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Elastoplastic parameter identification by simulation of static and dynamic indentation tests

机译:通过模拟静态和动态压痕测试来识别弹塑性参数

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This work presents a numerical optimisation procedure for the identification of elastoplastic material parameters by means of inverse analysis, through both static and dynamic indentation tests. A finite element method (FEM) modelling of the indentation test is put in place by analysing first macroscopic effects (indentation curve, residual imprint geometry) at variable constitutive parameters (elastic modulus, yield stress, hardening coefficient). The FEM solver is then linked to an optimisation routine by assembling an integrated loop towards the solution of the inverse problem. Later, the FEM solver is replaced by a radial basis function network interpolation of pre-calculated data, combined to a principal component analysis, allowing the reduction of the computational burden of each non-linear analysis. Next, a detailed study on the identification procedure is performed by applying it to pseudo-experimental data that is generated numerically prior to the inverse analysis, which is possibly affected by random noise with given variance. The reliability of the inverse procedure is then demonstrated for both static and dynamic indentation tests as a necessary condition for further validations with true experimental data. The information from only the imprint geometry is shown to be sufficient for consistent material parameter identification.
机译:这项工作提出了一种数值优化程序,用于通过静态和动态压痕测试通过反分析来识别弹塑性材料参数。通过分析在可变本构参数(弹性模量,屈服应力,硬化系数)下的第一宏观效应(压痕曲线,残余压印几何形状),对压痕测试进行了有限元方法建模。 FEM求解器然后通过组装一个集成回路来解决反问题,从而将其链接到优化例程。后来,FEM求解器被预先计算的数据的径向基函数网络插值代替,并与主成分分析相结合,从而减轻了每个非线性分析的计算负担。接下来,对识别过程进行详细研究,方法是将其应用于在逆分析之前以数字方式生成的伪实验数据,该伪实验数据可能会受到具有给定方差的随机噪声的影响。然后证明了静态和动态压痕测试的逆过程的可靠性,这是用真实实验数据进行进一步验证的必要条件。仅来自压印几何形状的信息已显示出足以进行一致的材料参数识别。

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