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• W2324996970 abstract "Motivated by modeling of gasoline particulate filters (GPFs), a probability density function (PDF) based heterogeneous multiscale filtration (HMF) model is developed to calculate filtration efficiency of clean particulate filters. A new methodology based on statistical theory and classic filtration theory is developed in the HMF model. Based on the analysis of experimental porosimetry data, a pore size probability density function is introduced to represent heterogeneity and multiscale characteristics of the porous wall. The filtration efficiency of a filter can be calculated as the sum of the contributions of individual collectors. The resulting HMF model overcomes the limitations of classic mean filtration models which rely on tuning of the mean collector size. Sensitivity analysis shows that the HMF model recovers the classical mean model when the pore size variance is very small. The HMF model is validated by fundamental filtration experimental data from different scales of filter samples. The model shows a good agreement with experimental data at various operating conditions. The effects of the microstructure of filters on filtration efficiency as well as the most penetrating particle size are correctly predicted by the model." @default.
• W2324996970 created "2016-06-24" @default.
• W2324996970 creator A5056106733 @default.
• W2324996970 creator A5069161814 @default.
• W2324996970 date "2015-04-09" @default.
• W2324996970 modified "2023-10-06" @default.
• W2324996970 title "PDF-Based Heterogeneous Multiscale Filtration Model" @default.
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• W2324996970 doi "https://doi.org/10.1021/acs.est.5b00329" @default.
• W2324996970 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25822651" @default.
• W2324996970 hasPublicationYear "2015" @default.
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