A Study On Inversion Method Of Hyperelastic Constitutive Parameters Of Biological Soft Tissues

Muscles and joints,two important components to support living organism motion,are also parts which easily vulnerable to be damaged,in the process of organism movement,the muscles and joints will be permanently damaged when the body is subjected to excessive load,thus,the research for mechanical properties of biological soft tissue to find out the deformation characteristics and stress distribution principle when subjected to load is of great guiding significance for the effective damage prediction and organism protection.The determination of key constitutive parameters of biological soft tissue have a vital influence on finite element analysis and simulation.However,it is usually difficult to obtain the material parameters directly because of the complexity of biological structure and other constraints.Therefore,material identification technique based on biological soft tissue mechanics experiments has increasingly become a significant method to obtain material parameters.This paper proposed a material identification method for biological soft tissue based on the idea of inverse procedure combining simulation analysis and optimization algorithm.The specified contents are listed as follows:(1)Existed objective function used for parameters inversion were summarized,a novel objective function utilized for parameters inversion was proposed.Niche genetic algorithm was introduced into the process to identify the constitutive parameters,the inverse procedure utilized for identify the constitutive parameters of biological soft tissue was coded by Python.According to the unique fiber structure of skeletal muscle and meniscus,the basic information of finite element model learned by simulation is compiled into the optimization program.(2)Skeletal muscle was selected as the test object,and unconstrained uniaxial compression experiment were carried out.Two different loading mode including loading direction parallel to fiber orientation and perpendicular to the fiber orientation were adopted,force and displacement result data from the uniaxial compression for skeletal muscle were obtained.The obtained experimental data was read into the optimization algorithm as the experimental response utilized for identifying constitutive parameters,the novel objective function and one of existed objective function were utilized in inverse procedure respectively to identify the constitutive parameters of skeletal muscle.According to the comparison between calculated response and experimental response,the constitutive parameters of skeletal muscle were identified.The result shows that the calculated result through the inverse process with novel objective function have a lower error to the experimental result,verify the rationality of the proposed objective function.(3)The niche genetic algorithm was improved,and the improved niche genetic algorithm was selected to be the search algorithm,the optimization algorithm utilized to identify the constitutive parameters of biological soft tissue were recoded by Python.The meniscus was chosen to be the test object,and unconstrained uniaxial compression experiment were carried out,the experimental data including load and displacement were obtained.The experimental data was fed into the improved parameters inversion program,the constitutive parameters of meniscus was identified.A relative error function is utilized to evaluate these parameters.