Damage parameters identification of dual-phase 800 steel based on microvoids analysis and response surface methodology

Abstract

Accurately identifying the unknown parameters of the Gurson-Tvergaard-Needleman (GTN) damage model is essential to better understand the damage behavior of materials and improve the simulation accuracy. In order to solve the problem that traditional parameter identification methods are cumbersome and inefficient, this paper proposed an efficient damage parameter identification strategy with the combination of microscopic analysis, finite element simulation, and response surface analysis. The relationship between the evolution of microvoids and plastic strain in DP800 steel was quantified through the in-depth analysis of the microstructure of tensile specimens. Response surface method and Box-Behnken experimental design were adopted to efficiently identify and optimize the crucial damage parameters (fN, fC, fF) with the difference ratio of fracture strain as the response variable. Through analysis of variance, the factors that have significant influence on the damage parameters were further confirmed. Through the experimental comparison with the simulation results based on the GTN damage model, the effectiveness of the identified damage parameters was verified, and the influence of these parameters on the stress-strain curve was deeply revealed. The results show that the damage parameter identification strategy has achieved remarkable results in accuracy and efficiency, and has important engineering significance for the accurate prediction of the actual dual-phase steel sheet forming process.