What is Computational Fluid Dynamics (CFD)?

Introduction to CFD simulation

Computational fluid dynamics, also known as CFD, is a scientific discipline that uses numerical tools to model, simulate and analyze the behavior of fluids (liquids and gases) in a given environment. This discipline is now indispensable to industry, enabling engineers to predict, for example, the airflow around an aircraft, the circulation of water in a hydroelectric dam, or the dispersion of pollutants in the atmosphere, without having to build costly physical prototypes (or fewer of them).

What are the different steps of a CFD simulation?

Numerical simulation involves several key phases:

1. Modeling the physical domain
   A geometry representing the system under study is created: channel, aircraft wing, heat exchanger, etc.
2. Meshing (for most software packages… but this depends on the numerical method used!)
   The domain is divided into small elementary volumes called cells. The mesh size must be adapted to the characteristics of the flow being studied (more or less fine areas, compromise between accuracy and computational time).
3. Choice of physical model and equations
   CFD is primarily based on the Navier-Stokes equations, which describe the fundamental laws of conservation of mass and momentum. Additional physical models can be added to describe turbulence, heat transfer, multiphase flows (liquids/gases/granulars, etc.).
4. Boundary conditions and physical parameters
   Inlet temperature, flow velocity, pressure, roughness… all parameters must be carefully defined to obtain a model that adequately represents the problem being studied.
5. Numerical solution
   A CFD solver (such as those available in ANSYS Fluent or OpenFOAM software) is used to numerically solve the equations on the mesh and obtain a converged solution to the problem
6. Post-processing
   After checking the convergence and validity of the solution obtained, the results are analyzed by extracting physical quantities (temperature profiles, velocity profiles, averaged, minimum, and maximum quantities over volumes, surfaces, temporal variations, etc.) or visualizations (streamlines, temperature fields, pressure fields, etc.) in order to draw useful conclusions.

What are the advantages of CFD simulation over physical models?

• Increased accuracy in areas that are difficult to access or even dangerous.
• Drastic reduction in the number of bench tests.
• Ability to perform rapid iterations and explore extreme scenarios.
• Simulation of real phenomena under realistic conditions (no similarity effects, for example).
• Characterization of flow parameters (velocities, pressure, temperature, etc.) at any point in space and time—unlike experimental sensors (which are point-based or even linear).

But be careful! CFD simulation and physical models are not antagonistic but complementary approaches, particularly for the most complex problems.

Limitations and best practices

Although powerful, CFD is not without limitations. It is highly dependent on:

• The definition of the problem,
• The modeling and simplification of the geometry,
• The quality of the mesh,
• The choice of appropriate physical models (turbulence, radiation, multiphase, etc.) and numerical settings.
• Knowledge and choice of boundary conditions
• Available computing power
• Analysis and interpretation of results

It is therefore clear that validating results using experimental data or simplified test cases is essential to ensure their reliability. And as the saying goes, the problem often lies between the chair and the computer!

In summary

CFD simulation, or Computational Fluid Dynamics, is a scientific and industrial tool that has become indispensable, capable of transforming the way we design, test, and optimize systems involving fluids (liquids or gases, i.e., almost all of them!). Thanks to this discipline, it is possible to anticipate physical behavior, accelerate innovation, and reduce the environmental footprint of projects.