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Epistemic Uncertainty Modeling of Johnson-Cook Plasticity Model Using Evidence Theory

机译:基于证据理论的Johnson-Cook可塑性模型的认知不确定性建模

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Principles of evidence theory are used to develop a methodology for quantifying epistemic uncertainty in constitutive models that are often used in nonlinear finite element analysis involving large plastic deformation at different strain rates and temperatures. The developed methodology is used for modeling epistemic uncertainty in Johnson-Cook plasticity model. All sources of uncertainty emanating from experimental stress-strain curves for different temperatures and strain rates, as well as expert opinions for method of fitting the model constants and the representation of homologous temperature in the model are considered. The five Johnson-Cook model constants are determined in interval form using two different fitting approaches and three sets of experimental data. Rules for identifying intervals that are in agreement, conflict, or ignorance are discussed. The presented methodology is used to find the basic belief assignment (BBA) for separate intervals of uncertainty, and the Yager rule is used for combining different sources of evidence and generating a consolidated BBA structure for each model constant. The represented uncertainty intervals with corresponding BBA are used to estimate belief and plausibility of precision intervals for a published set of Johnson-Cook constants for AI6061-T6. Results show that the constants of Johnson-Cook plasticity model are subject to considerable uncertainty.
机译:证据理论原理用于开发一种量化本构模型中认知不确定性的方法,该模型通常用于非线性有限元分析,涉及在不同应变率和温度下的大塑性变形。所开发的方法用于对Johnson-Cook可塑性模型中的认知不确定性进行建模。考虑了来自不同温度和应变速率的实验应力-应变曲线产生的所有不确定性来源,以及有关模型常数拟合方法和模型中同源温度表示方法的专家意见。使用两种不同的拟合方法和三组实验数据,以区间形式确定五个Johnson-Cook模型常数。讨论了确定一致,冲突或无知的时间间隔的规则。所提出的方法用于查找不确定性的单独区间的基本信念分配(BBA),而Yager规则用于组合不同的证据来源并为每个模型常数生成合并的BBA结构。带有相应BBA的表示的不确定性区间用于估计AI6061-T6的一组Johnson-Cook常数发布的精确度区间的置信度和合理性。结果表明,Johnson-Cook可塑性模型的常数存在很大的不确定性。

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