Grant: Postgraduate Scholarships - Doctoral
University of Washington
$33,666.67
Data-Driven Modeling of Turbulent Separation for Sustainable Aviation: Bridging the Gap Between Measurement Constraints and Predictive Insights
EF 2024-25
Résumé
Turbulent flows, Physics-informed machine learning, Turbulent separated flows, Data-driven reconstruction, Experimental fluid mechanics, Machine learning, Sustainable aviation, High-lift wings, Particle image velocimetry, Unsteady flows
Programme
Postgraduate Scholarships - Doctoral
Bénéficiaire
Emplacement
Washington, UNITED STATES
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
587724-2024
Name nom
Manohar, Kevin KH
Department département
Aeronautics and Astronautics
Organization id
1607
Institution établissement
University of Washington
Province en
Washington
Country en
UNITED STATES
Country fr
ÉTATS-UNIS
Fiscal year exercice financier
2024
Competition year année de concours
2024
Award amount
33666.67
Program id
PGSD
Program name en
Postgraduate Scholarships - Doctoral
Program name fr
Bourses d'études supérieures - doctorat
Group en
RESEARCH TRAINING AND TALENT DEVELOPMENT
Group fr
FORMATION EN RECHERCHE ET PERFECTIONNEMENT DES COM
Committee code
202
Committee name en
S&F Selection Committee for Mechanical Engineering
Committee name fr
Comité de sélection des bourses en génie mécanique
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
9999
Research subject group en
Not available
Research subject group fr
Non disponible
Research subject en
Not available
Research subject fr
Non disponible
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Data-Driven Modeling of Turbulent Separation for Sustainable Aviation: Bridging the Gap Between Measurement Constraints and Predictive Insights
Application summary
Turbulent flows, Physics-informed machine learning, Turbulent separated flows, Data-driven reconstruction, Experimental fluid mechanics, Machine learning, Sustainable aviation, High-lift wings, Particle image velocimetry, Unsteady flows
