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Results for “Self-Noise”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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48 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Acoustic Characterization and Prediction of Representative, Small-Scale Rotary-Wing Unmanned Aircraft System Components

In this study, hover performance and acoustic measurements are taken on two different isolated rotors representative of small-scale rotary-wing unmanned aircraft systems (UAS) for a range of rotation rates. Each rotor system consists of two fixed-pitch blades powered by a brushless motor. For nearly the same thrust condition, significant differences in overall sound pressure level (OASPL), up to 8 dB, and directivity were observed between the two rotor systems. Differences are shown to be in part attributed to different rotor tip speeds, along with increased broadband and motor noise levels. In addition to acoustic measurements, aeroacoustic predictions were implemented in order to better understand the noise content of the rotor systems. Numerical aerodynamic predictions were computed using the unsteady Reynoldsaveraged Navier Stokes code OVERFLOW2 on one of the isolated rotors, while analytical predictions were computed using the Propeller Analysis System of the Aircraft NOise Prediction Program (ANOPP-PAS) on the two rotor configurations. Preliminary semi-empirical frequency domain broadband noise predictions were also carried out based on airfoil self-noise theory in a rotational reference frame. The prediction techniques further supported trends identified in the experimental data analysis. The brushless motors were observed to be important noise contributors and warrant further investigation. It is believed that UAS acoustic prediction capabilities must consider both rotor and motor components as part of a combined noise-generating system.

Zawodny, Nikolas S.↗
NASA NTRSDate not supplied

Acoustics and Performance Characteristics of an Ideally Twisted Rotor in Hover

A series of experiments were conducted in an anechoic chamber to investigate the noise and performance of an ideally twisted rotor design, leading to validation of a low-fidelity aerodynamic performance and acoustic modeling tool chain. An "ideally twisted" rotor was designed in order to simplify the theoretical rotor inflow for a target thrust condition in hover. This rotor design was then fabricated using state-of-the-art rapid prototyping and tested in an anechoic chamber facility. Aerodynamic load and acoustic data were acquired across a range of rotation rates (RPM) and rotor collective settings in order to ascertain the accuracy of the low-fidelity modeling codes. Emphasis was placed on modeling of the broadband self-noise generated by the rotor system due to the fact that it was found to be a prominent contributor to the overall rotor system noise.

Nicole A. Pettingill↗
NASA NTRSDate not supplied

Computational Prediction of Broadband Noise from a Representative Unmanned Aerial System Rotor

This work details the application of a lattice-Boltzmann method–very-large-eddy simulation (LBM-VLES) employed by the software suite, PowerFLOW. This LBM-VLES simulation predicted the aeroacoustic noise emanating from a representative, small unmanned aircraft system rotor, namely, the DJI-9450 in a hover condition. Predicted total aerodynamic loading as well as 2D aerodynamic loading along discrete spanwise sections of a rotor blade were compared to lower fidelity predictions and experimental results acquired in the Structural Acoustic Loads and Transmission anechoic chamber facility at the NASA Langley Research Center. The total acoustic spectra were decomposed into tonal and broadband components, which showed that broadband noise was a dominant contributor above 1 kHz for this rotor. These data were then compared to experimentally acquired data, showing good agreement up to approximately 11 kHz. Above 11 kHz, however, a grid sensitivity study showed dependency of the highest resolvable frequency on the spatial resolution of the computational domain, explaining the roll off in predicted data. Individual broadband noise sources were further investigated by calculating one-third octave sound pressure levels of the unsteady pressure fluctuations acting on the rotor, providing evidence that blade self-noise was the prominent noise source. Using these results, blade wake interaction noise was seen to be negligible for this particular rotor, which was further validated by calculating blade vortex miss distances and comparing to theory.

Christopher S. Thurman↗
NASA NTRSDate not supplied

Acoustic and Performance Characteristics of an Ideally Twisted Rotor in Hover

A series of experiments were conducted in an anechoic chamber to investigate the noise and performance of an ideally twisted rotor design, leading to validation of a low-fidelity aerodynamic performance and acoustic modeling tool chain. An “ideally twisted” rotor was designed in order to simplify the theoretical rotor inflow for a target thrust condition in hover. This rotor design was then fabricated using state-of-the-art rapid prototyping and tested in an anechoic chamber. Aerodynamic load and acoustic data were acquired across a range of rotation rates and rotor collective settings in order to both identify noise trends and ascertain the accuracy of the low-fidelity modeling codes. Emphasis was placed on modeling of the broadband self-noise generated by the rotor system due to the fact that it was found to be a prominent contributor to the overall rotor system noise.

Nicole A Pettingill↗
NASA NTRSDate not supplied

Aeroacoustic Characterization of Optimum Hovering Rotors using Artificial Neural Networks

This work illustrates the use of artificial neural network modeling in the aerodynamic and aeroacoustic characterization of optimum hovering rotors over a broad range of design and operating conditions. Design of Experiments was used to create input feature spaces over eight input factors: the number of rotor blades, rotor radius, rotor rotation rate, design thrust condition, collective pitch, airfoil camber, the location of maximum camber, and the airfoil thickness. A low-fidelity tool chain was then used at the discrete data points defined by the designed input feature spaces to analytically design optimum hovering rotors and simulate aerodynamic and aeroacoustic quantities. This allowed for the generation of data sets over which to train and test the artificial neural network prediction models. Prediction models were trained over the data sets for the actual thrust generated by the rotor, power loading, tonal thickness and loading noise at the fundamental blade passage frequency, and broadband self-noise at seventeen one-third octave bands between 1 kHz and 40 kHz. These prediction models were validated by testing over data previously unseen by the models to quantify their capability for generalization to new data within the design feature space. The models were then used to study the effect each input feature had on the aeroacoustics and aerodynamics of optimum hovering rotors and physical insights were concluded to further explain the effect of each input. This characterization study showed that tonal noise and power loading were most sensitive to the number of rotor blades and the rotor rotation rate and that broadband noise was most sensitive to collective pitch and the design thrust condition.

Christopher S Thurman↗
NASA NTRSDate not supplied

The Effect of Boundary Layer Character on Stochastic Rotor Blade Vortex Shedding Noise

This work illustrates the effect of a rotor blade’s boundary layer on the broadband LBL-VS self-noise emitted from an optimum hovering rotor through experimental and multi-fidelity computational studies. Blade surface roughness effects associated with different manufacturing techniques and the effect of adding a boundary layer trip were shown to decrease LBL-VS noise by upwards of 30 dB at the frequency of maximum emission with a slight penalty in aerodynamic performance when compared with smooth rotor blades. Low-fidelity 2-D viscous flow analysis verified the presence of laminar separation bubbles on the rotor blades which are responsible for LBL-VS noise. Three high-fidelity lattice-Boltzmann simulations were conducted with different wall-functions to predict the boundary layer character correspondent to their experimental counterpart and the resultant presence or absence of LBL-VS noise. Excellent aerodynamic and aeroacoustic agreement was seen between the lattice-Boltzmann simulations and the experimental data for the cases with surface roughness and the boundary layer trip, with the broadband noise results from the simulation with fully turbulent wall-functions diverging from the experimental results above 5 kHz. The transitional wall-function simulation which emulated the smooth experimental blades underpredicted thrust by 14% and broadband noise by a minimum of 10 dB with an accurately predicted broadband noise trend.

Christopher S Thurman↗
NASA NTRS2019

Identification and Prediction of Broadband Noise for a Small Quadcopter

The growing interest in the noise of small unmanned aircraft systems (sUAS) in operation has motivated this study to characterize and predict broadband rotor noise sources. This paper analyzes the performance and acoustic data collected from two sets of wind tunnel experiments for hover and forward flight operating conditions. The first set of data is a result of testing a representative vehicle configuration of the Straight Up Imaging (SUI) Endurance quadcopter, while the second set of data represents an isolated rotor from the same vehicle. Following the analysis of the empirical data, a broadband noise prediction methodology is employed to compare with the experiments. This methodology uses NASA’s ROTONET and BARC tools to predict blade loading and self-noise at conditions matching the wind tunnel experiments. This methodology is effective at predicting the broadband noise at certain conditions. Furthermore, some predictions are repeated with the inflow conditions calculated by the rotorcraft analysis tool CAMRAD II, which shows improved prediction results for cases with nonuniform inflow. This work confirms some of the unique challenges associated with testing small rotor configurations, explores the limitations of this prediction methodology, and suggests improvements that can be made for future studies.

Nicole A Pettingill↗
NASA NTRS2023

Computational Study of Vortex-Induced Separation for a 5-Bladed Rotor

This work computationally investigated the rotor blade vortex-induced separation recently observed during an aerodynamic rotor test campaign in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel. Two separate approaches (i.e., airfoil modification and blade tip modification) were studied to mitigate the vortex-induced separation. Low-fidelity tools based on blade element momentum theory were shown to mispredict the rotor inflow and were also shown to not capture the vortex-induced separation caused by perpendicular blade-vortex interaction. This misprediction was exploited to isolate the aerodynamic thrust deficit caused by the vortex-induced separation (i.e., 20%) from the thrust deficit due to inflow variation (i.e., 31%). High-fidelity tools were shown to reasonably predict aerodynamic forces within 13% and flow separation when compared to experimental results. The modified airfoil variant of the baseline rotor effectively mitigated the vortex-induced separation while the blade tip modified variant still showed separation, though the size and strength of the vortex was reduced. Acoustic predictions were underpredicted by 10 dB from preliminary measurements taken in the untreated wind tunnel. Broadband noise contributions from different rotor blade sections showed that self-noise due to flow separation and other turbulent boundary layer mechanisms was the dominant noise source for all three rotor cases, followed by blade-wake interaction noise caused by perpendicular blade-vortex interactions.

aerodynamics↗
NASA NTRSDate not supplied

A Psychoacoustic Test for Urban Air Mobility Vehicle Sound Quality

This paper describes a psychoacoustic test in the Exterior Effects Room (EER) at the NASA Langley Research Center. The test investigated the degree to which sound quality metrics (sharpness, tonality, etc.) are predictive of annoyance to notional sounds of Urban Air Mobility (UAM) vehicles (i.e., air taxis). A suite of 136 unique (4.6 second duration) UAM rotor noise stimuli was generated. These stimuli were based on aeroacoustic predictions of a NASA reference UAM quadrotor aircraft under two flight conditions. The synthesizer changed rotor noise parameters such as the blade passage frequency, the relative level of broadband self-noise, and the relative level of tonal motor noise. With loudness constant, the synthesis parameters impacted sound quality in a way that created a spread of predictors both in synthesizer parameters and in sound quality metrics. Forty subjects listened to the suite of UAM noise stimuli in the EER and judged each sound individually on a standard scale of annoyance. Additionally, a subset of the UAM noise stimuli were compared to a reference sound that varied in loudness. From these responses, the relative effect of changes in loudness or changes in other sound quality metrics on annoyance was evaluated. This paper covers background and motivation for the test, details of how the sound stimuli were generated, and details of the test design and execution. Test results investigate how sound quality may affect perceived annoyance to UAM vehicle noise, indicating the importance of sharpness, tonality, impulsiveness, and roughness on annoyance to UAM noise.

UAM↗
NASA NTRSDate not supplied

Best Practices for Predicting Acoustics of a Single Rotor Using the NASA RVLT Conceptual Design Toolchain

To facilitate the development of the Urban Air Mobility (UAM) market, the NASA Revolutionary Vertical Lift Technology Project has created the Conceptual Design Toolchain, a suite of tools developed and/or selected to assist rotorcraft designers in all stages of rotorcraft design. Of particular interest to the UAM noise community are the following two steps in this toolchain: comprehensive analysis and acoustic prediction. Since the UAM application is relatively new, there is a need for a systematic study on how best to utilize these codes. To this end, the current study documents best practices for using the comprehensive analysis codes, CAMRAD II and CHARM, along with the acoustic code AARON. Two single rotors are considered: i) a simple rotor and ii) a rotor that is more exemplary of what UAM designers might use. Best practices are presented for the prediction of both tonal and broadband self-noise, along with the corresponding results. The goal is to provide conceptual designers the tools to conduct accurate noise prediction using the RVLT Conceptual Design Toolchain.

Acoustics↗