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Computational Analysis of Woven Fabric Composites: Single- and Multi-Objective Optimizations and Sensitivity Analysis in Meso-scale Structures

  • This study permits a reliability analysis to solve the mechanical behaviour issues existing in the current structural design of fabric structures. Purely predictive material models are highly desirable to facilitate an optimized design scheme and to significantly reduce time and cost at the design stage, such as experimental characterization. The present study examined the role of three majorThis study permits a reliability analysis to solve the mechanical behaviour issues existing in the current structural design of fabric structures. Purely predictive material models are highly desirable to facilitate an optimized design scheme and to significantly reduce time and cost at the design stage, such as experimental characterization. The present study examined the role of three major tasks; a) single-objective optimization, b) sensitivity analyses and c) multi-objective optimization on proposed weave structures for woven fabric composites. For single-objective optimization task, the first goal is to optimize the elastic properties of proposed complex weave structure under unit cells basis based on periodic boundary conditions. We predict the geometric characteristics towards skewness of woven fabric composites via Evolutionary Algorithm (EA) and a parametric study. We also demonstrate the effect of complex weave structures on the fray tendency in woven fabric composites via tightness evaluation. We utilize a procedure which does not require a numerical averaging process for evaluating the elastic properties of woven fabric composites. The fray tendency and skewness of woven fabrics depends upon the behaviour of the floats which is related to the factor of weave. Results of this study may suggest a broader view for further research into the effects of complex weave structures or may provide an alternative to the fray and skewness problems of current weave structure in woven fabric composites. A comprehensive study is developed on the complex weave structure model which adopts the dry woven fabric of the most potential pattern in singleobjective optimization incorporating the uncertainties parameters of woven fabric composites. The comprehensive study covers the regression-based and variance-based sensitivity analyses. The second task goal is to introduce the fabric uncertainties parameters and elaborate how they can be incorporated into finite element models on macroscopic material parameters such as elastic modulus and shear modulus of dry woven fabric subjected to uni-axial and biaxial deformations. Significant correlations in the study, would indicate the need for a thorough investigation of woven fabric composites under uncertainties parameters. The study describes here could serve as an alternative to identify effective material properties without prolonged time consumption and expensive experimental tests. The last part focuses on a hierarchical stochastic multi-scale optimization approach (fine-scale and coarse-scale optimizations) under geometrical uncertainties parameters for hybrid composites considering complex weave structure. The fine-scale optimization is to determine the best lamina pattern that maximizes its macroscopic elastic properties, conducted by EA under the following uncertain mesoscopic parameters: yarn spacing, yarn height, yarn width and misalignment of yarn angle. The coarse-scale optimization has been carried out to optimize the stacking sequences of symmetric hybrid laminated composite plate with uncertain mesoscopic parameters by employing the Ant Colony Algorithm (ACO). The objective functions of the coarse-scale optimization are to minimize the cost (C) and weight (W) of the hybrid laminated composite plate considering the fundamental frequency and the buckling load factor as the design constraints. Based on the uncertainty criteria of the design parameters, the appropriate variation required for the structural design standards can be evaluated using the reliability tool, and then an optimized design decision in consideration of cost can be subsequently determined.show moreshow less

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Metadaten
Document Type:Doctoral Thesis
Author:Senior Lecturer Ilyani Akmar Abu BakarGND
DOI (Cite-Link):https://doi.org/10.25643/bauhaus-universitaet.4176Cite-Link
URN (Cite-Link):https://nbn-resolving.org/urn:nbn:de:gbv:wim2-20200605-41762Cite-Link
ISSN:1610-7381
Series (Serial Number):ISM-Bericht // Institut für Strukturmechanik, Bauhaus-Universität Weimar (2020,1)
Advisor:Prof. Dr.-Ing. Timon RabczukORCiDGND
Language:English
Date of Publication (online):2020/06/04
Date of first Publication:2020/06/04
Date of final exam:2020/02/03
Release Date:2020/06/05
Publishing Institution:Bauhaus-Universität Weimar
Granting Institution:Bauhaus-Universität Weimar, Fakultät Bauingenieurwesen
Institutes:Fakultät Bauingenieurwesen / Institut für Strukturmechanik
Pagenumber:151
Tag:Gewebeverbundwerkstoff
woven composites
GND Keyword:Verbundwerkstoff
Dewey Decimal Classification:500 Naturwissenschaften und Mathematik
600 Technik, Medizin, angewandte Wissenschaften / 620 Ingenieurwissenschaften / 624 Ingenieurbau
BKL-Classification:51 Werkstoffkunde / 51.75 Verbundwerkstoffe, Schichtstoffe
56 Bauwesen / 56.59 Bauingenieurwesen, Bautechnik: Sonstiges
Licence (German):License Logo Creative Commons 4.0 - Namensnennung-Weitergabe unter gleichen Bedingungen (CC BY-SA 4.0)