A system for bridge network condition assessment and prediction

B. Samali, K. I. Crews, K. Aboura, W. Ariyaratne, P. B. Manamperi

Research output: Chapter in Book / Conference PaperConference Paperpeer-review

Abstract

Traditionally, bridge management systems were designed using a Markov chain decision model. Based on the analysis of 15 years of bridge inspection data, we apply the gamma process instead. After extracting all relevant information, enough data was collected on the condition paths of elements to build a deterioration model. The element conditions follow a time period in full condition then start deteriorating. We consider a random variable for the last time the condition was observed to be 100%. We consider the stochastic deterioration process that follows. The amalgamation of the two parts process through probabilistic arguments creates a new stochastic process. The novel stochastic process characteristics are derived through the data to provide a predictive model for the element, bridge and network conditions. We showcase a software solution for bridge network condition assessment, monitoring and prediction.
Original languageEnglish
Title of host publicationIncorporating Sustainable Practice in Mechanics of Structures and Materials: Proceedings of the 21st Australian Conference on the Mechanics of Structures and Materials, Melbourne, Australia, 7- 10 December 2010
PublisherCRC Press
Pages739-744
Number of pages6
ISBN (Print)9780415616577
DOIs
Publication statusPublished - 2011
EventAustralasian Conference on the Mechanics of Structures and Materials -
Duration: 11 Dec 2012 → …

Conference

ConferenceAustralasian Conference on the Mechanics of Structures and Materials
Period11/12/12 → …

Keywords

  • bridges
  • maintenance and repair
  • structural health monitoring

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