Paper Publications

• [16] 王龙滟.Deep reinforcement learning-based adaptive yaw control for wind farms in fluctuating winds
• [17] 王龙滟.Advanced wake modeling in wind farm: A physics-informed framework with virtual LiDAR measurements
• [18] 王龙滟.Innovative sparse data reconstruction approaches for yawed wind turbine wake flow via data-driven and physics-informed machine learning
• [19] 王龙滟.Effectiveness of cooperative yaw control based on reinforcement learning for in-line multiple wind turbines
• [20] 王龙滟.Wind turbine dynamic wake flow estimation (DWFE) from sparse data via reduced-order modeling-based machine learning approach
• [21] 王龙滟.A deep learning framework for reconstructing experimental missing flow field of hydrofoil
• [22] 王龙滟.A novel generative-predictive data-driven approach for multi-objective optimization of horizontal axis tidal turbine
• [23] 王龙滟.A cost-effective CNN-BEM coupling framework for design optimization of horizontal axis tidal turbine blades
• [24] 王龙滟.A novel cost-efficient deep learning framework for static fluid–structure interaction analysis of hydrofoil in tidal turbine morphing blade
• [25] 王龙滟.Flow reconstruction from sparse sensors based on reduced-order autoencoder state estimation
• [26] 王龙滟.Study of cooperative wake control for multiple wind turbines under variable wind speeds/directions
• [27] 王龙滟.Reconstruction of missing flow field from imperfect turbulent flows by machine learning
• [28] 王龙滟.Study of New Mini-Channel Trans-Critical CO2 Heat Pump Gas Cooler
• [29] 王龙滟.Effectiveness of data-driven wind turbine wake models developed by machine/deep learning with spatial-segmentation technique
• [30] 王龙滟.Performance analysis of geometrically optimized PaT at turbine mode: A perspective of entropy production evaluation