What are the best practices for modeling airflow around a vehicle with CFD simulation?

Les études se multiplient sur l’impact de la géométrique des jantes et des pneumatiques sur les performances des véhicules de tourisme ou de course. Des fabricants de pneumatiques prennent notamment part à des campagnes de mesures expérimentales impliquant de nombreux acteurs industriels et universitaires.

Make sure you have captured (NOT deleted) the features which might affect airflow. Minor features like small gaps can be ignored, but if the gaps are through and through, it changes results considerably.

Normally the domain space should be of 10-11 car lengths. 3 car lengths ahead of the car and around 7 behind the car. Also the height and breath should be 3 car lengths. This domain space gives enough space to capture the far field effects and does not increase the computational cost.

Utilize AutoCAD 3D modeling in the automotive industry to swiftly adapt to changing trends. The software enables designers to efficiently prototype and modify vehicle components, staying agile in response to evolving automotive trends, such as aerodynamics, electric propulsion, and advanced materials, ensuring designs align with industry innovations.

In fact, it all depends on what you are looking to study. We will not proceed in the same way if we are interested in global phenomena (drag, influence of yaw, side wind effects, etc.), if we are interested in the cooling of the engine compartment or in more complex phenomena, such as stability, unsteady or aeroacoustic effects. Thus, we will not simplify the geometry, obviously, when it has a strong influence on the phenomena studied (notably in terms of noise, wake, evolution of the boundary layer, etc.). For example, we studied the phenomena linked to the wake of antennas, rear-view mirrors or windshield pillars. In this case, it is obvious that we will not neglect them...

Les divers modèles de turbulence utilisés dans les simulations RANS diffèrent par la modélisation du tenseur de Reynolds uiuj . L’utilisation d’équations de transport faisant toujours appara?tre des moments d’ordre supérieurs, il est toujours nécessaire de passer par une étape de modélisation, toutes les quantités ne pouvant être résolues. C’est ce qu’on appelle le problème de fermeture.

Adaptive meshing tailors the cell density to the phenomenon being studied. Finer meshes capture critical details in areas with high gradients or complex flow features, while coarser meshes in less significant regions optimize computational efficiency. This balance ensures accurate results where it matters most, making it a valuable technique in diverse CFD applications like aerodynamics, combustion, and heat transfer.

Here too, the mesh depends on the phenomena studied. If we are interested in the wake and its effects, in terms of stability, influence on the behavior of the vehicle or on following vehicles, or in terms of aeroacoustics, we will emphasize the fineness of the mesh in this region (in creating areas where the mesh is more refined). In fact, anywhere there will be significant velocity gradients. On the wall, we apply a mesh method using prisms (parallelepipeds) in order to take into account changes in the boundary layer without excessively increasing the size of the mesh.

Diverses approches numériques plus ou moins matures sont utilisées pour la résolution instationnaire des écoulements turbulents. Elles diffèrent par leur niveau de précision et par leur co?t. Les méthodes les plus précises sont également les plus co?teuses en temps de calcul donc les moins adaptées à une utilisation industrielle.

To continue with the mesh : Today, a good method is to evolve the prisms towards a polyhedral mesh (rather than tetrahedra) in order to improve the convergence of the calculation and reduce calculation times. This method should be used with caution, and on a sufficiently fine mesh.

In FSAE, our 690cc beast craved every gasp of air it could get. To feed it right, we used CFD, not just a simulator, but a tool to fine-tune its air flow. No more guessing! We mapped its breathing. Walls, though silent, held secrets: the friction zone's tango. We used magic formulas (wall functions) to capture its heat and drag. It wasn't one run and done. We tweaked, simulated, and compared to the engine's real roars until airflow matched perfectly. Those scary limits became allies, sculpting an intake that squeezed every drop of power from our beast. That's CFD's magic: not just showing the flow, but building the perfect stage for it to shine.

The LES method is now becoming accessible and, if possible, it should be preferred over URANS (unsteady RANS) models. We will particularly try to implement it in the case of aeroacoustic studies because it provides a better description of the flow.This method, however, remains quite difficult to implement and may require greater resources and calculation time. But, in the case of studies relating only to global phenomena (drag, etc.), we can make do with RANS (or URANS) methods, using a sufficiently optimized mesh (notably in boundary layer ).

Les premières études aérodynamiques menées sur l’écoulement se développant autour des roues de voitures ont été réalisées au début des années 1970. L’expérience de référence est celle de Fackrell & Harvey [30, 31] qui, à l’époque, fut la seule à considérer une roue en rotation en contact complet avec un sol en translation.

Le nombre entré ici détermine de combien la valeur calculée à gauche de la contrainte doit différer de la valeur de droite afin que la contrainte soit satisfaite. Une contrainte est satisfaite si la relation qui la représente est vraie à l'intérieur d'une petite variation ; la valeur mise dans Précision est cette variation.

Avec une valeur par défaut de 1.0E-6 (=0.000001). Par exemple, une variation de 1.0E-7 autour de A1=0 satisferait une contrainte telle que A1>=0.

Pour indiquer un espace de variation "moins bon", entrez un nombre avec peu de décimales. Un "meilleur" espace de variation est indiquée par une valeur de Précision plus petite, avec plus de décimales. Dans tous les cas il est conseillé de garder la Précision dans le segment [1.0E-4,1.0E-8]

Select appropriate numerical methods and algorithms for time integration, spatial discretization, and linear solvers to ensure stability, accuracy, and efficiency while preventing numerical errors and instabilities. Monitoring solution convergence and validation through residual checks, conservation of mass and momentum, aerodynamic coefficients, and flow patterns is imperative. Adhering to these best practices guarantees robust and reliable CFD simulations for accurate representation of airflow around the vehicle.

Be clear about what questions you're trying to answer, and be aware that CFD may be incorrect. Be careful to ensure your simulation is validated against real-world data, and that you're not venturing too far away from that validated simulation case, i.e., extrapolating to situations that are not similar enough in their geometry, phenomenology, etc. A design change that is predicted to be beneficial in CFD may very well be detrimental in the wind tunnel, especially if you're looking for marginal benefits!

The first thing you have to determine is what you are searching for. If you are doing the calculation in order to optimize the drag, your simplifications, turbulence model and set up can be different that those for a research project or those to optimize the cooling. A research project will be done on a simplified geometry, while a drag optimization calculation will be done with a very detailed geometry.

This discussion needs more time and mental energy to improve design in automotive system. While it's done in spare time while people needs to rest, so don't expect contributions being hundred percent useful to determine expartise