Turbulence and wind energy

Learn advanced turbulence modeling, with a focus on 1/ CFD 2/ Wind energy systems, that always operate under turbulent conditions.

Program and contents:

1. Reynolds Averaged Navier-Stokes (RANS) approach and models
   We study turbulence modelling for computational fluid dynamics (CFD) by focusing on the RANS approach and models. The RANS approach is indeed closely linked to the statistical theory of turbulence, which is quite relevant. The RANS approach is basically interesting to characterize and gain some understanding on turbulence phenomena. Finally, RANS models are still, today, the preferred choice for engineering studies. After a brief discussion of Reynolds stress equations and  models, the focus is on eddy-viscosity 2-equations models, namely, the k – ε and k –  ω models.
2. Using a problem-based learning approach, studies of the Direct Numerical Simulations (DNS) database of Lee & Moser (2015) will be performed with Matlab.
   
   
3. Stochastic models, especially, in the context of wind energy
4. This second part of the module is focused on the wind energy sciences. Knowing that the wind in the atmospheric boundary layer is always turbulent, the small scale statistics of turbulent flows is reviewed, with a focus on the intermittency phenomena and extreme events like `wind gusts'. The principles of wind energy conversion and the aerodynamics of wind turbines are also presented. The International Electrotechnical Commission (IEC) standards to evaluate power curves and annual energy production of a given wind turbine is introduced. The limitations of this approach are discussed and more accurate stochastic approaches are introduced, which lead for instance to the notion of `Langevin power curves'.
   
   The students will use the statistical computing software R to study various `turbulence experimental databases'.
   

Please check the web page of this module on http://emmanuelplaut.perso.univ-lorraine.fr/twe : it sketches the planning of this module, gives instructions and files, etc...

The RANS approach - the LES approach - Strengths and weaknesses of each approach

The notion of intermittency and extreme events

The RANS approach - the LES approach

Analyze a velocity time series: be able to extract mean and standard deviation values, a PDF of the velocity and of the velocity increments, etc...

Analyze a wind time series: construct the IEC power curve