A combined experimental-computational approach to design optimization of high temperature alloys

Rajesh Jha, George S. Dulikravich, Frank Pettersson, Henrik Saxén, Nirupam Chakraborti

Research output: Chapter in Book/Conference proceedingConference contributionScientificpeer-review

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationASME 2014 Symposium on Elevated Temperature Application of Materials for Fossil, Nuclear, and Petrochemical Industries, ETAM 2014
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791840740
DOIs
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventASME 2014 Symposium on Elevated Temperature Application of Materials for Fossil, Nuclear, and Petrochemical Industries, ETAM 2014 - Seattle, United States
Duration: 25 Mar 201427 Mar 2014

Publication series

NameASME 2014 Symposium on Elevated Temperature Application of Materials for Fossil, Nuclear, and Petrochemical Industries, ETAM 2014

Conference

ConferenceASME 2014 Symposium on Elevated Temperature Application of Materials for Fossil, Nuclear, and Petrochemical Industries, ETAM 2014
Country/TerritoryUnited States
CitySeattle
Period25/03/1427/03/14

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