Highly interpretable machine learning framework for prediction of mechanical properties of nickel based superalloys-Reference-Cited by-同舟云学术

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Highly interpretable machine learning framework for prediction of mechanical properties of nickel based superalloys

Published:2022-12-07 Issue:12 Volume:6 Page:
ISSN:2475-9953
Container-title:Physical Review Materials
language:en
Short-container-title:Phys. Rev. Materials

Author:

Khatavkar Nikhil^ORCID,Singh Abhishek Kumar^ORCID

Funder

Aeronautics Research and Development Board

Ministry of Defence

University Grants Commission

Indian Institute of Science

Institute of Eminence

Supercomputer Education and Research Centre

Publisher

American Physical Society (APS)

Subject

Physics and Astronomy (miscellaneous),General Materials Science

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevMaterials.6.123603/fulltext

Reference161 articles.

1. Non-isothermal creep at very high temperature of the nickel-based single crystal superalloy MC2

2. Secondary γ′ evolution and relationship to hot deformation behavior of a supersolvus-treated superalloy with high precipitate volume fraction

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