Genetic algorithms for an improved parameter estimation with local refinement of tetrahedral meshes in a wind model

Authors:
G. Montero;E. Rodríguez;R. Montenegro;J. M. Escobar;J. M. González-Yuste
Affiliations:
University Institute of Intelligent Systems and Numerical Applications in Engineering, University of Las Palmas de Gran Canaria, Campus Universitario de Tafira, 35017 Las Palmas de Gran Canaria, S ...;University Institute of Intelligent Systems and Numerical Applications in Engineering, University of Las Palmas de Gran Canaria, Campus Universitario de Tafira, 35017 Las Palmas de Gran Canaria, S ...;University Institute of Intelligent Systems and Numerical Applications in Engineering, University of Las Palmas de Gran Canaria, Campus Universitario de Tafira, 35017 Las Palmas de Gran Canaria, S ...;University Institute of Intelligent Systems and Numerical Applications in Engineering, University of Las Palmas de Gran Canaria, Campus Universitario de Tafira, 35017 Las Palmas de Gran Canaria, S ...;University Institute of Intelligent Systems and Numerical Applications in Engineering, University of Las Palmas de Gran Canaria, Campus Universitario de Tafira, 35017 Las Palmas de Gran Canaria, S ...
Venue:
Advances in Engineering Software - Special issue on evolutionary optimization of engineering problems
Year:
2005

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Abstract

The efficiency of a mass-consistent model for wind field adjustment depends on several parameters that arise in various stages of the process. On one hand, those involved in the construction of the initial wind field using horizontal interpolation and vertical extrapolation of the wind measures registered at meteorological stations. On the other hand, the stability parameter which allows from a strictly horizontal wind adjustment to a pure vertical one. In general, the values of all of these parameters are based on empirical laws. The main goal of this work is the estimation of these parameters using genetic algorithms, such that some of the wind velocities observed at the measurement station are regenerated as accurately as possible by the model. In addition, we study the effect of the mesh refinement on the parameter estimation in several numerical experiments.