Simulation-Based Analysis of Tunnel Boring Machine Performance in Tunneling Excavation

dc.contributor.author	Limao Zhang
dc.contributor.author	Xianguo Wu
dc.contributor.author	Miroslaw J. Skibniewski
dc.date.accessioned	2017-05-08T22:31:21Z
dc.date.available	2017-05-08T22:31:21Z
dc.date.copyright	July 2016
dc.date.issued	2016
dc.identifier.other	48299724.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl/handle/yetl/81974
dc.description.abstract	This paper develops a hybrid simulation approach that integrates a dynamic default tree (DFT) and discrete-time Bayesian network (DTBN) to support tunnel boring machine (TBM) performance prediction and diagnosis. A causal network model consisting of 20 nodes is built to simulate shield cutter head failure over time during the TBM operation. A total of three indicators, namely,
dc.publisher	American Society of Civil Engineers
dc.title	Simulation-Based Analysis of Tunnel Boring Machine Performance in Tunneling Excavation
dc.type	Journal Paper
dc.journal.volume	30
dc.journal.issue	4
dc.journal.title	Journal of Computing in Civil Engineering
dc.identifier.doi	10.1061/(ASCE)CP.1943-5487.0000542
dc.tree	Journal of Computing in Civil Engineering:;2016:;Volume ( 030 ):;issue: 004
dc.contenttype	Fulltext