Research On Constitutive Parameters Identification Of Ceramic Matrix Composites Based On Digital Image Correlation

Ceramic matrix composites have their unique advantages in industrial applications.With its expanding range of application,how to evaluate the material properties of ceramic matrix composites becomes even more important.Characterization of its mechanical properties,to obtain constitutive material parameters is the focus of the study.Therefore,this paper proposes the use of full deformation measurement method to study the mechanical behavior of ceramic matrix composites.Firstly,this thesis briefly introduces the research on the inversion of the constitutive relation of composite materials using the full deformation measurement technology.In particular,the deformation measurement technique of the whole field,digital image correlation method(DIC),is introduced.Secondly,the finite model correction technique is introduced,and the material parameters of the uniaxial tensile test are identified based on the technique.In the process of research,the influence of the objective function,the optimization algorithm,the initial parameters and the random error of the displacement field on the parameter identification results are discussed.Combined with numerical experiment,the experimental simulation and multiparameter identification of off-axis tension are carried out to verify the efficiency and robustness of the optimization algorithm in multi-parameter identification.Finally,the finite element reconstruction technique is introduced and the method is used to reconstruct numerical simulation displacement field with random noise.The influence of random noise level and gradient of displacement field on the size selection of finite element reconstruction unit is discussed in this study.The Young's modulus and Poisson's ratio of the material are obtained by finite element model correction technique and numerical simulation of displacement field.The effects on the recognition results are studied by superimposing different levels of random noise and using different sizes of reconstruction units.