CFD Analysis for Wind Turbine Noise Control

Adaptive trailing edge comb on wind turbine blades to reduce noise emissions. The trailing edge comb has serrations that can be adjusted in geometry and orientation based on parameters like air density, wind speed, and load. This allows optimizing the comb shape for specific operating conditions to reduce noise compared to fixed comb designs.

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Characterizing vortex wake losses in wind turbine blades using an effective energy analysis method. The method involves simulating flow through the blades to calculate the effective energy balance. By tracking the effective energy throughout the system, losses due to irreversible processes like vortex shedding can be quantified. This provides a more comprehensive analysis of blade energy losses compared to just measuring power output or blade forces.

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A wind turbine blade with rapid noise reduction by using internal and external noise reduction components attached to the blade. The blade has a mounting plate on one side connected to the fan and a hub on the other side. Inside the blade near the hub is a fixed tooth-shaped component with an air guide groove in its outer surface. The tooth component has a base layer fixed to the blade outer surface and a sound-absorbing layer on the base layer outer surface. A smooth layer covers the sound-absorbing layer outer surface. Near the hub, there is also a fixed mounting block with a threaded fixing groove. Inside the hub, there is a threaded mounting hole and bolts to connect the mounting block and hub. This internal noise reduction component reduces blade vibration noise. Externally, the blade has a tooth-shaped component with an air guide groove on its outer surface. This external component reduces wind

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Method, equipment, and computer program for analyzing wind farm noise more accurately by considering the external environment impact on blade noise. It involves modeling and analyzing the entire wind farm instead of just individual blades. This allows accounting for factors like terrain, wind speed, vegetation that affect noise propagation. The method obtains virtual models and wind farm data for blades, determines the calculation domain, and solves numerically to obtain surface noise distribution. This improves blade noise analysis accuracy compared to single blade simulations.

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Representing rotating blade noise in a wind turbine using computer simulations to optimize blade design and reduce noise levels without expensive blade prototyping. The method involves importing 3D blade geometry, extracting blade parameters, computing airflow using blade momentum theory, and repeating simulations at multiple rotations to capture blade passage effects. The noise is calculated in the blade rotation frame of reference using scale-resolved CFD simulations covering a small fraction of a revolution. This allows statistical convergence by compensating for accurate noise signals over multiple rotations. The noise is then combined, corrected, and applied ground reflection/absorption/atmospheric absorption to represent rotating blade noise in the wind turbine.

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Computer method for accurately representing wind turbine blade noise using 2.5D simulations and blending to create realistic audio tracks. The method involves extracting blade geometry parameters and sectional flow data, simulating airflow past sections, computing noise spectra, blending spectra over a rotor revolution, synthesizing audio signals, and applying Doppler correction and absorption effects. This allows recovering blade noise over multiple revolutions by using 2.5D simulations covering a small portion of the rotor and blade.

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Optimal design method for wind turbine blades with high aerodynamic efficiency and low noise levels. It involves using a dual-objective optimization approach to find wind turbine blade airfoils with both high lift-to-drag ratios and low noise levels. The optimization targets are the maximum lift-to-drag ratio and total noise pressure level. Constraints ensure the airfoil meets other important aerodynamic requirements like lift coefficient, maximum lift coefficient, stall characteristics, and roughness stability.

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Aerodynamic optimization method for wind turbine airfoils that considers the effect of high turbulent free flow. The optimization aims to find airfoils with lower sensitivity to free flow turbulence, which is important for wind turbines operating in turbulent environments. The method involves iterative optimization using CFD simulation to find airfoils with lower sensitivity to high turbulence levels compared to low turbulence. It considers the relative change in aerodynamic coefficients between high and low turbulence conditions as a sensitivity metric.

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Low-noise wind turbine blade design that improves aerodynamic efficiency while reducing noise. The blade has an adjustable flap at the trailing edge made of acoustic metamaterial. The flap angle can be changed to increase lift at low wind speeds. The flap is also made of materials that absorb noise. By optimizing blade shape and adding noise-reducing flaps, the blade efficiency is increased while noise is reduced compared to traditional blades.

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Design method for improving aerodynamic performance of wind turbine blades with thick airfoils that stall easily. The method involves optimizing the suction side profile of the airfoil using a simulated annealing multi-objective evolutionary algorithm to find a profile that improves lift-to-drag ratio both before and after stall compared to the original airfoil. The algorithm calculates aerodynamic performance using fluid simulation software like Fluent. The optimized airfoil, named WT-E-300, was found to have better stall characteristics compared to the standard DU97-W-300 airfoil.

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Noise reduction system for wind turbine blades using both passive and active techniques to significantly reduce trailing edge noise. The passive part is a serrated edge profile on the blade trailing edge. The active part is a sensor near the serrated edge that measures turbulent flow conditions. A control unit analyzes the sensor data to generate an anti-noise signal that is emitted by an actuator. The anti-noise signal is tailored to the serrated edge shape and flow conditions. Combining passive serrations with active flow sensing allows synergistic noise reduction beyond what each method alone can provide.

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A noise reduction system for wind turbine blades that combines passive serrated edges with active noise control. The system has sensors along the serrated edge to detect turbulent flow. A control unit uses the sensor signals to generate an anti-noise signal that is emitted by actuators. This active noise cancels out some of the blade noise. By combining passive serrations with active cancellation, the system aims to further reduce blade noise compared to just passive serrations. The sensors follow the serrated edge path to capture flow details. The control unit maps sensor signals to far field noise using a transfer function.

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Quasi-three-dimensional linear calculation method for interference single-tone noise of turbine blade rows to improve turbine noise prediction capabilities for aeroengine design. The method involves segmenting the blade rows to account for large turning angles, linearizing the calculation by treating the segments as separate blades, using modified wake models for turbine blades, and applying pipe acoustics theory for propagation and cutoff. This allows applying aeroengine design tools like strip theory to turbine noise analysis.

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Method to design wind turbine blades for strong winds using numerical simulation. The method involves using existing aircraft airfoil data for wind turbine blades due to lack of specialized wind turbine airfoil data. The simulation involves selecting appropriate grid types, grid densities, time-space dispersion, numerical formats, algorithms, iterations, turbulence models, calculation domains, and rotation domains to accurately model wind turbine blades under strong winds. The simulation aims to optimize blade shape for reduced damage and improved performance in high wind conditions.

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Method for increasing power generation of high-altitude wind turbines by optimizing blade design and tip speed ratios. The method involves using optimization algorithms to find the best blade tip speed ratios for each wind turbine in a high-altitude wind farm. This maximizes wind energy capture and power generation at lower air densities found at high altitudes. By optimizing the tip speed ratios, it allows the blades to capture more wind energy at lower speeds where air density is lower, compared to sea level conditions. This compensates for the reduced aerodynamic performance due to lower air density at high altitude.

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Determining structural parameters of airfoils for wind turbine blades that have lower sensitivity to leading edge roughness. The method involves optimizing airfoil geometry using a design objective function that includes roughness sensitivity metrics along with constraints like stall point. Iterative optimization determines the target airfoil geometry to improve smooth surface performance while reducing roughness sensitivity compared to the initial airfoil. This provides an airfoil with better aerodynamics and noise when the blade surface is rough, like at wear prone outer sections.

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Rapid method for predicting aerodynamic noise of wind turbines that provides a faster and more accurate way to calculate wind turbine noise compared to traditional methods. The method involves breaking down the wind turbine blade into elements along the span direction. It calculates the effective incoming wind speed and angle of attack for each element using blade element momentum theory and models. This data is then used to calculate the wall pressure spectrum and boundary layer parameters using a software tool. The airfoil trailing edge noise model and turbulent incoming flow noise are applied to each element to calculate the sound pressure level or power level. Superimposing the results from all elements gives the overall wind turbine noise.

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Optimizing power generation of wind turbines operating in low air density environments by strategically placing vortex generators on the blades. The method involves using numerical simulation and optimal control algorithms to determine the best vortex generator shape and position that maximizes power output. The optimization considers factors like blade deformation, yaw effects, and dynamic inflow conditions to balance lift coefficient, tip speed ratio, and stability. The goal is to maintain optimal power generation after installing vortex generators on blades operating in low density air.

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A noise reduction device and blade design for wind turbines that reduces aerodynamic noise generated during operation. The device has a body that attaches to the blade and a sawtooth unit with a sawtooth edge. The sawtooth angle is set to disrupt vortex formation on the blade surface. This breaks up vortex pairs, reduces vortex energy, and lowers blade surface pressure fluctuations to reduce noise. The body and sawtooth are angled to optimize vortex disruption.

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Simulating wind turbine wake distributions for wind farms with high accuracy, efficiency, and timeliness using CFD pre-calculation. Instead of running CFD simulations for each wind speed in real-time, the method involves pre-calculating the wake distributions at multiple wind speeds using CFD. These calculated wake distributions are stored in a database. To simulate the wake for a specific wind speed, the database is interpolated using the known wind speed as input. This allows fast, accurate wake simulation by avoiding repetitive CFD calculations for each wind speed.

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