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首页> 外文期刊>International Journal of Fatigue >Characterization of pitting damage and prediction of remaining fatigue life
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Characterization of pitting damage and prediction of remaining fatigue life

机译：点蚀损伤的表征和剩余疲劳寿命的预测

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Quantification of corrosion and modeling of subsequent fatigue crack growth have been the focus of much intense inquiry in recent years. In previous work, the present authors proposed a crack growth model for this fatigue damage scenario that incorporated recent laboratory observations and built upon the approaches of other researchers. Here this model is extended to establish fatigue life prediction distributions for pre-corroded 2024-T3 aluminum using random cross-sectional plane micrographs as the damage quantification means. First, using automated image analysis, metrics are extracted from these micrographs that are shown to bear relevance to the fatigue performance of the material. Insight was gained by studying this pitting from a number of different perspectives, including analysis of spatial distribution and morphology. Based on the observation that the failure of individual, pre-corroded, fatigue specimens often results from the simultaneous nucleation of several cracks, a life prediction method is presented. Here, multiple crack evolution scenarios are simulated with the understanding that the distribution of lowest resulting lives will be limiting and thus representative of the experimentally observed lives. The resulting life predictions are shown to compare well against experimental values. Model sensitivities are addressed and the merits and limitations of the proposed methodology are discussed.
机译：近年来，腐蚀的量化和随后的疲劳裂纹扩展的建模一直是研究的重点。在先前的工作中，作者针对这种疲劳损伤场景提出了裂纹扩展模型，该模型结合了最近的实验室观察结果，并建立在其他研究人员的研究方法之上。在这里，该模型扩展为使用随机横截面显微照片作为损伤量化手段来建立预腐蚀2024-T3铝的疲劳寿命预测分布。首先，使用自动图像分析，从这些显微照片中提取指标，这些指标显示出与材料的疲劳性能相关。通过从许多不同的角度研究点蚀，包括对空间分布和形态的分析，获得了洞察力。基于观察到单个预腐蚀疲劳样品的失效通常是由多个裂纹同时形核导致的，提出了一种寿命预测方法。在这里，模拟多个裂纹扩展方案时应理解，最低寿命的分布将受到限制，因此可以代表实验观察到的寿命。结果表明寿命预测可以很好地与实验值进行比较。解决了模型敏感性问题，并讨论了所提出方法的优缺点。

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