关键词: 螺纹连接, 多目标优化, 有限元分析, 遗传算法

Abstract: For improving the serving life of the threaded connection, an elastic-plastic contact finite element method was used for analyzing the stress distribution of the connecting threads. After that, the parametric modeling technique was used for establishing the multi-objective optimization model where the load distribution uniform and the stress peak values were considered. This model was then solved by the radial basis function (RBF) neural network method and the elitist non-dominated sorting GA (NSGA-Ⅱ).The numerical results indicate that compare with the original design, the non-uniform rates of load distribution between the teeth in the optimized design are reduced by 13.6%, and the maximum of equivalent stresses is dropped by 6.9%, and the peak values of the first principal stress are cut down by 11.5%.

Key words: threaded connection, multi-objective optimization, finite element analysis(FEA), genetic algorithm(GA)