United States Department of Transportation
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Edition:Final report
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Abstract:Deterioration models for the Wyoming Bridge Inventory were developed using both stochastic and deterministic models.
The selection of explanatory variables is investigated and a new method using LASSO regression to eliminate human bias
in explanatory variable selection. The cross validation technique is used to determine the minimum number of explanatory
variables. The relative significance of candidate variables is used to rank the explanatory variables in hierarchical order.
The deterministic deterioration models are developed by using curve-fitting methods for the mean of bridge ages for each
condition rating. In order to improve the accuracy in the model, bridges are split into the multiple subsets using first two
explanatory variables for deck, superstructure, and substructure. Although the deterministic deterioration model is
insufficient to predict condition ratings for a specific bridge, it is worthy to observe a general feature of how the
functionality of bridges becomes worse over time.
The stochastic models are developed to capture the uncertainty in the deterioration process using the Markov chain. The
transition probability matrix is estimated using percentage prediction method, which counts the numbers corresponding to
the element of transition probability matrix. The same subsets used in the deterministic deterioration models are considered.
For each subset, zoning technique is used such that the bridge data is grouped for every 30 years to estimate transition
probability matrix separately.
The source codes are provided for the future update of bridge inventory and stochastic deterioration models. A computer
program is used develop and plot deterioration models. A simple guideline is also included so that the user can access the
source codes conveniently.
Author ORCID information:
Minwoo Chang; ORCID number 0000-0002-5749-078X
Marc Maguire; ORCID number 0000-0002-7897-0344
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