Bridge Resilience Assessment with INSPIRE Data

Robotic data collection, both automated and remote, will enable post-disaster assessment of bridge components where it would normally be difficult and potentially dangerous for field workers to inspect manually. Approach and Methodology: To perform bridge resilience assessment, data will first be used to update component, e.g., column and girder, fragility assessments. Next, these updated component assessments will be input into bridge models to update overall bridge safety assessments. Safety will be determined based on updated assessments of load carrying capacity and updated bridge fragility functions. Finally, comparing these assessments across the bridges inspected will enable prioritization of repair across the transportation system for decreased system down time and improved resilience. Overall Objectives: This project aims to develop and validate a new framework that uses the data collected from the robotic exploration of infrastructure, particularly after a disaster, to assess the condition of bridges and prioritize these structures for repair. This will improve the resilience of the transportation system to disasters by targeting bridge repairs and enabling resources to be distributed more effectively across the system for more rapid recovery after a disaster. Scope of Work in Year 1: (1) Create a framework of global resilience analysis, moving from component to system bridge fragility assessments, and (2) Develop a robust method and software for computationally efficient analysis of strongly nonlinear structures. Scope of Work in Year 2: (1) Improve finite element modeling of structural components based on material and geometrical properties as well as inspection data (e.g., crack width, depth, and direction; corrosion induced mass loss of reinforcement), and (2) Understand the effect of corrosion on the strength and stiffness degradation of components and thus on the component and system fragility curves.

Project

Subject/Index Terms

Filing Info

  • Accession Number: 01646006
  • Record Type: Research project
  • Source Agency: Inspecting and Preserving Infrastructure through Robotic Exploration University Transportation Center
  • Contract Numbers: 69A3551747126
  • Files: UTC, RiP
  • Created Date: Sep 14 2017 10:57AM