The use of nested sampling for prediction of infrastructure degradation under uncertainty
| Autor: | André Orcesi, H. R. Noel van Erp |
|---|---|
| Přispěvatelé: | Faculty of Technology, Policy and Management [Delft], Delft University of Technology (TU Delft), Expérimentation et modélisation pour le génie civil et urbain (IFSTTAR/MAST/EMGCU), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Communauté Université Paris-Est, REGEN |
| Rok vydání: | 2018 |
| Předmět: |
[SPI.OTHER]Engineering Sciences [physics]/Other
Operations research PREDICTION Computer science media_common.quotation_subject INFRASTRUCTURE Markov process 020101 civil engineering Ocean Engineering 02 engineering and technology CYCLE DE VIE 0201 civil engineering Scarcity symbols.namesake 0502 economics and business Life cycle costs Asset management Life cycle costing ADMINISTRATION (GESTION) Safety Risk Reliability and Quality ENTRETIEN Nested sampling algorithm Civil and Structural Engineering media_common ASSET MANAGEMENT 050210 logistics & transportation business.industry COUT Mechanical Engineering 05 social sciences CALCUL ECONOMIQUE GESTION DES ROUTES Building and Construction DEGRADATION BASE DE DONNEES Geotechnical Engineering and Engineering Geology INSPECTION MAINTENANCE GESTION DU PATRIMOINE D'INFRASTRUCTURE MARKOV PROCESS symbols business CONTROLE CHAINE DE MARKOV MAINTENANCE COSTS Degradation (telecommunications) |
| Zdroj: | Structure and Infrastructure Engineering Structure and Infrastructure Engineering, 2018, 14 (7), pp. 1025-1035. ⟨10.1080/15732479.2018.1441318⟩ Scopus-Elsevier |
| ISSN: | 1744-8980 1573-2479 |
| DOI: | 10.1080/15732479.2018.1441318 |
| Popis: | Because of the competing demands for scarce resources (funds, manpower, etc) national road owners are required to monitor the condition and performance of infrastructure elements through an effective inspection and assessment regime as part of an overall asset management strategy, the primary aim being to keep the asset in service at minimum cost. A considerable amount of information is then already available through existing databases and other information sources. Various analyses have been carried out to identify the different forms of deterioration affecting infrastructures, to investigate the parameters controlling their susceptibility to, and rate of, deterioration. This paper proposes such an approach by building a transition matrix directly from the condition scores. The Markov assumption is used stating that the condition of a facility at one inspection only depends on the condition at the previous inspection. With this assumption, the present score is the only one which is taken into account to determine the future of the facility. The objective is then to combine nested sampling with a Markov-based estimation of the condition rating of infrastructure elements to put some confidence bounds on Markov transition matrices, and ultimately on corresponding maintenance costs. |
| Databáze: | OpenAIRE |
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