Finite element analysis of thermal conductivity and thermal resistance behaviour of woven fabric

Siddiqui, Muhammad Owais Raza; Sun, Danmei

doi:10.1016/j.commatsci.2013.04.003

Cited by 45 publications

(23 citation statements)

References 13 publications

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“…Attempts have been made to develop computational models for thermal resistance, moisture transmission and impact resistance of woven fabrics [11][12][13] using finite element modeling. ANN-GA has been used as a computational platform in various domains of materials engineering including processes of powder metallurgy of pure iron [14], injection molding of plastic [15] and laser welding of stainless steel [16].…”

Section: Introductionmentioning

confidence: 99%

Optimization of woven fabric parameters for ultraviolet radiation protection and comfort using artificial neural network and genetic algorithm

Majumdar

Das

Hatua

et al. 2015

Neural Comput & Applic

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Optimization of woven fabric parameters for ultraviolet protection factor (UPF) and comfort properties has been attempted using hybrid artificial neural network (ANN)-genetic algorithm (GA) system. ANN was used for developing the prediction models, and GA was employed as an optimization tool. Four feasible combinations of UPF, air permeability and moisture vapor transmission rate (MVTR) were chosen from the Pareto charts of UPF-air permeability and UPF-MVTR. Penalty function method was adopted to form a single objective function by combining the objectives and constraints related to UPF, air permeability and MVTR. The developed ANN-GA hybrid system was executed to obtain the solution set of input parameters for achieving the targeted fabric properties. To validate the developed ANN-GA-based fabric parameter optimization system, four fabric samples were woven using the solution sets of input parameters and functional properties of these engineered fabrics were evaluated. The targeted and achieved values of fabric properties of four validation samples were in reasonably good agreement.

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Section: Introductionmentioning

confidence: 99%

Optimization of woven fabric parameters for ultraviolet radiation protection and comfort using artificial neural network and genetic algorithm

Majumdar

Das

Hatua

et al. 2015

Neural Comput & Applic

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“…A simple way to apply the RVE model is to use the minimal structural repeating unit with a periodicity hypothesis. For example, Siddiqui et al [18] investigated the effective thermal conductivity and thermal resistance of a 2-D woven fabric using the finite element method. An RVE model including two warp yarns and two weft yarns was applied based on the scanning electron microscope, and the geometrical size of the RVE was 0.862 mm × 0.862 mm × 0.5 mm.…”

Section: Introductionmentioning

confidence: 99%

Prediction Model for the Anisotropic Thermal Conductivity of a 2.5-D Braided Ceramic Matrix Composite with Thin-Wall Structure

Mao

Han

et al. 2019

Applied Sciences

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The thickness of the hot component in a turbine engine is usually small. Therefore, the traditional prediction model of anisotropic thermal conductivity (ATC) based on the periodic hypothesis may be improper for use in the thermal analysis of ceramic matrix composite (CMC) components with a thin-wall structure. Thus, the prediction model for the ATC of a 2.5-D braided CMC was investigated, taking into account the actual thickness of the CMC thin-wall structure. An RVE (Representative Volume Element) model with a periodic boundary and a full-size model with the actual thickness were built to study the temperature field, the heat flux field, and the effective thermal conductivity of the CMC. A validation experiment was carried out to verify the accuracy of the two prediction models. The effect of the composite’s thickness on the ATC and the critical thickness suitable for the RVE model were also studied. The results showed that in the thermal analysis of the thin-wall structure, the RVE model had a large deviation in the estimation of the effective thermal conductivity in the thickness direction. The relative error between the numerical data based on the RVE model and the experimental data reached 10.93%, while the relative error was only 3.53% for the full-size model. Additionally, with increasing thickness, the effective thermal conductivities, based on the RVE model and the full-size model, were close to each other. For the critical thickness for the RVE model, which would be suitable for the prediction of the ATC, if the material’s thermal properties such as the absolute value ratio and the level of anisotropy changed, the corresponding critical thickness was also different. For the ATC of the SiC/SiC composites used in this study, the critical thickness was found to be 18.4 mm, nearly 31 times larger than the RVE model’s thickness.

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“…And this paper is also focused on the simulation of the initial fracture properties of the hybrid fabric reinforced composite. Siddiqui and Sun [26] …”

Section: Introductionmentioning

confidence: 99%

A Study on the Initial Fracture Behavior of CF/GF Intra-Hybrid Woven Fabric Reinforced Composites

Xu¹,

Nakai²,

Yang³

et al. 2018

OJCM

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In this paper, woven fabrics of glass fiber/carbon fiber intra-hybrid in plain structure were used to fabricate fiber reinforced plastic (FRP) composite by hand lay-up method. The investigation on tensile property was carried out on specimens in 7 orientations including 0˚/5˚/15˚/75˚/85˚/90˚ in previous works. With the specimen parameters and experimental data, FEM model was built by the software of Marc. By combining the experimental results and finite element analysis, the modulus was simulated and calculated at the first stage. Then interfacial stress of the 0 degree and 90 degree was also calculated. By the initial fracture stress data from experiment as well as the simulation value of interfacial strength of 0 and 90 degree, the initial fracture stress of the off-axial specimens was calculated and predicted. The result shows that the interfacial strength of the glass fiber bundle is higher than that of the carbon fiber bundle in transverse direction. By using the interfacial strength and according to the Von Mises yielding criterion, the initial fracture stress was predicted, which can be a contribution to the design or predict of the material properties.

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Finite element analysis of thermal conductivity and thermal resistance behaviour of woven fabric

Cited by 45 publications

References 13 publications

Optimization of woven fabric parameters for ultraviolet radiation protection and comfort using artificial neural network and genetic algorithm

Optimization of woven fabric parameters for ultraviolet radiation protection and comfort using artificial neural network and genetic algorithm

Prediction Model for the Anisotropic Thermal Conductivity of a 2.5-D Braided Ceramic Matrix Composite with Thin-Wall Structure

A Study on the Initial Fracture Behavior of CF/GF Intra-Hybrid Woven Fabric Reinforced Composites

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