The development of a bridge management system involving standardised scour inspection procedures and flood forecasting

dc.availability.bitstreamopenaccess
dc.check.chapterOfThesisSection 6.2, Section 6.3, Section 6.4, Section 6.5, Annex J, Annex Ken
dc.contributor.advisorLeahy, Paulen
dc.contributor.advisorMckeogh, Eamonen
dc.contributor.advisorexternalBekić, Damiren
dc.contributor.authorKerin, Igor
dc.contributor.funderFP7 People: Marie-Curie Actionsen
dc.date.accessioned2021-05-31T11:18:47Z
dc.date.available2021-05-31T11:18:47Z
dc.date.issued2020-07-29
dc.date.submitted2020-07-29
dc.description.abstractAgencies charged with managing infrastructure face a difficult and very responsible task in managing their bridge stock. Historically, bridge management relied upon paper-based processing of information and the knowledge of engineering staff. However, if the knowledge gathered is not passed on to new staff, corporate memory loss occurs. Thus, bridge managers are increasingly using computer-based infrastructure management systems, e.g. Bridge Management Systems (BMS) in order to collect and store all information relating to bridges and to support their decision-making processes. A BMS is a means for managing bridge infrastructure during its lifetime (i.e. during design, construction, operation and maintenance of the bridges). A BMS comprises of collection of inventory data, bridge inspections (a fundamental of BMS), maintenance/repairs or replacement and allocation of funds. As the funds allocated to managing bridges are often significantly lower than for other infrastructure, for example annual allocations for road resurfacing, the requirement for an effective BMS becomes even more important. As funds are limited, prioritisation of bridge maintenance and maintenance is required. The outcome of most of bridge inspections is a bridge condition. A bridge condition is a classification number or a letter describing the bridge state based on which the bridge stock can be prioritised for maintenance and/or repair. The main problem with current bridge inspection methods is the lack of focus on scour, i.e. the removal of the river bed around the bridge structure due to flowing water. Only a few countries, for example, the U.S., prescribe scour assessment as being mandatory for bridges over waterways. Still, there is no fully standardised method for bridge scour inspection. With scour being the main cause of bridge collapses worldwide, the focus of this thesis was placed on research and development of new scour inspection method(s). This thesis applied a methodology to analyse existing bridge inspection methods. The analysis proved that most bridge inspections have inadequate focus on scour or they require standardisation and improvement of their rating systems. As a result, new inspection method(s) for Level 1 - designed for simple, single span bridges; and for Level 2 - designed for complex, multi-span bridges were developed.   Both methods were verified on 100 bridges in Ireland. The verification process was based on correlation analysis, detailed pair-wise comparison with other methods and any discrepancies in the results were examined in case-by-case analysis. Verification confirmed that both of the methods (L1 and L2) are applicable on large numbers of bridges. Future training that was set-up during writing of this thesis is an important part of the dissemination and utilisation of the proposed methods to other systems. Further enhancement of the inspection methods was carried out by integration with a Flood Forecasting System (FFS). The idea behind incorporation of FFS in BMS was to adapt the bridge stock to changing climate and to save resources by operating and planning bridge inspections in a more efficient way. With FFS in place, scour inspections can be scheduled during or after a flood event and not just based on the time of the previous inspection, which required assuming a time interval during which the bridge would remain safe if a flood event occurred. When it comes to the price of FFS, a budgeting prediction tool was developed as part of this thesis. Based on 11 questions the tool will predict the overall cost of setup and maintenance of a FFS for desired number of years. The tool “PREDICT” is informative and to be taken as an initial guidance for costing of the project. For bridge inspections, it is estimated that the overall price per bridge inspection is reduced by 81% for L1 bridge scour inspection and between 10-30% for L2 bridge scour inspection. Reducing the reporting time is one of the main reasons for this. By introducing tablet computers for bridge inspections, the reporting time is near zero, enabling bridge inspector to focus only on bridge inspections and reduce time spent in the office. This work provides bridge scour inspection methods that are verified for practical use. The role of FFS is successfully demonstrated and recommended for use as a standard for BMS resilient to extreme weather events.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationKerin, I. 2020. The development of a bridge management system involving standardised scour inspection procedures and flood forecasting. PhD Thesis, University College Cork.en
dc.identifier.endpage251en
dc.identifier.urihttps://hdl.handle.net/10468/11414
dc.language.isoenen
dc.publisherUniversity College Corken
dc.relation.projectinfo:eu-repo/grantAgreement/EC/FP7::SP3::PEOPLE/612517/EU/Intelligent Bridge Assessment Maintenance and Management System/BRIDGE SMSen
dc.rights© 2020, Igor Kerin.en
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectScouren
dc.subjectBridge management systemen
dc.subjectBridge inspectionen
dc.subjectFlood forecastingen
dc.subjectResilient infrastructureen
dc.titleThe development of a bridge management system involving standardised scour inspection procedures and flood forecastingen
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD - Doctor of Philosophyen
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