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An approach to decision-making analysis for implementation of structural health monitoring in bridges
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Structural Engineering and Bridges.
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Structural Engineering and Bridges.ORCID iD: 0000-0002-2833-4585
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Structural Engineering and Bridges.
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Structural Engineering and Bridges.ORCID iD: 0000-0002-5447-2068
2019 (English)In: Structural Control and Health Monitoring: The Bulletin of ACS, ISSN 1545-2255, E-ISSN 1545-2263, Vol. 26, no 6, article id e2352Article in journal (Refereed) Published
Abstract [en]

Adverse situations such as prolonged downtime of a structure, unnecessary inspections, expensive allocation of personal and equipment, deficient structural performance, or failure can be avoided by using structural health monitoring (SHM). Enhanced structural safety is the leading reason for its implementation, but one of the remaining obstacles to fully implement SHM systems deals with justifying their economic benefit. At any point in time, the preference towards one particular action depends on factors such as the probability of the triggered events and their consequences. All the possible decisions and relevant information can be illustrated by decision tree models, and the optimal decision corresponds to the one with the highest utility. Applying the Bayesian Theorem, the assumed prior probabilities of the structural state are updated in the light of new information provided by a system and the optimal decision is revised. This paper proposes a dynamic decision-making framework to manage civil engineering structures, where the ultimate goal is to achieve greater overall economy without jeopardizing safety. This paper covers a case study of a bridge where the optimal SHM and maintenance decisions are determined in the context of different scenarios in which the event probabilities and associated costs are made-up.

Place, publisher, year, edition, pages
JOHN WILEY & SONS LTD , 2019. Vol. 26, no 6, article id e2352
Keywords [en]
Bayesian decision analysis, bridge structural health monitoring, event trees, expected utility theory, value of information
National Category
Civil Engineering
Identifiers
URN: urn:nbn:se:kth:diva-252589DOI: 10.1002/stc.2352ISI: 000467742400005Scopus ID: 2-s2.0-85063567974OAI: oai:DiVA.org:kth-252589DiVA, id: diva2:1322826
Note

QC 20190611

Available from: 2019-06-11 Created: 2019-06-11 Last updated: 2019-06-25Bibliographically approved

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Neves, Ana C.Leander, JohnGonzalez, IgnacioKaroumi, Raid

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