涡轮榫连接结构抗微动疲劳损伤优化设计

Optimization of turbine tenon structure against fretting fatigue damage

为了提高涡轮榫连接结构的微动疲劳寿命,以涡轮榫连接结构上齿模拟件为研究对象,建立了其参数化有限元模型,并对结构的特征参数开展了灵敏度分析,确定了对微动疲劳寿命影响最大的5个参数为设计参数。基于多学科优化平台ISIGHT集成ANSYS和MATLAB,实现了优化过程的自动化。分别采用序列二次规划算法和多岛遗传算法,在满足几何约束和强度约束的条件下,完成了榫连接结构抗微动疲劳损伤优化设计,并进行了试验验证。优化结果表明,两种优化算法均能有效地延长榫连接结构微动疲劳寿命,且序列二次规划算法可以较少的迭代次数得到较好的优化结果。

To improve the fretting fatigue life of the turbine tenon joint structure, the parametric finite element model of the first tenon simulator specimen of a turbine tenon structure was established. Through the sensitivity analysis of the structural characteristic parameters, the five parameters that had the greatest impact on fretting fatigue life were determined. Based on the multidisciplinary optimization platform ISIGHT,ANSYS and MATLAB were integrated to achieve the automation of the optimization process. The sequential quadratic programming algorithm and the multi-island genetic algorithm were used to complete the optimal design of the tenon structure against fretting fatigue damage under the conditions of geometric constraints and strength constraints. Experiments were carried out to verify the reliability of the optimization algorithm.The optimization results show that both optimization algorithms can extend the fretting fatigue life of the tenon structure, and the sequential quadratic programming algorithm can obtain better optimization results with fewer iterations.