LINCOM wind flow model: application to complex terrain with thermal stratification

2001 ◽  
Vol 26 (10) ◽  
pp. 839-842 ◽  
Author(s):  
F. Dunkerley ◽  
J. Moreno ◽  
T. Mikkelsen ◽  
I.H. Griffiths
Keyword(s):  
Complex Terrain ◽  
Thermal Stratification ◽  
Flow Model ◽  
Wind Flow ◽  
Model Application

Extension of the Fast Spectral LINCOM Model to Flow over Complex Terrain with Thermal Stratification

2006 ◽  
pp. 701-702
Author(s):  
F. N. Dunkerley ◽  
J. Moreno Santabarbara ◽  
T. Mikkelsen ◽  
I. H. Griffiths
Keyword(s):  
Complex Terrain ◽  
Thermal Stratification

Wind speed modeling over complex terrain with the artificial neural network in the measure-correlate-predict technique: A case study of Malaysia

2021 ◽  
pp. 0309524X2110558
Author(s):  
Yong Kim Hwang ◽  
Mohd Zamri Ibrahim ◽  
Marzuki Ismail ◽  
Ali Najah Ahmed ◽  
Aliashim Albani
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Spatial Modeling ◽  
Complex Terrain ◽  
Simulated Data ◽  
Wind Flow ◽  
Acceptable Accuracy ◽  
Network Measure ◽  
Artificial Neural

This study aimed to create a Malaysian wind map of greater accuracy. Compared to a previous wind map, spatial modeling input was increased. The Genetic Algorithm-optimized Artificial Neural Network Measure–Correlate–Predict method was used to impute missing data, and managed to control over- or under-prediction issues. The established wind map was made more reliable by including surface roughness to simulate wind flow over complex terrain. Validation revealed that the current wind map is 33.833% more accurate than the previous wind map. Furthermore, the correlation coefficient between wind map-simulated data and observed data was high as 0.835. In conclusion, the new and improved wind map for Malaysia simulates data with acceptable accuracy.

Implementation Issues in 3D Wind Flow Predictions Over Complex Terrain

2006 ◽  
Vol 128 (4) ◽  
pp. 539-553 ◽  
Author(s):  
John Prospathopoulos ◽  
Spyros G. Voutsinas
Keyword(s):  
Wind Energy ◽  
Boundary Conditions ◽  
Complex Terrain ◽  
Flow Direction ◽  
Region Of Interest ◽  
Field Measurements ◽  
Navier Stokes ◽  
Wind Flow ◽  
Computational Domain

Practical aspects concerning the use of 3D Navier-Stokes solvers as prediction tools for micro-siting of wind energy installations are considered. Micro-siting is an important issue for a successful application of wind energy in sites of complex terrain. There is a constantly increasing interest in using mean wind flow predictions based on Reynolds averaged Navier-Stokes (RANS) solvers in order to minimize the number of required field measurements. In this connection, certain numerical aspects, such as the extent of the numerical flow domain, the choice of the appropriate inflow boundary conditions, and the grid resolution, can decisively affect the quality of the predictions. In the present paper, these aspects are analyzed with reference to the Askervein hill data base of full scale measurements. The objective of the work is to provide guidelines with respect to the definition of appropriate boundary conditions and the construction of an adequate and effective computational grid when a RANS solver is implemented. In particular, it is concluded that (a) the ground roughness affects the predictions significantly, (b) the computational domain should have an extent permitting the full development of the flow before entering the region of interest, and (c) the quality of the predictions at the local altitude maxima depends on the grid density in the main flow direction.

A Drainage Wind Flow Model

1975 ◽  
Vol 10 (3) ◽  
pp. 177-190
Author(s):  
Edward M. Macomber ◽  
Joe O. Ledbetter
Keyword(s):  
Flow Model ◽  
Wind Flow

Preliminary field test of an urban canyon wind flow model

1990 ◽  
Vol 15 (3-4) ◽  
pp. 325-332 ◽  
Author(s):  
G.T. Johnson ◽  
L.J. Hunter ◽  
A.J. Arnfield
Keyword(s):  
Field Test ◽  
Flow Model ◽  
Urban Canyon ◽  
Wind Flow
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