MPC
Project Details

Title:	Development of Age and State Dependent Stochastic Model for Improved Bridge Deterioration Prediction
Principal Investigators:	Gaofeng Jia
University:	Colorado State University
Status:	Active
Year:	2017
Grant #:	69A3551747108 (FAST Act)
Project #:	MPC-536
RiP #:	01650583
RH Display ID:	15696
Keywords:	bridges, data mining, deterioration, inspection, maintenance, Markov chains, mathematical prediction, stochastic programming

Abstract

Reliable and accurate assessment and prediction of the condition deterioration of bridges is critical for effective bridge preservation, which can help extend the service life of bridges. Bridge inspection serves as an important task in assessing the current condition of bridges. The inspection data over time can also help establish condition deterioration models to predict bridge conditions in the future. The deterioration models combined with the information on the current condition can help guide inspection, maintenance, repair, and rehabilitation planning, and can also be incorporated for risk and life-cycle analysis. Therefore, it is very important to develop deterioration models that can better predict the condition deterioration of bridges and bridge elements.

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