Effects of inlet velocity and structure parameters on the performance of a rotary diesel particulate filter for truck diesel engine based on fuzzy grey relational analysis
In this paper, a three-dimensional mathematical model of the rotary diesel particulate filter (RDPF) for truck diesel engine is established according to the fluid mechanics and porous media theory. The effects of inlet velocity and structure parameters (diameter ratio, expansion angle and filter len...
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Veröffentlicht in: | Chemosphere (Oxford) 2022-11, Vol.307, p.135843-135843, Article 135843 |
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Sprache: | eng |
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Zusammenfassung: | In this paper, a three-dimensional mathematical model of the rotary diesel particulate filter (RDPF) for truck diesel engine is established according to the fluid mechanics and porous media theory. The effects of inlet velocity and structure parameters (diameter ratio, expansion angle and filter length) on the flow uniformity in the RDPF are investigated. Furthermore, the Fuzzy grey relational analysis (FGRA) is employed to make a weight analysis of the influences of structure parameters on the regeneration performance and pressure drop of the RDPF. The results show that the velocity uniformity in the RDPF can be improved by properly reducing the inlet velocity, diameter ratio or expansion angle θ1. The capture-regeneration volume ratio with 8–10 is appropriate range for the structural optimization. Finally, the expansion angle θ1 is the most important structure parameter for the filter regeneration performance (regeneration time R = 0.8467; regeneration efficiency R = 0.6849) and the diameter ratio is the most important structure parameter for the pressure drop at the capture-regeneration “balance point” (R = 0.9352).
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•A 3D model of the rotary diesel particulate filter for truck diesel engine is established.•Effects of inlet velocity and structure parameters on the flow uniformity are investigated.•Fuzzy grey relational analysis is used to make a weight analysis of the effect factors. |
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ISSN: | 0045-6535 1879-1298 |
DOI: | 10.1016/j.chemosphere.2022.135843 |