Abstract
The purpose of this study is to demonstrate the conceptual design of a low-boom super sonic transport aircraft by utilizing multi-fidelity and multi-disciplinary design optimization techniques. The research group aims to set forth a commercial supersonic aircraft model for future benchmarking studies. The presented multi-disciplinary design framework coherently incorporates aerodynamic, aero elasticity and sonic boom prediction solvers into the design process. In the multi-fidelity modelling approach, the rigid flow solution is chosen to be the low-fidelity model while the aero elastic flow solution is used as the high-fidelity model. For aero dynamic and fluid-structure interaction (FSI) solutions, the SU2 open-source suite is employed. For sonic boom prediction, NASA’s sBOOM code is coupled with the SU2 code’s output pressure data using in-house Python scripts. The parametric geometric modelling is achieved by using the ESP (Engineering Sketch Pad) program. In the multi-fidelity optimization study, the in-house coKriging and genetic algorithm codes of ITU AeroMDO Lab are used for multi fidelity surrogate modelling and optimization studies, respectively. A 8.48%reduction in PLdB(perceived loudness in decibels) is achieved by the current shape optimization process for a commercial supersonic aircraft model with a complex geometry.
Original language | English |
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Title of host publication | AIAA SciTech Forum and Exposition, 2023 |
Publisher | American Institute of Aeronautics and Astronautics Inc, AIAA |
ISBN (Print) | 9781624106996 |
DOIs | |
Publication status | Published - 2023 |
Event | AIAA SciTech Forum and Exposition, 2023 - Orlando, United States Duration: 23 Jan 2023 → 27 Jan 2023 |
Publication series
Name | AIAA SciTech Forum and Exposition, 2023 |
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Conference
Conference | AIAA SciTech Forum and Exposition, 2023 |
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Country/Territory | United States |
City | Orlando |
Period | 23/01/23 → 27/01/23 |
Bibliographical note
Publisher Copyright:© 2023, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.