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基于遗传算法的黏弹性材料模型拟合实验应力-应变曲线及其在软组织模拟物中的应用。

Visco-hyperelastic material model fitting to experimental stress-strain curves using a genetic algorithm and its application to soft tissue simulants.

机构信息

Mechanical Engineering Department, Universidad Carlos III de Madrid, Avda. de la Universidad 30, 28911, Leganés, Madrid, Spain.

Department of Mechanical Engineering and Materials, Institute of Mechanical and Biomechanical Engineering-I2MB, Universitat Politècnica de València, Camino de Vera, 46022, Valencia, Spain.

出版信息

Sci Rep. 2024 Aug 4;14(1):18026. doi: 10.1038/s41598-024-67603-8.

DOI:10.1038/s41598-024-67603-8
PMID:39098981
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11298554/
Abstract

Ballistic impacts on human thorax without penetration can produce severe injuries or even death of the carrier. Soft tissue finite element models must capture the non-linear elasticity and strain-rate dependence to accurately estimate the dynamic human mechanical response. The objective of this work is the calibration of a visco-hyperelastic model for soft tissue simulants. Material model parameters have been calculated by fitting experimental stress-strain relations obtained from the literature using genetic algorithms. Several parametric analyses have been carried out during the definition of the optimization algorithm. In this way, we were able to study different optimization strategies to improve the convergence and accuracy of the final result. Finally, the genetic algorithm has been applied to calibrate two different soft tissue simulants: ballistic gelatin and styrene-ethylene-butylene-styrene. The algorithm is able to calculate the constants for visco-hyperelastic constitutive equations with high accuracy. Regarding synthetic stress-strain curves, a short computational time has been shown when using the semi-free strategy, leading to high precision results in stress-strain curves. The algorithm developed in this work, whose code is included as supplementary material for the reader use, can be applied to calibrate visco-hyperelastic parameters from stress-strain relations under different strain rates. The semi-free relaxation time strategy has shown to obtain more accurate results and shorter convergence times than the other strategies studied. It has been also shown that the understanding of the constitutive models and the complexity of the stress-strain objective curves is crucial for the accuracy of the method.

摘要

弹道冲击对人体胸部未穿透时也可能造成载体严重损伤甚至死亡。软组织有限元模型必须捕获非线性弹性和应变率相关性,以准确估计动态人体力学响应。这项工作的目的是为软组织模拟物的粘弹性模型进行校准。使用遗传算法,通过拟合文献中获得的实验应力-应变关系,计算出材料模型参数。在定义优化算法时,进行了多次参数分析。通过这种方式,我们能够研究不同的优化策略,以提高最终结果的收敛性和准确性。最后,遗传算法已应用于校准两种不同的软组织模拟物:弹道明胶和苯乙烯-乙烯-丁烯-苯乙烯。该算法能够非常精确地计算粘弹性本构方程的常数。关于合成的应力-应变曲线,在使用半自由策略时,计算时间短,导致应力-应变曲线的结果具有高精度。本工作开发的算法,其代码作为读者使用的补充材料包含在内,可以应用于根据不同应变率下的应力-应变关系来校准粘弹性参数。半自由松弛时间策略显示出比所研究的其他策略更准确的结果和更短的收敛时间。还表明,对本构模型的理解和对目标曲线的复杂的应力-应变关系是该方法准确性的关键。

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