Upload
others
View
13
Download
0
Embed Size (px)
Citation preview
Turbulent flows using Lattice Boltzmann Method : application on automotive configurations
Denis Ricot, Renault, Digital Mockup, CAE and PLM Division
MUSAF 16, September 27 & 29, 2016, ONERA, Toulouse
with contributions of :J-P La-Hargue, H. Touil, B. Gaston, R. Cuidard, CSE. Leveque, Lab. de Mécanique des Fluides et d’Acoustique, EC Lyon P. Sagaut, Lab. de Mécanique, Modélisation et Procédés Propres, Univ. Aix MarseilleO. Coste, Gantha
01 LBM and LaBS PRESENTATION
02 OCTREE MESH
03 IMMERSED SOLID METHOD : WALL-RESOLVED LES
04
05
CONCLUDING REMARKS
SUMMARY
IMMERSED SOLID METHOD : WALL-MODELED LES
INDUSTRIAL VALIDATIONS
06
Statistical mechanics• Boltzmann equation• Particles
– Kinetic energy– Momentum– Shocks– Mean free path
Continuum mechanics• Navier-Stokes equations• Continuous media
– Temperature– Pressure– Density– Viscosity
Lattice Boltzmann method
• Particle velocity discretization (finite discrete velocity set for particles instead of continuous particle velocity)• Space and time discretizations of the discrete velocity Boltzmann equation
Chapman-Enskog theoretical expansion Navier-Stokes equations
Chapman-Enskog theoretical expansion
Lattice Boltzmann Method
« LaBS Consortium » collaborates with partners whose scientific expertise enables building mathematical models, improving HPC
performance and workflow and establishing simulation best-practices for several application domains.
LaBS : collaborative development
Three industrial companies and two scientific laboratories, software’s co-owner and developpers, leading, supporting and validating LaBS.
LaBS Consortium
LaBS (2009-2013) & CLIMB (2014-2017) : collaborative projects with strong partnerships
With the support of competitiveness clusters :
Financial support from FUI & PIA CISN :
…
Post-processing
Parallel solverGUI
LaBS software and simulation workflow
Developed from scratch since 2009- a GUI for simulation setup- a parallel solver, including the volumetric mesher- PostLaBS : a Paraview script suite for automatic post-processing (incl. signal processing)
CADSurface mesh
Ensight
Paraview
Report
ANSA, Salome, … PostLaBS
LaBS
Others…
LaBS architecture
Simulation setup : dedicated GUI, with script capacities
Base octree generation & load balancing optimization
Computation scheduling (dataflow programming)
Mesh and data structure generation
Time-step loop
Merge result files and format conversion
Main numerical issues
txutxftxftxf eqcollision ,,,1
,1
1,
txftx ,,
txfctxutx ,,,
Macroscopic quantities
txctxp s ,, 2
t
xcs
3
1
2
2 tcs
Sub-grid turbulence model
Immersed solids
Wall law
txf ,
txftttcxf collision ,,
core LBM : « Collide and Stream »
Mesh refinement based on octree meshTurbulence modeling
Numerical stability
Porous media
Moving mesh
01 LBM and LaBS PRESENTATION
02 OCTREE MESH
03 IMMERSED SOLID METHOD : WALL-RESOLVED LES
04
05
CONCLUDING REMARKS
SUMMARY
IMMERSED SOLID METHOD : WALL-MODELED LES
INDUSTRIAL VALIDATIONS
06
Volumetric mesh
Based on efficient parallel octree mesher Interior of surface meshes are excluded, without limitation in term of shape, number of
surfaces, and overlapping regions Zero-thickness surfaces (« open shells ») are accepted : two-sided surfaces, one
boundary condition for each side Refinement regions are defined using boxes, hand-made shapes, automatic offsets,…
exclusion
exclusion
raffinement
exclusion
raffinement
Volumetric mesh
AMR-like mesh : successive refinement of the volume mesh (M. J. Berger and P. Colella, "Local adaptive mesh refinement for shock
hydrodynamics," J. Comp. Phys, 82:64-84, 1989)
In LaBS : vertex-centered formulation coarse mesh nodes are coincident with fine mesh nodes Partial mesh overlapping approach for data exchanges between refinement blocks Need for rescaling of distribution functions (O. Fillipova and D. Hänel. Grid refinement for lattice-BGK models. J. Comput. Phys., 147(1):219–
228, 1998)
Fine to coarse mesh transfer
Mesh refinement
Example of validation for an acoustic pulse propagation in a multi-resolution grid
Coarse to fine mesh transfer for coincident fine nodes Coarse to fine mesh transfer for non-
coincident fine nodes
01 LBM and LaBS PRESENTATION
02 OCTREE MESH
03 IMMERSED SOLID METHOD : WALL-RESOLVED LES
04
05
CONCLUDING REMARKS
SUMMARY
IMMERSED SOLID METHOD : WALL-MODELED LES
INDUSTRIAL VALIDATIONS
06
Full separation between the octree volumetric mesh and the surface mesh (triangles)
An immersed solid boundary algorithm must be used
Immersed boundary conditions : several available approaches in literature deduced from the original Navier-Stokes techniques (Peskin, 1977). See for example : Z.-G. Feng and E.E. Michaelides. The Immersed
Boundary-Lattice Boltzmann Method for Solving Fluid-Particles Interaction Problems. J. Comput. Phys., 195(2):602-628, 2004
In LaBS, not IBC : a kind of cut-cell method No cells inside the solids Special treatment of the fluid boundary nodes : « reconstruction method », similar to the model
described in : J.C.G. Verschaeve and B. Müller, "A curved no-slip boundary condition for the lattice Boltzmann method", J. Comput. Physics, 2010, 229(19), pp.6781-6803
Immersed solid
Distribution functions associated with velocity #7 and velocity #3 in its example can not be calculated by the collision / propagation LBM algorithm because neighbor nodes are inside the solid
Immersed solid : reconstruction method
Reconstruction of the distribution functions from the macroscopic data (pressure, velocity and velocity
gradients) :
Spatial interpolation needed using the available standard fluid nodes
Boundary node to be calculated
ij
ijijsji
ss
ijsjiji
s
iineqeqSccc
cc
cccuu
c
uctxftxftxf
2
,,24
2
,,
2
,
21,,,
(Chapman-Enskog expansion)
i
j
j
iij
x
u
x
uS
2
1iu ,
Spatial interpolationCalculation of velocity gradients by
off-centered finite difference scheme
Lattice Boltzmann is a native unsteady algorithm with very low numerical dissipation : it is well adapted to Large Eddy Simulation
Two sub-grid models are implemented in LaBS : Shear-Improved Smagorinsky Model (SISM) The Approximate Deconvolution Model (ADM)
Turbulence model
txutxftxftttcxf eq ,,,1
,1
1,
2
2 tcs
The shear-improved Smagorinsky model is a sub-grid turbulent viscosity model : E. Leveque, F. Toschi, L. Shao and J.-P. Bertoglio, Shear-Improved Smagorinsky Model for Large-Eddy Simulation of Wall-Bounded Turbulent
Flows, Journal of Fluid Mechanics 2007, vol. 570, pp. 491-502
Teff eff
“< >” is low-pass filtering based on an exponentially-weighted moving time average
Turbulence model
The Approximate Deconvolution Model (ADM) is not a turbulent viscosity model : dissipation is added through selective spatial filtering
Navier-Stokes : Stolz S, Adams NA, Kleiser L. An approximate deconvolution model for large-eddy simulation with application to incompressible wall-bounded flows. Phys Fluids 2001;13:997–1015
Validation of ADM for LES simulations have been done with Navier-Stokes solver (Bogey, C. & Bailly, C., 2006,
Computation of a high Reynolds number jet and its radiated noise using large eddy simulation based on explicit filtering, Computer & Fluids, 35(10),
1344-1358) and LBM solver (Lattice Boltzmann : O. Malaspinas and P.Sagaut, Advanced large-eddy simulation for lattice Boltzmann methods:
The approximate deconvolution model Phys. Fluids 23, 105103, 2011 )
LBM algorithm is unchanged compared to the DNS case : only an explicit filtering step is added
Small scales are damped without affecting the larges scales
In LaBS : 7 point stencil is used : D. Ricot, S. Marié, P. Sagaut, C. Bailly Lattice Boltzmann method with selective viscosity filter, Journal of
Computational Physics 228 (2009) 4478–4490
Wall-resolved LES : turbulent plane channel flow Ret=395
DNS = pseudo-spectral solver
LES-FV = Finite-volume LES solver (mesh size comparable to the LES of LaBS, SISM)
y+=5 à la paroi !
y+=20 in bulk
Mean axial velocity
3 resolution domains
SGS model: SISM
Wall-resolved LES : Cylinder at Re 47000
LES with SISM model9 refinement levels
17 millions on mesh nodes128 procs.
H Touil, D. Ricot, E; Lévêque, J. Comp. Phys. Vol 256, 1 January 2014
01 LBM and LaBS PRESENTATION
02 OCTREE MESH
03 IMMERSED SOLID METHOD : WALL-RESOLVED LES
04
05
CONCLUDING REMARKS
SUMMARY
IMMERSED SOLID METHOD : WALL-MODELED LES
INDUSTRIAL VALIDATIONS
06
Wall-modeled LES
Both Shear-Improved Smagorinsky model and Approximate deconvolution model can be associated with a wall law model
Analytical wall law is used : in-house composite model + viscous sub-layer continuousadaptation
Pressure gradient effectLocal curvature effect
Roughness effect
dx
dP
U 3
N. Afzal. Wake layer in a turbulent boundary layer with
pressure gradient: a new approach. In IUTAM Symposium
on Asymptotic Methods for Turbulent Shear flows at High
Reynolds Numbers. K., G., ed., Kluwer Academic
Publishers, 1996, 95-118
Patel & Sotiropoulos, « Longitudinal curvature
effects in turbulent boundary layer », Prog.
Aerospace Sci, Vol 33, pp1-70, 1997
59 eK
Wall law
35.1 e
0K
0
Both wall pressure gradient and wall curvature terms are active on high range of y+ : not useful for “standard” wall-adapted mesh (y+≈ 40)
On vehicle minimum mesh size around 1-2mm that leads to y+ ≈ 200 on vehicles (U0 ≈ 40 m/s) Some geometrical details are only a few millimeters (gap between panels, seals,…) : the
curvature term can « help » the flow to be sensitive to this local surface irregularity
Wall law calculation
Strategy :
Choose a « reference point » • at a fixed distance from de
wall (in the wall normal direction) Use known values in order to interpolate the velocity at this
reference point Calculate the wall pressure gradient and streamwise
curvature at this point • Calculate the friction velocity Utau with the Newton method Supposing the wall pressure gradient and curvature are the
same than at the reference point, calculate the tangential
velocity at the boundary node
Use the standard mixing length model to calculate the
turbulent viscosity at the boundary node
Similar to the implementation presented in “Wall Model for Large-Eddy
Simulation based on Lattice Boltzmann Method”, O. Malaspinas, P. Sagaut,
J. Comput. Physics, 2014, 275, pp 25-40
Boundary node to be calculated
Curvature calculation
One of the challenging task : calculation of the streamwise curvature… in the framework of complex geometry with open or closed solid surfaces, overlapping surfaces,…
The curvature vector is calculed during the pre-processing step using an adaptative algorithmthat depends on the local surface mesh size and on the local fluid cell size
tangtang UKK
High sensitive curvature sensor Medium sensitive curvature sensor
K
Example on a full vehicle : only convex curvature is taken into account
Curvature calculation
Wall law validation
Flat plate boundary layer development (2D computation, « RANS » mode development)
Fixed velocity U0=40m/s Fixed pressure
« 2D » configuration :
periodic in the transverse
direction
Wall law
Velocity profile at Re_X=600000
2
0
2
U
UC f
2.0Re059.0
x
emp
fC
Friction coefficient along the plate
y+=12
y+=56
y+=113
y+170
y+=215
5 computation, same mesh size (dx+ =226
à Re_X=600000) but varying the position
of the first mesh node layer regarding the
wall
Wall law validation
Flat plate boundary layer development (2D computation, « RANS » mode development)
Flat plate boundary layer development (2D computation, « RANS » mode development)
Wall law on vehicle
On the vehicle skin : some refinement
regions are defined near critical zones
The wall distance varies suddenly
y+≈ 400
y+≈ 200
28
Wall law validation on inclined flat plates
Flat plate,
aligned with the
mesh
Inclined flat plate,
small angle
Inclined flat plate,
intermediate
angle
29
Wall law validation on inclined flat platesU
tau
X (mm)
Intermediate angle
Aligned with mesh axis
Small angle
Uta
u
01 LBM and LaBS PRESENTATION
02 OCTREE MESH
03 IMMERSED SOLID METHOD : WALL-RESOLVED LES
04
05
CONCLUDING REMARKS
SUMMARY
IMMERSED SOLID METHOD : WALL-MODELED LES
INDUSTRIAL VALIDATIONS
06
Drag coefficient of a full-scale car
Setup:
≈ 2h engineering time
Solver:
≈ 48h/196 cores
Post-processing:
Automatic
Surface mesh:
O(2-4M) Δ
Volume mesh:
O(100M) cells
10 refinement levels
Simulated physical
time:
1s
300 000 time-steps
CAD mgt and surface
mesh
preparation lead time
depends on the CAD
CAD:
O(200) surfaces
AERODYNAMIC VALIDATION : Industrial case
RESULTS
CdA
(m²)
∆CdA ClA
(m²)
∆ClA
Tests in wind tunnel 0.677 REF 0.458 REF
LaBS 0.678 0% 0.315 -31%
Reference vehicle
Good overall topology
Flow detachment on the
rear part is well predicted
Good estimation of the
vortex came from A-pillars
Good accuracy of the
value of CdA
TESTS
AERODYNAMIC VALIDATION : Industrial case
RESULTS
CdA
(m²)
∆CdA ClA
(m²)
∆ClA
Tests in wind tunnel 0.800 REF 0.254 REF
LaBS 0.780 -3% 0.251 -1%
Scenic II
TESTS
Duster
SCx Ecart
Tests in wind tunnel 1.016
LaBS 1.010 -1%
TESTS
AERODYNAMIC VALIDATION : with porous media and rotating fan
Mégane IIIMean Velocity
(m/s) on radiator
LaBS(m/s)
V=165km/h 5.47
V=2km/h 1.51 Fan OFF
V = 165 km/h
Fan ON
V = 2 km/h
OK withExperimentalresults
Wall pressure fluctuation
Full scale vehicle simulation 10 levels of refinement, around 30 millions mesh nodes, 300 000 time-steps U0 = 44.4 m/s Wall Law LES (Approximate Deconvolution Model)
Aeroacoustic sources inside mufflers
Comparison expe/num of the power spectral density of the
acoustic pressure field at the external reference probe.
Sponge zone modeling to
avoid acoustic reflection on
fluid domain boundaries
Instantaneous velocity
physical noise coming
from internal sources
spurious source region
due to mesh size jump
(fine to coarse)
Instantaneous pressure
Tailpipe measurement test bench.
01 LBM and LaBS PRESENTATION
02 OCTREE MESH
03 IMMERSED SOLID METHOD : WALL-RESOLVED LES
04
05
CONCLUDING REMARKS
SUMMARY
IMMERSED SOLID METHOD : WALL-MODELED LES
INDUSTRIAL VALIDATIONS
06
Concluding remarks
Lattice Boltzmann method for complex geometry: Immersed solid approach is not a choice with LBM “false” LBM (Finite-Difference LBM, Finite volume LBM) that allow wall-adapted meshes
(unstructured-like,…) are not LBM : they loose of the main advantage of the LB scheme (high accuracy-cost ratio).
Wall-Modeled LES is natural choice : still many challenges In many industrial configurations : large regions of attached flow with poor mesh
refinement toward Wall-Modeled DDES or other hybrid RANS/LES approaches
“Easy-to-use” immersed solid methods need special attention : Surface result management : must be treated as a “HPC” challenge with its own data
structure (no direct direct/natural connectivity between surface and volume mesh) Independent and overlapping surfaces are not efficient to accurately calculate surface
integrated data (e.g. wetted surface) : need for some sewing algorithms