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Document Title Author Full Name Author Short Name Index Corresponding Address ResearcherID ResearcherID Author Name ORCID ORCID Author Name Related Email
Physics driven interpretable deep learning-based insights into boiling crisis of smooth and roughened surfaces Hussain, Imtiyaz Hussain, I 3 Natl Taipei Univ Technol, Dept Energy & Refrigerat Air Conditioning Engn, Taipei 10607, Taiwan energyengineer01@gmail.com; mm_rashidi@yahoo.com; wmyan1234@gmail.com;
Physics driven interpretable deep learning-based insights into boiling crisis of smooth and roughened surfaces Rehman, Tauseef-ur Rehman, TU 4 Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea AAE-3086-2022 Rehman, Tauseef-ur energyengineer01@gmail.com; mm_rashidi@yahoo.com; wmyan1234@gmail.com;
Physics driven interpretable deep learning-based insights into boiling crisis of smooth and roughened surfaces Sultan, Muhammad Sultan, M 5 Bahauddin Zakariya Univ, Dept Agr Engn, Multan 60800, Pakistan AAE-7883-2020 Sultan, Muhammad 0000-0002-7301-5567 Sultan, Muhammad energyengineer01@gmail.com; mm_rashidi@yahoo.com; wmyan1234@gmail.com;
Physics driven interpretable deep learning-based insights into boiling crisis of smooth and roughened surfaces Rashidi, Mohammad Mehdi Rashidi, MM 6 교신저자 Univ Elect Sci & Technol China, Chengdu 610056, Sichuan, Peoples R China energyengineer01@gmail.com; mm_rashidi@yahoo.com; wmyan1234@gmail.com;
Physics driven interpretable deep learning-based insights into boiling crisis of smooth and roughened surfaces Yan, Wei-Mon Yan, WM 7 교신저자 Natl Taipei Univ Technol, Dept Energy & Refrigerat Air Conditioning Engn, Taipei 10607, Taiwan energyengineer01@gmail.com; mm_rashidi@yahoo.com; wmyan1234@gmail.com;
Physics driven interpretable deep learning-based insights into boiling crisis of smooth and roughened surfaces Yan, Wei-Mon Yan, WM 7 교신저자 Natl Taipei Univ Technol, Res Ctr Energy Conservat New Generat Residential C, Taipei 10608, Taiwan energyengineer01@gmail.com; mm_rashidi@yahoo.com; wmyan1234@gmail.com;
Physics-aware machine learning for computational fluid dynamics surrogate model to estimate ventilation performance Kim, Munho Kim, M 1 Kyungpook Natl Univ, Sch Mech Engn, Daegu, South Korea s-choi@knu.ac.kr;
Physics-aware machine learning for computational fluid dynamics surrogate model to estimate ventilation performance Kim, Munho Kim, M 1 Kyungpook Natl Univ, IEDT, Daegu, South Korea s-choi@knu.ac.kr;
Physics-aware machine learning for computational fluid dynamics surrogate model to estimate ventilation performance Kim, Munho Kim, M 1 Univ Iowa, Dept Mech & Engn, Iowa City, IA 52242 USA s-choi@knu.ac.kr;
Physics-aware machine learning for computational fluid dynamics surrogate model to estimate ventilation performance Chau, Ngan-Khanh Chau, NK 2 Kyungpook Natl Univ, Sch Mech Engn, Daegu, South Korea s-choi@knu.ac.kr;
Physics-aware machine learning for computational fluid dynamics surrogate model to estimate ventilation performance Chau, Ngan-Khanh Chau, NK 2 Kyungpook Natl Univ, IEDT, Daegu, South Korea s-choi@knu.ac.kr;
Physics-aware machine learning for computational fluid dynamics surrogate model to estimate ventilation performance Chau, Ngan-Khanh Chau, NK 2 Vietnam Natl Univ Ho Chi Minh City, An Giang Univ, Ho Chi Minh, Vietnam s-choi@knu.ac.kr;
Physics-aware machine learning for computational fluid dynamics surrogate model to estimate ventilation performance Park, Sujin Park, S 3 Kyungpook Natl Univ, Sch Mech Engn, Daegu, South Korea s-choi@knu.ac.kr;
Physics-aware machine learning for computational fluid dynamics surrogate model to estimate ventilation performance Park, Sujin Park, S 3 Kyungpook Natl Univ, IEDT, Daegu, South Korea s-choi@knu.ac.kr;
Physics-aware machine learning for computational fluid dynamics surrogate model to estimate ventilation performance Nguyen, Phong C. H. Nguyen, PCH 4 Univ Virginia, Sch Data Sci, Charlottesville, VA 22903 USA IUM-5515-2023 Ngân Khánh, Châu s-choi@knu.ac.kr;
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