论文标题
在农业脱粒机中使用的飞轮的形状优化
Shape optimization of flywheel used in agricultural thresher
论文作者
论文摘要
本研究论文介绍了使用立方B-Spline曲线和Jaya算法在农业脱粒机中使用的飞轮优化的过程。飞轮是在现代机器中存储动能的重要元素。使用立方B-Spline曲线进行飞轮的形状优化，以最大程度地发挥飞轮的动力，受到飞轮质量的约束，并在飞轮中的von-Mises应力的允许值。使用B-Spline曲线是因为它提供了局部控制，并且不受控制点的限制。 B-Spline的控制点被认为是设计变量。通过使用有限差方法求解两点边界值的差微分方程来确定飞轮中所有点的von-mises应力。最后，使用JAYA算法解决了优化问题。然后将这些结果与使用遗传算法（GA）（GA）和粒子群优化（PSO）（PSO）等其他自然启发算法获得的结果进行比较，并发现Jaya算法可获得更好的结果。该项目基于使用自然风格的优化算法（Prem Singh，Himanshu Choudhary）的研究纸最佳设计，该算法应用了GA，PSO和Jaya算法。
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.
