Optimal shape synthesis of a metallic flywheel using non-dominated sorting Jaya algorithm

This study describes the shape synthesis of a metallic flywheel using a non-dominated sorting Jaya algorithm. Generally, the flywheel is used to store the kinetic energy in the machines. Kinetic energy is an essential parameter to measure flywheel performance and can be improved by the optimal shape of the flywheel. In order to the optimal shape of the flywheel, the multi-objective problem with the maximization of the kinetic energy and minimization of von Mises stresses is formulated under appropriate design constraints using the cubic B-spline curve. A flowchart is proposed to solve the two-point boundary value differential equation for the calculation of von Mises stress at each point between the inner and outer radii of the flywheel. The design variables are represented by the control points of the cubic B-spline curve. A posteriori approach-based algorithm as non-dominated sorting Jaya algorithm (NSJaya) is used to solve the formulated optimization problem. This algorithm is based on the concepts of crowding distance and non-dominated sorting approach and gives the optimal Pareto set. The proposed method is applied to the flywheel of the agricultural thresher. The performance of the proposed algorithm is compared with that of non-dominated sorting genetic algorithm (NSGA-II) using hyper-volume performance metric. It is found that the NSJaya algorithm gives better results compared to NSGA-II and a posteriori approach-based algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), and Jaya. The optimal Pareto set for the optimal shape of the flywheel is calculated and outlined in this paper. The designer can choose any solution from the Pareto set for the optimal shape of the flywheel. ANSYS parameter design language (APDL) software is used for the validation of the von Mises stresses in the optimized shapes of the flywheel.