陈龙, 蔡力勋. 基于材料低周疲劳的裂纹扩展预测模型[J]. 工程力学, 2012, 29(10): 34-39. DOI: 10.6052/j.issn.1000-4750.2011.02.0081
引用本文: 陈龙, 蔡力勋. 基于材料低周疲劳的裂纹扩展预测模型[J]. 工程力学, 2012, 29(10): 34-39. DOI: 10.6052/j.issn.1000-4750.2011.02.0081
CHEN Long, CAI Li-xun. THE LOW CYCLIC FATIGUE CRACK GROWTH PREDICTION MODEL BASED ON MATERIAL’S LOW CYCLIC FATIGUE PROPERTIES[J]. Engineering Mechanics, 2012, 29(10): 34-39. DOI: 10.6052/j.issn.1000-4750.2011.02.0081
Citation: CHEN Long, CAI Li-xun. THE LOW CYCLIC FATIGUE CRACK GROWTH PREDICTION MODEL BASED ON MATERIAL’S LOW CYCLIC FATIGUE PROPERTIES[J]. Engineering Mechanics, 2012, 29(10): 34-39. DOI: 10.6052/j.issn.1000-4750.2011.02.0081

基于材料低周疲劳的裂纹扩展预测模型

THE LOW CYCLIC FATIGUE CRACK GROWTH PREDICTION MODEL BASED ON MATERIAL’S LOW CYCLIC FATIGUE PROPERTIES

  • 摘要: 该文基于疲劳裂纹尖端循环应力-应变场, 定义了基于应变幅的平均单位循环损伤参量D, 并引入Miner累积损伤率, 从而从理论上建立起材料低周疲劳性能和疲劳裂纹扩展行为之间的联系。以裂尖扩展方向上的单调塑性区尺寸作为疲劳过程区大小, 并提出了基于弹塑性应变疲劳累积损伤的疲劳裂纹扩展预测模型。模型改进了前人提出的疲劳裂纹扩展预测模型, 考虑了单调塑性区内所有材料的弹塑性应变疲劳损伤贡献;模型中参数均有物理意义, 不需要人为调试。基于完成的Cr2Ni2MoV 材料的低周疲劳结果所建立的该文新模型对该材料裂纹扩展速率的预测结果与实验结果有良好一致性。并且, 借助手册数据, 在TC4钛合金材料上进一步得到了验证。

     

    Abstract: Based on the cyclic stress-strain field of a fatigue crack tip, an average cyclic damage parameter from the strain amplitude is defined. By introducing Miner theory, this paper theoretically establishes the relationship between the material’s low cycle fatigue properties and the low cycle fatigue crack propagation behavior. And the fatigue process size is measured as the monotonic plastic zone size in the crack propagation direction. Thus, based on elasto-plastic strain fatigue cumulative damage, a new fatigue crack growth prediction model is set up, which improve the prediction models proposed in the pertinent published literatures. This new model considers the elasto-plastic strain damage contribution of the material located in the monotonic plastic zone. What is more, parameters involved in the model are determined by their physical properties without human debugging. Through the comparisons with the experimental results of Cr2Ni2MoV steel and TC4 alloy, it is clearly concluded that the new low cyclic fatigue crack growth prediction model have good accuracy.

     

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