Multidisciplinary design optimisation of a fully electric regional aircraft wing with active flow control technology
Multidisciplinary design optimisation of a fully electric regional aircraft wing with active flow control technology
The German research Cluster of Excellence SE2A (Sustainable and Energy Efficient Aviation) is investigating different technologies to be implemented in the following decades, to achieve more efficient air transportation. This paper studies the Hybrid Laminar Flow Control (HLFC) using boundary layer suction for drag reduction, combined with other technologies for load and structural weight reduction and a novel full-electric propulsion system. A multidisciplinary design optimisation framework is presented, enabling physics-based analysis and optimisation of a fully electric aircraft wing equipped with HLFC technologies and load alleviation, and new structures and materials. The main focus is on simulation and optimisation of the boundary layer suction and its influence on wing design and optimisation. A quasi three-dimensional aerodynamic analysis is used for drag estimation of the wing. The tool executes the aerofoil analysis using XFOILSUC, which provides accurate drag estimation through boundary layer suction. The optimisation is based on a genetic algorithm for maximum take-off weight (MTOW) minimisation. The optimisation results show that the active flow control applied on the optimised geometry results in more than 45% reduction in aircraft drag coefficient, compared to the same geometry without HLFC technology. The power absorbed for the HLFC suction system implies a battery mass variation lower than 2%, considering the designed range as top-level requirement (TLR).
Mosca, V.
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Karpuk, S.
583b7aff-008d-4d29-b697-01745a423095
Sudhi, A.
16caf5df-d8a2-4401-b187-76687846ae62
Badrya, C.
ea88f8cd-d0fd-4ff0-bfa5-d19ed94c1402
Elham, A.
676043c6-547a-4081-8521-1567885ad41a
Mosca, V.
8c7c1bf1-f96d-44f8-93ed-b627c39672c5
Karpuk, S.
583b7aff-008d-4d29-b697-01745a423095
Sudhi, A.
16caf5df-d8a2-4401-b187-76687846ae62
Badrya, C.
ea88f8cd-d0fd-4ff0-bfa5-d19ed94c1402
Elham, A.
676043c6-547a-4081-8521-1567885ad41a
Mosca, V., Karpuk, S., Sudhi, A., Badrya, C. and Elham, A.
(2021)
Multidisciplinary design optimisation of a fully electric regional aircraft wing with active flow control technology.
Aeronautical Journal, 126 (1298).
(doi:10.1017/aer.2021.101).
Abstract
The German research Cluster of Excellence SE2A (Sustainable and Energy Efficient Aviation) is investigating different technologies to be implemented in the following decades, to achieve more efficient air transportation. This paper studies the Hybrid Laminar Flow Control (HLFC) using boundary layer suction for drag reduction, combined with other technologies for load and structural weight reduction and a novel full-electric propulsion system. A multidisciplinary design optimisation framework is presented, enabling physics-based analysis and optimisation of a fully electric aircraft wing equipped with HLFC technologies and load alleviation, and new structures and materials. The main focus is on simulation and optimisation of the boundary layer suction and its influence on wing design and optimisation. A quasi three-dimensional aerodynamic analysis is used for drag estimation of the wing. The tool executes the aerofoil analysis using XFOILSUC, which provides accurate drag estimation through boundary layer suction. The optimisation is based on a genetic algorithm for maximum take-off weight (MTOW) minimisation. The optimisation results show that the active flow control applied on the optimised geometry results in more than 45% reduction in aircraft drag coefficient, compared to the same geometry without HLFC technology. The power absorbed for the HLFC suction system implies a battery mass variation lower than 2%, considering the designed range as top-level requirement (TLR).
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Accepted/In Press date: 4 October 2021
e-pub ahead of print date: 28 October 2021
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Local EPrints ID: 468849
URI: http://eprints.soton.ac.uk/id/eprint/468849
ISSN: 0001-9240
PURE UUID: d04bc1bb-3e76-4096-bc95-500dac78a300
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Date deposited: 30 Aug 2022 16:36
Last modified: 16 Mar 2024 21:27
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Author:
V. Mosca
Author:
S. Karpuk
Author:
A. Sudhi
Author:
C. Badrya
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