A Multiscale Simulation Approach for Diesel Particulate Filter Design Based on OpenFOAM and DexaSIM

773 views
610 views

Published on

The majority of Diesel exhaust gas aftertreatment system design and development
work is done experimentally by means of long and expensive engine bench tests.
The final system configuration is generally the product of a series of experimental
“trial and error” operations. In order to shorten the development process, to reduce
testing costs and to increase the durability of Diesel Particulate Filters (DPFs), multidisciplinary
simulation tools are needed to predict possible failures of the DPF.
Recently, several numerical models have been developed to simulate globally the
soot loading capacity, the pressure drop evolution and the regeneration behaviour in
ceramic wall-flow filters. Less effort has been devoted to the development of
dedicated models for the simulation of the microstructural flow phenomena and
thermo-mechanical behaviour of the filters.
This paper describes the development of a multi-physics software tool based on
OpenFOAM embedded in the DexaSIM Graphical User Interface (GUI) which is able
to handle the evolution of microstructural material properties and complex physical
phenomena inside the filter material as well as response of complete filters under
engine operating conditions.
The modelling approach hence builds on the multiscale link between microstructural
evolution and specific macroscopic exhaust system features with the objective to
achieve major improvements in material design and lifecycle assessment.

Published in: Technology, Design
0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
773
On SlideShare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
28
Comments
0
Likes
2
Embeds 0
No embeds

No notes for slide

A Multiscale Simulation Approach for Diesel Particulate Filter Design Based on OpenFOAM and DexaSIM

  1. 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. 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. 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. 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. 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. 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. 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. 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
  9. 9. Multiscale SimulationsMultiscale Simulations -- PresentPresent 2/22/2
  10. 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. 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
  12. 12. ParaViewParaView -- postprocessorpostprocessor ParaviewParaview OpenSource • Very flexible • Multi platform LinkLink http://www.paraview.org/New/index.html
  13. 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. 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. 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
  16. 16. Microscopic SimulationsMicroscopic Simulations 1/61/6 Equi-distant Cartesian mesh porosity 0.77 Body Fitted (SPIDER) mesh porosity 0.89 (350K) and 0.81 (1500K)
  17. 17. Microscopic SimulationsMicroscopic Simulations 2/62/6
  18. 18. Microscopic SimulationsMicroscopic Simulations 3/63/6
  19. 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
  20. 20. Microscopic SimulationsMicroscopic Simulations 5/65/6
  21. 21. Microscopic SimulationsMicroscopic Simulations 6/66/6
  22. 22. Filter 1: Continuous Regeneration Trap (CRT)Filter 1: Continuous Regeneration Trap (CRT) Filter 2: Passive soot trapFilter 2: Passive soot trap Macroscopic SimulationsMacroscopic Simulations 1/21/2 Oxidation of CO and NO Passive soot trap 22 22262 22 222 6472 22 CONCONO OHCOOHC COOCO +→+ +→+ →+
  23. 23. Macroscopic SimulationsMacroscopic Simulations 2/22/2 CO2 Temperature
  24. 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 ...)

×