Numerical modeling of the dynamic strain aging in steels at high strain rates and high temperatures

Carbon steels can be heat treated to produce different microstructural variations and mechanical properties. At high temperatures the material plasticity and strength can be influenced by diffusional effects like the Portevin-Le Chatelier effect, leading to a commonly observed increased strength at elevated temperatures. The diffusional effects are influenced by the chemical composition, but also the heat treatment history that affects the local composition and especially the concentrations of free solute atoms. In this work, a numerical approach was implemented to reproduce the thermomechanical behaviour of two different microstructural variants of steel grade C45. The experimental data used to calibrate the model includes information of the plastic behaviour of material subjected to dynamic compression loading at a wide range of temperatures. Special emphasis was focused to describe the effects of the dynamic strain aging (DSA) on the flow stress. A strategy based on machine learning was implemented to obtain a model that reproduces the strengthening of the material due to diffusional effects. Cubic Support Vector Machine models were trained for both microstructure variants of the steel and different surfaces were obtained to describe the topology of the flow stress as function of temperature and strain rate. The model predictions were compared to the behaviour described by the Johnson-Cook model to estimate the influence of the DSA effect on the strength of the material at high strain rates and temperatures. Furthermore, the model quantifies how the microstructure affects the strength of the material and the strength of the DSA-hardening.