Automated Design Framework of Viscous Damping Walls for Structures under Multidirectional Earthquakes Using Physics-Informed Deep Reinforcement Learning

dc.contributor.author	Zhou, Chenying
dc.contributor.author	Shu, Wenhui
dc.contributor.author	Li, Xin
dc.contributor.author	Cao, Liyuan
dc.contributor.author	Li, Chunxiang
dc.date.accessioned	2026-08-20T12:14:02Z
dc.date.available	2026-08-20T12:14:02Z
dc.date.copyright	2026/03/18
dc.date.issued	2026
dc.identifier.other	JSDCCC.SCENG-2015.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4313259
dc.description.abstract	AbstractIn current engineering practice, the optimal design of the classical viscous damping wall (VDW) model typically relies on traditional optimization algorithms, which often involve the use of a large number of VDWs. To address this problem, this ...
dc.publisher	American Society of Civil Engineers
dc.title	Automated Design Framework of Viscous Damping Walls for Structures under Multidirectional Earthquakes Using Physics-Informed Deep Reinforcement Learning
dc.type	Journal Article
dc.journal.volume	31
dc.journal.issue	3
dc.journal.title	Journal of Structural Design and Construction Practice
dc.identifier.doi	10.1061/JSDCCC.SCENG-2015
dc.journal.fristpage	04026027-1
dc.journal.lastpage	04026027-19
dc.page	19
dc.tree	Journal of Structural Design and Construction Practice:;2026:;Volume ( 031 ):;issue: 003
dc.contenttype	Fulltext