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首页> 外文期刊>Engineering Structures >Digital Twin-driven framework for fatigue life prediction of steel bridges using a probabilistic multiscale model: Application to segmental orthotropic steel deck specimen
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Digital Twin-driven framework for fatigue life prediction of steel bridges using a probabilistic multiscale model: Application to segmental orthotropic steel deck specimen

机译：概率多尺度模型的钢结构疲劳寿命预测数字双向框架：应用于分段正交钢甲板标本

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摘要

Accurate fatigue life prediction facilitates the fatigue maintenance of steel bridges. Since Digital Twin can simulate the lifecycle for physical objects at various scales, this study aims to provide a Digital Twin-driven framework for non-deterministic fatigue life prediction of steel bridges. A probabilistic multiscale model was developed to depict the fatigue evolution throughout the bridge lifecycle. The small crack initiation period was well described by the modified Fine and Bhat model considering microstructure uncertainties. After obtaining the critical model parameter via crystal plastic finite element simulation, the modified model was further calibrated using the assumed historical fatigue data in Digital Twin database. Based on the initiated half-penny-shaped small crack, the small crack initiation period was connected to the macrocrack extension period. Given the uncertainties of macrocrack propagation, the Paris' law with random growth parameters was adopted. The Bayesian inference of the growth parameters realized the real-time calibration of the macrocrack growth model using Markov chain Monte Carlo simulation. The feasibility of the proposed framework was demonstrated through fatigue tests on a segmental steel deck specimen with mixed-mode deformed U-rib to diaphragm welded joints. The results show that the predicted fatigue initiation life and residual fatigue life are in good agreement with the experimentally observed life results. In summary, the proposed framework enhances our understanding of the fatigue evolution mechanism throughout the bridge lifecycle and provides an entirely new approach to accurately predict the fatigue life of steel bridges under various sources of uncertainties.
机译：精确的疲劳寿命预测有助于钢结构的疲劳维护。由于数码双胞胎可以在各种尺度上模拟物理物体的生命周期，因此该研究旨在为钢结构的非确定性疲劳寿命预测提供数字双向驱动框架。开发了一个概率的多尺度模型，以描绘整个桥梁生命周期的疲劳演化。考虑微观结构不确定因素，通过修改的精细和BHAT模型很好地描述了小裂纹启动期。通过晶体塑料有限元模拟获得临界模型参数后，使用数字双胞胎数据库中的假定历史疲劳数据进一步校准修改模型。基于发起的半便士形小裂缝，小裂纹启动期与MacRecrack延伸期连接。鉴于MacRecrack传播的不确定性，采用了随机增长参数的巴黎法律。增长参数的贝叶斯推断实现了MACROCRAK GRANG MOLTE CARLO模拟的MACROCK增长模型的实时校准。通过疲劳试验对具有混合模式变形U形肋的节段钢甲板标本的疲劳试验来证明了所提出的框架的可行性。结果表明，预测的疲劳发起寿命和残余疲劳生活与实验观察的生命结果吻合良好。总之，拟议的框架提高了我们对整个桥梁生命周期的疲劳演化机制的理解，并提供了一种完全新的方法，可以在各种不确定性源下准确预测钢结构的疲劳寿命。

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