Applications of Genetic Algorithms in Realistic Wind Field Simulations

  • R. Montenegro
  • G. Montero
  • E. Rodríguez
  • J. M. Escobar
  • J. M. González-Yuste
Part of the Studies in Computational Intelligence book series (SCI, volume 102)

Mass consistent models have been widely use in 3-D wind modelling by finite element method. We have used a method for constructing tetrahedral meshes which are simultaneously adapted to the terrain orography and the roughness length by using a refinement/derefinement process in a 2-D mesh corresponding to the terrain surface, following the technique proposed in [14,15,18]. In this 2-D mesh we include a local refinement around several points which are previously defined by the user. Besides, we develop a technique for adapting the mesh to any contour that has an important role in the simulation, like shorelines or roughness length contours [3,4], and we refine the mesh locally for improving the numerical solution with the procedure proposed in [6].

This wind model introduces new aspects on that proposed in [16, 19, 20]. The characterization of the atmospheric stability is carried out by means of the experimental measures of the intensities of turbulence. On the other hand, since several measures are often available at a same vertical line, we have constructed a least square optimization of such measures for developing a vertical profile of wind velocities from an optimum friction velocity. Besides, the main parameters governing the model are estimated using genetic algorithms with a parallel implementation [12,20,26]. In order to test the model, some numerical experiments are presented, comparing the results with realistic measures.


Genetic Algorithm Control Point Wind Velocity Turbulence Intensity Planetary Boundary Layer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • R. Montenegro
    • 1
  • G. Montero
    • 1
  • E. Rodríguez
    • 1
  • J. M. Escobar
    • 1
  • J. M. González-Yuste
    • 1
  1. 1.Institute for Intelligent Systems and Numerical Applications in EngineeringUniversity of Las Palmas de Gran CanariaLas Palmas de Gran CanariaSpain

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