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Improvement of Cyclic Void Growth Model for Ultra-Low Cycle Fatigue Prediction of Steel Bridge Piers

机译:钢桥墩超低周疲劳预测的循环空隙生长模型的改进

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摘要

The cyclic void growth model (CVGM) is a micro-mechanical fracture model that has been used to assess ultra-low cycle fatigue (ULCF) of steel structures in recent years. However, owing to the stress triaxiality range and contingency of experimental results, low goodness of fit is sometimes obtained when calibrating the model damage degradation parameter, resulting in poor prediction. In order to improve the prediction accuracy of the CVGM model, a model parameter calibration method is proposed. In the research presented in this paper, tests were conducted on circular notched specimens that provided different magnitudes of stress triaxiality. The comparative analysis was carried out between experimental results and predicted results. The results indicate that the number of cycles and the equivalent plastic strain to ULCF fracture initiation by the CVGM model calibrated by the proposed method agree well with the experimental results. The proposed parameter calibration method greatly improves prediction accuracy compared to the previous method.
机译:循环空隙生长模型(CVGM)是一种微机械断裂模型,近年来已用于评估钢结构的超低循环疲劳(ULCF)。但是,由于应力三轴性范围和实验结果的偶然性,在校准模型损伤退化参数时有时会获得较低的拟合优度,从而导致较差的预测。为了提高CVGM模型的预测精度,提出了一种模型参数校正方法。在本文提出的研究中,对提供不同强度三轴应力的圆形缺口试样进行了测试。在实验结果和预测结果之间进行了比较分析。结果表明,所提出的方法校准的CVGM模型对ULCF断裂起始的循环次数和等效塑性应变与实验结果吻合良好。与以前的方法相比,所提出的参数校准方法大大提高了预测精度。

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