Fuzzy Markov development for buried transportation bridges: Review of analysis and modeling technique. Issue 2 (28th October 2019)

• Record Type: Journal Article
• Authors: Gharehbaghi, Koorosh; McManus, Kerry; Robson, Kathryn; Eves, Chris; Myers, Matt
• Is Part Of: International journal of structural integrity. Volume 11:Issue 2(2020)
• Page Start: 338
• Page End: 353
• Publication Date: 2019-10-28
• Subjects: Bridges -- Buried transportation bridges -- Fuzzy Markov model -- Resilient structures; Structural engineering -- Research -- Periodicals; 620.11205
• DOI: 10.1108/IJSI-08-2019-0082
• Languages: English
• ISSNs: 1757-9864

Abstract

Abstract : Purpose: The purpose of this paper is to review the Fuzzy Markov development for assessing the structural integrity of buried transportation bridges. In doing so, the appropriateness of Fuzzy Markov will be assessed, leading to the subsequent model. Design/methodology/approach: This research will utilize the Fuzzy Markov techniques as the conceptual framework. Such methodology is further supported via the utilization and evaluation of 30 buried transportation bridges using the developed Fuzzy Markov model. Findings: Subsequently, through a developed Fuzzy Markov model, this research found that as the basis of structural resilience, specific matrices for age-dependent transition probability can be compiled using conditional survival probabilities in the various structural states; as the basis of structural integrity, specific environmental and economic schemes can also be established based on inspection intervals, intervention systems and failure phases; exact inspection and maintenance intervals can be scheduled to further prolong an asset's life; and clear and early warning signs can also be formulated for immediate intervention when the structural integrity of the asset are indeed compromised. Originality/value: The gap within the literature currently surrounds the limitation of computational analysis for some buried structures such as bridges. Specifically, to streamline such evaluation and regimes, a Fuzzy Markov is developed and reviewed.