LAUSR

Abstract In industrial forming and machining process, the large plastic deformation of material takes place in wide loading ranges of strain-rate and forming temperature. A satisfactory modelling of quasi-static and dynamic material behaviors is of great importance for understanding physical process and processes optimization. A dependence-based integrated methodology, together with an improved weighted multi-objective parameter identification strategy is presented for the development of phenomenological constitutive model and the parameter identification using experimental data from quasi-static and dynamic tests with instantaneous strain rate variations and plastic strain-related temperature changes. The improved multi-objective parameter identification model is reformulated by introducing three weighting factors for valuing different measure errors and fit standard errors in individual objective function corresponding to each test, considering the sampling point number and active material parameter number under different loading conditions, and balancing optimization opportunity of quasi-static and dynamic sub-objective functions. The methodology is verified for feasibility through illustrative constitutive identification for SiCp/Al composites. This may provide a methodology of constitutive modelling for predicting material behaviors in quasi-static and dynamic modes equally well.