Data-Efficient Machine Learning for Airfoil Prediction via Targeted Data AugmentationSource: Journal of Aerospace Engineering:;2026:;Volume ( 039 ):;issue: 005::page 04026027-1Author:Zhang, Yi
,
Ross, James
,
Thompson, Brianna
,
Haehnel, Robert
,
Allen, Luke
,
Dettwiller, Ian
,
Kubiak, Lisa
DOI: 10.1061/JAEEEZ.ASENG-6770Publisher: American Society of Civil Engineers
Abstract: AbstractOptimizing airfoil geometry is critical for improving rotorcraft efficiency by directly
influencing blade lift and drag forces. However, the inherent nonlinearity of fluid
dynamics and the high dimensionality of design space make airfoil geometry ...Practical ApplicationsOptimizing airfoil shapes is critical for improving the performance and energy efficiency
of rotorcraft, such as helicopters and drones. Traditional approaches rely on complex
and time-consuming computational fluid dynamics ...
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| contributor author | Zhang, Yi | |
| contributor author | Ross, James | |
| contributor author | Thompson, Brianna | |
| contributor author | Haehnel, Robert | |
| contributor author | Allen, Luke | |
| contributor author | Dettwiller, Ian | |
| contributor author | Kubiak, Lisa | |
| date accessioned | 2026-08-20T21:15:54Z | |
| date available | 2026-08-20T21:15:54Z | |
| date copyright | 2026/05/25 | |
| date issued | 2026 | |
| identifier other | JAEEEZ.ASENG-6770.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314199 | |
| description abstract | AbstractOptimizing airfoil geometry is critical for improving rotorcraft efficiency by directly influencing blade lift and drag forces. However, the inherent nonlinearity of fluid dynamics and the high dimensionality of design space make airfoil geometry ...Practical ApplicationsOptimizing airfoil shapes is critical for improving the performance and energy efficiency of rotorcraft, such as helicopters and drones. Traditional approaches rely on complex and time-consuming computational fluid dynamics ... | |
| publisher | American Society of Civil Engineers | |
| title | Data-Efficient Machine Learning for Airfoil Prediction via Targeted Data Augmentation | |
| type | Journal Article | |
| journal volume | 39 | |
| journal issue | 5 | |
| journal title | Journal of Aerospace Engineering | |
| identifier doi | 10.1061/JAEEEZ.ASENG-6770 | |
| journal fristpage | 04026027-1 | |
| journal lastpage | 04026027-11 | |
| page | 11 | |
| tree | Journal of Aerospace Engineering:;2026:;Volume ( 039 ):;issue: 005 | |
| contenttype | Fulltext |