Polycrystalline crystal plasticity constitutive parameter rapid calibration method

Abstract

The invention discloses a rapid calibration method for plastic constitutive parameters of a polycrystalline crystal. The rapid calibration method comprises the following steps: carrying out EBSD characterization on a metal material; establishing a-cube element polycrystalline geometric model, and endowing constitutive parameters and grain orientation by means of a Python script; writing a crystal plasticity constitutive model subprogram UMAT; applying a periodic boundary condition by means of a Python script; extracting a stress-strain relationship of the polycrystalline model, and interpolating test data to calculation data points; using uniaxial tension and fatigue test stress-strain / stress-time data to calibrate constitutive parameters; taking the sum of squares of differences of test and simulation data points as an optimization target, and performing iterative optimization by adopting a Hook-Jeeves optimization algorithm; constitutive parameters are adjusted through an iterative algorithm, and material parameters are updated by means of a Python script. The method can reflect the mechanical properties of the material, remarkably reduces the finite element calculation consumption, shortens the optimization period, and improves the parameter calibration efficiency.

Description

technical field [0001] The invention relates to a method for quickly calibrating parameters of a polycrystalline plastic constitutive model, belonging to the field of structural strength and finite element numerical simulation. Background technique [0002] With the rapid development of advanced experimental characterization methods and calculation methods, multi-scale simulation is widely used in the in-depth study of deformation and failure mechanisms of engineering materials, and further promotes the design and development of high-strength and high-fatigue-resistant materials, as well as high-precision structural integrity. Establishment of performance assessment methods. The finite element simulation of crystal plasticity at the grain scale serves as a bridge connecting dislocation motion at the micro-nano scale and macroscopic plastic deformation, and becomes a powerful tool for studying the mesoscopic deformation failure mechanism of metallic materials. [0003] For f...

AI Technical Summary

Problems solved by technology

For the 2D Vorinoi model, there are fewer grids and less computational consumption, but due to the introduction of the plane strain assumption, it cannot reflect the real mechanical response of the material at the macro level, such as materials with significant texture features have larger The difference in mechanical properties; for the 3D Voronoi model, the statistical grain size distribution can be consistent with the real material by controlling the distribution of the grain center point. At the same time, by introducing the preferred orientation of the real material and considering the texture characteristics of the material, it can be better reflect the mechanical response characteristics of the material, but the finite element model contains more mesh elements, and the amount of calculation increases significantly, resulting in huge calculation consumption of traditional optimization tools and a long period of constitutive parameter calibration process

Images