dc.contributor.authorAditya Mahesh Khatri
dc.identifier.citationAditya Mahesh Khatri. (2014). Predictive modeling for composites properties based on reinforcing fibre architecture. Master’s thesis, Nanyang Technological University, Singapore.
dc.description.abstractUse of structurally reinforced composites is widespread in many industries and applications due to their high strength-to-weight ratio. For textile fiber architectures, their entwined nature ensures that multi-directional integrity is maintained without being affected much by climate and other wear-and-tear. Different types of fiber reinforcement architectures impart different properties to the corresponding composites. This study seeks to compare the mechanical properties of differently structured performs – namely, unidirectional, woven and braided textiles. Novel expressions for the transverse Young’s modulus and Poisson’s ratio of unidirectional fibers were derived to provide improvements over the contemporary computational and classical models. These new expressions make use of shear effects at the yarn-matrix interface and are adapted for non-circular yarns as well. Consequently, mechanical property predictors for woven and braided textile composites are created. Geometric and mechanical stiffness models in MATLAB® using Classical Lamination Theory (CLT) are developed. These models make use of contemporary as well as the new-improved yarn formulations. As envisaged, improvements over the existing textile modeling work are observed. A general modeling methodology that can be used for implementing CLT for predicting properties of other textiles (such as knitted) is also established.en_US
dc.format.extent249 p.en_US
dc.subjectDRNTU::Engineering::Materials::Composite materialsen_US
dc.subjectDRNTU::Engineering::Aeronautical engineering::Materials of constructionen_US
dc.subjectDRNTU::Engineering::Mathematics and analysis::Simulationsen_US
dc.titlePredictive modeling for composites properties based on reinforcing fibre architectureen_US
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.contributor.supervisorSunil Chandrakant Joshien_US
dc.description.degreeMASTER OF ENGINEERING (MAE)en_US

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