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Estimating Inspection Intervals for Bridges Based on Statistical Analysis of National Bridge Inventory Data
AbstractThis paper describes a statistical approach to estimating an appropriate inspection interval for highway bridges based on historical condition data collected from 20 years of routine inspections. Condition ratings of 4,270 bridges with concrete, steel, and prestressed-concrete superstructures were analyzed in this study to determine the time-in-condition rating (TICR) for superstructure components. The Anderson-Darling test was used to assess five conventional distributions to determine goodness of fit for describing the distribution of the TICR probabilistically. The test results revealed that the Weibull distribution was the best fit for the TICR for superstructure components. Parameters of the Weibull distribution were estimated for concrete, steel, and prestressed concrete in different condition ratings and used to define probability-density functions (PDFs), which were then used to determine the likelihood of a bridge deteriorating from a good condition to a poor condition over some time period. These data can be used for rational decision making regarding the appropriate inspection interval for bridges of a given type based on quantitative historical analysis of data. This study is beneficial because of the simplicity of the models developed and their accessibility for practicing engineers.
Estimating Inspection Intervals for Bridges Based on Statistical Analysis of National Bridge Inventory Data
AbstractThis paper describes a statistical approach to estimating an appropriate inspection interval for highway bridges based on historical condition data collected from 20 years of routine inspections. Condition ratings of 4,270 bridges with concrete, steel, and prestressed-concrete superstructures were analyzed in this study to determine the time-in-condition rating (TICR) for superstructure components. The Anderson-Darling test was used to assess five conventional distributions to determine goodness of fit for describing the distribution of the TICR probabilistically. The test results revealed that the Weibull distribution was the best fit for the TICR for superstructure components. Parameters of the Weibull distribution were estimated for concrete, steel, and prestressed concrete in different condition ratings and used to define probability-density functions (PDFs), which were then used to determine the likelihood of a bridge deteriorating from a good condition to a poor condition over some time period. These data can be used for rational decision making regarding the appropriate inspection interval for bridges of a given type based on quantitative historical analysis of data. This study is beneficial because of the simplicity of the models developed and their accessibility for practicing engineers.
Estimating Inspection Intervals for Bridges Based on Statistical Analysis of National Bridge Inventory Data
Washer, Glenn (author) / Nasrollahi, Massoud
2015
Article (Journal)
English
BKL:
56.23
Brückenbau
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