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Enhancing Energy Generation While Mitigating Noise Emissions in Wind Turbines Through Multi‐Objective Optimization: A Deep Reinforcement Learning Approach

open access: yesWind Energy, Volume 28, Issue 8, August 2025.
ABSTRACT We develop a torque‐pitch control framework using deep reinforcement learning for wind turbines to optimize the generation of wind turbine energy while minimizing operational noise. We employ a double deep Q‐learning, coupled to a blade element momentum solver, to enable precise control over wind turbine parameters.
Martín Frutos   +3 more
wiley   +1 more source

Fiber reinforced superalloys for rocket engines [PDF]

open access: yes
High-pressure turbopumps for advanced reusable liquid-propellant rocket engines such as that for the Space Shuttle Main Engine (SSME) require turbine blade materials that operate under extreme conditions of temperature, hydrogen environment, high-cycle ...
Petrasek, Donald W., Stephens, Joseph R.
core   +1 more source

Enhanced Aerodynamic Performance of Savonius Wind Turbines Through Blade Design Modifications: A CFD Study

open access: yesWind Energy, Volume 28, Issue 8, August 2025.
ABSTRACT The conventional Savonius wind turbine's power coefficient is comparatively low, which limits its efficiency. Because the power coefficient depends significantly on the blade design, this study investigates the potential of improving the turbine performance by modifying the rotor blade designs.
Shihab Shahriare   +2 more
wiley   +1 more source

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