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On information modeling in structural integrity management

Author(s):


Medium: journal article
Language(s): English
Published in: Structural Health Monitoring, , n. 1, v. 21
Page(s): 147592172096829
DOI: 10.1177/1475921720968292
Abstract:

Value of information analyses in structural integrity management has gained significant interest over especially the last decade. The concept of value of information analysis provides a methodical framework facilitating for the optimization of strategies for information collection through inspections and structural health monitoring. The information, which is collected, represents indications of the condition and performance of the structure and is generally subject to significant uncertainties. An important part of this uncertainty is directly related to the quality of the techniques that are utilized for collecting information. Whereas such uncertainties are generally appreciated and accounted for in the research literature, it is generally assumed that information of relevance of integrity management, collected over space and time, is unbiased and independent. In the present contribution, we investigate the possible consequences of such assumptions. To this end, we model the value of information associated with information collection and evaluate the effect of introducing biases and dependencies on the value of information. Two different probabilistic models are introduced to represent and study the effect of possible biases corresponding to the case where biases in information collected at different times are independent or fully dependent, respectively. The study is supported by the address of two different integrity management problems considering (1) an oil well tubing system subject to scaling and (2) a welded detail in steel structures subject to fatigue degradation.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1177/1475921720968292.
  • About this
    data sheet
  • Reference-ID
    10562541
  • Published on:
    11/02/2021
  • Last updated on:
    17/02/2022
 
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