An Automated Framework for Streamlined CFD-Based Design and Optimization of Fixed-Wing UAV Wings
The increasing complexity of the UAV aerodynamic design, imposed by novel configurations and requirements, has highlighted the need for efficient tools for high-fidelity simulation, especially for optimization purposes. The current work presents an automated CFD framework, tailored for fixed-wing UA...
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MDPI AG
2025-03-01
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| author | Chris Pliakos Giorgos Efrem Dimitrios Terzis Pericles Panagiotou |
| author_facet | Chris Pliakos Giorgos Efrem Dimitrios Terzis Pericles Panagiotou |
| author_sort | Chris Pliakos |
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| description | The increasing complexity of the UAV aerodynamic design, imposed by novel configurations and requirements, has highlighted the need for efficient tools for high-fidelity simulation, especially for optimization purposes. The current work presents an automated CFD framework, tailored for fixed-wing UAVs, designed to streamline the geometry generation of wings, mesh creation, and simulation execution into a Python-based pipeline. The framework employs a parameterized meshing module capable of handling a broad range of wing geometries within an extensive design space, thereby reducing manual effort and achieving pre-processing times in the order of five minutes. Incorporating GPU-enabled solvers and high-performance computing environments allows for rapid and scalable aerodynamic evaluations. An automated methodology for assessing the CFD results is presented, addressing the discretization and iterative errors, as well as grid resolution, especially near wall surfaces. Comparisons with the results produced by a specialized mechanical engineer with over five years of experience in aircraft-related CFD indicate high accuracy, with deviations below 3% for key aerodynamic metrics. A large-scale deployment further demonstrates consistency across diverse wing samples. A Bayesian Optimization case study then illustrates the framework’s utility, identifying a wing design with an 8% improvement in the lift-to-drag ratio, while maintaining an average <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>y</mi></mrow><mrow><mo>+</mo></mrow></msup></mrow></semantics></math></inline-formula> value below 1 along the surface. Overall, the proposed approach streamlines fixed-wing UAV design processes and supports advanced aerodynamic optimization and data generation. |
| format | Article |
| id | doaj-art-ca25c55cdb16475dbbbaf864db0ec7d2 |
| institution | OA Journals |
| issn | 1999-4893 |
| language | English |
| publishDate | 2025-03-01 |
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| series | Algorithms |
| spelling | doaj-art-ca25c55cdb16475dbbbaf864db0ec7d22025-08-20T02:17:15ZengMDPI AGAlgorithms1999-48932025-03-0118418610.3390/a18040186An Automated Framework for Streamlined CFD-Based Design and Optimization of Fixed-Wing UAV WingsChris Pliakos0Giorgos Efrem1Dimitrios Terzis2Pericles Panagiotou3Laboratory of Fluid Mechanics and Turbomachinery, Department of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceLaboratory of Fluid Mechanics and Turbomachinery, Department of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceLaboratory of Fluid Mechanics and Turbomachinery, Department of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceLaboratory of Fluid Mechanics and Turbomachinery, Department of Mechanical Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceThe increasing complexity of the UAV aerodynamic design, imposed by novel configurations and requirements, has highlighted the need for efficient tools for high-fidelity simulation, especially for optimization purposes. The current work presents an automated CFD framework, tailored for fixed-wing UAVs, designed to streamline the geometry generation of wings, mesh creation, and simulation execution into a Python-based pipeline. The framework employs a parameterized meshing module capable of handling a broad range of wing geometries within an extensive design space, thereby reducing manual effort and achieving pre-processing times in the order of five minutes. Incorporating GPU-enabled solvers and high-performance computing environments allows for rapid and scalable aerodynamic evaluations. An automated methodology for assessing the CFD results is presented, addressing the discretization and iterative errors, as well as grid resolution, especially near wall surfaces. Comparisons with the results produced by a specialized mechanical engineer with over five years of experience in aircraft-related CFD indicate high accuracy, with deviations below 3% for key aerodynamic metrics. A large-scale deployment further demonstrates consistency across diverse wing samples. A Bayesian Optimization case study then illustrates the framework’s utility, identifying a wing design with an 8% improvement in the lift-to-drag ratio, while maintaining an average <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi>y</mi></mrow><mrow><mo>+</mo></mrow></msup></mrow></semantics></math></inline-formula> value below 1 along the surface. Overall, the proposed approach streamlines fixed-wing UAV design processes and supports advanced aerodynamic optimization and data generation.https://www.mdpi.com/1999-4893/18/4/186CFD automationfixed-wing UAVwing designuncertaintyoptimization |
| spellingShingle | Chris Pliakos Giorgos Efrem Dimitrios Terzis Pericles Panagiotou An Automated Framework for Streamlined CFD-Based Design and Optimization of Fixed-Wing UAV Wings Algorithms CFD automation fixed-wing UAV wing design uncertainty optimization |
| title | An Automated Framework for Streamlined CFD-Based Design and Optimization of Fixed-Wing UAV Wings |
| title_full | An Automated Framework for Streamlined CFD-Based Design and Optimization of Fixed-Wing UAV Wings |
| title_fullStr | An Automated Framework for Streamlined CFD-Based Design and Optimization of Fixed-Wing UAV Wings |
| title_full_unstemmed | An Automated Framework for Streamlined CFD-Based Design and Optimization of Fixed-Wing UAV Wings |
| title_short | An Automated Framework for Streamlined CFD-Based Design and Optimization of Fixed-Wing UAV Wings |
| title_sort | automated framework for streamlined cfd based design and optimization of fixed wing uav wings |
| topic | CFD automation fixed-wing UAV wing design uncertainty optimization |
| url | https://www.mdpi.com/1999-4893/18/4/186 |
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