The goal of the research is to develop a robust, self-learning, probabilistic model to predict the service life of concrete bridge decks, and subsequently other infrastructure components. The model will originate from the existing performance data for 22,000 bridge decks in the state of Pennsylvania and will utilize advanced statistical tools, including machine learning systems and Bayesian probabilistic networks. The newly developed tool will allow State Departments of Transportation to A) accurately predict the lifetime of concrete bridge decks and B) establish more efficient and accurate management decisions, resulting in an increased longevity of the Nation's infrastructure.
|Effective start/end date||3/1/19 → 5/29/20|
- University Transportation Centers