Effect of uncertainty of material parameters on stress triaxiality and Lode angle in finite elasto-plasticity—A variance-based global sensitivity analysis

IF 3.9 Q2 ENGINEERING, INDUSTRIAL Advances in Industrial and Manufacturing Engineering Pub Date : 2023-09-09 DOI:10.1016/j.aime.2023.100128
M. Böddecker , M.G.R. Faes , A. Menzel , M.A. Valdebenito
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Abstract

This work establishes a computational framework for the quantification of the effect of uncertainty of material model parameters on extremal stress triaxiality and Lode angle values in plastically deformed devices, whereby stress triaxiality and Lode angle are accepted as key indicators for damage initiation in metal forming processes. Attention is paid to components, the material response of which can be represented as elasto-plastic with proportional hardening as a prototype model, whereby the finite element method is used as a simulation approach generally suitable for complex geometries and loading conditions. Uncertainty about material parameters is characterized resorting to probability theory. The effects of material parameter uncertainty on stress triaxiality and Lode angle are quantified by means of a variance-based global sensitivity analysis. Such sensitivity analysis is most useful for apportioning the variance of the stress triaxiality and Lode angle to the uncertainty on material properties. The practical implementation of this sensitivity analysis is carried out resorting to a Gaussian process regression, Bayesian probabilistic integration and active learning in order to decrease the associated numerical costs. An example illustrates the proposed framework, revealing that parameters governing plasticity affect stress triaxiality and Lode angle the most.

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有限弹塑性中材料参数不确定性对应力三轴性和Lode角的影响——基于方差的全局灵敏度分析
这项工作建立了一个计算框架,用于量化材料模型参数的不确定性对塑性变形装置中的极限应力三轴度和Lode角值的影响,其中应力三轴向度和Lod角被认为是金属成形过程中损伤萌生的关键指标。关注的是部件,其材料响应可以表示为弹塑性,并作为原型模型进行比例硬化,从而使用有限元方法作为通常适用于复杂几何形状和载荷条件的模拟方法。利用概率论对材料参数的不确定性进行了表征。通过基于方差的全局灵敏度分析,量化了材料参数不确定性对应力三轴度和Lode角的影响。这种灵敏度分析对于将应力三轴度和Lode角的方差与材料性能的不确定性进行分配最为有用。这种敏感性分析的实际实现是通过高斯过程回归、贝叶斯概率积分和主动学习来实现的,以降低相关的数值成本。一个例子说明了所提出的框架,揭示了控制塑性的参数对应力三轴度和Lode角的影响最大。
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来源期刊
Advances in Industrial and Manufacturing Engineering
Advances in Industrial and Manufacturing Engineering Engineering-Engineering (miscellaneous)
CiteScore
6.60
自引率
0.00%
发文量
31
审稿时长
18 days
期刊最新文献
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