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An approach in parametric identification of high strain rate constitutive model using Hopkinson pressure bar test results

机译:用霍普金森压力棒测试结果进行高应变率本构模型参数识别的方法

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In the present work, an optimization approach has been introduced based on Levenberg-Marquardt method to identify the parameters of two different material constitutive models at high strain rate. This new procedure has been used to identify the parameters of two different steels, i.e. 1018 and 4340 steel within definite strain rate ranges. The experimental data has been taken from the split Hopkinson pressure bar data found in the literature. Firstly, the experimental data have been processed using the finite element optimization procedure in which the deformation has been applied to a specimen. An optimal set of material constants for Johnson-Cook (JC) and Zerilli-Armstrong (ZA) constitutive models have been computed by minimizing the standard deviation of the numerically obtained stress-strain curve from the experimental data. Then, the new procedure and new identified parameters have been validated successfully. It has been shown that the numerical algorithm has a very low dependency on the initial guess for the parameters. Finally, it has been shown that the algorithm is stable, and acceptable results can be obtained from data with Guassian noise.
机译:在目前的工作中,已经引入了一种基于Levenberg-Marquardt方法的优化方法,以在高应变率下识别两种不同材料本构模型的参数。该新程序已用于确定两种不同钢的参数,即在确定的应变速率范围内的1018和4340钢。实验数据取自文献中的霍普金森压力棒数据。首先,使用有限元优化程序对实验数据进行处理,其中将变形应用于样本。通过最小化从实验数据获得的数值应力-应变曲线的标准偏差,可以计算出Johnson-Cook(JC)和Zerilli-Armstrong(ZA)本构模型的最佳材料常数集。然后,新程序和新识别的参数已成功验证。已经表明,数值算法对参数的初始猜测具有非常低的依赖性。最后,已经证明该算法是稳定的,并且可以从具有高斯噪声的数据获得可接受的结果。

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