Optimizing Metal‐Surface Water Disinfection: CFD Study on Microorganism Collision Against a Triply Periodic Minimal Surface

Abstract: This research presents a point‐of‐use (POU) water treatment technology utilizing metal/metallic surfaces based on Triply Periodic Minimal Surface (TPMS) structured filtration infills. Computational Fluid Dynamics modeling using Ansys CFX software is employed to analyze the behavior of Escherichia coli bacteria within a continuous liquid phase moving through the filtration infill, assess particle collision dynamics, and evaluate the efficiency of filtration, considering pressure drop as a fundamental factor in process energy consumption. TPMS infill meshes are coded in a Schwarz P shape using Python, and the Darcy‐Forchheimer equation is employed to determine the permeability and resistance loss coefficient of the infill geometry. The results indicate that the TPMS infill efficiently captures particles while introducing a negligible pressure drop into the system. It is found that a single 40 mm infill configuration is the most efficient, exhibiting a higher collision rate compared to the smaller 20 mm infill configuration and a lower pressure drop compared to the two 20 mm infill configurations in the series. Additionally, this study provides insights into the behavior of continuous fluid flow through TPMS infill in view of scaled‐up implementation, including the presence of recirculation zones that can be exploited to further enhance the collision rate of particles.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Optimizing Metal‐Surface Water Disinfection: CFD Study on Microorganism Collision Against a Triply Periodic Minimal Surface ; day:22 ; month:03 ; year:2024 ; extent:12
Advanced sustainable systems ; (22.03.2024) (gesamt 12)

Creator
Melo, Leonardo G. T. C.
de Menezes, Frederico Duarte
da Costa, José Angelo Peixoto
Alves, João Vitor Pereira
Chiang, Yi Wai
Santos, Rafael M.

DOI
10.1002/adsu.202300663
URN
urn:nbn:de:101:1-2024032213345151435636
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
14.08.2025, 10:49 AM CEST

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Associated

  • Melo, Leonardo G. T. C.
  • de Menezes, Frederico Duarte
  • da Costa, José Angelo Peixoto
  • Alves, João Vitor Pereira
  • Chiang, Yi Wai
  • Santos, Rafael M.

Other Objects (12)