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)
75 Downloads (Pure)


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
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


Conference5th International Symposium on Life-Cycle Engineering (IALCCE 2016)
Abbreviated titleIALCCE 2016
Internet address


Dive into the research topics of 'Expert judgment in life-cycle degradation and maintenance modelling for steel bridges'. Together they form a unique fingerprint.

Cite this