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UBC Theses and Dissertations

Multi-scale characterization and modeling of shear-tension interaction in woven fabrics for composite forming and structural applications Komeili, Mojtaba

Abstract

Woven fiber-reinforced polymer composites have become superior materials of choice in advanced industries such as aerospace, energy and automotive. The low in-plane shear stiffness of woven fabrics provides them with high formability, and hence the characterization of this stiffness is of high impotence. Although it was assumed in the past that a fabric’s shear modulus is merely a function of its shear angle, recent evidences show that this material property is also dependent on other factors such as tension along yarns. However, there are currently difficulties to fully characterize the level of this shear-tension interaction. In this thesis, two different approaches are proposed to tackle the above characterization problem: (1) experimental measurements using a newly developed test fixture; (2) virtual experiments, which can greatly decrease the characterization cost. However, the input data for the virtual experiments including material properties for yarns must be provided. Accordingly, a new inverse identification approach using results of two conventional tests, (1) uni-axial tension and (2) shear frame tests with initial pre-tension, were used along with a multi-objective genetic algorithm optimization to arrive at material properties of yarns. Then, virtual experiments at meso-level are conducted to extract the response surface of a selected fabric (TWINTEX polypropylene/glass plain weave) under general in-plane combined shear-tension loadings. The outcome was used in studying twisting moment response of inflatable structures reinforced with woven fabrics as well as stamping process of the TWINTEX using three different punch and mold geometries. Eventually, a comparison between earlier models (without interaction between shear and tension modes) and the new model with shear-tension interaction is presented and practical recommendations are made for enhanced fabric simulations.

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Attribution-NonCommercial-NoDerivs 2.5 Canada