EconPapers    
Economics at your fingertips  
 

Computational fluid dynamics (CFD) mesh independency techniques for a straight blade vertical axis wind turbine

K.M. Almohammadi, D.B. Ingham, L. Ma and M. Pourkashan

Energy, 2013, vol. 58, issue C, 483-493

Abstract: This paper numerically investigates four methods, namely mesh refinement, General Richardson Extrapolation (GRE), Grid Convergence Index (GCI), and the fitting method, in order to obtain a mesh independent solution for a straight blade vertical axis wind turbine (SB-VAWT) power curve using computational fluid dynamics (CFD). The solution is produced by employing the 2D Unsteady Navier–Stokes equations (URANS) with two turbulence models (Shear Stress Transport (SST) Transitional and ReNormalized Groups (RNG) κ−ɛ models). The commonly applied mesh refinement is found to be computationally expensive and not often practical even for a full 2D model of the turbine. The mesh independent power coefficient produced using the General Richardson Extrapolation method is found to be encouraging. However, the Grid Convergence Index may not be applicable in mesh independency tests due to the oscillatory behaviour of the convergence for the turbine power coefficient. As an alternative, the fitting method shows a good potential for the predicting of the mesh independent power coefficient without the necessity to consider a massive number of meshes.

Keywords: Straight blade vertical axis wind turbine (SB-VAWT); Darrieus turbines; Grid independency; Computational fluid dynamics modelling; Richardson Extrapolation (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (56)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544213005100
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:58:y:2013:i:c:p:483-493

DOI: 10.1016/j.energy.2013.06.012

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:energy:v:58:y:2013:i:c:p:483-493