摘要
为评估不同等效应力强度因子模型在复合型疲劳裂纹扩展预测中的表现,以及解决有限样本条件下疲劳裂纹扩展模型参数计算的问题。首先,提出了一种基于Bootstrap法的裂纹扩展参数计算方法,并对标准紧凑拉伸试样进行Ⅰ型疲劳裂纹扩展试验以得到材料参数,并利用所提方法进行样本扩增以解决样本较少的问题。其次,结合样本扩增统计得到的材料参数,采用6005A-T6铝合金紧凑拉伸剪切试样和Richard加载装置,在0°、30°、45°和60°加载角度下进行Ⅰ+Ⅱ混合模式疲劳裂纹扩展试验,以验证不同等效应力强度因子计算模型的准确性。结果表明,Irwin模型具有最高的拟合优度,大小为0.9421,表现出最佳的裂纹扩展预测效果;加载角度的增加会导致初始裂纹扩展速率减慢,需要不同角度的试验来获取适配的Paris公式参数。研究验证了多种ΔK_(eq)模型的实用性,为复合型裂纹扩展行为的疲劳寿命预测提供了理论支持。
To evaluate the performance of various equivalent stress intensity factor models in predicting mixed-mode fatigue crack growth and to address the challenge of parameter estimation under limited sample conditions.A crack growth parameter estimation method based on the Bootstrap method resampling technique was proposed firstly.Mode Ⅰ fatigue crack growth tests were conducted on CT specimens to obtain the material parameters,and the proposed method was employed to expand the sample set and mitigate the issue of data scarcity.Then,using the statistically augmented material parameters,mixed-mode Ⅰ+Ⅱ fatigue crack growth experiments were performed on 6005A-T6 aluminum alloy CTS specimens under loading angles of 0°,30°,45°and 60°,employing a Richard-type loading fixture,to validate the accuracy of various equivalent stress intensity factor models.The results indicate that the Irwin model achieved the highest goodness-of-fit,with a value of 0.9421,demonstrating the best crack growth prediction performance.Increasing the loading angle was found to reduce the initial crack growth rate,highlighting the need for angle-specific experiments to obtain appropriate Paris law parameters.This study confirms the applicability of multiple ΔK_(eq) models and provides theoretical support for fatigue life prediction in mixedmode crack growth scenarios.
作者
何寒
白肖宁
曹阳
HE Han;BAI Xiaoning;CAO Yang(School of Mechanical and Aviation Manufacturing Engineering,Anyang Institute of Technology,Anyang 455000,China;CRRC Nanjing Puzhen Co.,Ltd.,Nanjing 210031,China)
出处
《机械强度》
北大核心
2025年第10期131-138,共8页
Journal of Mechanical Strength
基金
河南省科技攻关项目(252102220051)。
