Bayesian Model Updating for Predictive Maintenance of Concrete Sewers Experiencing Corrosion Using Distribution-Based Likelihood and an Improved Hamiltonian Monte Carlo Method

dc.contributor.author	Li, Ming-Hao
dc.contributor.author	Feng, Xin
dc.contributor.author	Zheng, Jin-Tong
dc.contributor.author	Yue, Qi-Feng
dc.date.accessioned	2026-08-20T21:33:22Z
dc.date.available	2026-08-20T21:33:22Z
dc.date.copyright	2026/06/02
dc.date.issued	2026
dc.identifier.other	AJRUA6.RUENG-1855.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4314642
dc.description.abstract	AbstractConcrete corrosion is a significant threat to the structural integrity of safety-critical sewer systems. Empirical models of corrosion prediction have been developed, but model parameters, such as the pH factor, dissolved sulfide concentration, ...
dc.publisher	American Society of Civil Engineers
dc.title	Bayesian Model Updating for Predictive Maintenance of Concrete Sewers Experiencing Corrosion Using Distribution-Based Likelihood and an Improved Hamiltonian Monte Carlo Method
dc.type	Journal Article
dc.journal.volume	12
dc.journal.issue	3
dc.journal.title	ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
dc.identifier.doi	10.1061/AJRUA6.RUENG-1855
dc.journal.fristpage	04026030-1
dc.journal.lastpage	04026030-14
dc.page	14
dc.tree	ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2026:;Volume ( 012 ):;issue: 003
dc.contenttype	Fulltext