A combined experimental-computational approach to design optimization of high temperature alloys
Conference
Jha, R, Dulikravich, GS, Pettersson, F et al. (2017). A combined experimental-computational approach to design optimization of high temperature alloys
. 10.1115/ETAM2014-1008
Jha, R, Dulikravich, GS, Pettersson, F et al. (2017). A combined experimental-computational approach to design optimization of high temperature alloys
. 10.1115/ETAM2014-1008
Experimental data were used to develop metamodels to predict high temperature alloy chemistry trends influencing stress-to-rupture and time-to-rupture of Nickel based superalloys. Chemistry optimization utilized evolutionary neural networks, bi-objective genetic programming and pruning algorithm. Optimization results were compared with the experimental data and IOSO optimization algorithm. Response surfaces were developed through various modules available in a commercial optimization package. Pareto optimized chemistries were tested using thermodynamic database, FactSageTM, by studying the phase distribution as a function of temperature of manufacture and exposure. Uniformity in the amount of critical phases over 0-1200 0C range confirmed high temperature stability for optimized alloys.
