<p> Road vehicle aerodynamics are primarily focused on developing and modeling performance at steady-state conditions, although this does not fully encompass the entire operating envelope. Considerable vehicle acceleration and deceleration occurs during operation, either because of driver input or from transient weather phenomenon such as wind gusting. With this considered, high performance road vehicles experience body acceleration rates well beyond ±1G to navigate courses during efficient transition in and out of corners, accelerating from maximum straight-line speed to manageable cornering speeds, and then back to maximum straight-line speed. This dissertation aims to answer if longitudinal acceleration is important for road vehicle aerodynamics with the use of transient Computational Fluid Dynamics (CFD) to develop a method for obtaining ensemble averages of forces and flow field variables. This method was developed on a simplified bluff body, a channel mounted square cylinder, achieving acceleration through periodic forcing of far field velocity conditions. Then, the method was applied to an open-source road vehicle geometry, the DrivAer model, and a high performance model which was created for this dissertation, the DrivAer-GrandTouringRacing (GTR) variant, as a test model that generates considerable downforce with low ground proximity. Each test body experienced drag force variations greater than ±10% at the tested velocities and acceleration rates with considerable variations to flow field distributions. Finally, an empirical formulation was used to obtain non-dimensional coefficients for each body from their simulated force data, allowing for force comparison between geometries and modeling of aerodynamic force response to accelerating vehicle conditions.</p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10791882 |
| Date | 10 May 2018 |
| Creators | Peters, Brett |
| Publisher | The University of North Carolina at Charlotte |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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