODYNAMICS SIMULATION – DRAG COEFFICIENT CALCULATION
Rotating mesh around the wheels
Unsteady velocity
Good accuracy
and trend
Cd.A vs Rim variation
Moving wheels setup
22
AERODYNAMICS SIMULATION – RIDE AND HANDLING CALCULATION
Fully automatic setup update from a yaw angle variable
Good
accuracy
Setup Exp.
Calculation
Iso Cpi representation
23
AERODYNAMICS SIMULATION – PANEL LOADING CALCULATION
Pressure load on the driver’s window Pressure load on the panel
Direct unsteady pressure calculation
Coupling with Abaqus and Nastran codes
ProLB CFD results Structure mesh
(Nastran or Abaqus) Projection of ProLB CFD
results on structure mesh
24
AERODYNAMICS SIMULATION – FAN CALCULATION
Rotating fan mesh
Setup Velocity field
Good accuracy
and trend
25
AERODYNAMICS SIMULATION – UNDERHOOD CALCULATION
Porous media model + Rotative Fan
Good accuracy
and trend
Underhood representation
Porous medium Underhood flow
26
AEROACOUSTICS SIMULATION – WALL PRESSURE SIMULATION
Pressure spectrums on the driver window (160 km/h)
Mirror geometries variation :
Aerodynamic fields impact
Wall pressure fluctuation impact
Version initiale Rétroviseur modifié
110
115
120
125
130
135
63 80 100
125
160
200
250
315
400
500
630
800
1000
1250
1600
2000
2500
3150
4000
5000
6300
8000
Fréquence en 1/3 octave (Hz)
dB
(re
f =
2.1
0-5
Pa
)
LaBS - BaseLaBS - Modif.Exp. - BaseExp. - Modif
27
AEROACOUSTICS SIMULATION – INNER NOISE CALCULATION
Direct access to AAC variables (unsteady pressure, Prms, …)
Coupling with Actran for solid propagation
Root Mean Square of the Pressure (Prms) Pressure levels – Thirds: 80 Hz
Mean velocity measured on the Laguna 3 driver's
window in S2A wind tunnel, with and without outside mirror.
Mean velocity calculated on the Laguna 3 driver's window
in S2A wind tunnel, with and without outside mirror.
28
AEROACOUSTICS SIMULATION – EXHAUST LINE CALCULATION
Direct access to AAC variables
(unsteady pressure, Prms, …)
Exp.
Setup
Unsteady pressure
Unsteady velocity
Power Spectral Density
29
AEROACOUSTICS – BLOWER SIMULATION
Type of simulation: Isothermal aeroacoustic simulation
Rotating mesh
Goal: Pressure and velocity calculation
Good accuracy vs exp.
Velocity field OASPL
ProLB vs exp.
Exp.
30
AEROACOUSTICS SIMULATION – HVAC
Hanning window function used
ΔXmax= 25,6 cm
ΔXmin= 2 mm
8 refinement levels
Tonal peaks observed
at 400Hz and 800 Hz
31
LAGOON DATABASE
Airbus-ONERA collaboration(2006-2010)
3 configurations with various geometries complexity
Configuration #1 (simulation with ProLB)
Aerodynamic measurements (WD F2)
PIV fields & Velocity profiles (LDV)
Static pressure distributions (Cp)
Aerodynamic measurements (WD CEPRA19)
Pressure spectrums
Near-field spectrums and directivities
32
TURBULENT EDDIES WEALTH
Lagoon simulation: ProLB 7x faster than AVBP !
33
AVERAGED AXIAL VELOCITY, Z = 0 MM
Boundary layer thickness:
Too large in COARSE
Ok in MEDIUM
Recirculation zone:
Size OK
Intensity OK
Global wake size:
Good wake width
Better wake form prediction with
LBM than classical LES code
LaBS_COARSE LaBS_MEDIUM
EXPE (PIV) LES (AVBP)
34
ROOT MEAN SQUARE OF THE AXIAL VELOCITY (Z=0)
External side shear:
Vortex size and intensity more
realistic in MEDIUM case
(X=-0,2 ; Y=0,15)
Equivalent to classical LES
code
PIV measurements not
enough accurate to be able to
compare them with CFD
results
LaBS_COARSE LaBS_MEDIUM
EXPE (PIV) LES (AVBP)
35
POWER SPECTRAL DENSITY
110
100
90
80
70
60
50
Pre
ssu
re P
SD
(d
B/H
z)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
Kulite 2 AVBP Fine Mesh LABs Coarse Mesh LABs Medium Mesh
Filtre
LF
filter in
the
measu
rement
s
130
120
110
100
90
80
70
Pre
ssu
re P
SD
(d
B/H
z)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
Kulite 6 AVBP Fine Mesh LABs Coarse Mesh LABs Medium Mesh
120
110
100
90
80
70
60
Pre
ssu
re P
SD
(d
B/H
z)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
Kulite 13 AVBP Fine Mesh LABs Coarse Mesh LABs Medium Mesh
130
120
110
100
90
80
70
Pre
ssu
re P
SD
(d
B/H
z)
102
2 3 4 5 6 7 8 9
103
2 3 4 5 6 7 8 9
104
Frequency (Hz)
Kulite 14 AVBP Fine Mesh LABs Coarse Mesh LABs Medium Mesh
36
SNOW INGESTION SIMULATION
Coupling with SPHFlow
Snow ingestion validation
(∆(exp-sim) < 150g) : Scenic 3 :
Dacia Lodgy :
Kangoo :
Scenic 4 :
Ongoing: Soiling simulation
37
THERMAL SIMULATION (ON-GOING)
ProLB aerothermal model
TAITherm solid thermal model
Two-way coupling MPCCI platform
Siemens/Amesim thermo-hydraulic model
Two-way coupling
38
PROLB / TAITHERM / AMESIM SIMULATION OF UNDER-HOOD AND UNDERBODY THERMAL FIELDS
Around 1000 solid parts coupled between ProLB and TAITherm
Expe vs. ProLB / TAITherm / Amesim simulation of under-hood and underbody thermal
41 Tair probes
Under-hood temperature
39
BRAKE COOLING PERFORMANCE
ProLB : Rotating mesh on wheel rim and brake disk
TAItherm model
Expe vs. ProLB / TAITherm simulation of brake
disk temperature decrease
4 configurations on the Megane :
Brake disk wall heat flux Wheel temperature Time (s)
Tem
per
atu
re (°
C)
Exp.
Calculation
40
AIR CONDITIONING LOOP PERFORMANCE
Air flow and temperature at idle, motor fan ON
Expe vs. ProLB / Amesim simulation of AC condenser performance at idle for 5 vehicle configurations
Quantifying warm air
recycling
Condenser heat Blown air temperature High pressure
41
EXCHAUST JET / REAR BUMPER INTERACTIONS
Exp.
ProLB
42
EXCHAUST JET / REAR BUMPER INTERACTIONS
Exp.
ProLB
43
PROLB AUTOMOTIVE SOLUTION SYNTHESIS
* Use in production
ProLB Physics Applications
Availability Availability
Aerodynamics
Drag coefficient*
Ride & Handling*
Panel Loading*
Fan*
Underhood*
Indoor Vehicle*
Aeroacoustics
Pressure load*
Exhaust line*
Blower*
HVAC*
Thermal
Engine cooling* Coming soon
Brake cooling* Coming soon
AC * Coming soon
Exhaust line* Coming soon
Snow ingestion
Hydraulics
44
Solving of the direct equations ( f )
Solving of the adjoint equations ( f*)
Calculation of the surface gradients 𝛻𝐼0
Morphing of the surface mesh
(𝑥𝑘+1 = 𝑥𝑘 − 𝜆 𝛻𝐼0)
𝑓𝑖∗ 𝑥𝑘 − 𝑐𝑖∆𝑡, 𝑡 − ∆𝑡 = 𝑓𝑖
∗ 𝑥𝑘 , 𝑡 −1
𝜏𝑓𝑖∗ 𝑥𝑘 , 𝑡 − 𝑓𝑖
∗,𝑒𝑞𝑥𝑘 , 𝑡 −
𝜕𝐼0𝜕𝑓𝑖(𝑥𝑘0, 𝑡𝑛0)
Adjoint Lattice Boltzmann Method
𝛻𝐼0 = 𝑓𝑖∗ 𝑥𝑘 , 𝑡𝑛+1
4 𝑑′
(1 + 2𝑑)2𝑓𝑜𝑝𝑝(𝑖)𝑐𝑜𝑙𝑙 𝑥𝑘 + 𝑐𝑖 , 𝑡𝑛 − 𝑓𝑖
𝑐𝑜𝑙𝑙 𝑥𝑘 , 𝑡𝑛𝑖𝑘
Standard simulation
Adjoint solver (beta)
Mesh morphing tool (e.g. Ansa)
Gradient calculation on surface
PROLB ADJOINT SOLVER (ON-GOING WORK)
45
Primary simulation, velocity field after time averaging
Adjoint field
Standard simulation
Adjoint solver (beta)
Mesh morpher tool (e.g. Ansa)
Gradient on some surface points : comparison between ProLB adjoint calculation and finite difference calculations of various order
Cylinder after morphing (image shown : after three adjoint loop)
PROLB ADJOINT SOLVER: VALIDATION ON A CYLINDER
46
Initial shape Optimized shape
PROLB ADJOINT SOLVER: EXAMPLE ON A CAR
7% reduction of the drag force (but with no style and dimension constraints…)
Sensitivy map of the surface mesh
regarding the aerodynamic drag
47
HYDRAULICS SIMULATION
Type of simulation: Isothermal
water simulation
Objective: Velocity field
comparison
Good accuracy vs Standard
Navier-Stokes code
ProLB Standard Navier-
Stokes code
Re 154420 154420
Turbulence Model LES (SISM) RANS/ k-ε
Inlet-Outlet Delta P (Bar) 0.533 0.501
ProLB
ProLB
48
HYDRAULICS SIMULATION
Type of simulation: Isothermal water simulation
Objective: Velocity profile comparison
Reference:S. Menanteau, Thesis 2012, Etude
expérimentale et numérique des fluctuations de
température en aval d’une jonction orthogonale
d’écoulements turbulents de températures différentes.
Good accuracy vs exp.
Equal CPU time vs Standard Navier-Stokes code
Geometry representation
Averaged velocity field at
the junction of the pipe
Averaged velocity data comparison
ProLB
Standard
Navier-Stokes
code
Turbulence model LES (SISM)
+ Wall law RANS
Number of mesh
cells 12 000 000 10 000 000
CPU time (same
CPU number) 20h 16h
49
HYDRAULICS SIMULATION - NUCLEAR APPLICATION
Type of simulation: Isothermal water simulation
Objective: Volumic mass flow calculation
Plenum explicit geometry (no geometry simplification)
Good accuracy vs Standard Navier-Stokes code
Very good CPU time vs Standard Navier-Stokes code
Mesh representation
Instantanous velocity
field in the plenum
Instantanous velocity field
in the exchangers part
ProLB Standard Navier-
Stokes code
Turbulence model
LES
(SISM) +
Wall law
SAS WML
ES
Number of mesh
cells
80 000
000 80 000 000
CPU time (same
CPU number,
(simulted time:1s)
5h 50h 324h
CS GROUP 22, AVENUE GALILÉE
92350 – LE PLESSIS-ROBINSON
TÉL : 01.41.28.40.00
C-S.FR