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免疫算法在汽轮机转子低周疲劳裂纹扩展速率中的应用 被引量:1

Application of Immune Algorithm in the Low-cycle Fatigue Crack Growth Rate of Steam Turbine Rotor
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摘要 首次将免疫算法应用于汽轮机高中压转子钢(30Cr1Mo1V)的低周疲劳裂纹扩展速率计算。根据断裂力学中Pairs公式(da/dN=CΔKn),在此之上引用F.Jeglie的裂纹扩展模型,以低周疲劳裂纹扩展速率最小化为目标函数,基于免疫算法和遗传算子原理,通过MATLAB软件编程,计算出满足转子钢疲劳裂纹扩展速率的应力强度因子幅值、温度和材料参数的最优解。研究表明,基于免疫算法具有良好的搜索性能,能够较好地对汽轮机转子在复杂条件下的低周疲劳裂纹扩展速率进行准确的预测。 Firstly,apply immunity algorithm in the calculation of low-cycle fatigue crack growth rate of turbine' s high-mid pressure rotor steel (30Cr1Mo1 V). According to the Pairs formula ( da/dN = C△K^n ) in fracture mechanics, on this quote Jeglie' s crack growth model,let minimization of low-cycle fatigue crack growth rate become objective function,base on immunity algorithm and genetic operator principle with MATLAB software programming, solving optimal solution of stress strength factor amplitude, temperature and material parameter that satisfies crack growth rate of the rotor steel. The results show that the calculation method of low-cycle fatigue crack growth rate of turbine rotor based on the immunity algorithm is effective and feasible.
出处 《汽轮机技术》 北大核心 2009年第1期11-13,共3页 Turbine Technology
基金 国家自然科学项目(50775015)资助 湖南省教育厅重点项目(06A002)资助
关键词 免疫算法 遗传算子 转子钢 低周疲劳 裂纹扩展 immunity algorithm genetic operator rotor steel low-fide fatigue crack growth
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