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Deep learning-based modeling of CO2 corrosion rate prediction in oil and gas pipelines

Jian Cui

Jian Cui

Department of Industrial Engineering and Management, Peking UniversityBeijing, China
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Cui, Jian
, 
Kun Fang

Kun Fang

  • China Petroleum Engineering & Construction Corp. Beijing CompanyBeijing, China
  • Postdoctoral Workstation of China Construction BankBeijing, China
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Fang, Kun
, 
Xueyi Sun

Xueyi Sun

China Petroleum Engineering & Construction Corp. Beijing CompanyBeijing, China
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Sun, Xueyi
, 
Ya Gao

Ya Gao

Department of Industrial Engineering and Management, Peking UniversityBeijing, China
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Gao, Ya
 e 
Yilan Shen

Yilan Shen

Postdoctoral Workstation of China Construction BankBeijing, China
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Shen, Yilan
  
19 mar 2025
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Pubblicato online: 19 mar 2025
Ricevuto: 06 nov 2024
Accettato: 04 feb 2025
DOI: https://doi.org/10.2478/amns-2025-0415
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© 2025 Jian Cui et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Cui, Jian
Department of Industrial Engineering and Management, Peking UniversityBeijing, China
Fang, Kun
China Petroleum Engineering & Construction Corp. Beijing CompanyBeijing, China
Postdoctoral Workstation of China Construction BankBeijing, China
Sun, Xueyi
China Petroleum Engineering & Construction Corp. Beijing CompanyBeijing, China
Gao, Ya
Department of Industrial Engineering and Management, Peking UniversityBeijing, China
Shen, Yilan
Postdoctoral Workstation of China Construction BankBeijing, China
Lingua:
Inglese
Frequenza di pubblicazione:
1 volte all'anno
Argomenti della rivista:
Scienze biologiche, Scienze della vita, altro, Matematica, Matematica applicata, Matematica generale, Fisica, Fisica, altro
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