Masters Theses

Keywords and Phrases

Aerodynamics Workflow; CFD workflow; Formula SAE Aerodynamics; Formula SAE CFD; FSAE CFD; Workflow Optimization

Abstract

This research identifies and resolves inefficiencies in the Computational Fluid Dynamics (CFD) workflow of the Missouri S&T Racing Formula SAE Team’s aerodynamic development. Key bottlenecks were found in simulation runtime, laborious simulation preparation, an overly manual simulation submission process, and unchecked mesh quality. A fully reimagined workflow was implemented with simulation parameters to adjust vehicle attitudes. From this, an automated design sweep could be executed to generate aero maps of the developing vehicle using the Design Manager Project. A Python-based submission app handles the terminal interfacing and macro editing that significantly slowed the job submission process before. Using a university HPC, the computational throughput was increased from 128 cores to 256, cutting simulation wall time by 35%. A proof-of-concept geometry optimization was conducted using Siemens HEEDS to reduce the drag of a rear wing assembly. The HEEDS interface meshed well with the STAR-CCM+ parameters that were made, and minimal user input is needed to conduct a large design study. Beyond aerodynamic metric optimization, the software can also be used to ensure other vehicle systems like cooling are being sufficiently supplied with air. The changes reduced the time needed to generate an aero map by 36 hours. This significant time savings can put teams ahead by weeks in a typical design cycle. The application of all process optimizations enabled for a more accurate, automated simulation workflow that saves significant amounts of time.

Advisor(s)

Pernicka, Henry J.
Du, Xiaosong

Committee Member(s)

Fink, Coraline

Department(s)

Mechanical and Aerospace Engineering

Degree Name

M.S. in Aerospace Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2025

Pagination

viii, 66 pages

Note about bibliography

Includes_bibliographical_references_(pages 63-64)

Rights

© 2026 Kyle Maynor , All Rights Reserved

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 12572

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