An intercomparison study between RAMS and CRES-Flow-NS models and evaluation with wind tunnel experimental data: Toward improving atmospheric modeling for wind resource assessment

Barranger, Nicolas; Ternisien, Thomas; Kallos, George

doi:10.1016/j.jweia.2015.04.003

Cited by 6 publications

(4 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Despite the significant increase in computing power, the need for solutions on finer resolution scales and the continuous development of more complex physics such as the implementation of higher‐order models for the solution of sub‐grid processes (e.g. Barranger and Kallos, ) requires substantially higher computational resources than those typically available at the desktop level or in small research clusters.…”

Section: Introductionmentioning

confidence: 99%

A novel approach to statistical‐dynamical downscaling for long‐term wind resource predictions

Chávez-Arroyo

Lozano-Galiana

Sanz-Rodrigo

et al. 2017

Meteorological Applications

View full text Add to dashboard Cite

A new method for the long-term prediction of the wind resource based on the concept of statistical-dynamical downscaling is presented. This new approach uses mean sea level pressure maps from global reanalysis data (National Centers for Environmental Prediction Department of Energy Atmospheric Model Intercomparison Project (NCEP-DOE AMIP-II)) and image processing techniques to identify a synthetic reference period which optimally matches the corresponding long-term maps. Four different image processing techniques, averaged into one image similarity error index, are used to evaluate image similarity. A representative set of days is selected by requiring the error index to be minimal. Validation of representativeness in terms of the wind resource for the Iberian domain is performed against 10 years of measured wind data from Navarra (Spain), as well as mesoscale simulations of the Iberian Peninsula. The new approach is shown to outperform not only the industry-standard method but also other recently proposed methods in its capability to achieve mesoscale level representativeness. A particular advantage of the new method is its capability of simultaneously providing a representative period for all potential wind farm sites located within large regional domains without requiring re-running of the method for different candidate sites.

show abstract

Section: Introductionmentioning

confidence: 99%

A novel approach to statistical‐dynamical downscaling for long‐term wind resource predictions

Chávez-Arroyo

Lozano-Galiana

Sanz-Rodrigo

et al. 2017

Meteorological Applications

View full text Add to dashboard Cite

show abstract

“…Theoretical and experimental research tools [2][3][4][5][6][7][8][9][10] were introduced to handle the environmental flow problems. Successful research tools are expected to give accurate information on the near-ground concentrations of air pollutants.…”

Section: Introductionmentioning

confidence: 99%

“…The CFD approach numerically solves the appropriate fluid flow equations governing various processes and events leading to the pollutants dispersion. Successful and frequently done laboratory measurements, supporting the CFD simulations, are those conducted in atmospheric boundary layer wind tunnels facilities (ABLWT) [7][8][9][10]. Such facilities allow accurate physical modeling of real environmental flow within atmospheric boundary layer for specified urban area.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Development and Validation of an in-House CFD Code for Environmental Flow Simulation Using Measurements in Atmospheric Boundary Layer Wind Tunnel

Al-Nahari

El-Dosoky

Abdelghany

et al. 2016

JES. Journal of Engineering Sciences

View full text Add to dashboard Cite

This paper deals with the important issue of the gaseous pollutants dispersion in the environmental flow within urban atmospheres including the products of on-ground agriculture fires. The paper presents an accurate and efficient semi-implicit pressure-based algorithm developed for solving numerically the conservation equations governing weakly compressible turbulent environmental flow of multicomponent fluid. An in-house CFD code has been developed to implement the numerical solution of the present algorithm. The code is an integrated one consisting of three main elements which are the pre-processor, the solver and the post-processor. This in-house CFD code undergoes a standard validation process, using six generic test cases simulating a steadystate environmental flow associated with gas flow from a ground point source under different flow conditions. A prerequisite verification of the code has been considered for successful validation. The detailed standard validation process was performed according to AIAA Guide by comparing the predicted results with measurements especially conducted for the present work in the test section of the Atmospheric Boundary Layer Wind Tunnel facility of Assiut University. The results showed good qualitative and quantitative agreements for the present in-house CFD code with the corresponding flow measurements. These agreements together with the satisfaction of the prerequisite verification insure a satisfactory validation of the present in-house CFD code.

show abstract

Estimation of Wind Energy Potential and Prediction of Wind Power

Shi

Erdem

2017

Wind Energy Engineering

View full text Add to dashboard Cite

An intercomparison study between RAMS and CRES-Flow-NS models and evaluation with wind tunnel experimental data: Toward improving atmospheric modeling for wind resource assessment

Cited by 6 publications

References 56 publications

A novel approach to statistical‐dynamical downscaling for long‐term wind resource predictions

A novel approach to statistical‐dynamical downscaling for long‐term wind resource predictions

Development and Validation of an in-House CFD Code for Environmental Flow Simulation Using Measurements in Atmospheric Boundary Layer Wind Tunnel

Estimation of Wind Energy Potential and Prediction of Wind Power

Contact Info

Product

Resources

About