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A Failure Risk-Based Culvert Renewal Prioritization Framework

Author(s):


Medium: journal article
Language(s): English
Published in: Infrastructures, , n. 3, v. 4
Page(s): 43
DOI: 10.3390/infrastructures4030043
Abstract:

Transportation agencies are currently challenged to keep up with culvert infrastructure that is rapidly deteriorating due to lack of adequate maintenance and capital improvement. It is imperative for the transportation agencies to identify and rehabilitate deteriorated culverts prior to their failures. Among several concerns, lack of rational rehabilitation prioritization tools is foremost. Complicating this need further, current practices vary widely across the state departments of transportation (DOTs) which makes it difficult to develop a universal approach for prioritizing failing culverts. This paper presents and demonstrates a failure risk-based culvert prioritization approach that is compliant with the inspection procedures of the South Carolina DOT. The approach presented in this paper is specifically developed for reinforced concrete pipe (RCP) and corrugated metal pipe (CMP) materials because of their wide popularity. Outcomes from a survey of state DOTs informed the development of parametric weightings using the principles of analytical hierarchy process (AHP). Weightings developed for several critical inspection parameters are combined with the corresponding condition assessment scores to determine the failure criticality of culverts, which are subsequently combined with estimated failure consequences to determine failure risk estimates. The prioritization approach is demonstrated using the condition assessment scores of over 5200 culvert structures in South Carolina.

Copyright: © 2019 the Authors. Licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10723275
  • Published on:
    22/04/2023
  • Last updated on:
    10/05/2023
 
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