Pore scale reactive flow simulation in catalytic particulate filters based on high resolution X-ray CT images

This study presents a comprehensive pore-scale simulation of reactive flows in particulate filters, focusing on selective catalytic reduction diesel particulate filters (SDPF). Emphasis is placed on the impact of internal washcoat pores and the development of a zero-dimensional surrogate model for first-order reactions. Nano-computed tomography (nano-CT) with a voxel resolution of 364 nm enabled detailed imaging and reconstruction of real filter samples, including the washcoat’s internal pores for the first time. Segmentation into pore, washcoat, and substrate phases provided a solid foundation for numerical simulations. To reduce computational cost, a representative elementary volume (REV) and a downsampling strategy were implemented and validated through geometric and flow parameter comparisons. Essential microstructural characteristics were preserved while significantly lowering computational demands. Results highlight the critical role of internal washcoat pores in mass transport and catalytic performance. SDPF samples with resolved internal pores outperformed those with closed washcoat structures (SDPF CWC), even with lower washcoat loading, underlining the importance of geometric connectivity and bimodal pore networks. Comparisons with catalytic gasoline particulate filters (cGPF) revealed the absence of internal washcoat pores in cGPF samples, suggesting finer pore structures. In the absence of experimental diffusion data, this work provides practical tortuosity values for estimating effective diffusion. To accelerate performance prediction, a zero-dimensional surrogate model based on residence time distribution (RTD) and washcoat efficiency was developed. Using Thiele modulus theory, it estimates conversion from effective diffusion lengths and efficiency factors, showing high accuracy across different geometries. The model emphasizes the equally important roles of RTD and washcoat efficiency in catalysis. Additionally, nonlinear (inhibition-controlled) reactions were simulated, demonstrating that spatial concentration profiles remain consistent across different inhibition factors at similar conversion levels. This finding enables simplification and generalization of spatial distributions in models of complex reaction kinetics.