Risk Informed Structural Systems Integrity Management: A Decision Analytical Perspective

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Abstract

The present paper is predominantly a conceptual contribution with an appraisal of major developments in risk informed structural integrity management for offshore installations together with a discussion of their merits and the challenges which still lie ahead. Starting point is taken in a selected overview of research and development contributions which have formed the basis for Risk Based Inspection Planning (RBI) as we know it today. Thereafter an outline of the methodical basis for risk informed structural systems integrity management, i.e. the Bayesian decision analysis is provided in summary. The main focus is here directed on RBI for offshore facilities subject to fatigue damages. New ideas and methodical frameworks in the area of robustness and resilience modeling of structural systems are then introduced, and it is outlined how these may adequately be utilized to enhance Structural Integrity Management (SIM). Finally, the concept of Value of Information analysis (VoI) from the Bayesian pre-posterior decision analysis is proposed, as an overarching methodical platform for the planning and optimization of structural Health Monitoring (SHM) activities in the context of SIM at both operational and strategic levels.
Copyright © 2017 by ASME
Original languageEnglish
Title of host publicationASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering : Offshore Geotechnics; Torgeir Moan Honoring Symposium
Volume9
PublisherAmerican Society of Mechanical Engineers
Publication date2017
PagesV009T12A040
Article numberOMAE2017-62715
ISBN (Electronic)978-0-7918-5777-9
DOIs
Publication statusPublished - 2017
Event36th International Conference on Ocean, Offshore & Arctic Engineering - Trondheim, Norway
Duration: 25 Jun 201730 Jun 2017
Conference number: 36

Conference

Conference36th International Conference on Ocean, Offshore & Arctic Engineering
Number36
Country/TerritoryNorway
CityTrondheim
Period25/06/201730/06/2017

Keywords

  • Risk
  • Structural systems

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