Optimizing the aerodynamic performance of archimedes spiral wind turbines: A parametric study on blade angle and length at constant radius

• Parametric variations in blade angle and length were investigated to identify the optimal ASWT configuration. • 36 design models were evaluated using CFD simulations to determine configurations with the highest power coefficient ( C P ). • The optimal design (SM-23) achieved a 14.67% increase in C P over the reference model. • Peak aerodynamic efficiency was observed within a TSR range of 1.5–2 across most tested configurations. • Blade geometry optimization significantly enhances ASWT performance in urban wind environments. This study explores the effect of variations in blade angle (α) and length at a fixed radius (r) on the aerodynamic performance of Archimedes Spiral Wind Turbines (ASWT), with the aim of enhancing their adaptability and efficiency in variable urban wind conditions. To identify the most effective blade design approach, two parametric methodologies were evaluated within the same dimensional range to maximize the power coefficient ( C P ), where (i) an unconstrained parametric study (FM), in which both blade angle and blade length (L) were allowed to vary simultaneously without geometric constraints, and (ii) a geometrically constrained parametric study (SM), in which blade length (L) was held constant while blade angle was adjusted. The results revealed that the SM approach outperformed the FM approach, with a 6.7% increase in C P over the reference model (0.22), demonstrating higher aerodynamic efficiency, greater flexibility in blade angle and length adjustment, and deeper insights into the effects of geometric parameters. Based on this methodology, 36 ASWT blade models were designed using SolidWorks 2020 and analyzed using 3D simulations conducted in ANSYS CFX-2020 R2. The power coefficient ( C P ), relative to the tip speed ratio (TSR), was employed as the performance metric to assess the performance of each model. The analysis identified SM-23 as the most efficient model, with an L of 140 mm and a blade angle of 80 0 . At a wind speed of 10 m/s, this model achieved a maximum C P of 0.265, representing a 14.67% improvement over the reference model. These findings highlight the potential of refined ASWT blade designs to enhance performance and support sustainable urban wind energy solutions.

Authors

Institutions

Publication Details

Journal
Results in Engineering
Published
2025-06-13
DOI
https://doi.org/10.1016/j.rineng.2025.105785
Citations
7
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
34.95

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing the aerodynamic performance of archimedes spiral wind turbines: A parametric study on blade angle and length at constant radius

Chung Hong Tan, Ahmed Essa Faisal, Jassinnee Milano, Chin Wai Lim et al.
7 citations
Results in Engineering
Wind Energy Research and Development
34.95
article

Optimizing the aerodynamic performance of archimedes spiral wind turbines: A parametric study on blade angle and length at constant radius

Chung Hong Tan, Ahmed Essa Faisal, Jassinnee Milano, Chin Wai Lim, Balasem Abdulameer Jabbar Al-Quraishi
article en
7 citations

Abstract

• Parametric variations in blade angle and length were investigated to identify the optimal ASWT configuration. • 36 design models were evaluated using CFD simulations to determine configurations with the highest power coefficient ( C P ). • The optimal design (SM-23) achieved a 14.67% increase in C P over the reference model. • Peak aerodynamic efficiency was observed within a TSR range of 1.5–2 across most tested configurations. • Blade geometry optimization significantly enhances ASWT performance in urban wind environments. This study explores the effect of variations in blade angle (α) and length at a fixed radius (r) on the aerodynamic performance of Archimedes Spiral Wind Turbines (ASWT), with the aim of enhancing their adaptability and efficiency in variable urban wind conditions. To identify the most effective blade design approach, two parametric methodologies were evaluated within the same dimensional range to maximize the power coefficient ( C P ), where (i) an unconstrained parametric study (FM), in which both blade angle and blade length (L) were allowed to vary simultaneously without geometric constraints, and (ii) a geometrically constrained parametric study (SM), in which blade length (L) was held constant while blade angle was adjusted. The results revealed that the SM approach outperformed the FM approach, with a 6.7% increase in C P over the reference model (0.22), demonstrating higher aerodynamic efficiency, greater flexibility in blade angle and length adjustment, and deeper insights into the effects of geometric parameters. Based on this methodology, 36 ASWT blade models were designed using SolidWorks 2020 and analyzed using 3D simulations conducted in ANSYS CFX-2020 R2. The power coefficient ( C P ), relative to the tip speed ratio (TSR), was employed as the performance metric to assess the performance of each model. The analysis identified SM-23 as the most efficient model, with an L of 140 mm and a blade angle of 80 0 . At a wind speed of 10 m/s, this model achieved a maximum C P of 0.265, representing a 14.67% improvement over the reference model. These findings highlight the potential of refined ASWT blade designs to enhance performance and support sustainable urban wind energy solutions.

Results in EngineeringVol. 27
University of Al-Qadisiyah (IQ), Al-Furat Al-Awsat Technical University (IQ), Universiti Tenaga Nasional (MY), Tenaga Nasional Berhad (Malaysia) (MY)
Universiti Tenaga Nasional
Affordable and clean energy
Openalex Percentile: Top 0%
Wind Energy Research and Development
34.95
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.