Weight and Cost Multi-Objective Optimization of Hybrid Composite Sandwich Structures

Weight and Cost Multi-Objective Optimization of Hybrid Composite Sandwich Structures

A. I. Salem S. L. Donaldson

Department of Mechanical & Aerospace Engineering, University of Dayton, USA

Department of Civil & Environmental Engineering & Engineering Mechanics, University of Dayton, USA

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Producing a light structure with affordable cost without sacrificing strength has always been a challenging task for designers. Using a hybrid material approach provides an expanded methodology to combine materials having different costs and properties (for example, combining fibers with high cost and high stiffness such as carbon with low cost, less stiffness fibers such as glass). Hence, a comparative approach is useful for the evaluation of design solutions in terms of weight and cost. In this study, a methodology for a combined weight and cost optimization for sandwich plates with hybrid composite facesheets and foam core is presented. The weight and cost of the hybrid sandwich plates considered are the objective functions subject to required equality constraints based on the bending and torsional stiffnesses. The hybrid sandwich plates considered consisted of thin hybrid composite facesheets, symmetric with respect to the mid-plane of the sandwich plates. The facesheets considered consisted of carbon/epoxy and E-glass/epoxy fiber-reinforced polymer. The layup of the fibers of the facesheets were restricted to some discrete sets of plies having orientation angles of 0, ±45 and 90. A multi-objective optimization technique was applied to minimize simultaneously the weight and the cost of the hybrid sandwich plate. The normalized normal constraint method with Pareto filter was used to generate the Pareto frontier trade-off curve. The Pareto trade-off curve was constructed by optimizing a sequence of combining weight and cost objective functions, while every function was minimized using the Active Set Algorithm.


cost, hybrid, multi-objective optimization, normalized normal constraint method, weight


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