Expert judgment in life-cycle degradation and maintenance modelling for steel bridges

A. Kosgodagan, O. Morales-Nápoles, J. Maljaars, W.M.G. Courage

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
49 Downloads (Pure)

Abstract

Markov-based models for predicting deterioration for civil infrastructures are widely recognized as suitable tools addressing this mechanism. The objective of this paper is to provide insights regarding a network of orthotropic steel bridges in terms of degradation. Consequently, a model combining a dynamic Bayesian network and a Markov chain is first introduced that builds up the network in a concise way. In an attempt to represent a network composed of two general classes of orthotropic steel bridges, the classical method of structured expert judgment is carried out as a quantification procedure. The first objective is to elicit indirectly transition probabilities for a Markov chain that describes how each bridge type deteriorates in time. Second, experts are asked to provide estimates on required conditional probabilities related to the Bayesian network. An in-depth analysis of the results is presented so that remarks and observations are subsequently pointed out and, finally conclusions are drawn.

Original languageEnglish
Title of host publicationLife-Cycle of Engineering Systems
Subtitle of host publicationEmphasis on Sustainable Civil Infrastructure - 5th International Symposium on Life-Cycle Engineering, IALCCE 2016, 16-19 October 2016, Delft, The Netherlands
Place of Publications.l.
PublisherCRC Press/Balkema
Pages2130-2137
Number of pages8
ISBN (Print)9781138028470
Publication statusPublished - 2017
Event5th International Symposium on Life-Cycle Engineering (IALCCE 2016) - Delft, Netherlands
Duration: 16 Oct 201619 Oct 2016
Conference number: 5
http://www.ialcce2016.org/

Conference

Conference5th International Symposium on Life-Cycle Engineering (IALCCE 2016)
Abbreviated titleIALCCE 2016
CountryNetherlands
CityDelft
Period16/10/1619/10/16
Internet address

Fingerprint

Steel bridges
Bayesian networks
Markov processes
Life cycle
Degradation
Deterioration

Cite this

Kosgodagan, A., Morales-Nápoles, O., Maljaars, J., & Courage, W. M. G. (2017). Expert judgment in life-cycle degradation and maintenance modelling for steel bridges. In Life-Cycle of Engineering Systems: Emphasis on Sustainable Civil Infrastructure - 5th International Symposium on Life-Cycle Engineering, IALCCE 2016, 16-19 October 2016, Delft, The Netherlands (pp. 2130-2137). s.l.: CRC Press/Balkema.
Kosgodagan, A. ; Morales-Nápoles, O. ; Maljaars, J. ; Courage, W.M.G. / Expert judgment in life-cycle degradation and maintenance modelling for steel bridges. Life-Cycle of Engineering Systems: Emphasis on Sustainable Civil Infrastructure - 5th International Symposium on Life-Cycle Engineering, IALCCE 2016, 16-19 October 2016, Delft, The Netherlands. s.l. : CRC Press/Balkema, 2017. pp. 2130-2137
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Kosgodagan, A, Morales-Nápoles, O, Maljaars, J & Courage, WMG 2017, Expert judgment in life-cycle degradation and maintenance modelling for steel bridges. in Life-Cycle of Engineering Systems: Emphasis on Sustainable Civil Infrastructure - 5th International Symposium on Life-Cycle Engineering, IALCCE 2016, 16-19 October 2016, Delft, The Netherlands. CRC Press/Balkema, s.l., pp. 2130-2137, 5th International Symposium on Life-Cycle Engineering (IALCCE 2016), Delft, Netherlands, 16/10/16.

Expert judgment in life-cycle degradation and maintenance modelling for steel bridges. / Kosgodagan, A.; Morales-Nápoles, O.; Maljaars, J.; Courage, W.M.G.

Life-Cycle of Engineering Systems: Emphasis on Sustainable Civil Infrastructure - 5th International Symposium on Life-Cycle Engineering, IALCCE 2016, 16-19 October 2016, Delft, The Netherlands. s.l. : CRC Press/Balkema, 2017. p. 2130-2137.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AB - Markov-based models for predicting deterioration for civil infrastructures are widely recognized as suitable tools addressing this mechanism. The objective of this paper is to provide insights regarding a network of orthotropic steel bridges in terms of degradation. Consequently, a model combining a dynamic Bayesian network and a Markov chain is first introduced that builds up the network in a concise way. In an attempt to represent a network composed of two general classes of orthotropic steel bridges, the classical method of structured expert judgment is carried out as a quantification procedure. The first objective is to elicit indirectly transition probabilities for a Markov chain that describes how each bridge type deteriorates in time. Second, experts are asked to provide estimates on required conditional probabilities related to the Bayesian network. An in-depth analysis of the results is presented so that remarks and observations are subsequently pointed out and, finally conclusions are drawn.

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Kosgodagan A, Morales-Nápoles O, Maljaars J, Courage WMG. Expert judgment in life-cycle degradation and maintenance modelling for steel bridges. In Life-Cycle of Engineering Systems: Emphasis on Sustainable Civil Infrastructure - 5th International Symposium on Life-Cycle Engineering, IALCCE 2016, 16-19 October 2016, Delft, The Netherlands. s.l.: CRC Press/Balkema. 2017. p. 2130-2137