Turbulence demands modeling just like any other equation in computational fluid dynamics (CFD). As the CFD engineer, you need to describe boundary conditions for your turbulence equations. This article describes how to define boundary conditions for turbulence and provides typical values for normal simulations.
Turbulence does tricky things near walls. Boundary layers and laminar sublayers compact interesting flow patterns into a very small space. Small it may be, but experience proved we cannot ignore it. The boundary layer forms on the body, which is our object of interest, arguably the most critical region. Turbulence is most critical near the wall, and we need to consider near wall effects.
How we address turbulence is the defining feature of modern computational fluid dynamics (CFD). No modern computer has the power to directly compute the full details of turbulence (as of 2019). Instead, we make approximations and develop empirical models. What type of approximation, and which models should you select?
The heart of any CFD program is an extremely efficient linear algebra solver. But CFD equations are non-linear. How do we stretch the limits of linear algebra to accommodate non-linear CFD equations? How do we take the mathematics from one cell and apply them to millions of cells?
CFD convergence is not an exact science. The CFD engineer relies on three tools to judge when a simulation finishes: monitors, flow patterns, and residuals. But none of these tools work 100% of the time. The well-trained engineer understands how to use these tools and how to combine them into a cohesive picture and reliably judge a converged CFD simulation.
The core of all calculus problems require us to consider something infinitely small. Ask a computer to ponder the concept of infinity and watch its circuits fry. If we want to solve the equations of computational fluid dynamics (CFD), we need a way to fake calculus. This impacts the stability, the mesh quality, and the ultimate simulation quality. Enter interpolation equations.