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<p>This study addresses the persistent issue of membrane fouling in filtration systems, a phenomenon that disrupts flow dynamics and reduces efficiency across various membrane types. To overcome the limitations of traditional models, a novel generalized framework, characterized by its fractional order (α), clogging indicator (n), and clogging rate constant (k), is proposed as a flexible and unified alternative to traditional models. This fractional formulation inherently allows the model to generalize effectively across various fouling behaviors: cake filtration, intermediate clogging, and standard blocking. Comparative analysis with classical models showed that the new framework consistently achieved higher accuracy, with normalized RMSE values ranging from 0.93% to 1.73% and R<sup>2</sup> values exceeding 0.995. Due to its fractional formulation, the model demonstrates strong generalization across various fouling behaviors, without requiring separate calibration for each scenario. It also enables one-step identification and characterization of the prevailing fouling mechanism while maintaining computational simplicity. Overall, this study introduces a scalable, accurate, and robust modeling framework that enhances membrane performance in fluid and mechanical engineering applications.</p>

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A generalized fractional model for one-step identification of membrane filtration clogging mechanisms

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月19日

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  • Leila Cherifi,
  • Yamina Ammi,
  • Salah Hanini,
  • Nadjem Bailek,
  • El-Sayed M. El-Kenawy,
  • Jihad A. Younis,
  • Bilel Zerouali,
  • Abdennasser Dahmani,
  • Ilhami Colak,
  • Abdulrazak H. Almaliki

摘要

This study addresses the persistent issue of membrane fouling in filtration systems, a phenomenon that disrupts flow dynamics and reduces efficiency across various membrane types. To overcome the limitations of traditional models, a novel generalized framework, characterized by its fractional order (α), clogging indicator (n), and clogging rate constant (k), is proposed as a flexible and unified alternative to traditional models. This fractional formulation inherently allows the model to generalize effectively across various fouling behaviors: cake filtration, intermediate clogging, and standard blocking. Comparative analysis with classical models showed that the new framework consistently achieved higher accuracy, with normalized RMSE values ranging from 0.93% to 1.73% and R2 values exceeding 0.995. Due to its fractional formulation, the model demonstrates strong generalization across various fouling behaviors, without requiring separate calibration for each scenario. It also enables one-step identification and characterization of the prevailing fouling mechanism while maintaining computational simplicity. Overall, this study introduces a scalable, accurate, and robust modeling framework that enhances membrane performance in fluid and mechanical engineering applications.