Estimation of material parameters in the subloading surface model for elastoplastic mechanics

Accurate prediction of plastic processing is important for the optimization of structural design and manufacturing processes. Estimation of material parameters is the important factor that affects the accuracy of finite element analysis (FEA) results. In this paper, we focus on the subloading surface model of elastoplastic mechanics and develop the new estimation model for material parameters using general-purpose CAE software. In this model, we estimate the material parameters of the subloading surface model that match the stress-strain curve of the experimental results as closely as possible. The method for estimating material parameters uses the optimization algorithm, which compares the experimental stress-strain curve with the analytical stress-strain curve to find the material parameter that minimizes the difference (objective function) between the experimental and analytical results. This optimization problem is mathematically formulated as the minimization problem of the objective function using the nonlinear least squares method. The purpose of this paper is to provide the framework for estimating the material parameters of the subloading surface model more efficiently and reliably by applying the material parameters estimation model, and to contribute to the future development of material design and simulation technology.