The aviation industry is a dynamic and ever-evolving sector. As technology advances and
becomes more sophisticated, the aviation industry must keep up with the changing trends …

The significant growth of artificial intelligence (AI) methods in machine learning (ML) and
deep learning (DL) has opened opportunities for fluid dynamics and its applications in …

Safe and high-density storage of hydrogen, for a clean-fuel economy, can be realized by
hydride-forming materials, but these materials should be able to store hydrogen at room …

Aeroacoustic noise is a major concern in wind turbine design that can be minimized by
optimizing the airfoils that shape the rotating blades. To this end, we present a framework for …

Develo** a high-fidelity, cost-effective aerodynamic database is crucial for addressing the
balance of accuracy and cost in aircraft design. Recently, data fusion technology has …

Fluid mechanics is a branch of physics that focuses on the study of the behavior and laws of
motion of fluids, including gases, liquids, and plasmas. The Yu–Toda–Sasa–Fukuyama …

We highlight the critical role of data in develo** sustainable combustion technologies for
industries requiring high-density and localized energy sources. Combustion systems are …

This work studies the problem of out-of-distribution fluid dynamics modeling. Previous works
usually design effective neural operators to learn from mesh-based data structures …

This paper investigates an approach for predicting whirl flutter bifurcations using pre-flutter
output data. The approach leverages the critical slowing down phenomenon, which makes …

We propose a reinforcement learning strategy to control wind turbine energy generation by
actively changing the rotor speed, the rotor yaw angle and the blade pitch angle. A double …