Browse Topic: Noise, Vibration, and Harshness (NVH)
A comprehensive numerical study was conducted to reduce helicopter rotor hub vibratory loads and fuselage vibrations using the Higher Harmonic Control (HHC) technique. A CAMRAD II model of a medium utility helicopter was developed for aeromechanical simulation, and a linear system model representing both hub vibratory load and fuselage vibration characteristics was identified offline. Optimal control inputs were then computed to minimize vibration responses under different weightings on hub vibratory load and fuselage vibration in the objective function. The predicted performance was verified through CAMRAD II simulations. Additionally, a closed-loop HHC system incorporating actuator amplitude limitations was investigated. A control algorithm regulated actuator amplitudes while maintaining phase consistency, dynamically adjusting control inputs after each iteration. The results demonstrate that the amplitude-limited closed-loop control limits excessive pitch link loads while
This paper describes the electromagnetic noise mitigation on the Maryland Tiltrotor Rig (MTR) and presents its first hover test results. The primary source of noise was found to be pulse width modulation associated with the motor controller. Due to this noise, testing was limited to unpowered, freewheeling cases. To solve the noise problem and allow powered testing, three hardware filters were integrated into the power and data systems. A complementary digital filter was also used. With the filtering solution in place, hover tests were carried out to high collectives of 30◦and blade loadings of 0.2. The test data was assessed using blade element-momentum theory predictions.
An experimental investigation was conducted to explore the loads, acoustics, and tip vortex trajectories of coaxial counter-rotating (CCR) rotor with unequal upper and lower radii. The upper and lower rotor radii were tested both at the nominal radius of 1.108 m, and also with a lower rotor radius of 90% nominal radius, for a constant rotor speed of 1180 RPM and a constant inter-rotor spacing of z/R = 0.108. Rotors were torque balanced and tested for a range of upper rotor collective pitch from -2◦ to 10◦ . The power required for both CCR systems was within 0.9% for most trim conditions, and equal thrust was produced at upper rotor collectives of 6◦ and 8◦ (within 1.0%). At low loading conditions the unequal radii configuration produced more thrust for the same power due to a reduction in profile drag. The overall sound pressure level (OASPL) was lower for the CCR rotor with shortened lower rotor blades at all angles of elevation. Larger reductions in A-weighted OASPL(A) were observed
This study examines the capability of medium-fidelity comprehensive analysis models to predict the acoustics for manned and unmanned rotorcraft configurations. Using the automated tool NDARC2RCAS developed at DEVCOM Army Research Laboratory, multiple configurations including a single main rotor, tilt rotor, coaxial and pusher, quadcopter, and hexacopter are evaluated at various mission segments including hover, advancing climb, and forward flight. Each configuration and condition is evaluated using a range of aerodynamic models from lower to higher fidelity, including uniform inflow, dynamic inflow, prescribed wake, free wake, and viscous vortex particle method (VVPM). These evaluations are then used with another automated tool, RCAS Acoustics, to predict noise on a Voronoi observer sphere. A comparison of the results for the single main showed good agreement between all of the aerodynamic models except VVPM. For the tilt rotor in forward flight, the higher-fidelity models produced
Achieving noise reduction in rotorcraft requires an analysis of various design parameters and flight conditions. However, high-fidelity methods are computationally expensive. To overcome this limitation, reduced order model (ROM)-based surrogate models have been applied to aerodynamics and aeroacoustics prediction. This study proposes a ROM-based surrogate model employing a variational autoencoder (VAE) to predict rotor aerodynamic loads and associated noise. Train and test datasets were generated using reformulated vortex particle method across a wide range of flight conditions. The proposed framework was applied to a single rotor, and its performance was evaluated qualitatively and quantitively in comparison with proper orthogonal decomposition (POD)-based surrogate model. The results show that VAE-based model consistently outperformed the POD model in noise prediction. These results demonstrate that the proposed framework enables accurate rotor noise prediction under various flight
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