41 citations · 41 across the 3 of their papers we have counts for
3 papers
Physics-Informed Machine Learning for Steel Development: A Computational Framework and CCT Diagram Modelling
Peter Hedström, Victor Lamelas Cubero, Jón Sigurdsson +6
Machine learning (ML) has emerged as a powerful tool for accelerating the computational design and production of materials. In materials science, ML has primarily supported large-s…
Simulation and experimental studies of induction hardening behavior of a new medium-carbon, low-alloy wear resistance steel
Vahid Javaheri, John-Inge Asperheim, Bjørnar Grande +2
Flux2D commercial software together with a Gleeble thermomechanical simulator has been employed to numerically and physically simulate the material properties profile of an inducti…
Insight into the Induction Hardening Behavior of a New 0.40% C Microalloyed Steel: Effects of Initial Microstructure and Thermal Cycles
Vahid Javaheri, Satish Kolli, Bjørnar Grande +1
The induction hardening behavior of a new, hot-rolled 0.4 wt.% carbon steel with the two different starting microstructures of upper and lower bainite has been simulated using a Gl…