affiliation not provided to SSRN
aerodynamic modification, class function/shape function transformation (CST) method, galloping-based wind energy harvesting, energy harvesting efficiency, Wind tunnel test, CFD
3-order sympodial tree, Tree geometry, Tree aerodynamics, Extreme gust wind
3-order branched tree, Tree morphology, Tree aerodynamics, Extreme gust wind
Rectangular cylinder, database, wind tunnel testing, PIV, deep learning
Deep reinforcement learning, Active flow control, Transfer Learning, Aerodynamic force, Square cylinder
Flow field reconstruction, Sparse sensor observations, Generalized Fourier Neural Operator, Graph neural network embedding, Physics-informed learning
Urban wind environment, Neural Fields, Doppler LiDAR, Wind profiler radar, Data fusion, Deep learning
Graph Neural Operator, Multi-Fidelity Learning, Heterogeneous Data Fusion, Uncertainty Quantification, computational fluid dynamics, Wind Tunnel Experiments
Wind turbine, wind tunnel test, aerodynamic characteristics, blade-tower interference, Reynolds number effect
rounded-corner high-rise building, extreme wind pressure, pressure tap placement, particle swarm optimization-random forest (PSO-RF)
