Bridge Resilience Assessment with INSPIRE Data (RR-1)

Universities: Georgia Institute of Technology
                           Missouri University of Science and Technology

Principal Investigator: Dr. Iris Tien, Georgia Institute of Technology

PI Contact Information: Phone: (404) 894-8269  |  Email:

Co-Principal Investigators: Dr. Reginald DesRoches, Rice University
                                                        Dr. Genda Chen, Missouri S&T

Funding Sources and Amounts Provided:
Georgia Institute of Technology: $201,388
INSPIRE UTC: $311,141

Total Project Cost: $512,529

Match Agency ID or Contract Number:
Georgia Institute of Technology: In-Kind Match    |    INSPIRE UTC: 00055082-02B

INSPIRE Grant Award Number: 69A3551747126

Start Date: November 30, 2016
End Date: December 31, 2020

Brief Description of Research Project:

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.

Scope of Work in Year 3: (1) Build nonlinear finite element bridge models to automate the updating of bridge parameters based on INSPIRE-collected scour data, (2) Conduct static and dynamic analyses of bridge performance, and (3) Perform multi-hazard fragility assessment for bridges with combined loading effects and varying degrees of measured scour.

Scope of Work in Year 4: Year 1 of this project will comprise three main tasks: 1) We will create classes of bridges based on asset characteristics and collected inspection data. The classes will enable us to characterize the inventory of bridges in a transportation network and will form the basis in defining the similarity measures in Task 2. 2) Task 2 focuses on way to connect information about bridges from individual structures to structures across a network. The connection will be achieved by defining new similarity measures across bridges. The measures will be adaptable across asset types. 3) We will create a robust way to map specific inspection data from individual bridges to assets across a transportation network. We will accomplish this by creating a probabilistic mapping procedure that takes into account the bridge classes and similarity measures in Tasks 1 and 2. The outcome will be the ability to infer the states of multiple assets based on individually-collected inspection data.

Describe Implementation of Research Outcomes:
Research outcomes and implementation plan will be described towards the end of this project.

Impacts/Benefits of Implementation:
Impact/Benefits of Implementation will be summarized at the end of this project.

Project Website:
Progress Reports: