Jevon Ashman

MIT Department: Mechanical Engineering
Faculty Mentor: Prof. Wesley Harris
Undergraduate Institution: Morehouse College
Research Poster


Hello, my name is Jevon Ashman, a rising senior majoring in Physics with a concentration in computational physics at Morehouse College. Where I served as the Vice President of the robotics team and as the Safety Officer for the NASA Student Launch team. Using my skills and education I plan to earn a Ph.D. in aerospace engineering focusing on alternative propulsion systems. My research interests lie at the intersection of engineering and computer science; specifically where I hope to find integrative approaches to optimize physical systems using machine learning. When I’m not in an engineering lab, I am engaging in community service where I mentor young students on leadership, tutor math & science, and increase interest in the STEM field to underrepresented communities. My hobbies include sewing, video games, rollerskating, and making music playlists.

2021 Abstract

Investing the Effects of Numerical Parameters and Mesh Resolution within
Exasim Code

Jevon Ashman1, Dominique Hoskin2, Wesley Harris2
1Division of Mathematics and Computational Science,
2Morehouse College Department of Aeronautics and Astronautics, Massachusetts Institute of Technology

Modeling fluid-structure interactions in hypersonic airflows with high definition is of great interest in the aerodynamics field because of the need to predict skin-friction and heat transfer on aircraft bodies. To accurately model these computational fluid dynamics (CFD) cases, Exasim code is used to numerically solve parametrized partial differential equations (PDEs). In order to qualify the model’s accuracy, numerical parameters and the mesh resolution are altered between different cases and compared to previous data found experimentally and computationally. Understanding how these initial conditions affect the model will garner better simulations that can predict hypersonic turbulent flows with more precision and accuracy. To provide meaningful information for improving the Exasim code, specific initial conditions will be changed while other conditions are kept the same. After that case, different initial conditions will be varied to investigate how the simulation’s stability, accuracy, and efficiency are affected. Thus far the stability and accuracy of previous simulations have been measured by the number of oscillations appearing on the heat transfer graph of the leading edge, which is produced by the code with those conditions. Based on the initial conditions changed between cases, there is a promising correlation between the code’s numerical parameter and mesh resolution of the stability and accuracy of the simulation.