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Computational Fluid Dynamics

 

Computational fluid dynamics (CFD) is a branch of the field of fluid mechanics. It addresses the flow of liquid and gases under various conditions. Included among these conditions are the following:

  • Flow with and without heat transfer
  • Laminar, transitional, and turbulent flow regimes
  • Subsonic, transonic, and supersonic regimes
  • Gas/liquid mixtures
  • Incompressible and compressible flow
  • Non-Newtonian fluids

CFD uses numerical methods and algorithms to solve fluid flow problems.

Problem solving is performed in accordance with the following steps:

  • Define the physical geometry of the problem
  • Establish a mesh which fills the volume occupied by the fluid
  • Define the specific fluid and heat transfer (if any) conditions relative to the process for which a solution is desired.
  • Define the boundary conditions by specifying the fluid properties at the boundary
  • Perform the computer simulation for the analysis and flow visualization of the solution.

The interaction between different areas of fluid flow, or the interaction between a fluid and a surface can be predicted using the Navier-Stokes equations. CFD software uses boundary conditions entered by the user to calculate solutions to this set of equations over a series of pre-defined elements into which the model being analyzed has been subdivided. Similarly to the finite element method for stress analysis, computational fluid dynamics results in a solution only as accurate as the number of elements over which calculations have been performed. Hence, the more elements, the more reliable the results are likely to be.

Complex simulations can easily be computed with high-speed computers, resulting in accurate representations of fluid flow in two or three dimensions. Furthermore, certain simplifications can be made to the Navier-Stokes equations in order to facilitate execution of the simulation. Computational fluid dynamics techniques are quite useful in the product design process, since fluid interactions could be predicted with a high degree of accuracy, without going through the task of prototype manufacturing and wind tunnel testing.





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