Project Title

Preserving Coastal Infrastructure through the Design and Implementation of Image-Based Structural Health Monitoring (iSHM)

Collaborating Universities

University of Virginia
351 McCormick Dr.
P.O. Box 400742
Charlottesville, VA 22904-4742
www.virginia.edu

Principal Investigator(s)

Devin Harris (UVa)
Email: dharris@virginia.edu

Total Project Costs

$150,435

Start Date

08/01/16

Completion Date

08/31/18

Description

Motivation 

With infrastructure systems across the globe approaching the end of their service lives, there is an ever-pressing need for techniques to assess current condition and remaining life. As a case in point, bridges in the United States, with an average age approaching 45 years, represent one particular infrastructure system that is at risk. In this environment, deterioration has outpaced solutions for preservation and owners are faced with the challenges of assessing and managing this infrastructure without the resources and staffing necessary for proper management. This feature is particularly critical in coastal regions such as Hampton Roads, where high-profile infrastructure systems such as the Hampton Road Bridge Tunnel and Chesapeake Bay Bridge provide critical linkages along the Mid-Atlantic coastal corridor. The infrastructure in these coastal regions are particularly vulnerable to environmental change such as sea level rise extreme weather events, which not only has the potential to impact daily and event driven operation, but also impact the long-term performance as these structures are exposed to more extreme operational demands. Examples of these extreme operational demands include: larger and overloaded trucks, greater thermal cycles, more exposure to salting during snowstorm events, topside seawater exposure from storm surges, and underside exposure saltwater spray.

Assessment represents one of the key components of the broader framework of structural health monitoring (SHM) and is essential to an overall mission of transportation sustainability, specifically infrastructure sustainability. Historically, much of this assessment has relied heavily on visual inspection as the standard method to characterize condition state, but research has shown that visual inspections yield results that are subjective and somewhat unreliable. While traditional visual assessment has a number of limitations when used in an subjective manner, vision as a quantitative tool is proving to be a powerful approach for assessment of condition and structural behavior.

Research Objectives and Tasks 

The investigation proposes to leverage advances in vision-based assessment to develop and approach for integration into the domain of structural health monitoring. Within the scope of this work, we proposed to evaluate the capabilities of vision-based deformation measurement approaches for describing condition state, system behavior, damage identification, and model updating. The following tasks highlight the proposed direction of the investigation.

  • Task 1 – Comprehensive Literature Review
  • Task 2 – Experimental Design for Vision-Based Assessment
  • Task 3 – Extension of Vision-Based Assessment for System Identification
  • Task 4 – Reporting

Implementation

In accordance with MATS UTC guidelines, this task will focus on reporting and dissemination. Update reports on project progress will be submitted on a quarterly basis with a final report submitted at the conclusion of the project. In addition to reporting, the project team will focus their efforts on result dissemination through appropriate peer-review journals and conference presentations.

Impacts

The expected benefits of the proposed investigation will be realized through the development of a comprehensive understanding of the capabilities of vision-based sensing for integration into a SHM framework. With the wealth of data derived from these approaches, we expect to be able to provide a better understanding of the performance of in-service bridges with minimal disruption of operations. The proposed approach also provides a major improvement over current in-place sensing methods in that the sensing method is not fixed and durability with respect to long-term operation of the measurement system is not a major concern.

Web Links to Reports and to the Project website