KWN Modeling for Increased Efficiency of Al-Sc Precipitation Strengthening
Kyle Deane, kjdeane@mtu.edu, Michigan Technological University; 1400 Townsend Dr, Houghton, MI 49931
An adaptation of the Kampmann and Wagner Numerical (KWN) model was developed as a Matlab program to predict precipitation and growth of Al3Sc precipitate phase given varying starting concentration, heat treatment steps, etc.
Kyle Deane, Yang Yang, Joseph J. Licavoli, Vu Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh, and Paul G. Sanders. "Utilization of Bayesian Optimization and KWN Modeling for Increased Efficiency of Al-Sc Precipitation Strengthening." Metals 12, no. 6 (2022): 975.
Wagner, R., Kampmann, R., & Voorhees, P. W. (1991). Homogeneous Second‐Phase Precipitation. Materials science and technology.
Dai Nguyen, T., Gupta, S., Rana, S., Nguyen, V., Venkatesh, S., Deane, K.J. and Sanders, P.G., 2016, December. Cascade Bayesian Optimization. In Australasian Joint Conference on Artificial Intelligence (pp. 268-280). Springer International Publishing.
Nguyen, V., Rana, S., Gupta, S. K., Li, C., & Venkatesh, S. Budgeted batch bayesian optimization. In 2016 IEEE 16th International Conference on Data Mining (ICDM) (pp. 1107-1112). IEEE.