Soot filtration simulation in diesel particulate filter with GeoDict

Mehdi  Azimian, Math2Market GmbH

Soot filtration simulation in diesel particulate filter with GeoDict

Liping Cheng, Mehdi Azimian, Andreas Wiegmann

Math2Market GmbH, Kaiserslautern, Germany, E-Mail:


In diesel and gasoline engines, it becomes increasingly important to filer soot emissions from the exhaust. Soot emissions can be reduced by forcing the soot particles to be trapped physically through an installed diesel particulate filter (DPF). The DPF is one of the most essential after-treatment devices invented to reduce particulate matter from diesel engines discharge. For optimal protection of environment, the international emission standards become stricter and mandatory for more countries. In this way, the study of soot filtration process through the DPF becomes respectively very important. Moreover, the advancement of computational power contributes to better investigation and understanding of the soot filtration phenomena using modelling and simulation techniques.

The goal of this study was to use computer simulation tool (GeoDict®) to design a better DPF having lower pressure drop, higher filter efficiency and longer life time. The key parameter that governs the DPF performance is the ceramic filter media. In this way, a ceramic filter media was modelled using the GrainGeo module of GeoDict® software and the flow behaviour and soot filtration were simulated using FlowDict and FilterDict modules [1].

The simulation steps contain modelling the ceramic, simulating the air flow through the filter media, simulating the transport of soot particles, simulating the deposition of soot particles and the conversion of deposited particles into a porous media, determining the soot layer packing density and the soot layer’s viscous flow resistivity. The simulations provide all the details on deposition location and pressure drop over time.

In fluid-solid filtration processes, solid particles are carried by a fluid and can be trapped whether inside the filter media called as depth filtration or on top of the filter media called as cake filtration. In current study, the depth filtration and cake filtration regimes can be clearly distinguished through the simulations (See Fig. 1).

Soot particles to be filtered are much smaller than the computational grid size. Therefore, when soot particles deposit, they do not fill the computational cell, but rather form a permeable media inside and on top of the ceramic filter. The FilterDict module of the GeoDict® software allows to control how much a cell can get filled, and how much resistivity to the flow the cell will have, depending on the degree of filling. Sub-voxel-sized soot particles form a filter cake which is modeled as porous media with locally varying permeability. These soot particles do most of the work to filter more particles.

The simulation results show that initially a fast increase in pressure drop occurs during the depth filtration regime. Afterwards, it follows with a long, slower pressure drop increase during the cake filtration regime. The simulation results agree very well with the experimental data provided by Fraunhofer IKTS [1, 2].

Modifications were carried out to shorten the depth phase and to reduce the pressure drop during cake phase. This work confirms a key step in virtual material design. The outcome of the simulation studies led to a granted patent for the particulate filter [3].


Fig. 1: Soot particles deposition as depth and filter cake regimes


The authors thank the Fraunhofer Society for funding this work in the FeiFilTools MEF project.




[1] L. Cheng, S. Rief, A. Wiegmann, J. Adler, L. Mammitzsch and U. Petasch, “Simulation of Soot Filtration on the Nano-, Micro- and Meso-scale”, Proceedings of 11th World Filtration Congress, 17.-19. April 2012, Graz, Austria.

[2] J. Adler and U. Petasch, Effect of membranes in exhaust particulate filtration. Advances in Ceramic Armor, Bioceramics, and Porous Materials: Ceramic Engineering and Science Proceedings Vol. 37 (4), Ed. Jerry C. LaSalvia, Ed. Roger Narayan, Ed. Paolo Colombo, John Wiley & Sons, 2016, pp. 139-147.

[3] Patent No. DE102012220181 A1

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