Through thickness air permeability and thermal conductivity analysis for textile materials - Saldaeva, Elena (2010)
Woven fabrics have found enormous application in our daily life and in industry because of their flexibility, strength and permeability. The aim of this work was to create a general model for through thickness air permeability and thermal conductivity for different types of textile fabrics because of their applications in industries and everyday life. An analytical model to predict through thickness air permeability was developed. The objective was to create a model which will take into consideration the two primary mechanisms of air flow in fabrics: through the gaps between yarns and through the yarns. Through thickness air permeability was measured according to British Standard BS EN ISO 9237: 1995. Several fabrics were tested including plain weave, twill weave and satin weave fabrics. The analytical model is a combination Kulichenko and Van Langenhove's analytical model which predicts the permeability through gaps between yams with Gebart's model to predict permeability within yams. Analytical predictions were compared to the experimental data. Computational modelling of through thickness air permeability using Computational Fluid Dynamics CFD software is presented in this thesis. The Polymer Composites Research Group in the University of Nottingham has created a textile schema, named TexGen. The prerequisites of this software were to be able to model various types of textile structures. A CFD model using CFX 11.0 was developed to be able to predict fabric permeability. In addition, an analytical model was developed for fabrics deformed by shear, compaction and tension. Experimental work for through thickness air permeability of sheared fabric was used to verify predicted results. An analytical model for thermal conductivity of fabrics was developed including the influence of moisture content on thermal conductivity. Two existing approaches for single-layer fabrics are described and compared: rule of mixtures and thermal resistance approach. A me6iod for thermal conductivity prediction for multiple layer fabrics is presented. The results are compared to the experimental data and analysed.