Optimal design of the blunt trailing-edge wind wheel with a bionic V-riblets structure for H-type vertical axis wind turbines

The unconventional V-riblets structure originated from the shark skin has excellent performance in drag-reduction, and is applied to the suction surface of the airfoil. The blade trailing-edge thickening delays the flow separation, increases the pressure difference, and reduces the roughness sensitivity, but it also causes an increase in drag. To achieve both the optimal drag-reduction and the optimal lift enhancement of H-type vertical axis wind turbines (VAWTs), a new optimization method is developed for the design of the blunt trailing-edge wind wheel with a bionic V-riblets structure. The blunt trailing-edge airfoil is obtained using the coordinate rotation-scaling method, and then its parametric representation is realized by the mean camber and thickness functions. The V-riblets structure is arranged from the flow separation point of the airfoil, and its expression is constructed through the vector and coordinate transformation. The optimizer, based on the particle swarm optimization (PSO) algorithm integrated with the computational fluid dynamics (CFD) method, seeks the solutions maximizing the wind energy utilization, where the airfoil shape control factors, chord length, blunt trailing-edge thickness, V-riblets structure dimensions, wind wheel radius, and blade length are the design variables. The power and flow characteristics of un-optimized and optimized wind wheels are analyzed to further understand the improvement effect of the simultaneous optimization of V-riblets structure and blunt trailing-edge wind wheel. The results show that after the optimization, the maximum instantaneous torque coefficient of every blade increases by 32.8%, the torque coefficient of the wind wheel improves within the azimuth angle range of 62.5%, and the instantaneous torque of three blades and wind wheel improves significantly. The pressure difference of upper and lower surfaces and the wake region of every blade respectively increases and decreases in most upwind regions and partial downwind regions. The shedding vortex strength of the wind wheel obviously reduces during the operating cycle.

Authors

Institutions

Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy
Published
2026-06-26
DOI
https://doi.org/10.1177/09576509261463983
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Optimal design of the blunt trailing-edge wind wheel with a bionic V-riblets structure for H-type vertical axis wind turbines

Xu Zhang, Wei Li, Lengshuang Cui, Yuliang Qi
Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy
Wind Energy Research and Development
article

Optimal design of the blunt trailing-edge wind wheel with a bionic V-riblets structure for H-type vertical axis wind turbines

Xu Zhang, Wei Li, Lengshuang Cui, Yuliang Qi
article en

Abstract

The unconventional V-riblets structure originated from the shark skin has excellent performance in drag-reduction, and is applied to the suction surface of the airfoil. The blade trailing-edge thickening delays the flow separation, increases the pressure difference, and reduces the roughness sensitivity, but it also causes an increase in drag. To achieve both the optimal drag-reduction and the optimal lift enhancement of H-type vertical axis wind turbines (VAWTs), a new optimization method is developed for the design of the blunt trailing-edge wind wheel with a bionic V-riblets structure. The blunt trailing-edge airfoil is obtained using the coordinate rotation-scaling method, and then its parametric representation is realized by the mean camber and thickness functions. The V-riblets structure is arranged from the flow separation point of the airfoil, and its expression is constructed through the vector and coordinate transformation. The optimizer, based on the particle swarm optimization (PSO) algorithm integrated with the computational fluid dynamics (CFD) method, seeks the solutions maximizing the wind energy utilization, where the airfoil shape control factors, chord length, blunt trailing-edge thickness, V-riblets structure dimensions, wind wheel radius, and blade length are the design variables. The power and flow characteristics of un-optimized and optimized wind wheels are analyzed to further understand the improvement effect of the simultaneous optimization of V-riblets structure and blunt trailing-edge wind wheel. The results show that after the optimization, the maximum instantaneous torque coefficient of every blade increases by 32.8%, the torque coefficient of the wind wheel improves within the azimuth angle range of 62.5%, and the instantaneous torque of three blades and wind wheel improves significantly. The pressure difference of upper and lower surfaces and the wake region of every blade respectively increases and decreases in most upwind regions and partial downwind regions. The shedding vortex strength of the wind wheel obviously reduces during the operating cycle.

Proceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy
Tianjin Chengjian University (CN), Tiangong University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Tianjin City
Affordable and clean energy
Openalex Percentile: Top 3%
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.