Condition based bridge management with SHM integration: A novel approach to remaining life estimation of bridges

dc.contributor.advisor Brent Phares
dc.contributor.author Jayathilaka, Sameera
dc.contributor.department Department of Civil, Construction and Environmental Engineering
dc.date 2019-03-26T17:59:13.000
dc.date.accessioned 2020-06-30T03:13:51Z
dc.date.available 2020-06-30T03:13:51Z
dc.date.copyright Sat Dec 01 00:00:00 UTC 2018
dc.date.embargo 2001-01-01
dc.date.issued 2018-01-01
dc.description.abstract <p>Bridge deterioration and aging are important problems in the United States. According to the infrastructure report card from the American Society of Civil Engineers, as of 2016, almost one in 11 (9.1%) bridges are structurally deficient and approximately 4 out of 10 (40%) bridges are older than 50 years. Rehabilitation cost for these bridges are estimated to be about $123 billion, pointing to the need for proper bridge management plans. There are many bridge management systems in the world. All of these lack of an integrated SHM system and are subject to criticism of being subjective. Condition-Based Maintenance (CBM) coupled with the Structural Health Monitoring (SHM) data can be used to actively manage bridges while minimizing subjective effects.</p> <p>The current research work consisted of two primary tasks. The first task was to update the current automated CBM-SHM framework developed at the Bridge Engineering Center (BEC) at Iowa State University (ISU), by improving its current load rating calculation process. The current load rating approach underestimates the rating factor of a bridge by 20% to 40%. The load rating calculation process was improved by developing a relationship between moment of inertia and flexural strength of bridges. An extensive experimental program was conducted to validate the relationship. The proposed method may significantly improve the rating factor of a bridge.</p> <p>The second task was to develop a novel condition rating prediction model to predict future condition ratings of the bridges. The condition rating information in the National Bridge Inventory (NBI) database was used in this development. The research group developed two different types of future condition rating prediction models, Current Practice Model (CPM) and Deterioration Prediction Model (DPM). CPM is capable of simulating the effects of historical maintenance activities and DPM does not consider the effects of historical maintenance activities when predicting the future condition rating probabilities. Both CPMs and DPMs were quantitatively and qualitatively validated.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/16822/
dc.identifier.articleid 7829
dc.identifier.contextkey 14007250
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/16822
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/31005
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/16822/Jayathilaka_iastate_0097E_17726.pdf|||Fri Jan 14 21:06:37 UTC 2022
dc.subject.disciplines Civil Engineering
dc.subject.keywords Bridge deterioration
dc.subject.keywords Capacity
dc.subject.keywords Condition rating prediction
dc.subject.keywords Load rating
dc.subject.keywords Remaining life
dc.subject.keywords Structural Health Monitoring (SHM)
dc.title Condition based bridge management with SHM integration: A novel approach to remaining life estimation of bridges
dc.type dissertation
dc.type.genre dissertation
dspace.entity.type Publication
relation.isOrgUnitOfPublication 933e9c94-323c-4da9-9e8e-861692825f91
thesis.degree.discipline Civil Engineering
thesis.degree.level dissertation
thesis.degree.name Doctor of Philosophy
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