Multi-objective Optimization of Hybrid Carbon/Glass Fiber Reinforced Epoxy Composite Automotive Drive Shaft
TL;DRAbstract
In design and fabricate drive shafts with high value of fundamental natural frequency that represented high value of critical speed; using composite materials instead of typical metallic materials could provide longer length shafts with lighter weight. In this paper, multi-objective optimization (MOP) of a composite drive shaft is performed considering three conflicting objectives: fundamental natural frequency, critical buckling torque and weight of the shaft. Fiber orientation angle, ply thickness and stacking sequence are also considered as the design variables in this MOP. To solve this MOP, Modified Non-Dominated Sorting Genetic Algorithm (modified NSGA II) is employed. To calculate fundamental natural frequency and critical buckling torque, finite element model of a truck composite drive shaft has been carried out using commercial software ABAQUS/Standard. Finally optimum design points are obtained and from all non-dominated optimum design points, some trade-off points are picked
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In design and fabricate drive shafts with high value of fundamental natural frequency that represented high value of critical speed; using composite materials instead of typical metallic materials could provide longer length shafts with lighter weight. In this paper, multi-objective optimization (MOP) of a composite drive shaft is performed considering three conflicting objectives: fundamental natural frequency, critical buckling torque and weight of the shaft. Fiber orientation angle, ply thickness and stacking sequence are also considered as the design variables in this MOP. To solve this MOP, Modified Non-Dominated Sorting Genetic Algorithm (modified NSGA II) is employed. To calculate fundamental natural frequency and critical buckling torque, finite element model of a truck composite drive shaft has been carried out using commercial software ABAQUS/Standard. Finally optimum design points are obtained and from all non-dominated optimum design points, some trade-off points are picked
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