Value of Information Analysis with Structural Reliability Methods

Published on Jul 1, 2014in Structural Safety3.52
· DOI :10.1016/j.strusafe.2013.08.006
Daniel Straub23
Estimated H-index: 23
(TUM: Technische Universität München)
Abstract When designing monitoring systems and planning inspections, engineers must assess the benefits of the additional information that can be obtained and weigh them against the cost of these measures. The value of information (VoI) concept of the Bayesian statistical decision analysis provides a formal framework to quantify these benefits. This paper presents the determination of the VoI when information is collected to increase the reliability of engineering systems. It is demonstrated how structural reliability methods can be used to effectively model the VoI and an efficient algorithm for its computation is proposed. The theory and the algorithm are demonstrated by an illustrative application to monitoring of a structural system subjected to fatigue deterioration.
  • References (50)
  • Citations (32)
#1Sebastian Thöns (BAM: Bundesanstalt für Materialforschung und -prüfung)H-Index: 9
#1Matteo Pozzi (University of California, Berkeley)H-Index: 11
#2Armen Der Kiureghian (University of California, Berkeley)H-Index: 46
Cited By32
#1Sergio Cantero-Chinchilla (University of Nottingham)H-Index: 1
#2Juan Chiachio (UGR: University of Granada)H-Index: 7
Last.Arthur Jones (University of Nottingham)H-Index: 9
view all 0 authors...
#1Guang Zou (Lloyd's Register)H-Index: 1
#2Arturo González (UCD: University College Dublin)H-Index: 18
Last.Michael Havbro Faber (AAU: Aalborg University)H-Index: 24
view all 0 authors...
#1Luc Chouinard (McGill University)H-Index: 10
#2Vahid Shahsavari (UNH: University of New Hampshire)H-Index: 1
Last.Josée Bastien (Laval University)H-Index: 8
view all 3 authors...
#1Ana C. Neves (KTH: Royal Institute of Technology)
#2John Leander (KTH: Royal Institute of Technology)H-Index: 5
Last.Raid Karoumi (KTH: Royal Institute of Technology)H-Index: 17
view all 4 authors...
View next paperApplied statistical decision theory