Development of an Automated Simulation Pipeline for Assessing Effectiveness of Far-UV Disinfection of Air

This project aims to help hospitals reduce the spread of airborne infections—such as influenza, COVID-19, and other respiratory illnesses—by improving how a new disinfecting light technology called far-UVC is deployed. Far-UVC light can safely kill viruses and bacteria in the air while people are present in the room, but hospitals currently have no reliable way to predict how many lamps they need or where to place them for maximum protection. Working with UVX Inc., the student researcher will build a “digital twin” tool that uses 3D scans of real rooms to simulate how air moves, how germs spread, and how effectively far-UVC light can inactivate them. This tool will allow infection-control teams to test different lamp layouts virtually before purchasing equipment. The expected benefit to UVX is faster product adoption, lower installation costs for customers, and strong scientific validation of their technology. More broadly, this work will support safer hospitals, reduced energy use compared with ventilation-only approaches, and improved readiness for future pandemics.

Faculty Supervisor:

Christopher DeGroot

Student:

Partner:

UVX

Discipline:

Engineering

Sector:

Manufacturing

University:

The University of Western Ontario

Program: