The New Mexico Consortium (NMC) enables leadership in New Mexico in the area of Cyber-Physical Systems, by supporting a unique collaboration between Los Alamos National Laboratory (LANL) and the University of New Mexico (UNM). This collaboration is a project that uses enhanced drones which will be able to tap on surfaces and collect information on their condition. This will enable collecting hundreds of thousands of hits of data without having to climb remote structures.
The project led by David Mascarenas, a LANL scientist and Fernando Moreu a professor in the Department of Civil, Construction, & Environmental Engineering at UNM, won the 2016 student competition award in the engineering category. This project is one of several collaborations between the Engineering Institute of LANL and the Smart Management of Infrastructure Laboratory (SMILab) of UNM to advance new solutions for Structural Health Monitoring (SHM) with new interfaces, mechanisms, sensors, and algorithms that collect new information for owners and decisions makers.
Another example is the participation of Dr. Mascarenas as Expert Review Panel member on a National Academy of Sciences project measuring displacements of railroad bridges with lasers, cameras and drones. According to Fernando Moreu, “We are interested to assist railroads monitor their bridges more safely and accurately.”
Their partnership may advance with the development of a new outdoor drone facility in the University of New Mexico called “LoboDrome” which is currently in the planning phase. This facility on the UNM campus will be a place where students can build, test and use drones for a variety of projects.
The new LoboDrome facility has been recently covered by the local news (https://www.krqe.com/news/albuquerque-metro/unm-school-of-engineering-working-on-building-lobodrome/) and it is expected to increase the leadership of the state in new solutions for SHM of critical infrastructure.
Other collaborations between Mascarenas and Moreu include, but are not limited to: Augmented Reality, Computer-vision techniques, laser-drone monitoring of railroad bridges, and cybersecurity of SHM.