Pinto, Joseph Ciano, MARIMUTHU, Siva, Rajendran, Parvathy and Natarajan, Manikandan (2025) Computational Analysis of Blended Winglet Designs to Reduce the Wake Turbulence on the Airbus A380 Wingtip. Eng, 6 (68). pp. 1-17. ISSN 2673-4117
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Abstract or description
The aviation sector faces a significant challenge in balancing the rising demand for air travel with the need to reduce its environmental impact. Because air travel accounts for approximately 2.5% of global carbon emissions, there is a need to find sustainable solutions to reduce its environmental impact. Improving aerodynamic performance is a crucial area for reducing fuel consumption and emissions. Nowadays, more focus is given to commercial aviation, which contributes to global aviation emissions. The A380 is the largest passenger aircraft in the world at the moment. It was observed in real life that the wake turbulence from the A380 led to a sudden loss of the Challenger aircraft’s control and a rapid descent of more than 10,000 feet. This Challenger incident is a wake-up call to address the A380’s wake turbulence. Hence, this research focuses on designing and analysing blended winglets for the Airbus A380 to reduce wake turbulence. With the use of modern computational fluid dynamics tools, the current A380 winglets’ performance was evaluated to identify the level of lift, drag and wake vortex patterns. To address these challenges, the performance of newly designed blended winglets with different cant angles, i.e., 0, 15, 45 and 80, was analysed computationally using the K-ω SST turbulent model in the software ANSYS Fluent 2024 R1. It resulted in a decrease in the wake vortex size accompanied by a 1.724% decrease in drag. This research project evidenced that addressing the wake turbulence issue on a large aircraft could improve aerodynamic performance and thus contribute towards sustainable aviation.
Item Type: | Article |
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Uncontrolled Keywords: | aerodynamics; wake turbulence; induced drag; blended winglet; computational analysis |
Faculty: | School of Digital, Technologies and Arts > Engineering |
Depositing User: | Siva MARIMUTHU |
Date Deposited: | 04 Apr 2025 12:24 |
Last Modified: | 05 Apr 2025 04:30 |
URI: | https://eprints.staffs.ac.uk/id/eprint/8859 |