4.6 Article

A proposal for a correlation to calculate pressure drop in reticulated porous media with the help of numerical investigation of pressure drop in ideal & randomized reticulated structures

期刊

CHEMICAL ENGINEERING SCIENCE
卷 237, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ces.2021.116518

关键词

Direct pore level simulation; Pressure drop correlation; Kelvin structure; Randomization

资金

  1. Science and Engineering Research Board (SERB) through the startup research grant (SRG) scheme
  2. National Institute of Technology Karnataka
  3. Indian Ministry of Human Resource Development
  4. Amrita Vishwa Vidyapeetham

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This study presents a numerical investigation on estimating pressure drop in fluid flow through ideal and randomized porous structures. A pressure drop correlation is proposed based on the analysis of pressure drop variation with respect to different factors. The proposed correlation is compared with experimental and numerical data from real structures to validate its effectiveness.
This paper presents a numerical investigation to estimate pressure drop in fluid flow through reticulated ideal and randomized porous structures. The 3D open-cell foam geometries are constructed using an inhouse code along with the use of visualization tool kit (VTK) libraries. In this study, the ideal and randomized Kelvin structures with different porosities and pore densities are generated. These structures have been used to perform direct pore level simulations (DPLS) with the aid of a commercial CFD software. The simulation results are used to acquire the pressure drop across the structures. The pressure drop variation with respect to pore density, porosity, specific surface area, and randomization are analyzed and a pressure drop correlation for reticulated structures with new values of viscous and inertial coefficients is proposed. The validity of the proposed correlation is compared against the experimental and numerical data of the real structures that are available in the literature. (c) 2021 Elsevier Ltd. All rights reserved.

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