The goal of this project is to develop new materials, applied in the form of paints, for damage detection in bridges. These paints are unique in that they emit a visible light signal as cracks propagate through them. This allows an inspector to identify and monitor active cracks during visual inspection of bridges and other civil infrastructure. The project combines the development and processing of luminescent paints with the testing of these materials as sensors for crack detection and categorization in civil infrastructures. The paints will be studied by a combination of laboratory experiments, which includes the design of new material compositions, and the field-testing of the paints on both in-service and decommissioned bridges, which will allow development of field protocols for use of these materials. The emphasis is on systematically optimizing basic materials processing and behavior that will result in enhanced signal strength during field use and developing a model that describes the luminescent response of a variety of materials for crack detection. The project is divided into two parts: (1) the development of luminescent powders and their incorporation into slurries to form a paint mixture that can be applied to structures and (2) the testing of these materials under realistic conditions for assessment of their effectiveness for structural health monitoring, specifically detection and categorization of fatigue cracks.

If successful, the benefit of this research will be the development of unique paints that can visually detect active cracks in bridges, increasing the effectiveness of the visual inspection and the timeliness of repair strategies. As many state and federal agencies develop a replacement and rehabilitation strategy for aging infrastructure, this is an opportune time to integrate an innovative sensing methodology that exploits all available material advancements. An innovative monitoring tool that provides real-time information, does not require a power source, and is visual, would be a significant advancement in the area of fatigue crack detection. This tool could be integrated during hands-on inspection or during rehabilitation of bridge structures.

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University of California San Diego
La Jolla
United States
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