Uncertainty quantification using evidence theory in concrete fatigue damage prognosis

He-sheng Tang, Dawei Li, Wei Chen, S. Xue
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引用次数: 5

Abstract

Fatigue failure is the main failure mode of mechanical components in the research of engineering structures. As fatigue life may be a basis for the fatigue reliability design, it is very important to predict it for the normal usage of the structure. Uncertainties rooted in physical variability, data uncertainty and modeling errors of the fatigue life prediction analysis. Furthermore, the predicted life of concrete structures in civil engineering field will be more obviously uncertain than other engineering structures. Due to lack of knowledge or incomplete, inaccurate, unclear information in the modeling, there are limitations in using only one framework (probability theory) to quantify the uncertainty in the concrete fatigue life prediction problem because of the impreciseness of data or knowledge. Therefore the study of uncertainty theory in the prediction of fatigue life is very necessary. This study explores the use of evidence theory for concrete fatigue life prediction analysis in the presence of epistemic uncertainty. The empirical formula S-N curve and the Paris law based on the fracture mechanics are selected as the fatigue life prediction models. The evidence theory is used to quantify the uncertainty present in the models' parameters. The parameters in fatigue damage prognosis model are obtained by fitting the available sparse experimental data and then the uncertainty in these parameters is taken into account. In order to alleviate the computational difficulties in the evidence theory based uncertainty quantification (UQ) analysis, a differential evolution (DE) based interval optimization method is used for finding the propagated belief structure. The object of the current study is to investigate uncertainty of concrete fatigue damage prognosis using sparse experimental data in order to explore the feasibility of the approach. The proposed approach is demonstrated using the experimental results of the plain concrete beams and the steel fibred reinforced concrete beams.
证据理论在混凝土疲劳损伤预测中的不确定性量化
疲劳失效是工程结构研究中机械构件的主要失效形式。疲劳寿命是疲劳可靠性设计的依据,对结构的疲劳寿命进行预测对结构的正常使用具有十分重要的意义。疲劳寿命预测分析的不确定性来源于物理变异性、数据不确定性和建模误差。此外,土木工程领域的混凝土结构的寿命预测比其他工程结构具有更明显的不确定性。由于建模中知识的缺乏或信息的不完整、不准确、不明确,仅使用一种框架(概率论)来量化混凝土疲劳寿命预测问题中由于数据或知识的不精确性而产生的不确定性存在局限性。因此,研究不确定性理论在疲劳寿命预测中的应用是十分必要的。本研究探讨了在存在认知不确定性的情况下,证据理论在混凝土疲劳寿命预测分析中的应用。选择了基于断裂力学的经验公式S-N曲线和Paris定律作为疲劳寿命预测模型。证据理论用于量化模型参数中存在的不确定性。对现有的稀疏实验数据进行拟合,得到疲劳损伤预测模型的参数,并考虑这些参数的不确定性。为了减轻基于证据理论的不确定性量化分析的计算困难,采用基于差分进化的区间优化方法寻找传播的信念结构。本研究的目的是利用稀疏实验数据研究混凝土疲劳损伤预测的不确定性,以探索该方法的可行性。用素混凝土梁和钢纤维混凝土梁的试验结果验证了该方法的有效性。
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