Deep learning-based modeling of the strain rate-dependent thermomechanical processing response for a novel HIPed P/M nickel-based superalloy-Reference-Cited by-同舟云学术

Deep learning-based modeling of the strain rate-dependent thermomechanical processing response for a novel HIPed P/M nickel-based superalloy

Published:2024-03 Issue: Volume:324 Page:118226
ISSN:0924-0136
Container-title:Journal of Materials Processing Technology
language:en
Short-container-title:Journal of Materials Processing Technology

Author:

Wen Hongning,Wang Shaolei,Jin Junsong,Wang Xinyun,Tang Xuefeng,Zhang Yiding,Deng Lei,Gong Pan^ORCID,Li Desong,Ning Bo,Wei Qingsong

Funder

Fundamental Research Funds for the Central Universities

National Major Science and Technology Projects of China

National Science and Technology Major Project

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Metals and Alloys,Computer Science Applications,Modeling and Simulation,Ceramics and Composites

Reference39 articles.

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5. Orientation gradients and geometrically necessary dislocations in ultrafine grained dual-phase steels studied by 2D and 3D EBSD;Calcagnotto;Mater. Sci. Eng. A,2010

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