Area of research
Aerospace Engineering · Astronomy and Astrophysics
Research interest
Research focused on Turbine and Wake, with related work in Wind power, Blade (archaeology), Robustness (evolution). Notable publications include 'A reduced order modeling-based machine learning approach for wind turbine wake flow estimation from sparse sensor measurements', 'A cost-effective CNN-BEM coupling framework for design optimization of horizontal axis tidal turbine blades', and 'Effectiveness of optimized control strategy and different hub height turbines on a real wind farm optimization'.
A reduced order modeling-based machine learning approach for wind turbine wake flow estimation from sparse sensor measurements
Wind turbine dynamic wake flow estimation (DWFE) from sparse data via reduced-order modeling-based machine learning approach
DLFSI: A deep learning static fluid-structure interaction model for hydrodynamic-structural optimization of composite tidal turbine blade
Off-Design Operation and Cavitation Detection in Centrifugal Pumps Using Vibration and Motor Stator Current Analyses
A cost-effective CNN-BEM coupling framework for design optimization of horizontal axis tidal turbine blades
A deep learning framework for reconstructing experimental missing flow field of hydrofoil
Effectiveness of optimized control strategy and different hub height turbines on a real wind farm optimization