Abstract
The deformation behavior of metal materials in plastic forming is intimately related to deformation conditions, which are greatly affected by deformation rate, forming temperature, and plastic variables. Macroscopic mechanical properties research is an important basis and technical means to analyze the process parameters and deformation process of metal plastic forming. Therefore, to reveal the influence mechanism of macroscopic mechanical properties of metal materials, and establish material constitutive models under different deformation conditions, it is of great significance to choose reasonable forming parameters and prevent forming defects. There are substantial variances in the macroscopic mechanical characteristics of different materials in the deformation process. In order to accurately predict its deformation behavior, the phenomenological constitutive model, the microscopic constitutive model reflecting the microscopic deformation mechanism, and the artificial neural network constitutive model based on the neural network were constructed respectively on the basis of macroscopic mechanical tests and microscopic microstructure tests. On the basis of the existing research results, the advantages and disadvantages of phenomenological constitutive model, microscopic constitutive model, and neural network constitutive model are compared and analyzed, respectively. The research results of this paper will provide support for the selection of constitutive models for reasonably predicting the deformation behavior of metal materials.
Funder
National Natural Science Foundation of China
Subject
General Materials Science,Metals and Alloys
Cited by
15 articles.
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