Neural network-assisted probabilistic creep-fatigue assessment of hydrogenation reactor with physics-based surrogate model-Reference-Cited by-同舟云学术

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Neural network-assisted probabilistic creep-fatigue assessment of hydrogenation reactor with physics-based surrogate model

Published:2023-12 Issue: Volume:206 Page:105051
ISSN:0308-0161
Container-title:International Journal of Pressure Vessels and Piping
language:en
Short-container-title:International Journal of Pressure Vessels and Piping

Author:

Wang Xiaoxiao,Chen Haofeng^ORCID,Xuan Fuzhen

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

East China University of Science and Technology

University of Strathclyde

Publisher

Elsevier BV

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Reference60 articles.

1. Low cycle fatigue of 2.25Cr1Mo steel with tensile and compressed hold loading at elevated temperature;Zhang;Mater. Sci. Eng.,2016

2. Low cycle fatigue and creep–fatigue interaction behaviour of 2.25 Cr1MoV steel at elevated temperature;Tian;Mater. A. T. High. Temp.,2016

3. Effect of cyclic softening and stress relaxation on fatigue behavior of 2.25Cr1Mo0.25V steel under strain-controlled fatigue-creep interaction at 728 K;Zhao;Int. J. Fatig.,2020

4. Ratcheting‐fatigue behaviour of bainite 2.25 Cr1MoV steel with tensile and compressed hold loading at 455 C;Zhao;Fatig. Fract. Eng. Mater. Struct.,2019

5. The effect of environment on high-temperature hold time fatigue behavior of annealed 2.25 pct Cr 1 pct Mo steel;Hecht;Metall. Mater. Trans.,1998

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