Assessing Transition Probability of Bridge Deterioration Using Dempster–Shafer Theory of Evidence

Reliable deterioration models for forecasting the condition of bridge elements, systems, and networks are essential components of any bridge management system. Estimating deterioration transition probabilities is the basis of the popular Markov chain deterioration model. Transition probabilities have been produced in the literature by statistical and probabilistic analysis performed on available bridge inspection and condition data. The available data may be limited or inconsistent with the Markov chain transition period. In addition, the conventional probability theory has limitations when applied to problems with a stochastic nature such as bridge deterioration. This paper introduces a novel method based on the theory of evidence for bridge deterioration modeling through expert judgment elicitation. The advantages of the theory of evidence over the traditional probability theory are discussed and the process for the theory implementation is demonstrated with a case study to validate the application of Dempster–Shafer theory of evidence to estimate the transition probabilities. Based on the results, the theory of evidence is proposed as a scientific expert judgement elicitation technique in the area of bridge condition rating and deterioration modeling. Expert judgment elicitation and theory of evidence application hold potential in the field of bridge management and require further investigation and research.

• Record URL:
  https://doi.org/10.3233/BRS-170105
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/15732487
• Supplemental Notes:
  • ©2017 IOS Press and Saleh Abu Dabous. All rights reserved.
• Authors:
  • Abu Dabous, Saleh
• Publication Date: 2017

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 97-106
• Serial:
  • Bridge Structures - Assessment, Design & Construction
  • Volume: 12
  • Issue Number: 3-4
  • Publisher: IOS Press
  • ISSN: 1573-2487
  • EISSN: 1744-8999
  • Serial URL: https://content.iospress.com/journals/bridge-structures

Subject/Index Terms

• TRT Terms: Bridge members; Maintenance; Mathematical models; Probability; Structural deterioration and defects; Structural health monitoring
• Subject Areas: Bridges and other structures; Highways; Maintenance and Preservation;

Filing Info

• Accession Number: 01643936
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 22 2017 4:27PM