Fig. 5: The RAFM steels design process through surrogate optimization module in MLMD.

a The prediction of UTS via the tuned MLMD regression model. b The prediction of TE via the tuned MLMD regression model. c The Pareto front of RAFM steels in original data is represented by red circles, and the pushed forward Pareto front of RAFM steels by NSGA-II algorithm with surrogate optimization module are represented by yellow circles at ambient temperature 600 °C. The blue Pentasta represents the material designed by the original work. d The Pareto front of RAFM steels in original data are represented by blue circles, and the pushed forward Pareto front of RAFM steels by NSGA-II algorithm with surrogate optimization module are represented by yellow circles at ambient temperature 300 °C. The red Pentasta represents the optimal material designed by MLMD at an ambient temperature 300 °C.