Time-Based Modeling of Concrete Bridge Deck Deterioration Using Probabilistic Models
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2021-01-01
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Edition:Final Report 03/01/2019 – 08/31/2021
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Abstract:This research developed a robust, self-learning, probabilistic model to predict the service life of concrete bridge decks and subsequently other infrastructure components. The model originated from the existing performance data for 22,000 bridge decks in the State of Pennsylvania and utilized advanced statistical tools, including Bayesian probabilistic networks. The newly developed tool can allow state departments of transportation to: (1) accurately predict the lifetime of concrete bridge decks, and (2) establish more efficient and accurate management decisions, resulting in increased longevity of the nation’s infrastructure.
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