Jayson Johnson
MIT Department: Aeronautics and Astronautics
Faculty Mentor: Prof. Wesley Harris
Research Supervisors: Stewart Isaacs, Chelsea Onyeador
Undergraduate Institution: Howard University
Hometown: Silver Spring, Maryland
Website: Intern’s Website, LinkedIn
Biography
Jayson Johnson is a rising junior at Howard University and a Karsh STEM Scholar pursuing a bachelor’s degree in Mechanical Engineering. He is the co-founder of Tree Tech, a startup focused on facilitating improved information access in his college communities through AI. This venture aligns with his commitment to helping minorities and underserved populations through data science and engineering. Jayson accumulated extensive experience through various projects at the Johns Hopkins Applied Physics Lab, Howard, and Johns Hopkins University involving heat transfer for hypersonic vehicles and International Space Station (ISS) payloads, as well as solid state synthesis for superconductors. At MIT, Jayson worked in the Hypersonics Research Lab to find optimal aerodynamic designs for solar panels to mitigate dust accumulation on the surface. His career aspirations involve obtaining a PhD in Aerospace Engineering to continue helping underserved communities. Outside of school, Jayson enjoys physical activities such as gymnastics, going to the gym, and playing soccer.
Abstract
Reduced Ordered Models for Self-Cleaning Solar Panels
Jayson Johnson1, Dr. Stewart Isaacs2, Dr. Chelsea Onyeador, and Dr. Wesley Harris2
1Department of Mechanical Engineering, Howard University
2Department of Aerospace Engineering, Massachusetts Institute of Technology
As the world moves towards renewable energy, decentralized solar photovoltaic (PV) systems offer a solution for regions without access to modern electricity infrastructure. Of the estimated 660 million people that will lack electricity in 2030, 85% of them will be in Sub-Saharan Africa. In regions like West Africa, the annual dry season brings challenges to PV systems due to dust aerosols and soiling, leading to up to 50% reductions in power output. We propose Shape-Enhanced Aerodynamic Dust Removal (SEADR), a novel method for mitigating the soiling of photovoltaic panels by employing shape-induced aerodynamic forces to remove dust. However, the design of SEADR shapes requires negotiating a tradeoff between energy generation and improved dust removal from aerodynamics. This project integrates a Gaussian Process model with Computational Fluid Dynamics (CFD) simulations to develop a reduced order model (ROM) that quickly simulates panel geometry effects on aerodynamics. Using the ROM, we can estimate average shear on the surface of a panel within 0.28% of the predicted mean value 200,000x faster than traditional CFD. Ultimately, the ROM contributes to the development of resilient solar systems in dusty environments, offering a pathway for future innovations in sustainable energy and addressing limitations of traditional CFD methods.
