A Comparative Study of Geometric Models for Predicting Permeability Coefficients and Specific Surface Areas of Fibrous Porous Media

被引:5
|
作者
Mare, Esmari [1 ]
Woudberg, Sonia [1 ]
机构
[1] Stellenbosch Univ, Dept Math Sci, Appl Math Div, Private Bag 11, ZA-7602 Stellenbosch, Western Cape, South Africa
基金
新加坡国家研究基金会;
关键词
Metal foams; Fibrous media; Permeability; Specific surface area; Darcy; Forchheimer; PRESSURE-DROP MEASUREMENTS; HEAT-TRANSFER; CERAMIC FOAMS; MASS-TRANSFER; FLOW; EQUATION; SUPPORTS;
D O I
10.1007/s11242-023-01948-y
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Several studies in the literature have been devoted to the permeability prediction of metal foams and stacked fibres, including the representative unit cell (RUC) model. This study is the first to involve a comparative analysis for the permeability and specific surface area prediction of different versions of the RUC model for fibrous media, i.e. the 2D RUC models for in-plane and through plane flow, the 3D RUC model, the two-strut RUC models for in-plane and through plane flow and the three-strut RUC model. These models are chosen due to their simple rectangular geometry, as well as its satisfying performance in comparison with other models and experimental data as proven elsewhere in the literature for fibrous media. The Darcy and Forchheimer permeability coefficients of these models are presented of which some are novel contributions. A geometric approach requiring measured geometric parameters and a combined geometric-kinetic approach requiring measured permeability coefficients are included for determining the specific surface area for all the models of which the majority of expressions are new. Also novel to this study is the comparative analysis of the 2D and 3D RUC modelling approaches to that of the two-strut and three-strut approaches. An evaluation of which models would suit fibre-like media and which would suit foam-like media is also included with regard to permeability and specific surface area predictions, based on geometric features and model predictive ability. The models are evaluated through comparison with other models from the literature as well as available experimental and numerical data.
引用
收藏
页码:383 / 416
页数:34
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