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Kazem Fayazbakhsh

Researcher at Ryerson University

Publications -  36
Citations -  1237

Kazem Fayazbakhsh is an academic researcher from Ryerson University. The author has contributed to research in topics: Ultimate tensile strength & Fused filament fabrication. The author has an hindex of 12, co-authored 27 publications receiving 893 citations. Previous affiliations of Kazem Fayazbakhsh include McGill University & Sharif University of Technology.

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Optimum stacking sequence design of composite materials Part II: Variable stiffness design

TL;DR: In this paper, a composite laminate may be designed as a permutation of several straight-fiber layers or as a matrix embracing fibers positioned in curvilinear paths.
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Optimization of variable stiffness composites with embedded defects induced by Automated Fiber Placement

TL;DR: In this paper, the authors investigate how the parameters governing the formation of defects impact the set of optimal solutions for a multi-objective optimization problem, where in-plane stiffness and buckling load are simultaneously maximized.
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Defect layer method to capture effect of gaps and overlaps in variable stiffness laminates made by Automated Fiber Placement

TL;DR: In this paper, a composite laminate with curvilinear fiber paths is designed to maximize simultaneously its in-plane stiffness and buckling load, and a defect layer is proposed to characterize the change in properties of each layer in the composite laminates that results from the occurrence of gaps and overlaps.
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Surrogate-based multi-objective optimization of a composite laminate with curvilinear fibers

TL;DR: In this paper, the problem of simultaneous optimization of stiffness and buckling load of a composite laminate plate with curvilinear fiber paths is formulated and solved through a surrogate-based optimization algorithm capable of finding the set of optimum Pareto solutions.
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A comparative study of metamodeling methods for the design optimization of variable stiffness composites

TL;DR: In this paper, a set of metamodeling techniques for the design optimization of composite laminates with variable stiffness is examined. And the results show that the most accurate and robust models in exploring the design space are Kriging and Radial Basis Functions.