详情

Data-Driven Risk-Informed Bridge Asset Management and prioritization Across Transportation Networks

项目名称：	Data-Driven Risk-Informed Bridge Asset Management and prioritization Across Transportation Networks
摘要：	A transportation network comprises hundreds to thousands of assets, each with a varying combination of design characteristics, ages, conditions, repair histories, and hazard exposures. With typically limited resources to both inspect and repair these assets, an approach to efficiently and effectively distribute the resources to ensure reliability and resilience of the network is needed. At the same time, inspection data is increasing in type, amount, and capability to assess structural states. This data includes information collected from new robotic technologies developed through the Inspecting and Preserving Infrastructure through Robotic Exploration University Transportation Center (INSPIRE UTC). This project seeks to utilize the inspection data to assess assets across a transportation network to more effectively manage and prioritize resources across the network. It is a natural extension to the network of bridges from the risk analysis of individual bridges using localized inspection data for corrosion or scour evaluation. Approach and Methodology: This project will create a framework to map inspection data from individual bridges to assets across a transportation network. One of the challenges in doing this is the uncertainty in bridge conditions, aging processes, loadings, and predictions of performance across varying bridges. A risk-informed approach that considers varying characteristics across assets will therefore be implemented. Probabilistic inferences across a network will be made based on inspection data characteristics and similarity of parameters between assets, considering uncertainties in the inspection data, structural parameters, and environmental characteristics. Overall Objectives: This project aims to develop innovative ways to use inspection data and inform decisions for maintenance, repair, rehabilitation, or replacement actions at the infrastructure network scale. To inform these decisions, quantitative assessments and comparisons of estimated and predicted performance of bridges across a network must be made. This project will create a framework that takes input inspection data and infers risk for assets across a network to support bridge asset management and prioritization. Scope of Work in Year 1: (1) Create classes of bridges based on collected inspection data, (2) Define measures of similarity across bridges, and (3) Create a probabilistic mapping procedure to infer states of multiple assets based on individually-collected bridge inspection data.
状态：	Active
资金：	160951
资助组织：	Office of the Assistant Secretary for Research and Technology
执行机构：	Georgia Tech Research Corporation
开始时间：	20200101
预计完成日期：	20210630
主题领域：	Bridges and other structures；Data and Information Technology；Highways；Maintenance and Preservation；Planning and Forecasting