The Response Analysis Of The Brain Tissue And Its Constitutive Parameters Inversion Based On The Smooth Finite Element

With the rapid increase of the car ownership and the traffic accidents,the research on the biomechanics of collision damage has been paid more and more attention by researchers.The finite element method is an effective tool to study the collision damage of biological tissue,and it is of great significance to study the tolerance and damage mechanism of brain tissue.However,in the process of reproducing brain tissue collision by finite element method,the key mechanical parameters of the tissue material need to be strictly set.Only given the precise mechanical parameters of brain tissue,can get the actual collision process and the related data describing the damage.Then,it can be more precise to study the related reactions and injuries of brain tissue during the collision.Under the constraints of the experimental conditions and the complexity of brain structure,it is very difficult to obtain the key mechanical parameters of brain tissue directly by experimental method.Therefore,the material parameter inversion technology based on the finite element method is becoming an important method of parameter acquisition.In this paper,the unconfined compression experiment,smooth finite element technique and the computational reverse technology are combined on the basis of the biomechanics of collision damage,to carry out some meaningful research work in the field of the brain tissue parameter identification based on smooth finite element method to obtain a set of more accurate material parameters to improve the accuracy of the brain tissue finite element simulation model.Based on this idea,this paper has carried out the following tasks:(1)An unconfined compression experiment based on irregular brain tissue sample was carried out,the geometric model and the experimental compression force data of the irregular experimental sample were obtained.In this article,the unconfined compression experiment was carried out by the universal testing machine and the geometric model of the brain tissue sample was obtained by the 3d scanner.We use the related equipment to obtain the relation data of compression force and compression time in the compression process.It provides the necessary data support for the subsequent calculation of the inverse algorithm.In addition,according to the experimental data,the mechanical properties of brain tissue under compression conditions were studied to derive the constitutive relation of brain tissue.(2)The smooth finite element method of brain tissue compression was studied,and the accuracy of the code verified by an example of simulation.It provides an effective problem solver for parameter of brain tissue.In order to ensure that the positive problem model is more suitable to the real world and obtain the more accurate constitutive parameters,we rebuild the unconfined compression experiment.by the code based on the combination of the hyper-elastic constitutive model and the viscoelastic constitutive model.In addition,the accuracy and feasibility of the code are verified in a proper way.We use the code and the ABAQUS commercial software to carry out the simulation analysis of the standard cylindrical specimens and the irregular brain tissue samples respectively.We can see that their results are very close to each other by comparison,and the code can accurately reproduce the unconfined compression experiment of the brain tissue.Therefore,the self-compiled code has higher accuracy and can be used as the positive problem in the inverse of the brain tissue parameters.(3)The parameters of brain tissue were determined based on the sensitivity analysis,and the material parameters of brain tissue were obtained by the combination of smooth finite element simulation and genetic algorithm.The genetic algorithm is used as the algorithm to improve the precision of the parameter results under the premise of ensuring the efficiency.Besides,in order to ensure the accuracy of the results of the calculation results,we sampled and analyzed the sensitivity of each parameter.In addition,we determined the solution domain of the parameters by the trial method.Finally,the constitutive parameters of the brain tissue were obtained by the combination of the self-complied code and the genetic algorithm.