Top-of-line corrosion via physics-guided machine learning: A methodology integrating field data with theoretical models-Reference-Cited by-同舟云学术

Top-of-line corrosion via physics-guided machine learning: A methodology integrating field data with theoretical models

Published:2022-08 Issue: Volume:215 Page:110558
ISSN:0920-4105
Container-title:Journal of Petroleum Science and Engineering
language:en
Short-container-title:Journal of Petroleum Science and Engineering

Author:

Silakorn Passaworn,Jantrakulchai Nawat,Wararatkul Napat,Wanwilairat Sumbhath,Kangkachit Thanapat,Techapiesancharoenkij Ratchatee,Rakthanmanon Thanawin,Hanlumyuang Yuranan^ORCID

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference56 articles.

1. Modeling of heat transfer in dropwise condensation;Abu-Orabi;Int. J. Heat Mass Transfer,1998

2. An iterative solution approach to coupled heat and mass transfer in a steadily fed evaporating water droplet;Akkus;J. Heat Transfer,2019

3. Data-driven machine learning for accurate prediction and statistical quantification of two phase flow regimes;Ali;J. Pet. Sci. Eng.,2021

4. Initiation of roll waves in gas-liquid flows;Andreussi;AIChE J.,1985

5. Interfacial instabilities for horizontal gas-liquid flows in pipelines;Andritsos;Int. J. Multiph. Flow.,1987

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