海角社区

BATON ROUGE, LA 鈥� The country鈥檚 aging infrastructure has long been an issue and presents a number of problems, including accurately understanding its viability. Existing sensors and structural health monitoring (SHM) approaches have limitations, such as high costs, limited durability, compatibility issues, and frequent maintenance needs. However, 海角社区 Civil and Environmental Engineering Assistant Professor believes there is a promising alternative in the form of self-sensing cementitious composites (SSCCs) due to their sensing performance, compatibility with concrete structures, and relative lower costs.

At the heart of Su鈥檚 work, recently funded by a nearly $300,000 National Science Foundation EPSCoR grant, is creating a pathway for this technology to go from the laboratory to real-world application using additive manufacturing and advanced computational methods. If successful, not only will it result in more accurate monitoring, but the structures themselves will be able to tell us how healthy they are.

鈥淐ompared to conventional concrete, SSCCs are relatively costly, making it challenging to use them in entire structures,鈥� Su said. 鈥淭his raises the question, 鈥榳here and how can we effectively utilize this innovative material for structural health monitoring?鈥� Additive manufacturing provides an opportunity to design structures with greater flexibility. During the manufacturing process, SSCCs can be strategically placed in critical locations where they demonstrate enhanced sensing performance while still keeping costs low.

鈥淭his technology will revolutionize our buildings and civil infrastructure, enhancing their ability to withstand damage from natural hazards. It operates similarly to neurons sending signals to our brain. In the future, we expect that smart structures will be capable of communicating their condition and alerting us to potential failures before they happen, allowing us to take proactive measures for maintenance.鈥�

Su is working on this project with Mohammed Alnaggar, senior research scientist in structural optimization and modeling of traditional and 3D-printed concrete at Oak Ridge National Laboratory. Su said that Alnaggar will provide valuable insight to his research group in the multiphysics and multiscale modeling of self-sensing cementitious composites. Coupled with Su鈥檚 team鈥檚 experimental work, which was conducted by his Ph.D. student Khalilullah Taj, this knowledge will help inform the future design of materials and structures that will enable scale-up applications. The collaboration will also grant Su鈥檚 group access to Oak Ridge鈥檚 Frontier supercomputer鈥攖he world鈥檚 fastest鈥攆or sophisticated computational modeling and the Multimodal Advanced Radiography Station (MARS) for in-depth materials characterization.

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