Magnetic alloys design using multi-objective optimization

R. Jha, G. S. Dulikravich, M. J. Colaço, M. Fan, J. Schwartz, C. C. Koch

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Scopus citations

Abstract

This work presents a computational design of optimal chemical concentrations of chosen alloying elements in creating new magnetic alloys without rare earth elements that have their multiple desired macroscopic properties extremized. The design process is iterative and uses experimental data and a multi-objective evolutionary optimization algorithm combined with a robust response surface generation algorithm. Chemical concentrations of each of the alloying elements in the initial set of candidate alloys were created using a quasi-random sequence generation algorithm. The candidate alloys were then examined for phase equilibria and associated magnetic properties using a thermodynamic database. The most stable candidate alloys were manufactured and tested for macroscopic properties, which were then fitted with response surfaces. The desired magnetic properties were maximized simultaneously by using a multi-objective optimization algorithm. The best predicted Pareto-optimal alloy compositions were manufactured, synthesized and tested thus increasing a set of experimentally verified alloys. This design process converges in a few cycles resulting with alloy chemistries that produce significantly improved desired macroscopic properties, thus proving efficiency of this combined meta-modelling and experimental/computational alloy design method.

Original languageEnglish (US)
Title of host publicationProperties and Characterization of Modern Materials
EditorsAndreas Öchsner, Holm Altenbach
PublisherSpringer Verlag
Pages261-284
Number of pages24
ISBN (Print)9789811016011
DOIs
StatePublished - 2017
Event9th International Conference on Advanced Computational Engineering and Experimenting, ACE-X 2015 - Munich, Germany
Duration: Jun 29 2015Jul 2 2015

Publication series

NameAdvanced Structured Materials
Volume33
ISSN (Print)1869-8433
ISSN (Electronic)1869-8441

Other

Other9th International Conference on Advanced Computational Engineering and Experimenting, ACE-X 2015
Country/TerritoryGermany
CityMunich
Period6/29/157/2/15

All Science Journal Classification (ASJC) codes

  • General Materials Science

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