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dc.contributor.authorXu, Yanan
dc.date.accessioned2024-03-06T03:03:32Z
dc.date.available2024-03-06T03:03:32Z
dc.date.issued2024en_AU
dc.identifier.urihttps://hdl.handle.net/2123/32314
dc.descriptionIncludes publication
dc.description.abstractThe utilization of carbon fiber reinforced polymer (CFRP) composites is rapidly expanding across a range of industries attributable to their exceptional material properties, including lightweight, high strength-to-weight ratio, stiffness-to-weight ratio, corrosion resistance, great designability, and excellent fatigue characteristics. Topology optimization and fiber path optimization of CFRP structures enable to further improve the ratios of strength/stiffness to weight for achieving a better lightweight design. In this study, design optimization of topological configuration and fiber paths are conducted using the gradient-based methods, in which design sensitivities are derived for all the optimization methods, including discrete material optimization (DMO) and level set method (LSM). To address the problem of the convergence to local optima in the gradient-based methods, a novel procedure combining the machine learning (ML) techniques with DMO is proposed to search for a quasi-global optimum. To accommodate the advanced manufacturing technologies such as additive manufacturing (also named 3D printing), LSM is proposed for both topology and fiber path optimizations, which enables to present the filament paths inherently without further reconstruction of the nozzle path. Combing with the fast-marching method of LSM, manufacturing drawbacks of gaps and overlaps induced from the non-parallel filament paths can be addressed. Optimized and empirical samples are fabricated with 3D printers to demonstrate the effectiveness of the proposed new techniques for further improving the structural performances.en_AU
dc.language.isoenen_AU
dc.subjectTopology optimizationen_AU
dc.subjectLevel-seten_AU
dc.subjectFiber path optimizationen_AU
dc.subjectfiber reinforced plastics (FRP)en_AU
dc.subjectAdditive manufacturingen_AU
dc.subjectMachine learningen_AU
dc.titleTopology optimization of fiber reinforced plastic structuresen_AU
dc.typeThesis
dc.type.thesisDoctor of Philosophyen_AU
dc.rights.otherThe author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.en_AU
usyd.facultySeS faculties schools::Faculty of Engineering::School of Aerospace Mechanical and Mechatronic Engineeringen_AU
usyd.degreeDoctor of Philosophy Ph.D.en_AU
usyd.awardinginstThe University of Sydneyen_AU
usyd.advisorLi, Qing
usyd.include.pubYesen_AU


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