Difference between revisions of "Computational Fluid Dynamics"
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Revision as of 18:33, 24 August 2020
Computational Fluid Dynamics (CFD) is the method by which fluid flow can be simulated using computational methods. It generally involves discretizing the Navier-Stokes equations (partial differential equations that govern fluid motion) into series of algebraic equations that can then be solved.
In a Formula SAE/Student context, CFD is predominantly used for two purposes; simulating an external aerodynamics package (including radiators and other cooling components) and simulating the intake and exhaust systems of internal combustion engines. While either problem have their unique challenges, the process of running CFD for their simulation it quite similar.
As with all computational simulations (CFD, structural simulation, track time simulators, etc.), they break down into series of steps which introduce their own sources of error (there will be error and you must account for it):
- Idealization
- Discretization
- Solution
Idealization are the physical assumptions made to come to some mathematical model. Discretization is the process of breaking up that mathematical model into a series of smaller, simpler problems. Solution is the process of actually solving those smaller problems. The errors associated with each step are modeling errors, discretization errors, and numerical errors, respectively (though the latter two are often grouped together). While this wiki page won't go into these steps in detail (it's worthy of a textbook), it's important to understand where errors come from and (thus) how to mitigate/fix them.
Contents
Modeling (Idealization)
Turbulence Modeling
Other Physical Assumptions
Discretization
Finite Volume is by far the most popular discretization method for fluid problems, though Finite Difference and Finite Element methods are equally applicable.
Beyond discretization method, geometric and fluid feature resolution are very important.
is important near the wall
Solution
Description of order of accuracy considerations and convergence criteria
Solvers
ANSYS, Star CCM, OpenFOAM, SimScale (which is just cloud based OpenFOAM).
Fun Acronyms
- Colorful Fluid Dynamics
- Can't Fit the data.
- Conspiracy Fraud Deceit
probably should have notes on meshing, model selection (suggested and why), analysis/postprocessing