In this study, optimal design of two-dimensional functionally graded thick flywheels is obtained by the generalized differential quadrature method (GDQM) and the non-dominated sorting genetic algorithm II (NSGA II). The flywheel cross section is parameterized with the Bezier surface, and a mapping procedure to discretize non-rectangular solution domain by the GDQM is introduced. The results of this novel technique are compared with the results available in open literature and the ANSYS finite element solution, and a very good agreement is observed. Pareto optimal solutions for minimum mass and maximum energy storage capability are obtained for two types of bearing, one being mechanical and the other magnetic. Consequently, the optimal cross-section geometry and the two-dimensional material distribution of functionally graded (FG) flywheel are obtained.

在这项研究中，通过广义差分正交方法（GDQM）和非控制分类遗传算法II（NSGA II）获得了二维功能梯度厚飞轮的最佳设计。用Bezier曲面对飞轮横截面进行参数化，并介绍了一种通过GDQM离散化非矩形解域的映射过程。将该新技术的结果与公开文献和ANSYS有限元解决方案中的结果进行了比较，并观察到了很好的一致性。对于两种轴承，一种是机械轴承，另一种是磁性轴承，可获得最小质量和最大能量存储能力的帕累托最优解决方案。所以，