Bayesian Networks to Quantify Transition Rates in Degradation Modeling ; Bayesian Networks to Quantify Transition Rates in Degradation Modeling: Application to a Set of Steel Bridges in The Netherlands

International audience ; Bridge lifetime pose an important challenge in terms of maintenance for decision makers or asset managers. In this regard Markov chains have been used successfully in practice as models for bridge deterioration. However, one limitation of Markov chains can be the assessment of the transition probabilities. In this paper, we propose an approach based on Bayesian networks (BNs) to quantify the transition probabilities of the system state. One of the advantages of doing so is that the BN may be quantified through physical variables linked to the underlying degradation pro... Mehr ...

Verfasser: Kosgodagan-Dalla Torre, Alex
Morales-Nápoles, Oswaldo
Maljaars, Johan
Yeung, Thomas, G.
Castanier, Bruno
Dokumenttyp: conferenceObject
Erscheinungsdatum: 2015
Verlag/Hrsg.: HAL CCSD
Schlagwörter: [SPI.GCIV]Engineering Sciences [physics]/Civil Engineering / [SPI.GCIV.RISQ]Engineering Sciences [physics]/Civil Engineering/Risques / [SPI.GCIV.STRUCT]Engineering Sciences [physics]/Civil Engineering/Structures / [MATH.MATH-PR]Mathematics [math]/Probability [math.PR]
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-29174150
Datenquelle: BASE; Originalkatalog
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Link(s) : https://hal.science/hal-01517154