Computational Modeling of Turbulence
ME 60101/ 3 Cr.
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.
Primary Track: Fluid & Thermal Sciences
- Available Online: No
- Credit by Exam: No
- Laptop Required: No
Turbulent Flows, Pope, McGraw-Hill, any edition is acceptable
- Build up a sound background in the mathematical, physical, and statistical description of turbulence
- Apply Komogorov theory to quantitatively predict turbulence scales
- Derive governing equations for kinetic energy, vorticity, pressure, etc. from Navier-Stokes equation and apply them to non-complicated turbulence
- Apply major modeling tools to turbulence computation at different Re numbers.
- 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
- Statistical description of Turbulence
- Scales of turbulence motion
- Mean and filtered equations
- Direct numerical simulation of turbulence
- LES modeling