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