3-D CFD and response surface method for optimizing helical blade vertical axis wind turbines

The Helical- Blade- Vertical- Axis- Wind- Turbine (3-HB-VAWT) has a relatively uniform variation of generated power with its tip speed ratio (TSR) due to its special blade structure. Its required lower self-starting torque also justifies its application in low wind speed areas. By obtaining 3-D CFD (Computational Fluid Dynamic) results and by the use of these data as inputs to the Response Surface Method (RSM), the design/optimization of helical blade VAWT is performed for the first time in this research. As 3-D CFD simulations were very time consuming, RSM was applied due its smaller required number of CFD runs. Furthermore, an important feature of RSM is the ability to perform optimization in all possible points of decision variables in the allowed interval, which is a great advantage for this method. The objective-function ( C p − a v e ) and decision variables (blade- airfoil- chord, the angle- of- helix, and the blade- tip speed- ratio) after extensive 3-D CFD runs finally were selected. At the optimum point, 0.45 m, 30 ∘ , and 1.41 were obtained for turbine- blade- chord, angle- of- helix, and tip- speed- ratio, respectively. Also, at the optimum point, the objective-function ( C p − a v e ) was obtained 0.182, which showed 212% improvement in comparison with the ( C p − a v e ) max = 0.058 for the referenced turbine with TSR=1.77. Finally, 0.55% difference between the average-power-coefficients predicted by the response surface method and the 3-D CFD confirming test showed the proper procedure of estimation the VAWT power coefficient with assumption of three rigid helical blades.

Authors

Institutions

Publication Details

Journal
Applications in Engineering Science
Published
2026-03-17
DOI
https://doi.org/10.1016/j.apples.2026.100318
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

3-D CFD and response surface method for optimizing helical blade vertical axis wind turbines

Armin Farvizi, Sepehr Sanaye
Applications in Engineering Science
Wind Energy Research and Development
article

3-D CFD and response surface method for optimizing helical blade vertical axis wind turbines

Armin Farvizi, Sepehr Sanaye
article en

Abstract

The Helical- Blade- Vertical- Axis- Wind- Turbine (3-HB-VAWT) has a relatively uniform variation of generated power with its tip speed ratio (TSR) due to its special blade structure. Its required lower self-starting torque also justifies its application in low wind speed areas. By obtaining 3-D CFD (Computational Fluid Dynamic) results and by the use of these data as inputs to the Response Surface Method (RSM), the design/optimization of helical blade VAWT is performed for the first time in this research. As 3-D CFD simulations were very time consuming, RSM was applied due its smaller required number of CFD runs. Furthermore, an important feature of RSM is the ability to perform optimization in all possible points of decision variables in the allowed interval, which is a great advantage for this method. The objective-function ( C p − a v e ) and decision variables (blade- airfoil- chord, the angle- of- helix, and the blade- tip speed- ratio) after extensive 3-D CFD runs finally were selected. At the optimum point, 0.45 m, 30 ∘ , and 1.41 were obtained for turbine- blade- chord, angle- of- helix, and tip- speed- ratio, respectively. Also, at the optimum point, the objective-function ( C p − a v e ) was obtained 0.182, which showed 212% improvement in comparison with the ( C p − a v e ) max = 0.058 for the referenced turbine with TSR=1.77. Finally, 0.55% difference between the average-power-coefficients predicted by the response surface method and the 3-D CFD confirming test showed the proper procedure of estimation the VAWT power coefficient with assumption of three rigid helical blades.

Applications in Engineering ScienceVol. 26
Iran University of Science and Technology (IR)
Affordable and clean energy
Openalex Percentile: Top 17%
Wind Energy Research and Development
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.