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Mid-America Transportation Center

NDOR Development of PONTIS Deterioration Models for Nebraska Bridges

Final Report
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Researchers

  • Principal Investigator: George Morcous (gmorcous2@unl.edu 402-554-0571)
  • Project Status
    Complete
    Sponsors & Partners
  • Nebraska Department of Roads
  • Brief Project Description & Background
    During the service life of a bridge, different types of costs are incurred by both bridge owners and users, the sum of which represents the life-cycle cost. The owner costs represent construction cost, maintenance costs and demolition costs. The users’ costs incurred due to traffic congestion, detours, accidents and failures, besides the indirect costs of environmental pollution due to idling of vehicles. Although an accurate estimation of these costs is quite difficult, the life-cycle cost is considered an efficient approach to comparing the long-term effects of different maintenance strategies and identifying the optimal ones. Deterioration models are integral component of life-cycle cost assessment because maintenance costs and user costs are highly dependent on bridge condition that varies over the analysis period. The quality of LCC-based decision depends primarily on the accuracy and efficiency of the deterioration models used to predict the time-dependent performance and remaining service life of highway bridges. By definition a deterioration model is a link between a measure of bridge condition that assesses the extent and severity of damages, and a vector of explanatory variables that represent the factors affecting bridge deterioration such as age, material properties, applied loads, environmental conditionals, etc. The project represents the first phase of a multi-phase project that aims to optimizing decisions based on life-cycle costs assessment of bridge structures.
    Research Objective
    The objective is twofold: (1) Develop deterioration models for different bridge components, namely deck, superstructures, and substructure, using the inventory and condition data currently available for Nebraska bridges. These models include those required by the Pontis preservation module to determine the long-term policy that minimizes life-cycle cost and (2) Develop procedures for updating the developed models as new data becomes available.
    Abstract
    The life-cycle cost assessment of highway bridges is a decision making approach that is based on the total cost accrued over the entire life of a bridge extending from its construction to its replacement or final demolition. During the service life of a bridge, different types of costs are incurred by both bridge owners and users. The owner costs represent construction cost, maintenance costs and demolition costs. The users’ costs incurred due to traffic congestion, detours, accidents and failures, besides the indirect costs of environmental pollution due to idling of vehicles. Although an accurate estimation of these costs is quite difficult, the Life-cycle cost is considered an efficient approach to comparing the long-term effects of different maintenance strategies and identifying the optimal ones. This is extremely important for most bridge owners due to limitations on the availability of funds required to fulfill even urgent maintenance needs. Deterioration models are integral component of Life-cycle cost assessment because maintenance costs and user costs are highly dependent on bridge condition that varies over the analysis period. The quality of LCC-based decision depends primarily on the accuracy and efficiency of the deterioration models used to predict the time-dependent performance and remaining service life of highway bridges. By definition a deterioration model is a link between a measure of bridge condition that assesses the extent and severity of damages, and a vector of explanatory variables that represent the factors affecting bridge deterioration such as age, material properties, applied loads, environmental conditionals, etc. The literature on deterioration models of highway bridges comprises several approaches that can be categorized into deterministic, stochastic, and artificial intelligence approaches.
    Project Amount
    $ 32,917