IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v112y2016icp883-898.html
   My bibliography  Save this article

Filtration modelling in wall-flow particulate filters of low soot penetration thickness

Author

Listed:
  • Serrano, José Ramón
  • Climent, Héctor
  • Piqueras, Pedro
  • Angiolini, Emanuele

Abstract

A filtration model for wall-flow particulate filters based on the theory of packed beds of spherical particles is presented to diagnose the combined response of filtration efficiency and pressure drop from a reliable computation of the flow field and the porous media properties. The model takes as main assumption the experimentally well-known low soot penetration thickness inside the porous wall. The analysis of soot loading processes in different particulate filters shows the ability of the proposed approach to predict the filtration efficiency as a function of the particle size distribution. Nevertheless, pressure drop and overall filtration efficiency are determined by the mode diameter of the raw particulate matter emission. The results reveal the dependence of the filtration efficiency in clean conditions on the sticking coefficient. However, the dynamics of the pressure drop and filtration efficiency as the soot loading varies is governed by the soot penetration thickness. This parameter is closely related to the porous wall Peclet number, which accounts for the porous wall and flow properties influence on the deposition process. The effect of the transition from deep bed to cake filtration regime on the pressure drop is also discussed underlying the importance of the macroscale over microscale phenomena.

Suggested Citation

  • Serrano, José Ramón & Climent, Héctor & Piqueras, Pedro & Angiolini, Emanuele, 2016. "Filtration modelling in wall-flow particulate filters of low soot penetration thickness," Energy, Elsevier, vol. 112(C), pages 883-898.
    • Handle: RePEc:eee:energy:v:112:y:2016:i:c:p:883-898
    DOI: 10.1016/j.energy.2016.06.121
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216308957
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2016.06.121?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Torregrosa, A.J. & Serrano, J.R. & Arnau, F.J. & Piqueras, P., 2011. "A fluid dynamic model for unsteady compressible flow in wall-flow diesel particulate filters," Energy, Elsevier, vol. 36(1), pages 671-684.
    2. Serrano, José Ramón & Arnau, Francisco José & Piqueras, Pedro & García-Afonso, Óscar, 2013. "Packed bed of spherical particles approach for pressure drop prediction in wall-flow DPFs (diesel particulate filters) under soot loading conditions," Energy, Elsevier, vol. 58(C), pages 644-654.
    3. Payri, F. & Broatch, A. & Serrano, J.R. & Piqueras, P., 2011. "Experimental–theoretical methodology for determination of inertial pressure drop distribution and pore structure properties in wall-flow diesel particulate filters (DPFs)," Energy, Elsevier, vol. 36(12), pages 6731-6744.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhu, Xinning & Zuo, Qingsong & Tang, Yuanyou & Xie, Yong & Shen, Zhuang & Yang, Xiaomei, 2022. "Performance enhancement of equilibrium regeneration in a gasoline particulate filter based on field synergy theory," Energy, Elsevier, vol. 244(PA).
    2. García, Antonio & Monsalve-Serrano, Javier & Lago Sari, Rafael & Gaillard, Patrick, 2020. "Assessment of a complete truck operating under dual-mode dual-fuel combustion in real life applications: Performance and emissions analysis," Applied Energy, Elsevier, vol. 279(C).
    3. Zhao, Xiaohuan & Jiang, Jiang & Zuo, Hongyan & Jia, Guohai, 2023. "Soot combustion characteristics of oxygen concentration and regeneration temperature effect on continuous pulsation regeneration in diesel particulate filter for heavy-duty truck," Energy, Elsevier, vol. 264(C).
    4. Macián, V. & Serrano, J.R. & Piqueras, P. & Sanchis, E.J., 2019. "Internal pore diffusion and adsorption impact on the soot oxidation in wall-flow particulate filters," Energy, Elsevier, vol. 179(C), pages 407-421.
    5. Jiale Fu & Tiechen Zhang & Menghan Li & Su Li & Xianglin Zhong & Xiaori Liu, 2019. "Study on Flow and Heat Transfer Characteristics of Porous Media in Engine Particulate Filters Based on Lattice Boltzmann Method," Energies, MDPI, vol. 12(17), pages 1-29, August.
    6. Wang, Kai & Dong, Huzi & Wang, Long & Zhao, Wei & Wang, Yanhai & Guo, Haijun & Zang, Jie & Fan, Long & Zhang, Xiaolei, 2023. "Temperature-induced micropore structure alteration of raw coal and its implications for optimizing the degassing temperature in pore characterization," Energy, Elsevier, vol. 268(C).
    7. Zhao, Xiaohuan & Zuo, Hongyan & Jia, Guohai, 2022. "Effect analysis on pressure sensitivity performance of diesel particulate filter for heavy-duty truck diesel engine by the nonlinear soot regeneration combustion pressure model," Energy, Elsevier, vol. 257(C).
    8. Torregrosa, Antonio José & Serrano, José Ramón & Piqueras, Pedro & García-Afonso, Óscar, 2017. "Experimental and computational approach to the transient behaviour of wall-flow diesel particulate filters," Energy, Elsevier, vol. 119(C), pages 887-900.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Torregrosa, Antonio José & Serrano, José Ramón & Piqueras, Pedro & García-Afonso, Óscar, 2017. "Experimental and computational approach to the transient behaviour of wall-flow diesel particulate filters," Energy, Elsevier, vol. 119(C), pages 887-900.
    2. Bermúdez, Vicente & Serrano, José Ramón & Piqueras, Pedro & Campos, Daniel, 2015. "Analysis of the influence of pre-DPF water injection technique on pollutants emission," Energy, Elsevier, vol. 89(C), pages 778-792.
    3. Luján, José Manuel & Serrano, José Ramón & Piqueras, Pedro & García-Afonso, Óscar, 2015. "Experimental assessment of a pre-turbo aftertreatment configuration in a single stage turbocharged diesel engine. Part 2: Transient operation," Energy, Elsevier, vol. 80(C), pages 614-627.
    4. Serrano, J.R. & Climent, H. & Piqueras, P. & Angiolini, E., 2014. "Analysis of fluid-dynamic guidelines in diesel particulate filter sizing for fuel consumption reduction in post-turbo and pre-turbo placement," Applied Energy, Elsevier, vol. 132(C), pages 507-523.
    5. Macián, V. & Serrano, J.R. & Piqueras, P. & Sanchis, E.J., 2019. "Internal pore diffusion and adsorption impact on the soot oxidation in wall-flow particulate filters," Energy, Elsevier, vol. 179(C), pages 407-421.
    6. Zhao, Xiaohuan & Jiang, Jiang & Zuo, Hongyan & Jia, Guohai, 2023. "Soot combustion characteristics of oxygen concentration and regeneration temperature effect on continuous pulsation regeneration in diesel particulate filter for heavy-duty truck," Energy, Elsevier, vol. 264(C).
    7. Serrano, José Ramón & Arnau, Francisco José & Piqueras, Pedro & García-Afonso, Óscar, 2013. "Packed bed of spherical particles approach for pressure drop prediction in wall-flow DPFs (diesel particulate filters) under soot loading conditions," Energy, Elsevier, vol. 58(C), pages 644-654.
    8. Bermúdez, V. & Serrano, J.R. & Piqueras, P. & García-Afonso, O., 2015. "Pre-DPF water injection technique for pressure drop control in loaded wall-flow diesel particulate filters," Applied Energy, Elsevier, vol. 140(C), pages 234-245.
    9. Jiaqiang, E & Zhao, Xiaohuan & Xie, Longfu & Zhang, Bin & Chen, Jingwei & Zuo, Qingsong & Han, Dandan & Hu, Wenyu & Zhang, Zhiqing, 2019. "Performance enhancement of microwave assisted regeneration in a wall-flow diesel particulate filter based on field synergy theory," Energy, Elsevier, vol. 169(C), pages 719-729.
    10. Galindo, José & Serrano, José Ramón & Piqueras, Pedro & García-Afonso, Óscar, 2012. "Heat transfer modelling in honeycomb wall-flow diesel particulate filters," Energy, Elsevier, vol. 43(1), pages 201-213.
    11. Tsuneyoshi, Koji & Yamamoto, Kazuhiro, 2012. "A study on the cell structure and the performances of wall-flow diesel particulate filter," Energy, Elsevier, vol. 48(1), pages 492-499.
    12. Seok, Jungmin & Chun, Kwang Min & Song, Soonho & Lee, Jeongmin, 2014. "An empirical study of the dry soot filtration behavior of a metal foam filter on a particle number concentration basis," Energy, Elsevier, vol. 76(C), pages 949-957.
    13. Zhao, Xiaohuan & Zuo, Hongyan & Jia, Guohai, 2022. "Effect analysis on pressure sensitivity performance of diesel particulate filter for heavy-duty truck diesel engine by the nonlinear soot regeneration combustion pressure model," Energy, Elsevier, vol. 257(C).
    14. Hasannuddin, A.K. & Wira, J.Y. & Sarah, S. & Ahmad, M.I. & Aizam, S.A. & Aiman, M.A.B. & Watanabe, S. & Hirofumi, N. & Azrin, M.A., 2016. "Durability studies of single cylinder diesel engine running on emulsion fuel," Energy, Elsevier, vol. 94(C), pages 557-568.
    15. Xu, Wanrong & Kou, Chuanfu & E, Jiaqiang & Feng, Changling & Tan, Yan, 2024. "Effect analysis on the flow uniformity and pressure drop characteristics of the rotary diesel particulate filter for heavy-duty truck," Energy, Elsevier, vol. 288(C).
    16. Qiu, Tao & Li, Ning & Lei, Yan & Sang, Hailang & Ma, Xuejian & Liu, Zedu, 2024. "Research on the method of diesel particulate filters carbon load recognition based on deep learning," Energy, Elsevier, vol. 292(C).
    17. Orihuela, M. Pilar & Chacartegui, Ricardo & Martínez-Fernández, Julián, 2020. "New biomorphic filters to face upcoming particulate emissions policies: A review of the FIL-BIO-DIESEL project," Energy, Elsevier, vol. 201(C).
    18. Zhu, Xinning & Zuo, Qingsong & Tang, Yuanyou & Xie, Yong & Shen, Zhuang & Yang, Xiaomei, 2022. "Performance enhancement of equilibrium regeneration in a gasoline particulate filter based on field synergy theory," Energy, Elsevier, vol. 244(PA).
    19. Ye, Jiahao & Yang, Wenming & Peng, Qingguo & Liu, Haili, 2024. "Improvement and prediction of particles emission from diesel particulate filter based on an integrated artificial neural network," Energy, Elsevier, vol. 294(C).
    20. Payri, F. & Broatch, A. & Serrano, J.R. & Piqueras, P., 2011. "Experimental–theoretical methodology for determination of inertial pressure drop distribution and pore structure properties in wall-flow diesel particulate filters (DPFs)," Energy, Elsevier, vol. 36(12), pages 6731-6744.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:112:y:2016:i:c:p:883-898. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.