This document discusses a multiscale simulation approach for diesel particulate filter design using OpenFOAM and DexaSIM. It describes reconstructing filter material microstructures from CT scans and simulating soot deposition, porosity, and permeability at the microscopic scale. These microscopic properties are then used in macroscopic simulations of the entire exhaust system to determine overall filter performance. The approach aims to provide a detailed link between microscopic material changes and resulting macroscopic filter behavior to improve design through simulations rather than experiments.
1. OpenFOAM .International Conference 2007OpenFOAM .International Conference 2007
A Multiscale Simulation Approach for Diesel ParticulateA Multiscale Simulation Approach for Diesel Particulate
Filter (DPF) Design Based on OpenFOAM and DexaSIMFilter (DPF) Design Based on OpenFOAM and DexaSIM
JohannesJohannes LeixneringLeixnering, Bernhard Gschaider, ICE Strömungsforschung GmbH, Bernhard Gschaider, ICE Strömungsforschung GmbH
Wilhelm Brandstätter,Wilhelm Brandstätter, RiesRies Bouwman, Montanuniversität LeobenBouwman, Montanuniversität Leoben
2. IntroductionIntroduction
IntroductionIntroduction
Diesel Particulate Filters (DPF) – Past and Present
Multiscale Simulations
• OpenFOAM
• DexaSIM
Material reconstruction on a microscopic scaleMaterial reconstruction on a microscopic scale
Isotropic Material Reconstruction method (IMR)
Anisotropic Material Reconstruction method (AMR)
Microscopic SimulationsMicroscopic Simulations
Porous structures
Determination of Porosity and Permeability
Soot deposition
Macroscopic SimulationsMacroscopic Simulations
Exhaust system
Overall properties
ConclusionsConclusions
3. Diesel Particulate Filters (DPF)Diesel Particulate Filters (DPF) 1/41/4
DPF FiltersDPF Filters
Good solution to abate particulate matter (PM) quantity
to the required limits (EURO IV)
The innovation in this field is not yet finished
• Imposed limits evolve (EURO V)
• Different combustion products (particle dimension, density,
etc.) due to the introduction of new Combustion concepts
Difficult to study in detail
• Experiments with destructive tests (burning, cutting …)
• Simulations of global parameters with submodels. No direct
simulation of porous structure
• No connection between microstructures and macroscopic
material properties
4. DPFDPF 2/42/4
Experimental research and development (R&D)Experimental research and development (R&D)
Trial and error
The filter material is difficult to investigate in detail
• No detailed information on the soot deposition
• No detailed information on the heat transfer
Deeper insight required into chemical and physicalDeeper insight required into chemical and physical
phenomena inphenomena in DPFsDPFs
During filter regeneration
Shorten the development process
Increase the durability of DPFs
Multiscale simulation tools are needed to predict possibleMultiscale simulation tools are needed to predict possible
failures of the DPFfailures of the DPF
5. DPFDPF –– PastPast 3/43/4
ToolsTools
Test bench
• Expensive
• Only overall information
Commercial CFD tools
• Unflexible
• Experts
• High costs
NeedsNeeds
Fast and accurate methods for DPF
design to meet Euro V legislation
• Euro V, Euro VI ...
6. DPFDPF –– PresentPresent 4/44/4
New approachNew approach
Multiscale simulations
• Detailed study of microscopic heterogene porous structures
• Influence of porous structure on macroscopic homogene filter
OpenSource software
• Flexible
• Low costs
NeedsNeeds
Tools to easily reconstruct porous structures
Tools to study connection between microscopic
improvements on overall performance
7. Multiscale SimulationsMultiscale Simulations -- PastPast 1/21/2
MacroscopicMacroscopic
1D and 3D Simulations of filters (wall flow, foam …)
Homogeneous porosities
Measured permeabilities
• are used to model the effect of filter material on the exhaust gas
flow
Without extensive experimental calibration the predictive capability
of these models proved to be limited
MicroscopicMicroscopic
Lattice-Boltzmann-Method (LBM)
• Cold flow and particle deposition in porous media
• No heat transfer and chemical surface reactions
1D1D –– 3D coupling3D coupling
To improve calculation time
8. Multiscale SimulationsMultiscale Simulations -- PresentPresent 2/22/2
Multiscale approachMultiscale approach
Generation of 3D computational
microscopic and macroscopic geometry
• Based on Computer Tomography (CT)
image and DexaSIM
MicroFOAM
• OpenFOAM based solver to study
microscopic porous structures
MacroFOAM
• OpenFOAM based solver to study
complete exhaust systems
• Material properties calculated in
MicroFOAM are used to define overall
properties
10. DexaSIMDexaSIM -- preprocessorpreprocessor
Catalyst:
Chemical reactions? Efficiency?
Soot filter:
Loading? Structure?
Porosity, permeability in time?
Inlet:
Temp, pressure, species
Outlet:
Species? Temperature?
Pipeline:
Pressure drop? Turbulence?
11. OpenFOAMOpenFOAM -- solversolver
OpenFoamOpenFoam
Advantages
• OpenSource
• C++
• Very flexible
• Direct implementation of physics and mathematics
Disadvantages
• Not easy to use (for beginners)
GUIGUI
DexaSIM is preprocessor and GUI for exhaust gas
aftertreatment simulations
• Multi platform
LinkLink
http://www.ice-sf.at/dexasim_download.shtml
13. Modelling on a Microscopic ScaleModelling on a Microscopic Scale
DexaSIMDexaSIM
Reconstruction of 3D material samples from 2D
Computer Tomography Image
Statistical functions are used to characterise material
samples
• pore diameter distribution
• pore distance autocorrelations
• lineal path functions, etc.) material samples are
mathematically characterised.
Setup of complete exhaust geometry and boundary
conditions
14. Material reconstructionMaterial reconstruction 1/21/2
Isotropic material reconstruction methodIsotropic material reconstruction method
1. Obtaining a 2D CT image of the material
2. Converting the CT image to a digitised image
3. Retrieving statistical parameters from the digitised
image
4. Reconstruct 3D digital model or mesh according to
statistical parameters
15. Material reconstructionMaterial reconstruction 2/22/2
Anisotropic material reconstruction methodAnisotropic material reconstruction method
1. Obtain 2D grey-scale images of the material
2. Combine 2D images to one 3D grey-scale image
3. Digitise and reconstruct the 3D digital model or
mesh
19. Microscopic SimulationsMicroscopic Simulations 4/64/6
Soot deposition at the pore wallsSoot deposition at the pore walls
Transport equation
Depot ratio D
0=+∇⋅∇−⋅∇+
∂
∂
sootsootsoot
soot
SKu
t
ρρ
ρ
sootdepsoot RS αρ=
0=−
∂
∂
soot
dep
S
t
ρ
solid
fluid
D=0.2
A
solid
fluid
V
A
α = A/V
solid
fluid
D=1
Csolid
fluid
D=0.5
B solid
fluid
D
24. ConclusionConclusion
A complete method has been presented to study filter materials oA complete method has been presented to study filter materials on an a
microscopic level to see the influence of microscopic R&D on themicroscopic level to see the influence of microscopic R&D on the
macroscopic filter behaviourmacroscopic filter behaviour
Multiscale LinkMultiscale Link
Influence of microstructural evolution on macroscopic features
Objective: achieve major improvements in porous material design
OpenFOAMOpenFOAM
Combines microscopic and macroscopic scale simulations in one tool
• e.g. DexaSIM.
Validations of the simulations with experimental results look promising
OutlookOutlook
Extensive experimental validating of the models
Implementation of sub models for
• wall flow filter (anisotropic approach)
• thermal activity inside the filter material (Tension, cracking, fluid-structure
coupling ...)