Copernic Mensah

Copernic Mensah

Biography

Copernic Mensah is a computer science undergraduate at Hampton University, working toward a Ph.D. During the school year, he researches nuclear fusion at The Center for Fusion Research and Training, modeling Poincaré plots and experimenting with stellarator coil-winding. He is currently interning at MIT’s Hypersonics Research Laboratory, working under Dr. Wesley Harris and Dr. Stewart Isaacs to study shape-enhanced aerodynamic dust removal from solar panels in West Africa. Before that, he served as a Quantitative Developer Intern at the Nwagbara Group LLC, maintaining high-frequency trading engines in Rust. At the Center for Applied Biomechanics and Rehabilitation, he designed a 2D robotic hand exoskeleton game for stroke patients. He received recognition at NASA’s Solar Energy and Science Gateways hackathons for his work in astronaut augmented reality and LLM data portals for reproducible science. Across every difficult project, Copernic’s approach remains the same: understand the problem analytically, then solve it numerically.

Uniform Dust Deposition and Orientation Detection for Wind Tunnel
Testing of Photovoltaics
Copernic Mensah¹, Dr. Stewart Isaacs², Dr. Wesley Harris^2
1Department of Computer Science, Hampton University
²Department of Astronautics and Aeronautics, Massachusetts Institute of Technology

Dust accumulation on photovoltaic (PV) module surfaces limits power generation. While manual, automatic, and semi-automatic cleaning strategies exist to remove surface dust, no passive cleaning strategy currently exists. This project investigates passive dust removal through wind tunnel experimentation at 10 m/s on analog PV panels, testing three angles of attack (0°, 15°, and 30°). We first developed a standardized dust deposition method by comparing four candidate techniques—manual pile-and-push, manual mesh tapping, automatic mesh sifting, and manual mesh shaking—evaluated on deposition time, evenness, particle uniformity, and spread. Pile-and-push was fastest (1:30) but produced uneven coverage, corner gaps, and dust clumping. Mesh tapping (1:47) achieved even, uniform coverage but required strenuous, repeated effort, making it impractical across many trials. Automatic mesh sifting (2:30) produced even, uniform, fine, gap-free coverage without manual strain and was selected as our standardized deposition procedure. Alongside this work, we developed a ChArUco board-based computer vision model that uses corner detection and PnP (Perspective-n-Point) pose estimation to detect panel tilt. The findings of this work aim to improve PV module performance.