Development of the Multi-scale Analysis Model to Simulate Strain Localization Occurring During Material Processing

• Published in: Archives of computational methods in engineering Vol. 16; no. 3; pp. 287 - 318
• Main Authors: Madej, Lukasz, Hodgson, Peter D., Pietrzyk, Maciej
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.09.2009; Springer Nature B.V
• Subjects: Engineering; Heat treating; Localization; Mathematical and Computational Engineering; Metal forming; Original Paper; Scale models; Simulation; Studies; Cellular Automaton; Transition Rule; Strain Localization; Smooth Particle Hydrodynamic
• ISSN: 1134-3060; 1886-1784
• DOI: 10.1007/s11831-009-9033-6

A detailed description of possibilities given by the developed Cellular Automata—Finite Element (CAFE) multi scale model for prediction of the initiation and propagation of micro shear bands and shear bands in metallic materials subjected to plastic deformation is presented in the work. Particular emphasis in defining the criterion for initiation of micro shear and shear bands, as well as in defining the transition rules for the cellular automata, is put on accounting for the physical aspects of these phenomena occurring in two different scales in the material. The proposed approach led to the creation of the real multi scale model of strain localization phenomena. This model predicts material behavior in various thermo-mechanical processes. Selected examples of applications of the developed model to simulations of metal forming processes, which involve strain localization, are presented in the work. An approach based on the Smoothed Particle Hydrodynamic, which allows to overcome difficulties with remeshing in the traditional CAFE method, is a subject of this work as well. In the developed model remeshing becomes possible and difficulties limiting application of the CAFE method to simple deformation processes are solved. Obtained results of numerical simulations are compared with the experimental results of cold rolling process to show good predicative capabilities of the developed model.