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Ash Permeability Determination in the Diesel Particulate Filter from Ultra-High Resolution 3D X-Ray Imaging and Image-Based Direct Numerical Simulations
- Carl Justin Kamp - Massachusetts Institute of Technology ,
- Shawn Zhang - DigiM Solution LLC ,
- Sujay Bagi - Massachusetts Institute of Technology ,
- Victor Wong - Massachusetts Institute of Technology ,
- Greg Monahan - Massachusetts Institute of Technology ,
- Alexander Sappok - Massachusetts Institute of Technology ,
- Yujun Wang - Cummins
- Journal Article
- DOI: https://doi.org/10.4271/2017-01-0927
ISSN: 1946-3952, e-ISSN: 1946-3960
Published March 28, 2017 by SAE International in United States
Citation: Kamp, C., Zhang, S., Bagi, S., Wong, V. et al., "Ash Permeability Determination in the Diesel Particulate Filter from Ultra-High Resolution 3D X-Ray Imaging and Image-Based Direct Numerical Simulations," SAE Int. J. Fuels Lubr. 10(2):608-618, 2017, https://doi.org/10.4271/2017-01-0927.
Diesel engine exhaust aftertreatment components, especially the diesel particulate filter (DPF), are subject to various modes of degradation over their lifetimes. One particular adverse effect on the DPF is the significant rise in pressure drop due to the accumulation of engine lubricant-derived ash which coats the inlet channel walls effectively decreasing the permeability of the filter. The decreased permeability due to ash in the DPF can result in increased filter pressure drop and decreased fuel economy. A unique two-step approach, consisting of experimental measurements and direct numerical simulations using ultra-high resolution 3D imaging data, has been utilized in this study to better understand the effects of ash accumulation on engine aftertreatment component functionality.
In this study, ash permeability was directly measured on the surface of ceramic (cordierite) wafers as a function of ash type (field ash, lab-generated and with chemical/morphological variations) and packing density. Ultra-high resolution X-ray Computed Tomography (CT) with a transmission X-ray source (voxel size ~500nm) was utilized for direct and accurate 3D visualization of the catalyst substrate structure, the individual ash particles (which have an average size of 1-2µm) and the ash which penetrates into the substrate surface pores. In combination with CT data deep image analysis, a new generation of direct numerical simulation algorithms (solving Naiver-Stokes equations efficiently for imaging data with billions of voxels) is used to compute permeability of the combined ash/washcoat/substrate system directly from the 3D CT images.
This study discusses the sample preparations necessary for high CT resolution, the combination of CT data and deep image processing for permeability calculations, the comparison between calculated and experimentally measured permeability values and the implications of the ability to calculate accurate permeability values in the combined ash-catalyst substrate system.