金属材料疲劳短裂纹萌生与扩展研究综述

Research on Short Fatigue Crack Initiation and Propagation of Metallic Materials:A Review

系统梳理了金属材料疲劳短裂纹的定义、分类、试验方法、萌生机理及典型扩展率模型,对当前短裂纹行为研究面临的问题进行了总结与展望。研究结果表明,在萌生机理方面,材料自身的微观结构对短裂纹萌生及扩展有重要影响,短裂纹扩展至晶界处,受晶粒取向及晶界阻力影响,扩展率会下降,裂尖突破晶界束缚后,短裂纹扩展路径出现局部偏折。在扩展行为描述方面,短裂纹的扩展驱动力与承受的载荷水平、残余应力、表面处理方式、局部磨损状况等有关。扩展过程中,裂纹尖端材料在小范围内屈服而产生局部塑性区。同时,塑性尾迹区也逐渐形成,进而产生塑性诱导闭合,导致裂纹扩展门槛值降低。此外,晶体位错之间的相互作用和位错塞积会阻碍位错发展。机器学习算法作为一种先进技术手段,已在短裂纹扩展行为表征中得到应用,对提升预测精度有促进作用。随着金属材料短裂纹行为研究的进一步深入,未来可重点关注短裂纹萌生与扩展实时监测、试验影响因素控制、数据离散性分析、扩展率模型的工程应用等问题,探索建立适用于工程结构与零部件的在役长、短裂纹扩展率统一表征模型和实时监测与安全评估技术,结合先进的机器学习算法,实现对工程关键金属结构更有效、更准确的安全性评定和剩余寿命管理。

The short fatigue cracks of metal materials are systematically sorted out in terms of their definition,classification,test methods,initiation mechanism,and typical growth rate models,as well as the problems facing the current research on short crack behavior,are summarized and prospected.The results show that the microstructure of materials plays an important role in the initiation and propagation of short cracks.When the crack tip reaches the grain boundary,the growth rate of cracks decelerates due to the influence of grain orientation and grain boundary resistance,and the short crack propagation path appears to be locally deflected after the crack tip breaks through the grain boundary constraint.In terms of the short cracks propagation behavior description,the driving force of short crack propagation is related to the load level,residual stress,surface treatment and local wear condition,and so on.During propagation,the crack tip materials yield in a small area and produce a local plastic zone.At the same time,the plastic wake is gradually formed,which results in plastic-induced closure and a decrease in the crack propagation threshold value.Besides,the interaction between crystal dislocations and dislocation stacking can hinder the dislocation development.The machine learning algorithm,as an advanced technological tool,has been applied in the characterization of short crack growth behavior,which has contributed to the improvement of prediction accuracy.With further research on the behavior of short cracks in metal materials,we can focus on real-time monitoring of short crack initiation and propagation,control of test influencing factors,discrete data analysis,and engineering applications of the growth rate model in the future.The establishment of a unified characterization model for long and short crack growth rate as well as real-time monitoring and safety assessment techniques will be explored.In addition,more effective and accurate safety assessment and remaining life management of critical metal structures can be realized by combining advanced machine learning algorithms.