A professor at The University of Kentucky has been awarded a grant of close to $1.2 million (£960k) to use UAVs in the event of airborne contaminant dispersion.
Jesse Hoagg received the grant from the National Science Foundation, with his project, titled “Data-Driven Adaptive Real-Time (DART) Flow-Field Estimation Using Deployable UAVs” to be funded for three years.
Hoagg will work on the project alongside mechanical engineering associate professors Sean Bailey and Alexandre Martin and agricultural engineering associate professor Michael Sama.
According to the abstract, the project “addresses the problem of predicting atmospheric contaminant dispersion in real time by using a fleet of autonomous unmanned air vehicles (UAVs) to obtain sparse physical measurements of the atmospheric flow and contaminant concentrations.”
The primary aim of the project is to develop and demonstrate a new data-driven adaptive real-time (DART) system that produces accurate real-time micrometeorological estimates and forecasts contaminant dispersion near its source.
Developing the DART system requires new techniques for real-time data-driven model adaption, advances in computational turbulence modelling, improvements in UAV-based sensing and data processing, and new UAV formation flying methods that use cyber-feedback from the computational-fluid-dynamic cyber system.