Morphing and control of airfoils for optimum lift-to-drag ratio using shape-memory alloy with particle swarm optimization of PARSEC parameters
The optimal design of an airfoil varies across flight conditions, motivating the search for ways to implement adaptive designs. This study proposes an integrated framework for morphing airfoils using shape-memory alloy (SMA) actuators, targeting improved lift-to-drag (L/D) ratios during quasi-steady...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Engineering Applications of Computational Fluid Mechanics |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19942060.2025.2525904 |
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| author | Raed Bourisli Nesrin Ibrahim Mohammed Alajmi |
| author_facet | Raed Bourisli Nesrin Ibrahim Mohammed Alajmi |
| author_sort | Raed Bourisli |
| collection | DOAJ |
| description | The optimal design of an airfoil varies across flight conditions, motivating the search for ways to implement adaptive designs. This study proposes an integrated framework for morphing airfoils using shape-memory alloy (SMA) actuators, targeting improved lift-to-drag (L/D) ratios during quasi-steady flight. Airfoils are parameterized using the PARSEC method and optimized using particle swarm optimization (PSO), with CFD evaluations conducted in COMSOL. A PID-controlled SMA model implements the resulting shapes through voltage-controlled deformation, simulated in Simscape. This setup allows aerodynamic performance to be optimized while respecting actuation and control constraints. Validation against benchmark data confirms solver accuracy, and actuator tracking performance is demonstrated with displacement errors below 0.6%. The framework bridges aerodynamic design and real-time implementation, highlighting SMA's suitability for cruise-phase morphing. While the current study focuses on fixed-wing applications, future work may extend the approach to adaptive UAVs or other domains requiring geometry-responsive actuation. |
| format | Article |
| id | doaj-art-e70d85eedbc44f69a66c4a978b54bc79 |
| institution | Kabale University |
| issn | 1994-2060 1997-003X |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Engineering Applications of Computational Fluid Mechanics |
| spelling | doaj-art-e70d85eedbc44f69a66c4a978b54bc792025-08-20T03:28:51ZengTaylor & Francis GroupEngineering Applications of Computational Fluid Mechanics1994-20601997-003X2025-12-0119110.1080/19942060.2025.2525904Morphing and control of airfoils for optimum lift-to-drag ratio using shape-memory alloy with particle swarm optimization of PARSEC parametersRaed Bourisli0Nesrin Ibrahim1Mohammed Alajmi2Mechanical Engineering Department, Kuwait University, Safat, KuwaitMechanical Engineering Department, Kuwait University, Safat, KuwaitMechanical Engineering Department, Kuwait University, Safat, KuwaitThe optimal design of an airfoil varies across flight conditions, motivating the search for ways to implement adaptive designs. This study proposes an integrated framework for morphing airfoils using shape-memory alloy (SMA) actuators, targeting improved lift-to-drag (L/D) ratios during quasi-steady flight. Airfoils are parameterized using the PARSEC method and optimized using particle swarm optimization (PSO), with CFD evaluations conducted in COMSOL. A PID-controlled SMA model implements the resulting shapes through voltage-controlled deformation, simulated in Simscape. This setup allows aerodynamic performance to be optimized while respecting actuation and control constraints. Validation against benchmark data confirms solver accuracy, and actuator tracking performance is demonstrated with displacement errors below 0.6%. The framework bridges aerodynamic design and real-time implementation, highlighting SMA's suitability for cruise-phase morphing. While the current study focuses on fixed-wing applications, future work may extend the approach to adaptive UAVs or other domains requiring geometry-responsive actuation.https://www.tandfonline.com/doi/10.1080/19942060.2025.2525904Airfoil optimizationparticle swarm optimizationPARSEC parameterizationsmart materialsshape-memory alloyfeedback control |
| spellingShingle | Raed Bourisli Nesrin Ibrahim Mohammed Alajmi Morphing and control of airfoils for optimum lift-to-drag ratio using shape-memory alloy with particle swarm optimization of PARSEC parameters Engineering Applications of Computational Fluid Mechanics Airfoil optimization particle swarm optimization PARSEC parameterization smart materials shape-memory alloy feedback control |
| title | Morphing and control of airfoils for optimum lift-to-drag ratio using shape-memory alloy with particle swarm optimization of PARSEC parameters |
| title_full | Morphing and control of airfoils for optimum lift-to-drag ratio using shape-memory alloy with particle swarm optimization of PARSEC parameters |
| title_fullStr | Morphing and control of airfoils for optimum lift-to-drag ratio using shape-memory alloy with particle swarm optimization of PARSEC parameters |
| title_full_unstemmed | Morphing and control of airfoils for optimum lift-to-drag ratio using shape-memory alloy with particle swarm optimization of PARSEC parameters |
| title_short | Morphing and control of airfoils for optimum lift-to-drag ratio using shape-memory alloy with particle swarm optimization of PARSEC parameters |
| title_sort | morphing and control of airfoils for optimum lift to drag ratio using shape memory alloy with particle swarm optimization of parsec parameters |
| topic | Airfoil optimization particle swarm optimization PARSEC parameterization smart materials shape-memory alloy feedback control |
| url | https://www.tandfonline.com/doi/10.1080/19942060.2025.2525904 |
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