A novel concept for multi-objective optimization of composite power transmission shafts

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Abstract Shafts made of advanced composite materials and their applications in different fields are gaining momentum due to their optimized properties. This paper presents various multi-objective optimization (MOO) models for the structural design of slender, thin-walled spinning shafts made of advanced composite materials. The proposed mathematical formulation ensures the attainment of simultaneous and balanced improvements in the major design objectives, including minimal mass and maximum stability against whirling and torsional buckling under behavioral and side constraints. A hybrid genetic algorithm (GA) and sequential quadratic programming (SQP) are implemented to find the needed optimal solutions. Design variables encompass the fiber volume fraction, orientation angle, and thickness of each layer of the cross-section. A case study addresses the optimization of a pinned-pinned slender shaft made of carbon/epoxy composites is presented. The new approach exhibited its capacity to overcomes the uncertainty in ranking and selecting a solution from the set of Pareto-optimal solutions as it determines a unique optimal solution that has a nearly equal optimization gains for the selected design objectives

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