scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Comparison between 2.5-D and 3-D realistic models for wind field adjustment

TL;DR: In this paper, a 2.5D and 3D model for wind field simulation by the finite element method is presented, which is based on a triangular mesh adapted to the terrain topography and roughness length.
About: This article is published in Journal of Wind Engineering and Industrial Aerodynamics.The article was published on 2010-10-01 and is currently open access. It has received 25 citations till now. The article focuses on the topics: Roughness length & Wind profile power law.
Figures (13)
Citations
More filters
Journal ArticleDOI
01 Jan 2013-Energy
TL;DR: In this article, a three-dimensional finite element model for the pollutant dispersion is presented, where the first stage consists on the construction of an adaptive tetrahedral mesh of a rectangular region bounded in its lower part by the terrain and in its upper part by a horizontal plane.

26 citations


Cites background or methods from "Comparison between 2.5-D and 3-D re..."

  • ...Several two-dimensional [27] and three-dimensional [28, 29, 30] adaptive finite element solutions have been developed by the authors....

    [...]

  • ...Once the tetrahedral mesh is constructed, we consider a mass-consistent model [28, 29, 30] to compute a wind field u in the three-dimensional domain Ω, with a boundary Γ = Γa ∪Γb, that verifies the continuity equation (mass conservation) for constant density and the impermeability condition on the terrain Γa,...

    [...]

Journal ArticleDOI
TL;DR: A new method for wind field forecasting over complex terrain using the predictions of the HARMONIE meso-scale model as the input data for an adaptive finite element mass-consistent wind model with a minimal user intervention.
Abstract: In this paper, we introduce a new method for wind field forecasting over complex terrain. The main idea is to use the predictions of the HARMONIE meso-scale model as the input data for an adaptive finite element mass-consistent wind model. The HARMONIE results (obtained with a maximum resolution of about 1 km) are refined in a local scale (about a few metres). An interface between both models is implemented in such a way that the initial wind field is obtained by a suitable interpolation of the HARMONIE results. Genetic algorithms are used to calibrate some parameters of the local wind field model in accordance to the HARMONIE data. In addition, measured data are considered to improve the reliability of the simulations. An automatic tetrahedral mesh generator, based on the meccano method, is applied to adapt the discretization to complex terrains. The main characteristic of the framework is a minimal user intervention. The final goal is to validate our model in several realistic applications on Gran Canaria island, Spain, with some experimental data obtained by the AEMET in their meteorological stations. The source code of the mass-consistent wind model is available online at http://www.dca.iusiani.ulpgc.es/Wind3D/ .

18 citations


Cites methods from "Comparison between 2.5-D and 3-D re..."

  • ...Once the tetrahedral mesh is constructed, we consider a mass-consistent model (MONTERO et al. 1998, 2005; FERRAGUT et al. 2010) to compute a wind field u in the three-dimensional domain X, with a boundary C 1⁄4 Ca [ Cb, that verifies the continuity equation and the impermeability condition on the terrain Ca, Vol....

    [...]

Patent
24 Oct 2012
TL;DR: In this paper, the authors present systems and methods for estimating economic losses from wind storms, including estimating roughness length of an area surrounding a structure, estimating local wind speed at a structure and estimating wind pressure on a structure.
Abstract: The present invention relates to systems and methods for estimating economic losses from wind storms. Accordingly, provided herein are methods estimating roughness length of an area surrounding a structure, methods calculating local wind speed at a structure, methods of estimating wind pressure on a structure, and methods of calculating the insurability of a structure. Also provided are systems and computer-readable storage media configured for performing the disclosed methods.

16 citations

Journal ArticleDOI
TL;DR: In this paper, a multimesh adaptive scheme for convection-diffusion-reaction problems for a large number of components is presented, where the evaluation of the nonreactive part for each component and the reaction at each node constitute independent tasks.
Abstract: SUMMARY A multimesh adaptive scheme for convection–diffusion–reaction problems for a large number of components is presented. The problem is solved by splitting transport and reaction processes. This way, the evaluation of the nonreactive part for each component and the reaction at each node constitute independent tasks. This allows to discretize each component of the solution on a distinct computational mesh, adapted on the basis of its error indicator. The standard single-mesh strategy is used for comparison. Simulations of a point emission in a 3D domain are presented. Low remeshing periods of the adaptive scheme are found to be optimal, in terms of computational cost and accuracy, for the nonreactive problem. Examples with several reaction terms, with an increase of the complexity, are then presented. Results show that the accuracy of single-mesh and multimesh strategies are similar. Instead, the computational cost of the multimesh strategy is lower than the single-mesh in the majority of the examples; this process is controlled by the stiff behavior of the reactive term. The problem size of the multimesh scheme is much lower, and therefore, larger spatial discretizations can be simulated for a given available memory. The efficiency of the multimesh strategy increases with the number of species and the number of species that develop a plume. Finally, an example of a punctual emission considering realistic values of the initial concentrations and using the Community Multiscale Air Quality-CBO5 reaction model, which involves 62 components, is presented; the small-scale structure of the different nitrogen components near the emitter is captured. Copyright © 2013 John Wiley & Sons, Ltd.

11 citations


Cites background from "Comparison between 2.5-D and 3-D re..."

  • ...The extension to complex geometries (topography and build elements) [16], real wind fields [17], and more realistic stack emissions models [16,18] is left for future developments....

    [...]

Journal ArticleDOI
TL;DR: An easy-to-implement model, inspired in the ‘persistence’ model used in wind forecasting, that can be used as reference in wind spatial studies is proposed, allowing the comparison among different studies.

10 citations

References
More filters
01 Jan 2006
TL;DR: In this article, the authors present a model for the chemistry of the Troposphere of the atmosphere and describe the properties of the Atmospheric Aqueous phase of single aerosol particles.
Abstract: 1 The Atmosphere. 2 Atmospheric Trace Constituents. 3 Chemical Kinetics. 4 Atmospheric Radiation and Photochemistry. 5 Chemistry of the Stratosphere. 6 Chemistry of the Troposphere. 7 Chemistry of the Atmospheric Aqueous Phase. 8 Properties of the Atmospheric Aerosol. 9 Dynamics of Single Aerosol Particles. 10 Thermodynamics of Aerosols. 11 Nucleation. 12 Mass Transfer Aspects of Atmospheric Chemistry. 13 Dynamics of Aerosol Populations. 14 Organic Atmospheric Aerosols. 15 Interaction of Aerosols with Radiation. 16 Meteorology of the Local Scale. 17 Cloud Physics. 18 Atmospheric Diffusion. 19 Dry Deposition. 20 Wet Deposition. 21 General Circulation of the Atmosphere. 22 Global Cycles: Sulfur and Carbon. 23 Climate and Chemical Composition of the Atmosphere. 24 Aerosols and Climate. 25 Atmospheric Chemical Transport Models. 26 Statistical Models.

11,157 citations

Book
01 Jan 1997
TL;DR: In this paper, the authors present a model for the chemistry of the Troposphere of the atmosphere and describe the properties of the Atmospheric Aqueous phase of single aerosol particles.
Abstract: 1 The Atmosphere. 2 Atmospheric Trace Constituents. 3 Chemical Kinetics. 4 Atmospheric Radiation and Photochemistry. 5 Chemistry of the Stratosphere. 6 Chemistry of the Troposphere. 7 Chemistry of the Atmospheric Aqueous Phase. 8 Properties of the Atmospheric Aerosol. 9 Dynamics of Single Aerosol Particles. 10 Thermodynamics of Aerosols. 11 Nucleation. 12 Mass Transfer Aspects of Atmospheric Chemistry. 13 Dynamics of Aerosol Populations. 14 Organic Atmospheric Aerosols. 15 Interaction of Aerosols with Radiation. 16 Meteorology of the Local Scale. 17 Cloud Physics. 18 Atmospheric Diffusion. 19 Dry Deposition. 20 Wet Deposition. 21 General Circulation of the Atmosphere. 22 Global Cycles: Sulfur and Carbon. 23 Climate and Chemical Composition of the Atmosphere. 24 Aerosols and Climate. 25 Atmospheric Chemical Transport Models. 26 Statistical Models.

9,021 citations


"Comparison between 2.5-D and 3-D re..." refers background or methods in this paper

  • ...It considers the following classes for stability: A (extremely unstable), B (moderately unstable), C (slightly unstable) , D (neutral), E (slightly stable) and F (moderately stable) [34]....

    [...]

  • ...Following the Pasquill model for the atmospheric stability [34] and de fining new ranges of turbulence intensity, a new table for Pasquill stability cl assification is built....

    [...]

Book
01 Jan 1997
TL;DR: The Oxford University Press and the Institute of Physics have joined forces to create a major reference publication devoted to EC fundamentals, models, algorithms and applications, intended to become the standard reference resource for the evolutionary computation community.
Abstract: From the Publisher: Many scientists and engineers now use the paradigms of evolutionary computation (genetic agorithms, evolution strategies, evolutionary programming, genetic programming, classifier systems, and combinations or hybrids thereof) to tackle problems that are either intractable or unrealistically time consuming to solve through traditional computational strategies Recently there have been vigorous initiatives to promote cross-fertilization between the EC paradigms, and also to combine these paradigms with other approaches such as neural networks to create hybrid systems with enhanced capabilities To address the need for speedy dissemination of new ideas in these fields, and also to assist in cross-disciplinary communications and understanding, Oxford University Press and the Institute of Physics have joined forces to create a major reference publication devoted to EC fundamentals, models, algorithms and applications This work is intended to become the standard reference resource for the evolutionary computation community The Handbook of Evolutionary Computation will be available in loose-leaf print form, as well as in an electronic version that combines both CD-ROM and on-line (World Wide Web) acess to its contents Regularly published supplements will be available on a subscription basis

2,461 citations


"Comparison between 2.5-D and 3-D re..." refers methods in this paper

  • ...Genetic algorithms (GAs) are optimisation tools based on th e natural evolution mechanism [2,17,36]....

    [...]

Book
01 Jan 1984
TL;DR: The 3rd edition of Mesoscale Meteorological Modeling as mentioned in this paper is a fully revised resource for researchers and practitioners in the growing field of meteorological modeling at the mesoscale Pielke has enhanced the new edition by quantifying model capability by a detailed evaluation of the assumptions of parameterization and error propagation.
Abstract: The 3rd edition of Mesoscale Meteorological Modeling is a fully revised resource for researchers and practitioners in the growing field of meteorological modeling at the mesoscale Pielke has enhanced the new edition by quantifying model capability (uncertainty) by a detailed evaluation of the assumptions of parameterization and error propagation Mesoscale models are applied in a wide variety of studies, including weather prediction, regional and local climate assessments, and air pollution investigations Features: broad expansion of the concepts of parameterization and parameterization methodology; addition of new modeling approaches, including modeling summaries and summaries of data sets; and all-new section on dynamic downscaling

1,304 citations


"Comparison between 2.5-D and 3-D re..." refers methods in this paper

  • ...Diagnostic models are not used to make forecasts through int egrating conservative relations [30]....

    [...]

Book
01 Jan 1968
TL;DR: In this article, the authors propose the role of systemes gouvernes par des equations hyperboliques ou bien au sens de Petrowsky, and the regularization, approximation, and penalisation.
Abstract: Minimisation de fonctionnelles et problemes aux limites unilateraux - 2. Controle de systemes gouvernes par des aquations aux derivees partielles elliptiques - 3. Controle de systemes gouvernes par des equations aux derivees partielles paraboliques - 4. Controle de systemes gouvernes par des equations hyperboliques ou bien au sens de Petrowsky - 5. Regularisation, approximation et penalisation (Niveau avance)

979 citations


"Comparison between 2.5-D and 3-D re..." refers background in this paper

  • ...Moreover, p roblem (20),(21), has a unique solution [15]....

    [...]

  • ...Using the general optimal control theory [15], and introduc ing the adjoin state, then the problem (21) is characterized by the following three equ ations relatingp , q and u: •...

    [...]

Frequently Asked Questions (14)
Q1. What have the authors contributed in "Comparison between 2.5-d and 3-d realistic models for wind field adjustment " ?

In this paper the authors introduce several advances in the 2. 5-D and 3-D wind models and the authors compare their results on a region located in the Province of Lugo ( Spain ) with realistic data that have been provided by the company Desarrollos Eólicos S. A. ( DESA ). 

However, though such differences are small, further research is needed in order to construct new wind profiles that exactly satisfy all the available measures of wind velocities. However, further considerations should be taken into account in future works for a better performance of the models. For example, a finer map of roughness, a more sophisticated interpolation of wind velocities, a better approximation of the friction coefficient and a greater number of measurement stations well distributed over the studied region will help to reduce the errors of the models. 

In order to obtain an accurate windfield in zones with very steep slopes, the mesh should be adapted to the contour lines, since a change in the direction of edges in the mesh may strongly affect the computed wind. 

Wind models are interesting tools to the study of several problems related to the atmosphere, such as, the effect of wind on structures, pollutant transport [26], fire spreading [19], wind farm location, etc. 

It is evident that, in order to avoid spurious solutions, more than 20 repetitions for parameter setting of each hour should be done. 

The periodic updating of the main parameters of the models has proved to be fundamental for reducing the errors of the computed wind. 

Vi ∥ ∥ ∥ ∥ 2+ α2∫∂ω v2 (20)where ρǫ,i is a suitable smoothing function given for example byρǫ,i(x) = 1ǫ2 ρ( x − xi ǫ )ρ(x) = {Me− 1 1−||x||2 for ||x|| < 10 for ||x|| ≥ 1for a small ǫ and M such that ∫ρǫ,i(x)dx = 1The optimal control problem to be solved is posed as follow: Find u ∈ V such thatJ(u) = inf v∈V J(v) (21)The solution u of the optimal control problem (21) is characterized by J ′(u) = 0.Using the general optimal control theory [15], and introducing the adjoin state, then the problem (21) is characterized by the following three equations relating p , q and u:• ∫ω a∇p(u) · ∇ϕ+1α∫∂ω qϕ = −∫ω b∇t̂ · ∇ϕ ∀ϕ (22)• ∫ω a∇q(u) · ∇ψ− N ∑i=1∫ω ρǫ,i(m∇p(u) + n∇t̂− Vi)m · ∇ψ = 0 ∀ψ (23)•u = − 1α q on ∂ω (24)There exist a unique solution of the problem (9). 

Once the authors have interpolated the height and the roughness length in the nodes of these refined two-dimensional mesh, the authors use the derefinement algorithm [9,31] described in section 5.1 with εh = 10m and εr = 0.01m, keeping in any case the nodes located inside the six circles. 

The relative simplicity of diagnostic models makes them attractive from the practical point of view, since they do not require many input data and may be easily used. 

The use of their refinement/derefinement process in the 2-D mesh corresponding to the terrain surface allows us to obtain meshes that are accurately adapted to different functions as well as are locally refined around several points. 

The intensity of turbulence i is defined as the square root of the sum of variances σ21 , σ 2 2, σ 2 3 , of the three components of the velocity U 0 1 , U 0 2 , U 0 3 ,respectively, divided by the average wind velocity that has been measured,i =√σ21 + σ 2 2 + σ 2 3||U0|| (51)However, only measures of speed variations are often available but not of the wind direction. 

The authors have used a technique for constructing tetrahedral meshes which are simultaneously adapted to the terrain orography and the roughness length. 

For ε → 1, the importance of the horizontal distance from each point to the measurement stations is greater, while ε → 0 signifies more importance of the height difference between each point and the measurement stations. 

In addition, since several measures are often available at the same vertical line, the authors have constructed a least square adjustment of such measures for developing a vertical profile of wind velocities from an optimum friction velocity.