Abstract
This study presents an aerodynamic investigation of an innovative Coanda effect omni-flow wind turbine shroud, developed to enhance energy generation in low-wind urban environments and contribute to the UN’s Sustainable Development Goal 7 (SDG 7), which focuses on affordable and clean energy access for all, thereby tackling global warming. The design was analysed through Computational Fluid Dynamics (CFD) with the IDDES SST k−ω turbulence model, at the wind speed of 6 m/s, to understand the flow characteristics inside and around the shroud and further optimise its energy capture efficiency. The turbulent model IDDES SST k−ω effectively predicted key parameters, including velocity ratios and drag coefficient (Cd), while providing a good balance between computational efficiency and accuracy.A key feature of the shroud is its omni-directional flat plate base design, which allows it to harness wind from any horizontal direction, accelerate it into the turbine housing, and significantly improve energy conversion efficiency in environments with variable wind conditions, such as dense urban settings. The findings highlighted the shroud's effectiveness in harvesting wind starting at 1.5 m/s, resulting in better capabilities for self-starting. A highly turbulent zone characterises the internal region and an accelerated uniform flow region, reaching its maximum speed at the outlet of the shroud, thus indicating the optimal position of the turbine blade. The potential of this novel wind turbine shroud to play a critical role in sustainable energy generation, particularly in developing regions, is evident. The design's combination of simplicity, affordability, and environmental benefits underscores its significance in achieving the goals of the UN’s SDG 7.
| Original language | English |
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| Title of host publication | Proc. of International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA 2025) 7-9 August 2025, Antalya-Türkiye |
| Publisher | IEEE Xplore Digital Library |
| Number of pages | 5 |
| ISBN (Electronic) | 979-8-3315-3562-9 |
| ISBN (Print) | 979-8-3315-3563-6 |
| DOIs | |
| Publication status | Published - 9 Aug 2025 |
| Event | 2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA) - Antalya, Turkey Duration: 7 Aug 2025 → 9 Aug 2025 https://acdsa.org/2025/ |
Conference
| Conference | 2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA) |
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| Country/Territory | Turkey |
| City | Antalya |
| Period | 7/08/25 → 9/08/25 |
| Internet address |