Comparison of Acoustic Models and Trajectory Generation Methods for an Acoustically-Aware Aircraft
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Acoustics plays a vital role in maintaining the health, safety, and comfort of crew members aboard the International Space Station (ISS). In order to maintain this livable and workable environment, acoustic requirements have been established to ensure that ISS hardware and payload developers account for the acoustic emissions of their equipment and develop acoustic mitigations as necessary. These requirements are verified by an acoustic emissions test of the integrated hardware. The Amine Swingbed ExPRESS (Expedite the PRocessing of ExperimentS to Space) rack payload creates a unique challenge to the developers in that the payload hardware is transported to the ISS in phases, making an acoustic emissions test on the integrated flight hardware impossible. In addition, the payload incorporates a high back pressure fan and a diaphragm vacuum pump, which are recognized as significant and complex noise sources. In order to accurately predict the acoustic emissions of the integrated payload, the individual acoustic noise sources and paths are first characterized. These characterizations are conducted though a series of acoustic emissions tests on the individual payload components. Secondly, the individual acoustic noise sources and paths are incorporated into a virtual model of the integrated hardware. The virtual model is constructed with the use of hybrid method utilizing the Finite Element Acoustic (FEA) and Statistical Energy Analysis (SEA) techniques, which predict the overall acoustic emissions. Finally, the acoustic model is validated though an acoustic characterization test performed on an acoustically similar mock-up of the flight unit. The results of the validated acoustic model are then used to assess the acoustic emissions of the flight unit and define further acoustic mitigation efforts.
Loudspeakers have been used for acoustic qualification of spacecrafts, reflectors, solar panels, and other acoustically responsive structures for more than a decade. Even though a lot of hardware has been acoustic tested using this method, the nature of the acoustic field generated by controlling an ensemble of speakers with and without the hardware in the test volume has not been thoroughly investigated. Limited measurements from some of the recent speaker tests used to qualify flight hardware have indicated significant spatial variation of the acoustic field within the test volume. Also structural responses have been reported to differ when similar tests were performed using reverberant chambers. Unlike the reverberant chamber acoustic test, for which the acoustic field in most chambers is known to be diffuse except below several tens of Hz where acoustic standing waves and large spatial variations exist, the characteristics of the acoustic field within the speaker test volume has not been quantified. It has only been recently that a detailed acoustic field characterization of speaker testing has been made at Jet Propulsion Laboratory (JPL) with involvement of various organizations. To address the impact of non-uniform acoustic field on structures, a series of acoustic tests were performed using a flat panel and a 3-ft cylinder exposed to the field controlled by speakers and repeated in a reverberant chamber. The analysis of the data from this exercise reveals that there are significant differences both in the acoustic field and in the structural responses. In this paper the differences between the two methods are reviewed in some detail and the over- or under-testing of articles that could pose un-anticipated structural and flight qualification issues are discussed. A framework for discussing the validity of the speaker acoustic testing method with the current control system and a path forward for improving it will be provided.
Based on the acoustic radiation of point source, the physical mechanism of phase-coded acoustical vortices is investigated with formulae derivations of acoustic pressure and vibration velocity. Various factors that affect the optimization of acoustical vortices are analyzed. Numerical simulations of the axial, radial, and circular pressure distributions are performed with different source numbers, frequencies, and axial distances. The results prove that the acoustic pressure of acoustical vortices is linearly proportional to the source number, and lower fluctuations of circular pressure distributions can be produced for more sources. With the increase of source frequency, the acoustic pressure of acoustical vortices increases accordingly with decreased vortex radius. Meanwhile, increased vortex radius with reduced acoustic pressure is also achieved for longer axial distance. With the 6-source experimental system, circular and radial pressure distributions at various frequencies and axial distances have been measured, which have good agreements with the results of numerical simulations. The favorable results of acoustic pressure distributions provide theoretical basis for further studies of acoustical vortices.
Purpose: Previous work has demonstrated the detectability of acoustic waves induced following the irradiation of high density metals with radiotherapy linac photon beams. This work demonstrates the ability to experimentally detect such acoustic signals following both photon and electron irradiation in a more radiotherapy relevant material. The relationship between induced acoustic signal properties in water and the deposited dose distribution is explored, and the feasibility of exploiting such signals for radiotherapy dosimetry is demonstrated. Methods: Acoustic waves were experimentally induced in a water tank via the thermoacoustic effect following a single pulse of photon or electron irradiation produced by a clinical linac. An immersion ultrasound transducer was used to detect these acoustic waves in water and signals were read out on an oscilloscope. Results: Peaks and troughs in the detected acoustic signals were found to correspond to the location of gradients in the deposited dose distribution following both photon and electron irradiation. Signal amplitude was linearly related to the dose per pulse deposited by photon or electron beams at the depth of detection. Flattening filter free beams induced large acoustic signals, and signal amplitude decreased with depth after the depth of maximum dose. Varying the field size resulted in a temporal shift of the acoustic signal peaks and a change in the detected signal frequency. Conclusion: Acoustic waves can be detected in a water tank following irradiation by linac photon and electron beams with basic electronics, and have characteristics related to the deposited dose distribution. The physical location of dose gradients and the amount of dose deposited can be inferred from the location and magnitude of acoustic signal peaks. Thus, the detection of induced acoustic waves could be applied to photon and electron water tank and in vivo dosimetry. This work was supported in part by CIHR grants MOP-114910 and MOP-136774. S.H. acknowledges support by the NSERC CREATE Medical Physics Research Training Network grant 432290.
We investigate the criterion for the acoustic mechanism to work successfully in core-collapse supernovae. The acoustic mechanism is an alternative to the neutrino-heating mechanism. It was proposed by Burrows et al., who claimed that acoustic waves emitted by g -mode oscillations in proto-neutron stars (PNS) energize a stalled shock wave and eventually induce an explosion. Previous works mainly studied to which extent the g -modes are excited in the PNS. In this paper, on the other hand, we investigate how strong the acoustic wave needs to be if it were to revive a stalled shock wave. By adding the acoustic power as a new axis, we draw a critical surface, which is an extension of the critical curve commonly employed in the context of neutrino heating. We perform both 1D and 2D parametrized simulations, in which we inject acoustic waves from the inner boundary. In order to quantify the power of acoustic waves, we use the extended Myers theory to take neutrino reactions into proper account. We find for the 1D simulations that rather large acoustic powers are required to relaunch the shock wave, since the additional heating provided by the secondary shocks developed from acoustic waves is partially canceled by the neutrino cooling that is also enhanced. In 2D, the required acoustic powers are consistent with those of Burrows et al. Our results seem to imply, however, that it is the sum of neutrino heating and acoustic powers that matters for shock revival.
The performance of new acoustic liner concepts are, in general, characterized and assessed in grazing flow rigs early in the development cycle. These test rigs expose an acoustic liner sample, installed on the side wall of the duct, to a grazing flow and incident acoustic field. The process to characterize these liners involves educing the impedance on the wall where the sample is installed and examining the acoustic power attenuation. Standard approaches to computing impedance or power attenuation generally consider only the effects of a 2D shear flow or uniform flow, on the acoustic field. In this study, the objective is to incorporate 3D shear flow effects in the analysis of acoustic mode attenuation in a rectangular duct flow rig. A modal analysis of microphone measurements obtained on the side walls of the duct upstream and downstream of the test section of the rig is developed. A Galerkin projection of the Pridmore-Brown equation is performed with Chebyshev basis functions in order to incorporate the effects of the Mach number profile on the computation of the axial wavenumber of each mode. Measurements of the Mach number profile are obtained in the test rig and used as input to compute the modes. Comparisons made between the sound field computed with traditional convective Helmholtz modes and the new procedure using Pridmore-Brown modes indicate that the computed acoustic field using Pridmore-Brown modes more accurately reconstructs the acoustic signal at each microphone in the array. The mode structure of the lowest-order mode is shown to be significantly impacted by shear flow refraction effects, and higher-order mode structures are also affected at higher frequencies and centerline Mach number. An assessment of the acoustic mode attenuation for two acoustic liner samples demonstrates that the computed mode amplitudes for both the traditional and new approach are in agreement for the lowest-order mode, but discrepancies arise when higher-order modes are the dominant component of the acoustic field.
The performance of new acoustic liner concepts are, in general, characterized and assessed in grazing flow rigs early in the development cycle. These test rigs expose an acoustic liner sample, installed on the side wall of the duct, to a grazing flow and incident acoustic field. The process to characterize these liners involves educing the impedance on the wall where the sample is installed and examining the acoustic power attenuation. Standard approaches to computing impedance or power attenuation generally consider only the effects of a 2D shear flow or uniform flow, on the acoustic field. In this study, the objective is to incorporate 3D shear flow effects in the analysis of acoustic mode attenuation in a rectangular duct flow rig. A modal analysis of microphone measurements obtained on the side walls of the duct upstream and downstream of the test section of the rig is developed. A Galerkin projection of the Pridmore-Brown equation is performed with Chebyshev basis functions in order to incorporate the effects of the Mach number profile on the computation of the axial wavenumber of each mode. Measurements of the Mach number profile are obtained in the test rig and used as input to compute the modes. Comparisons made between the sound field computed with traditional convective Helmholtz modes and the new procedure using Pridmore-Brown modes indicate that the computed acoustic field using Pridmore-Brown modes more accurately reconstruct the acoustic signals at each microphone in the array. The mode structure of the lowest order mode is shown to be significantly impacted by shear flow refraction effects, and higher order mode structures are also effected at higher frequencies and centerline Mach number. An assessment of the acoustic mode attenuation for two acoustic liner samples demonstrates that the computed mode amplitudes for both the traditional and new approach are in agreement for the lowest order mode, but discrepancies arise when higher order modes are the dominant component of the acoustic field.
Abstract Machine learning can predict the timing and magnitude of laboratory earthquakes using statistics of acoustic emissions. The evolution of acoustic energy is critical for lab earthquake prediction; however, the connections between acoustic energy and fault zone processes leading to failure are poorly understood. Here, we document in detail the temporal evolution of acoustic energy during the laboratory seismic cycle. We report on friction experiments for a range of shearing velocities, normal stresses, and granular particle sizes. Acoustic emission data are recorded continuously throughout shear using broadband piezo‐ceramic sensors. The coseismic acoustic energy release scales directly with stress drop and is consistent with concepts of frictional contact mechanics and time‐dependent fault healing. Experiments conducted with larger grains (10.5 μm) show that the temporal evolution of acoustic energy scales directly with fault slip rate. In particular, the acoustic energy is low when the fault is locked and increases to a maximum during coseismic failure. Data from traditional slide‐hold‐slide friction tests confirm that acoustic energy release is closely linked to fault slip rate. Furthermore, variations in the true contact area of fault zone particles play a key role in the generation of acoustic energy. Our data show that acoustic radiation is related primarily to breaking/sliding of frictional contact junctions, which suggests that machine learning‐based laboratory earthquake prediction derives from frictional weakening processes that begin very early in the seismic cycle and well before macroscopic failure.
The ATK Launch Vehicle (ALV-X1) provided an opportunity to measure liftoff acoustic noise data. NASA Marshall Space Flight Center (MSFC) engineers were interested in the ALV-X1 launch because the First Stage motor and launch pad conditions, including a relativity short deflector ducting, provide a potential analogue to future Ares I launches. This paper presents the measured liftoff acoustics on the vehicle and tower. Those measured results are compared to predictions based upon the method described in NASA SP-8072 "Acoustic Loads Generated by the Propulsion System" and the Vehicle Acoustic Environment Prediction Program (VAEPP) which was developed by MSFC acoustics engineers. One-third octave band sound pressure levels will be presented. This data is useful for the ALV-X1 in validating the pre-launch environments and loads predictions. Additionally, the ALV-X1 liftoff data can be scaled to define liftoff environments for the NASA Constellation program Ares vehicles. Vehicle liftoff noise is caused by the supersonic jet flow interaction with surrounding atmosphere or more simply, jet noise. As the vehicle's First Stage motor is ignited, an acoustic noise field is generated by the exhaust. This noise field persists due to the supersonic jet noise and reflections from the launch pad and tower, then changes as the vehicle begins to liftoff from the launch pad. Depending on launch pad and adjacent tower configurations, the liftoff noise is generally very high near the nozzle exit and decreases rapidly away from the nozzle. The liftoff acoustic time range of interest is typically 0 to 20 seconds after ignition. The exhaust plume thermo-fluid mechanics generates sound at approx.10 Hz to 20 kHz. Liftoff acoustic noise is usually the most severe dynamic environment for a launch vehicle or payload in the mid to high frequency range (approx.50 to 2000 Hz). This noise environment can induce high-level vibrations along the external surfaces of the vehicle and surrounding launch facility structures. The acoustic pressure fluctuations will induce severe vibrations in relatively large lightweight structures. Consequently, there is the potential for failure of the structure or attached electrical components. Due to these potential failures, the liftoff acoustic noise is one of the noise source inputs used to determine the vibro-acoustic qualification environment for a launch vehicle and its components.
Launch vehicles experience high acoustic loads during ignition and liftoff affected by the interaction of rocket plume generated acoustic waves with launch pad structures. Application of highly parallelized Computational Fluid Dynamics (CFD) analysis tools optimized for application on the NAS computer systems such as the Loci/CHEM program now enable simulation of time-accurate, turbulent, multi-species plume formation and interaction with launch pad geometry and capture the generation of acoustic noise at the source regions in the plume shear layers and impingement regions. These CFD solvers are robust in capturing the acoustic fluctuations, but they are too dissipative to accurately resolve the propagation of the acoustic waves throughout the launch environment domain along the vehicle. A hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) modeling framework has been developed to improve such liftoff acoustic environment predictions. The framework combines the existing highly-scalable NASA production CFD code, Loci/CHEM, with a high-order accurate discontinuous Galerkin (DG) solver, Loci/THRUST, developed in the same computational framework. Loci/THRUST employs a low dissipation, high-order, unstructured DG method to accurately propagate acoustic waves away from the source regions across large distances. The DG solver is currently capable of solving up to 4th order solutions for non-linear, conservative acoustic field propagation. Higher order boundary conditions are implemented to accurately model the reflection and refraction of acoustic waves on launch pad components. The DG solver accepts generalized unstructured meshes, enabling efficient application of common mesh generation tools for CHEM and THRUST simulations. The DG solution is coupled with the CFD solution at interface boundaries placed near the CFD acoustic source regions. Both simulations are executed simultaneously with coordinated boundary condition data exchange.
Purpose: To measure the acoustic signal generated by a pulsed proton spill from a hospital-based clinical cyclotron. Methods: An electronic function generator modulated the IBA C230 isochronous cyclotron to create a pulsed proton beam. The acoustic emissions generated by the proton beam were measured in water using a hydrophone. The acoustic measurements were repeated with increasing proton current and increasing distance between detector and beam. Results: The cyclotron generated proton spills with rise times of 18 μs and a maximum measured instantaneous proton current of 790 nA. Acoustic emissions generated by the proton energy deposition were measured to be on the order of mPa. The origin of the acoustic wave was identified as the proton beam based on the correlation between acoustic emission arrival time and distance between the hydrophone and proton beam. The acoustic frequency spectrum peaked at 10 kHz, and the acoustic pressure amplitude increased monotonically with increasing proton current. Conclusions: The authors report the first observation of acoustic emissions generated by a proton beam from a hospital-based clinical cyclotron. When modulated by an electronic function generator, the cyclotron is capable of creating proton spills with fast rise times (18 μs) and high instantaneous currents (790 nA). Measurements of the proton-generated acoustic emissions in a clinical setting may provide a method for in vivo proton range verification and patient monitoring.
NoiseSpotter is a passive acoustic monitoring system that characterizes, classifies, and geo-locates anthropogenic and natural sounds in near real time. It was developed with the primary goal of supporting the evaluation of potential acoustic effects of offshore renewable energy projects. The system consists of a compact array of three acoustic vector sensors, which measures acoustic pressure and the three-dimensional particle velocity vector associated with the propagation of an acoustic wave, thereby inherently providing bearing information to an underwater source of sound. By utilizing an array of three vector sensors, the application of beamforming techniques can provide sound source localization, allowing for characterization of the acoustic signature of specific underwater acoustic sources. Here, performance characteristics of the system are presented, using data from controlled acoustic transmissions in a quiet environment and ambient noise measurements in an energetic tidal channel in the presence of non-acoustic flow noise. Data quality is demonstrated by the ability to reduce non-acoustic flow noise contamination, while system utility is shown by the ability to characterize and localize sources of sound in the underwater environment.
Nuclear power plant (NPP) process equipment such as fans, motors, valves, and pumps generate frequent or continuous noise, and deviations from the normal operational sounds made by this equipment can indicate potential issues. These deviations can be identified via automated acoustic anomaly detection, which involves using acoustic sensors (i.e., microphones) alongside detection algorithms to continuously monitor for changes in acoustic signatures. This task is made challenging by the substantial background noise that exists, such as operators opening and closing doors, manipulating valves, and conversing—in addition to typical plant noises. In collaboration with a nuclear power utility partner, this effort assessed the efficacy of acoustic anomaly detection when using a specific acoustic sensor that compresses data into a fixed set of features that are transferable over a standard Internet of Things communication protocol, thereby improving usability but potentially degrading detection performance. Two methods of performing automated acoustic anomaly detection were evaluated: one-class support vector machine (OC-SVM) and isolation forest (iForest). To enable the use of high-quality acoustic data encompassing both normal and anomalous conditions, the study utilized the publicly available Malfunctioning Industrial Machine Investigation and Inspection dataset, which includes real measured acoustic sensor data for a range of equipment types, model numbers, and signal-to-noise ratios (SNRs), along with a benchmark set of detection results. Using this dataset, the methods were tested and then compared against the benchmark results. The results indicated that although the specific acoustic sensor did not enable as rich a feature set extraction, the proposed methods with the limited feature set performed just as well. This provides solid justification for both the methods and the use of the proposed acoustic sensor.