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High-cycle fatigue model calibration with a deterministic optimization approach
International Journal of Fatigue ( IF 6 ) Pub Date : 2023-05-28 , DOI: 10.1016/j.ijfatigue.2023.107747
Arturo Rubio Ruiz , Timo Saksala , Djebar Baroudi , Mikko Hokka , Reijo Kouhia

A parameter identification approach is proposed to calibrate the Ottosen high cycle fatigue model using numerical optimization with regularization. The damage evolution was predicted by a continuum approach based on a moving endurance surface in the stress space, so the stress states outside the endurance surface may lead to damage evolution. The calibration of the model relied on uniaxial and multiaxial experimental data. The predictions of the calibrated models were in fair agreement with the experimental data for the 7075-T7451 and 7050-T6 aluminum alloys subjected to cyclic uniaxial and multiaxial loadings.



中文翻译:

采用确定性优化方法的高周疲劳模型校准

提出了一种参数识别方法,使用带正则化的数值优化来校准 Ottosen 高周疲劳模型。损伤演化是通过基于应力空间中移动的耐久面的连续方法预测的,因此在耐久面之外的应力状态可能导致损伤演化。模型的标定依赖于单轴和多轴实验数据。校准模型的预测与承受循环单轴和多轴载荷的 7075-T7451 和 7050-T6 铝合金的实验数据非常一致。

更新日期:2023-05-28
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