A systematic resilience assessment framework for multi-state systems based on physics-informed neural network
Yuxuan HeNational Engineering Laboratory for Pipeline Safety/ MOE Key Laboratory of Petroleum Engineering /Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249, Beijing, ChinaEnrico ZioCentre de recherche sur les Risques et les Crises (CRC), Mines Paris, PSL University, Sophia Antipolis, FranceZhaoming YangNational Engineering Laboratory for Pipeline Safety/ MOE Key Laboratory of Petroleum Engineering /Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249, Beijing, ChinaQi XiangCNOOC Research Institute Ltd., Beijing 100028, ChinaFan LinPetroChina planning and engineering institution, ChinaHe QianNational Engineering Laboratory for Pipeline Safety/ MOE Key Laboratory of Petroleum Engineering /Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249, Beijing, ChinaShiliang PengNational Engineering Laboratory for Pipeline Safety/ MOE Key Laboratory of Petroleum Engineering /Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249, Beijing, ChinaZongjie ZhangPipeChina Hunan Pipeline Co., Ltd, Hunan, ChinaHuai SuNational Engineering Laboratory for Pipeline Safety/ MOE Key Laboratory of Petroleum Engineering /Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249, Beijing, ChinaJinjun ZhangNational Engineering Laboratory for Pipeline Safety/ MOE Key Laboratory of Petroleum Engineering /Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, 102249, Beijing, China
2025en
ABI
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