摘要
疲劳裂纹数密度和裂纹扩展速率是描述材料疲劳损伤程度、预测材料疲劳寿命的两个重要参数。关于光滑试件表面疲劳裂纹数密度演化及疲劳裂纹扩展规律的定量化描述的研究 ,人们一直非常重视 ,业已提出了一些模型 ,但其适用范围均受到限制。因此 ,目前尚未有被广泛接受的裂纹演化定量模型。研究用 BP神经网络描述疲劳裂纹数密度演化、裂纹扩展速率演化规律 ,结果表明 :该方法合理可行 ,解决了传统描述方法确定长短裂纹分界点的困难 ,同时 ,也避免了显式模型中参数的物理意义不十分明确 ,实际应用时难以确定的问题。
The crack density and crack growth rate are important parameters which are used to describe the fatigue damage and predict fatigue life of a material. There are many researches on the quantitative description of the fatigue cracks density and the crack growth rate, and several models are proposed, but these model can not be widely used. In this paper, the BP network is used to describe the evolution of the fatigue cracks density and the crack growth rate. It can be seen that this method is feasible. This method doesn't need to determine the interface between the long and short crack, and overcome the shortcoming of traditional models in which the physical background of parameters are uncertain and it is difficult to be determined in engineering.
出处
《铁道学报》
EI
CSCD
北大核心
2000年第3期33-37,共5页
Journal of the China Railway Society
基金
国家自然科学基金 (高技术探索 )资助项目 !(596850 0 3)
四川省跨世纪杰出青年学科带头人培养基金资助项目
关键词
疲劳裂纹
数密度
扩展速率
神经网络
演化规律
fatigue crack
fatigue crack density
fatigue crack growth rate
neural network
