Probabilistic and mechanistic deterioration models for bridge management

G. Morcous, Z. Lounis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

This paper presents two approaches of modeling the deterioration of highway bridges that can lead to an effective maintenance management strategy. Probabilistic state-based/time-based models are used to predict the global or macro-response of bridge components for network level analysis, while reliability-based mechanistic models are used to predict the detailed or micro-response of bridge components for project level analysis. Probabilistic state-based/time-based models are developed using qualitative performance indicators (condition ratings) that are determined through visual inspections to identify the overall condition of damaged components in a bridge network. Reliability-based mechanistic models are developed using quantitative performance indicators (physical parameters) that are determined through detailed condition surveys, analytical modeling, and empirical investigations to identify the extent and severity of specific deterioration mechanisms for safety critical structures and/or highly damaged components. The condition rating data obtained from the Ministére des Transports du Quebec database and the condition assessment of the Dickson Bridge in Montreal, Canada were used to demonstrate the development of the two approaches in modeling the deterioration of concrete bridge decks.

Original languageEnglish (US)
Title of host publicationComputing in Civil Engineering - Proceedings of the 2007 ASCE International Workshop on Computing in Civil Engineering
Pages364-373
Number of pages10
DOIs
StatePublished - Dec 1 2007
Event2007 ASCE International Workshop on Computing in Civil Engineering - Pittsburgh, PA, United States
Duration: Jul 24 2007Jul 27 2007

Publication series

NameCongress on Computing in Civil Engineering, Proceedings

Conference

Conference2007 ASCE International Workshop on Computing in Civil Engineering
CountryUnited States
CityPittsburgh, PA
Period7/24/077/27/07

Fingerprint

Deterioration
Bridge components
Highway bridges
Bridge decks
Concrete bridges
Reliability analysis
Macros
Inspection

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Computer Science Applications

Cite this

Morcous, G., & Lounis, Z. (2007). Probabilistic and mechanistic deterioration models for bridge management. In Computing in Civil Engineering - Proceedings of the 2007 ASCE International Workshop on Computing in Civil Engineering (pp. 364-373). (Congress on Computing in Civil Engineering, Proceedings). https://doi.org/10.1061/40937(261)45

Probabilistic and mechanistic deterioration models for bridge management. / Morcous, G.; Lounis, Z.

Computing in Civil Engineering - Proceedings of the 2007 ASCE International Workshop on Computing in Civil Engineering. 2007. p. 364-373 (Congress on Computing in Civil Engineering, Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Morcous, G & Lounis, Z 2007, Probabilistic and mechanistic deterioration models for bridge management. in Computing in Civil Engineering - Proceedings of the 2007 ASCE International Workshop on Computing in Civil Engineering. Congress on Computing in Civil Engineering, Proceedings, pp. 364-373, 2007 ASCE International Workshop on Computing in Civil Engineering, Pittsburgh, PA, United States, 7/24/07. https://doi.org/10.1061/40937(261)45
Morcous G, Lounis Z. Probabilistic and mechanistic deterioration models for bridge management. In Computing in Civil Engineering - Proceedings of the 2007 ASCE International Workshop on Computing in Civil Engineering. 2007. p. 364-373. (Congress on Computing in Civil Engineering, Proceedings). https://doi.org/10.1061/40937(261)45
Morcous, G. ; Lounis, Z. / Probabilistic and mechanistic deterioration models for bridge management. Computing in Civil Engineering - Proceedings of the 2007 ASCE International Workshop on Computing in Civil Engineering. 2007. pp. 364-373 (Congress on Computing in Civil Engineering, Proceedings).
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