Shape optimization of flywheel used in agricultural thresher

TL;DR

This paper presents a shape optimization method for an agricultural thresher's flywheel using cubic B-spline curves and the Jaya algorithm, aiming to maximize kinetic energy while respecting stress and mass constraints.

Contribution

It introduces a novel shape optimization approach combining B-spline curves with the Jaya algorithm for flywheel design in agricultural machinery.

Findings

Jaya algorithm outperforms GA and PSO in flywheel shape optimization.

Optimized flywheel designs show improved energy storage capacity.

Finite difference method effectively evaluates stress constraints.

Abstract

This research paper presents the procedure for shape optimization of flywheel used in an agricultural thresher machine using a cubic B-spline curve and the Jaya algorithm. The flywheel is an essential element for storing kinetic energy in modern machines. Shape optimization of the flywheel was carried out using a cubic B-spline curve to maximize the kinetic energy of the flywheel subjected to constraints of mass of flywheel and permissible value of Von-Mises stress in a flywheel. The B-spline curve was used as it gives local control and is not restricted by control points. The control points of the B-spline are considered design variables. The Von-Mises stresses at all points in the flywheel are determined by solving two-point boundary value differential equations using the finite difference method. Finally, the optimization problem was solved using the Jaya algorithm. These results are then compared with results obtained using other nature-inspired algorithms like a genetic algorithm (GA), and particle swarm optimization (PSO), and it is found that the Jaya algorithm gives better results. This project is based on the research paper optimal design of the flywheel using nature-inspired optimization algorithms (Prem Singh, Himanshu Choudhary) which applied GA, PSO, and Jaya algorithms.