各向异性超弹性的皮肤本构模型参数识别方法研究
Identification of anisotropic hyperelastic constitutive parameters of skin tissue
温广全 1纪小刚 2李华彬 1孙榕1
作者信息
- 1. 江南大学机械工程学院,214122无锡
- 2. 江南大学机械工程学院,214122无锡;江苏省食品先进制造装备技术重点实验室,214122无锡
- 折叠
摘要
通过力学建模方法对病人皮肤组织疾病进行诊断、评估和治疗,需要准确识别皮肤组织的力学性能.为此,提出了一种运用自适应模拟退火优化算法结合代理模型技术的皮肤组织本构参数识别方法.首先,采用有限元方法模拟皮肤单轴拉伸试验,获取不同参数组合下,皮肤组织的数值计算力学响应数据.为提高参数识别的计算效率,分别构建了响应面模型、克里金模型、椭球基神经网络3种代理模型来代替重复的仿真计算过程,并采用决定系数R2对3种代理模型的拟合精度进行校验.最后,利用自适应模拟退火优化算法,以试验曲线与数值计算曲线均方根误差最小为优化目标,通过反演识别出了与普通家猪腹肋部皮肤组织单轴拉伸试验结果最匹配的本构参数:C10=0.140 1 MPa、k1=24.51 MPa、k2=0.496 1、κ=0.317 1、φ=13.86°.结果表明,椭球基神经网络模型更适合拟合皮肤本构模型参数与应力应变响应间的非线性关系.对比识别出的数值计算曲线与试验曲线,表明自适应模拟退火算法结合代理模型技术是识别皮肤组织各向异性超弹性本构参数的快速、可靠方法.
Abstract
It is necessary to accurately identify the mechanical properties of skin tissue for diagnosis,evalu-ation and treatment of skin tissue diseases by means of mechanical modeling.Therefore,this paper propo-ses a skin tissue constitutive parameter identification method using adaptive simulated annealing optimiza-tion algorithm combined with approximation model technology.First,the finite element method was used to simulate the skin uniaxial tensile test,and the numerical mechanical response data of skin tissue were ob-tained under different parameter combinations.In order to improve the computational efficiency of parame-ter identification,response surface model,Kriging model,and ellipsoidal neural network were constructed to replace the repeated simulation calculation process,and the fitting accuracy of the three approximation models was verified by the determination coefficient R2.Finally,an adaptive simulated annealing optimiza-tion algorithm was used to identify the constitutive parameters that best matched the uniaxial tensile test re-sults of skin tissue of common pig belly through inversion with the objective of minimizing the root mean square error of the test curve and the numerical calculation curve:C10=0.140 1 MPa,k1=24.51 MPa,k2=0.496 1,κ=0.317 1,and cp=13.86°.The results show that the ellipsoidal neural network model is more suitable for fitting the nonlinear relationship between skin constitutive model parameters and stress-strain response.The comparison between the identified numerical and experimental curves shows that the adaptive simulated annealing algorithm combined with the approximation model is a fast and reliable meth-od to identify the anisotropic hyperelastic constitutive parameters of skin tissue.
关键词
皮肤力学/参数识别/代理模型/自适应模拟退火算法Key words
skin mechanics/parameter identification/approximation model/adaptive simulated annealing algorithm引用本文复制引用
基金项目
国家自然科学基金资助项目(52175234)
国家自然科学基金资助项目(51105175)
江苏省"六大人才高峰"资助项目(JXQC-006)
出版年
2024
NETL
NSTL
万方数据