Purdue School of Engineering and Technology

Purdue School of Engineering and Technology

Computational Modeling of Turbulence

ME 60101 / 3 Cr. (3 Class)

This course consists of three parts: (i) turbulence principles including turbulence concepts, statistical description, and Kolmogorov hypothesis; (ii) major modeling concepts and formulations such as direct numerical simulation (DNS), large eddy numerical simulation (LES), and Reynolds averaged Navier-stokes simulation (RANS); (iii) Projects related to DNS/LES/RANS of turbulence with applications in environment, industry, and biomechanics.

S. B. Pope, Turbulent Flows, McGraw-Hill, New York, 2009 Recommended reference books: H. Tennekes and J. L. Lumley, A FirstCourse in Turbulence, The MIT Press.


Upon completion of the course, students are expected to be able to do the followings

1. Build up a sound background in the mathematical, physical, and statistical description of turbulence

2. Apply Komogorov theory to quantitatively predict turbulence scales   

3. Derive governing equations for kinetic energy, vorticity, pressure, etc. from Navier-Stokes equation and apply them to non-complicated turbulence

4. Apply major modeling tools to turbulence computation at different Re numbers.

5. Numerically analyze turbulence properties for decaying isotropic turbulence with and without rotation, turbulent rectangular jets, biological flows in the presence of turbulence etc. through provided computation output data
  • Introduction to turbulence
  • CFD tools
  • Ansys-Fluent
  • Statistical description of Turbulence
  • Scales of turbulence motion
  • Mean and filtered equations
  • Direct numerical simulation of turbulence
  • LES modeling