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dc.contributorNational Institute of Standards and Technologyen_US
dc.contributor.authorLi, Shengyen
dc.contributor.authorKattner, Ursula
dc.contributor.authorCampbell, Carelyn
dc.contributor.othershengyen.li@nist.goven_US
dc.date.accessioned2017-08-30T20:57:38Z
dc.date.available2017-08-30T20:57:38Z
dc.date.issued2017-08-18
dc.identifier.citationShengyen Li, Ursula R. Kattner, Carelyn E. Campbell. A computational framework for material design. Integrating Materials and Manufacturing Innovation. 2017, Volume 6, Issue 3, pp 229–248. DOI: 10.1007/s40192-017-0101-8en_US
dc.identifier.urihttp://hdl.handle.net/11256/946
dc.description.abstractA computational framework is proposed that enables the integration of experimental and computational data, a variety of user-selected models, and a computer algorithm to direct a design optimization. To demonstrate this framework a sample design of a ternary Ni-Al-Cr alloy with a high work-to-necking ratio is presented. This design example illustrates how CALPHAD phase-based, composition and temperature dependent phase equilibria calculations and precipitation models are coupled with models for elastic and plastic deformation to calculate the stress-strain curves. A genetic algorithm then directs the search within a specific set of composition and processing constrains for the ideal composition and processing profile to optimize the mechanical properties. The initial demonstration of the framework provides a potential solution to initiate the material design process in a large space of composition and processing conditions. This framework can also be used in similar material systems or adapted for other material classes.en_US
dc.subjectNi-based superalloyen_US
dc.subjectgenetic algorithmen_US
dc.subjectCALPHADen_US
dc.titleA computational framework for material designen_US
dc.typeDataseten_US
dc.typeEvaluated Dataen_US
dc.typeMacro/Scripten_US
dc.typePreprinten_US
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