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首页> 外文期刊>Computers, Materials & Continua >Identification of Elasto-Plastic Constitutive Parameters by Self-Optimizing Inverse Method: Experimental Verifications
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Identification of Elasto-Plastic Constitutive Parameters by Self-Optimizing Inverse Method: Experimental Verifications

机译：用自优化逆方法识别弹塑性本构参数：实验验证

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摘要

Abstract: In this paper, the Self-Optimizing Inverse Method (Self-OPTIM) has been experimentally verified by identifying constitutive parameters solely based on prescribed boundary loadings without full-field displacements. Recently the Self-OPTIM methodology was developed as a computational inverse analysis tool that can identify parameters of nonlinear material constitutive models. However, the methodology was demonstrated only by numerically simulated testing with full-field displacement fields and prescribed boundary loadings. The Self-OPTIM is capable of identifying parameters of the chosen class of material constitutive models through minimization of an implicit objective function defined as a function of full-field stress and strain fields in the optimization process. The unique advantages of the Self-OPTIM includes: 1) model independency that is expected to open up a wide range of applications for various engineering simulations; 2) capabilities of parameter identification based solely on global measurements of boundary forces and displacements. In this paper, the Self-OPTIM inverse method is experimentally verified by using two different shapes of specimens made of AISI 1095 steel: 1) dog-bone and 2) notched specimens under a loading and unloading course. Parameters of a cyclic plasticity model with nonlinear kinematic hardening rule and associated flow theory are identified by the Self-OPTIM. Multiple tests and the inverse simulations are conducted to ensure consistent performance of the Self-OPTIM. The identified parameters are successively used to reconstruct the material response.
机译：摘要：本文通过仅基于规定的边界载荷而无全场位移的情况下识别本构参数，通过实验验证了自优化逆方法（Self-OPTIM）。最近，Self-OPTIM方法被开发为一种计算逆分析工具，可以识别非线性材料本构模型的参数。但是，该方法仅通过对全场位移场和规定的边界载荷进行数值模拟测试来证明。 Self-OPTIM能够通过最小化隐式目标函数来识别所选材料本构模型类别的参数，该隐式目标函数在优化过程中被定义为全场应力和应变场的函数。 Self-OPTIM的独特优势包括：1）模型独立性有望为各种工程仿真打开广泛的应用； 2）仅基于边界力和位移的整体测量的参数识别功能。在本文中，通过使用两种不同形状的AISI 1095钢制成的标本，通过实验验证了Self-OPTIM逆方法：1）狗骨形和2）在加载和卸载过程中带有缺口的标本。具有非线性运动硬化规则和相关流动理论的循环塑性模型的参数由Self-OPTIM确定。进行了多次测试和逆向仿真，以确保Self-OPTIM的性能始终如一。识别出的参数被连续用于重建材料响应。

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