SAS vs SRS CFD models to full scale wind tunnel testing paper - NASCAR

[Hoffman900]

Published two weeks ago. Excellent paper comparing SAS and SRS CFD models to a full scale NASCAR Gen6 chassis in a wind tunnel with pressure taps throughout.

Abstract

Racecar aerodynamic development requires well-correlated simulation data for rapid and incremental development cycles. Computational Fluid Dynamics (CFD) simulations and wind tunnel testing are industry-wide tools to perform such development, and the best use of these tools can define a race team’s ability to compete. With CFD usage being limited by the sanctioning bodies, large-scale mesh and large-time-step CFD simulations based on Reynolds-Averaged Navier–Stokes (RANS) approaches are popular. In order to provide the necessary aerodynamic performance advantages sought by CFD development, increasing confidence in the validity of CFD simulations is required. A previous study on a Scale-Averaged Simulation (SAS) approach using RANS simulations of a Gen-6 NASCAR, validated against moving-ground, open-jet wind tunnel data at multiple configurations, produced a framework with good wind tunnel correlation (within 2%) in aerodynamic coefficients of lift and drag predictions, but significant error in front-to-rear downforce balance (negative lift) predictions. A subsequent author’s publication on a Scale-Resolved Simulation (SRS) approach using Improved Delayed Detached Eddy Simulation (IDDES) for the same geometry showed a good correlation in front-to-rear downforce balance, but lift and drag were overpredicted relative to wind tunnel data. The current study compares the surface pressure distribution collected from a full-scale wind tunnel test on a Gen-6 NASCAR to the SAS and SRS predictions (both utilizing SST 𝑘−𝜔
turbulence models). CFD simulations were performed with a finite-volume commercial CFD code, Star-CCM+ by Siemens, utilizing a high-resolution CAD model of the same vehicle. A direct comparison of the surface pressure distributions from the wind tunnel and CFD data clearly showed regions of high and low correlations. The associated flow features were studied to further explore the strengths and areas of improvement needed in the CFD predictions. While RANS was seen to be more accurate in terms of lift and drag, it was a result of the cancellation of positive and negative errors. Whereas IDDES overpredicted lift and drag and requires an order of magnitude more computational resources, it was able to capture the trend of surface pressure seen in the wind tunnel measurements.

https://www.mdpi.com/2311-5521/8/5/157

It really highlights how hard CFD correlation is and one can imagine how much harder it would be in an open wheel concept like F1.

[jjn9128]

Interesting stuff, thanks for sharing. Look forward to reading it properly when I get time!

[Hoffman900]

Interesting stuff, thanks for sharing. Look forward to reading it properly when I get time!

Dr. Uddin has several papers he’s co-authored / advises on the Gen 6 car (among other things) https://saemobilus.sae.org/search/?op=d ... C%20Mesbah

This paper may be up your alley too (published this past January):

https://www.sae.org/publications/techni ... 3-01-0735/

The only F1 related one:

https://www.sae.org/publications/techni ... 1-01-0961/

Effects of Domain Boundary Conditions on the CFD Prediction of Flow over an Isolated Tire Model

Abstract

Tire modeling has been an area of major research in automotive industries as the tires cause approximately 25% of vehicle drag. With the fast-paced growth of computational resources, Computational Fluid Dynamics (CFD) has evolved as an effective tool for aerodynamic design and development in the automotive industry. One of the main challenges in the simulation of the aerodynamics of tires is the lack of a detailed and accurate experimental setup with which to correlate. In this study, the focus is on the prediction of the aerodynamics associated with an isolated rotating Formula 1 tire and brake assembly. Literature has indicated differing mechanisms explaining the dominant features such as the wake structures and unsteadiness. Limited work has been published on the aerodynamics of a realistic tire geometry with specific emphasis on advanced turbulence closures such as the Detached Eddy Simulation (DES). In this study, we take a deeper look at the wake characteristics of an isolated tire model using CFD and compare it to the Particle Image Velocimetry (PIV) data on a Formula 1 tire model tested by Stanford University. The effects of domain size on the aero characteristics of the tire will be studied to provide a deeper insight into the influence of different boundary conditions at the domain walls. The impact on the characteristics and unsteady motion of the wake structure of the tire model is presented.