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dc.contributor.author서원호-
dc.date.accessioned2018-07-02T07:17:10Z-
dc.date.available2018-07-02T07:17:10Z-
dc.date.issued2017-08-
dc.identifier.citationSensors, v. 17, No. 4, Article no. 936en_US
dc.identifier.issn1424-8220-
dc.identifier.urihttp://www.mdpi.com/1424-8220/17/4/936/htm-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/72290-
dc.description.abstractRailway bridges are exposed to repeated train loads, which may cause fatigue failure. As critical links in a transportation network, railway bridges are expected to survive for a target period of time, but sometimes they fail earlier than expected. To guarantee the target bridge life, bridge maintenance activities such as local inspection and repair should be undertaken properly. However, this is a challenging task because there are various sources of uncertainty associated with aging bridges, train loads, environmental conditions, and maintenance work. Therefore, to perform optimal risk-based maintenance of railway bridges, it is essential to estimate the probabilistic fatigue life of a railway bridge and update the life information based on the results of local inspections and repair. Recently, a system reliability approach was proposed to evaluate the fatigue failure risk of structural systems and update the prior risk information in various inspection scenarios. However, this approach can handle only a constant-amplitude load and has limitations in considering a cyclic load with varying amplitude levels, which is the major loading pattern generated by train traffic. In addition, it is not feasible to update the prior risk information after bridges are repaired. In this research, the system reliability approach is further developed so that it can handle a varying-amplitude load and update the system-level risk of fatigue failure for railway bridges after inspection and repair. The proposed method is applied to a numerical example of an in-service railway bridge, and the effects of inspection and repair on the probabilistic fatigue life are discussed.en_US
dc.description.sponsorshipThis study was supported by a grant (17SCIP-B066018-05) from the Smart Civil Infrastructure Research Program funded by the Ministry of Land, Infrastructure and Transport (MOLIT) of the Korean government and the Korea Agency for Infrastructure Technology Advancement (KAIA).en_US
dc.language.isoen_USen_US
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)en_US
dc.subjectrailway bridgeen_US
dc.subjectfatigue life updatingen_US
dc.subjectinspection and repairen_US
dc.subjectsystem reliabilityen_US
dc.subjectSTEELen_US
dc.subjectSYSTEM RELIABILITYen_US
dc.subjectSMART SENSORSen_US
dc.subjectCRACK-GROWTHen_US
dc.subjectIDENTIFICATIONen_US
dc.subjectDAMAGEen_US
dc.titleProbabilistic Fatigue Life Updating for Railway Bridges Based on Local Inspection and Repairen_US
dc.typeArticleen_US
dc.relation.no4-
dc.relation.volume17-
dc.identifier.doi10.3390/s17040936-
dc.relation.page1-20-
dc.relation.journalSensors-
dc.contributor.googleauthorLee, Young-Joo-
dc.contributor.googleauthorKim, Robin E.-
dc.contributor.googleauthorSuh, Wonho-
dc.contributor.googleauthorPark, Kiwon-
dc.relation.code2017040070-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF ENGINEERING SCIENCES[E]-
dc.sector.departmentDEPARTMENT OF TRANSPORTATION AND LOGISTICS ENGINEERING-
dc.identifier.pidwonhosuh-
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > TRANSPORTATION AND LOGISTICS ENGINEERING(교통·물류공학과) > Articles
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