Contribution Of Noise Sources Research Articles

Aeroacoustic investigation of a ducted wind turbine employing bio-inspired airfoil profiles

Ducted wind turbines for residential purposes are characterized by a lower diameter with respect to conventional wind turbines for on-shore applications. The noise generated by the rotor plays a significant role in the overall aerodynamic noise. By making modifications to the blade sections of the wind turbine, we can alter the contributions of aeroacoustic noise sources. This study introduces innovative wind turbine blade designs inspired by owl wing characteristics, achieving significant noise reduction without compromising aerodynamic performance. A three-dimensional scan of an owl wing was first employed to derive a family of airfoils. The airfoils were employed to modify the blade of a referenced wind turbine airfoil section at various positions on the blade span to determine a blade operating more efficiently at the tip-speed ratio of the original one. While maintaining the same aerodynamic performance, the bio-inspired profiles show a more uniform pressure coefficient distribution, considerably decreasing in the noise level. Furthermore, this study makes considerable progress in ducted wind turbine design by obtaining an 8 dB noise reduction and a 12% improvement in sound pressure level. An in-depth aerodynamic examination shows a 6.4% rise in thrust force coefficient and optimized power coefficients, reaching a peak at a tip speed ratio of 8, demonstrating improved energy conversion efficiency. The results highlight the dual advantage of the innovative design: significant noise reduction and enhanced aerodynamic efficiency, offering a promising alternative for urban wind generation.

Investigation on the time/frequency domain prediction model of radiation noise based on the source map

The main exterior noise sources of the high-speed train CRH380AM, such as pantograph and bogie, are studied by using the field test sound imaging data, and the equivalent point source spectrums are obtained here. Then, the prediction model of the exterior train noise is presented by using the moving point sound source radiation model in the time/frequency domain. The correctness and effectiveness of the model are verified by the field test data. The radiation contribution of local noise sources is analyzed by using this model, and the following conclusions are obtained: The largest noise sources are in the bogie areas, which provide the radiation contribution rate of about 80% when the train speed is above 300 km/h. The variation of the maximum radiation noise level can be ignored when the train formation or the pantograph lifting position is changed. The model can evaluate the radiated noise of similar vehicles quickly and accurately, which provides technical reference for acoustic optimization design of high-speed train.

Beamformed Envelope Spectrum of acoustic signals for bearing diagnostics under varying speed conditions

Rolling element bearings are critical components in rotating machinery. Early damage detection methods are usually based on vibration signals from accelerometers. Microphones provide an interesting alternative, as they acquire system level information and could allow reducing the number of sensors. However, the bearing signature is mixed in these signals with noise coming from other nearby sources. Beamforming methods can enhance the targeted bearing signature while suppressing the contributions of other noise sources in the environment. The bearing impulses related to the localized surface defects are function of speed, and thus under varying speed conditions become nonstationary. Angular resampling based methods are therefore needed to compensate for the speed fluctuations in order to detect bearing damages. The goal of this paper is to propose a method for bearing diagnostics under varying speed conditions using an array of microphones and an encoder. The method is based on angular resampling of the microphone signals in function of the shaft speed and enhancing them using delay-sum beamforming based on the known positions of the microphones relative to the tested bearing. The method is validated on an experimental dataset acquired at a KU Leuven bearing test rig, under varying rotating speed conditions.

Contribution of jet flow noise sources to the far-field sound power

Jet noise is the dominant source of noise during aircraft takeoff. This study uses direct numerical simulation (DNS) data of subsonic jet flow obtained from computational fluid dynamics (CFD) simulations to perform acoustic analyses. The non-negative contribution technique (NNC) is employed to identify aeroacoustic sources of jet noise with the greatest contribution to far-field sound power. The NNC technique uses the Lighthill source distribution with an acoustic impedance matrix constructed from radiation kernels of the free-field Green’s function. The fast multipole method (FMM) is integrated with the NNC technique to reduce computational cost arising from decomposition of the acoustic impedance matrix as well as from the high number of CFD grids associated with the DNS data. The results showed that the dominant aeroacoustic sources are associated with the first component of the Lighthill tensor (T11) and are concentrated along the jet centerline, downstream of the nozzle exit.

Analysis of the Precision of CSST Time-domain Photometric Observation

The Chinese Space Station Telescope (CSST) is the first space optical survey telescope of China. It will perform scientific observations and yield important scientific results, e.g. multi-color photometry to find and characterize exoplanets. The precision of time-domain photometry affected by various astrophysical and instrument noises is crucial for exoplanet detection and characterization. This paper constructs a time-domain model to simulate the stellar signal and various noises based on the main technical parameters of CSST published so far. The precision of photometry is analyzed by modeling the signal and noises for an example of the gazing mode in the i-band. We investigate and discuss the contribution of various noise sources in aperture photometry, especially the jitter noise caused by pointing jitter and pixel response inhomogeneity. The test results also provide the recommended aperture sizes for photometry. Jitter noise can be suppressed by reducing jitter amplitude, uniforming pixels, or using differential photometry with reference stars. Our simulation results have broad applications, including precision predictions for time-domain photometry, the refinement of CSST instrumental specifications, the evaluation of exoplanet detection capabilities, and improvements in data reduction progress for CSST.

Large Eddy Simulation of the ACAT1 fan stage for broadband noise prediction

A numerical study is carried out to assess the aerodynamic and noise radiation specific features of the ACAT1 fan stage, which was tested in the framework of the European project TurbonoiseBB. This study deals with the prediction of the broadband noise radiated by the fan stage at approach conditions, and particularly focuses on the rotor–stator interaction (RSI) noise, which results from the impact of the fan wakes onto the outlet guide vanes (OGV). To this end, two wall-modeled Large Eddy Simulations (LES) with different levels of mesh refinement have been performed on the full fan-OGV stage. The finer mesh significantly improved the aerodynamic predictions in terms of mean flow profiles, but also in terms of RMS profiles and velocity spectra, for which significant disparities are highlighted for the coarser LES. Only slight disparities regarding the turbulent content of the flow remain for the finer LES. The typical flow features at approach conditions are examined and the noise sources on both the stator and the rotor are analyzed, revealing the presence of additional broadband noise sources. Noise predictions are performed by using the free-field Ffowcs Williams and Hawkings (FW-H) analogy, and Goldstein’s in-duct acoustic analogy informed with the pressure fluctuations recorded on the stator and rotor surfaces. FW-H predictions of the stator noise, though well recovering the shape of the experimental spectra, overestimate the radiated noise especially upstream of the fan. Using the finer simulation data substantially reduces the gap with the measurements. Accounting for the duct effect on the sound propagation, further improves the predictions in terms of absolute levels, leading to a good agreement between the finer simulation and the noise measurements. The breakdown of the different stator noise source contributions, in conjunction with rotor broadband noise predictions made it possible to confirm the presence of additional significant broadband noise sources, questioning the common assumption considering the RSI sources as the only dominant fan noise mechanism at approach conditions.

Study on Noise Source Contribution of Converter Cabinet Based on Transfer Path Analysis Test

There are fan noise and transformer noise sources inside the converter cabin which may bring the environmental noise pollution through airborne or structural borne paths. In order to identify the contribution of each source and its path, transfer path analysis test was performed. Take full load working condition at full speed as an example, the contributions of fan air borne noise, fan structural borne noise, transformer air borne noise and transformer structural borne noise are 88.33%, 3.79%, 7.37% and 0.51% respectively. The contribution of air borne noise is 95.70% more than that of structural borne noise which is 4.30%. In the end the aerodynamic noise simulation of converter cabin is compared with the experimental result which is in good coincidence, this result can also verifies the noise source contribution result.

Intracochlear noise-induced vibrations

When designing an engineered electroacoustic sensor, a key question is “what is the lowest level sound that can be sensed?” To answer this, we design to achieve a desired input referred noise. In the cochlea, there are many sources of internal noise, such as Johnson noise arising from membrane conductances, clatter noise in channels, and thermoviscous damping that will conspire to cause vibrational responses in the absence of external stimulus. Noise can dramatically affect our ability to sense desired sounds. Experimental and theoretical cochlear mechanics has focused on determining the sensitivity of the cochlea. However, to our knowledge, there is only one set of published measurements of the displacement response of the cochlea in quiet (the levels are low, below 1 atto-meter2 per Hz), and no simulations in a global cochlear model of the noise response. We introduce a method for predicting the global response to noise from electromotile outer hair cells in the cochlea for small fluctuations about equilibrium using our finite-element based numerical model. Furthermore, we show the relative contribution of different noise sources (in particular, channel noise versus conductance noise) and the spatial distribution of the response to these sources.

Investigation of electric vehicle noise sources on low-noise road surfaces

Electric vehicles (EVs) constitute an increasing share of the vehicle fleet, in particular regarding light vehicles. This ratio may be significantly enhanced in urban areas that favour access to low-emission vehicles. Acknowledged to be quieter than conventional vehicles due to a lower propulsion noise, EVs feature a comparatively heightened tyre-road noise contribution, further reduction of which can be achieved by selecting appropriate low-noise road surfaces. These factors may result in modified noise source distributions on the vehicles. In the framework of the LIFE E-VIA project, noise source contributions have been investigated on several light EVs from different segments on a reference ISO road surface, by using a microphone array with dedicated processing. Wide ranges of speeds and driving conditions were considered. In a second step, particular focus has been placed on the road surfaces, comparing the noise sources of selected EVs either driving on the ISO road surface or on low-noise prototypes optimized for EVs and developed within the project. These are two similar versions of a very thin asphalt concrete 0/6, one containing crumb rubber. The presentation gives an overview of the EV noise source behaviour and their ranking with regard to the various situations tested in the project.

Automated identification and assessment of environmental noise sources

Noise pollution is one of the major health risks in urban life. The approach to measurement and identification of noise sources needs to be improved and enhanced to reduce high costs. Long measurement times and the need for expensive equipment and trained personnel must be automated. Simplifying the identification of main noise sources and excluding residual and background noise allows more effective measures. By spatially filtering the acoustic scene and combining unsupervised learning with psychoacoustic features, this paper presents a prototype system capable of automated calculation of the contribution of individual noise sources to the total noise level. Pilot measurements were performed at three different locations in the city of Ljubljana, Slovenia. Equivalent sound pressure levels obtained with the device were compared to the results obtained by manually marking individual parts of each of the three measurements. The proposed approach correctly identified the main noise sources in the vicinity of the measurement points.

Effect of sound insulation on noise reduction in an agricultural tractor cab

Tractor cab interior noise is a risk factor that degrades operators’ work performance and threatens their health; therefore, the noise must be reduced to ensure farmworkers’ safety and efficiency. Cab interior noise can be classified as structure-borne noise and air-borne noise. Structure-borne noise has been extensively studied. However, although air-borne noise greatly contributes to cab interior noise, detailed frequency-domain analyses have not been performed. In this study, the components of cab interior noise were identified in the frequency domain through an order analysis, which helped improve the sound insulation of the cab and reduce the effects of air-borne noise. A test was performed while driving a tractor on a chassis dynamometer in a semi-anechoic chamber for reproducible measurement and evaluation. The A-weighted sound pressure was transformed by a fast Fourier transform algorithm, and its order was tracked by the engine speed signal. In addition, a direct path was identified by acoustic images using a sound camera. The contributions of major noise sources were identified through an order analysis. We proved that air-borne noise significantly contributes to the interior noise of tractor cabs and that improvement of the cab sound insulation is an effective noise-reduction technique.

Enhancing noise sources in stationary-phase zones for accurate phase-velocity estimation of high-frequency surface waves

Passive surface-wave methods are appealing tools for their ability to noninvasively obtain shear-wave velocity with high accuracy and low costs. A linear array of stations is widely adopted in urban areas for its convenient deployments and efficient utilization of ambient noise energy from stationary-phase zones (SPZs), which contributes the most to surface-wave retrieval. However, noise sources in nonstationary-phase zones may threaten the reliability of velocity estimation when they possess strong energy. To obtain reliable phase-velocity estimation of high-frequency surface waves (>1 Hz), we enhance the contribution of noise sources in SPZs by using the multichannel-coherency-weighted stack (MCWS) method for the stacking of noise crosscorrelation functions and dispersion spectra. We model a nonuniform source distribution with strong offline sources. The seismic interferometry (SI) and passive multichannel analysis of surface waves (PMASW) methods overestimate velocities at lower frequencies (<5 Hz), whereas phase velocities of short wavelengths are relatively accurate. The true velocities of short wavelengths are then set as the velocity scanning range for MCWS, and the waves whose apparent velocities lie within the scanning range would be emphasized by MCWS. Noise sources in SPZs are enhanced because the apparent velocities of waves from other noise sources are higher and not in the scanning range. After using MCWS, the phase-velocity estimations of SI and PMASW are consistent with the theoretical dispersion curve. A field data example at a crossroads demonstrates that uneven source distributions might cause serious artifacts and the feasibility of our method is again confirmed. In addition, the enhancement of noise sources in SPZs is verified through noise source distribution imaging by a matched field processing technique.

Generation–recombination noise in uniformly doped semiconductors with contacts of finite surface recombination velocities

The formula for the voltage noise spectrum due to generation–recombination (G–R) rate fluctuations is derived for uniformly doped majority-carrier n-type semiconductor samples with contacts of finite surface recombination velocities. In the derivation of the formula, a new boundary condition with finite surface recombination velocities considered is used instead of the ohmic boundary condition. The G–R voltage noise spectra are calculated to become saturated and equal in the high electric field region irrespective of surface recombination velocities. However, the behaviors of slow surface recombination velocities in the low electric field region differ from those of fast ones. The profiles of the electron density fluctuations of slow ones differ significantly from those of fast ones in the low-field region. In the high field region, a steep rise in the magnitude of the electron density fluctuation occurs near the voltage contact toward which electrons drift. The various location dependencies of the contribution of noise sources to the voltage power spectral density are also derived for low and high field regions as well as low and high surface recombination velocities, and analytical expressions are developed for the voltage power spectral densities and electron density fluctuations.

Re-entry high speed commercial air vehicles: Improving the environmental eligibility at take-off and approach accounting the flight safety restrictions

In addition to the flight safety of re-entry high speed commercial air vehicles their environmental eligibility come into particular important issue due to environmental requirements for commercial subsonic aviation are becoming more stringent. During the re-entry take-off and approach cycles the vehicles are a subject to almost the same type of environmental requirements as the commercial subsonic aviation. The requirements are primarily concern the limitations of community noise and engine exhaust emissions levels, as well as the sonic boom level (for commercial supersonic aviation). Meeting the requirements may significantly complicate the development, certification and further operation of the vehicles. The paper discusses one of the potential ways of increasing the acoustic eligibility of the vehicles during take-off and approach cycles at using the some number of turbofan engines as part of the propulsion system. The way is based on the creation of a special control of turbofan engines thrust/power (so called low noise thrust management) accounting the provision of flight safety restrictions. The assessment of the acoustic impact (community noise) of the vehicle is carried out taking into account the contribution of major noise sources of turbofan engines, i.e. the fan and exhaust jet. The impact of two parameters of turbofan engines such as the bypass ratio and the number of turbofan engines was evaluated. The variation of these parameters was performed under the condition meeting the specified mission requirements in term of the required field (runway) length and the approach speed. The estimations shown that using the created low noise turbofan engine thrust management at the take-off and approach may significantly increase the acoustic eligibility of the vehicles using turbofan engines.

Performance of the KAGRA detector during the first joint observation with GEO 600 (O3GK)

Abstract KAGRA, the kilometer-scale underground gravitational-wave detector, is located at Kamioka, Japan. In April 2020, an astrophysics observation was performed at the KAGRA detector in combination with the GEO 600 detector; this observation operation is called O3GK. The optical configuration in O3GK is based on a power-recycled Fabry–Pérot–Michelson interferometer; all the mirrors were set at room temperature. The duty factor of the operation was approximately 53%, and the displacement sensitivity was approximately 1 × 10−18 ${\rm m}/\sqrt{\rm {Hz}}$ at 250 Hz. The binary-neutron-star (BNS) inspiral range was about 0.6 Mpc. The contributions of various noise sources to the sensitivity of O3GK were investigated to understand how the observation range could be improved; this study is called a “noise budget”. According to our noise budget, the measured sensitivity could be approximated by adding up the effect of each noise. The sensitivity was dominated by noise from the sensors used for local controls of the vibration isolation systems, acoustic noise, shot noise, and laser frequency noise. Further, other noise sources that did not limit the sensitivity were investigated. This paper provides a detailed account of the KAGRA detector in O3GK, including interferometer configuration, status, and noise budget. In addition, strategies for future sensitivity improvements, such as hardware upgrades, are discussed.

Analysis of Noise in Current Mirror Circuits Based on CNTFET and MOSFET

In this paper we present a comparative analysis of noise performance of Carbon Nanotube Field Effect Transistors (CNTFETs) and MOSFET, through the design of two circuits: a basic current mirror and self-bias current mirror, each time with different current values. For this aim we use a semi-empirical compact CNTFET model, already proposed by us, including noise source contributions, and the BSIM4 model for MOS device. Then we analyze and discuss the spectral density of output noise current, comparing the two considered technology. The software used is Advanced Design System (ADS), compatible with the Verilog A programming language.

48 -cm-long room-temperature cavities in vertical and horizontal orientations for Sr optical clock.

The development of an optical clock with ultimate accuracy and stability requires lasers with very narrow linewidths. We present two ultrastable laser systems based on 48-cm-long Fabry-Perot cavities made of ultralow expansion glass in horizontal and vertical configurations operating at 698 nm. Fractional frequency instability of the beat signal between the two lasers reaches 1.6×10-15 at the averaging time of 1 s. We experimentally characterized the contribution of the different noise sources (power fluctuations, residual amplitude modulation, the Doppler noise, and sensitivity to the shock impact) and found that in our case the laser frequency instability to a large extent is determined by an optoelectronic feedback loop. Although the vertical configuration was easier to manufacture and transport, it is much more sensitive to acoustics and horizontal accelerations compared to the horizontal one. Both laser systems were transported over a 60 km distance from the Lebedev Physical Institute to the All-Russian Scientific Research Institute for Physical-Engineering and Radiotechnical Metrology (VNIIFTRI), where they serve as local oscillators for spectroscopy of the clock transition in the recently developed strontium optical clock.

Tagging ocean soundscapes with machine learning and topological approaches

With a multitude of sources simultaneously contributing to the ambient ocean soundscape, it is important to disaggregate noise source contributions for better monitoring and assessing noise impacts. Our work adopts a modular set of neural networks and topological pipelines to analyze multiple representations of time-series samples of the ambient ocean noise. Specifically, a convolutional neural network (CNN) is used to broadly tag the presence of local shipping and marine mammal vocalizations from spectrogram representations. Multiple approaches are investigated using topological data analysis to predict a class label of the ship hull type or specific marine mammal species using the audio data as input. The datasets used in training, testing, and validation comprise hydrophone recordings across varying sensors and ocean environments to address the wide variation in ambient background noise and propagation paths. Algorithm performance is characterized by classification accuracy on labeled data. This approach demonstrates a generalized tagging cabilitility of the presence of marine mammals and local shipping activity.

Mapping the seismic noise field in Europe: spatio-temporal variations in wavefield composition and noise source contributions

SUMMARYWe study spatial and temporal characteristics of the microseismic noise field across Europe. Rather than focusing on the areas of noise generation, the scope of this work is to characterize, at the scale of Europe, the spatio-temporal evolution of the noise wavefield that results from the interplay of the seismic noise sources and the propagation effect. To that end, we perform single station analysis in three period bands (PB1: 2.5−5 s; PB2: 5−10 s and PB3: 10−20 s) using three-component seismic data recorded by ∼1000 broad-band stations in the time period 2011–2019. We calculate, for each period band, station and day, a set of parameters that are practically possible to apply to a large data set, yet yields insight into the spatio-temporal evolution of the wavefield. These parameters are: the total energy level, the dominant period of the Primary and Secondary microseismic peaks, the horizontal direction with the most energy, the horizontal direction of the dominant Rayleigh waves and the square root of the energy ratio between the horizontal and vertical components. The analysis of these parameters shows that the noise field in Europe is dominated by surface waves from the North Atlantic Ocean with, in PB1 and PB2, an additional and significant contribution from the eastern part of the Mediterranean Sea. The relative contribution of these two source regions depends on the season, the influence of the eastern Mediterranean Sea being strongest in summer. The map of the peak period of the Primary and Secondary microseismic peaks indicates that the relative contribution of these two source regions is frequency dependent: the period of the Primary microseismic peak exhibits an overall increase with distance to the North Atlantic Sources, because of stronger attenuation of high-frequency wave contents. By contrast, the period of the Secondary microseismic peak is simultaneously influenced by sources in both the North Atlantic Ocean and eastern Mediterranean Sea. We show that in both microseismic peaks (PB2 and PB3), the wavefield is dominated by Love waves, as the horizontal components have the highest energy at approximately 90° angle to the direction of elliptical polarization. Moreover, our results show that lateral heterogeneities in the crust have a major influence on the noise field. In particular, the propagation directions of Love and Rayleigh waves show strong dependency on location (but not on time of year), with very sharp boundaries for example at the edge of the Alps. Thus, the scattering that takes place in the heterogeneous Alpine crust partly randomizes the directions of the microseismic wavefield in particular in PB1 and PB2. Finally, we show that the temporal evolution of the amplitude ratio between the horizontal and vertical components reflects the relative amounts of surface waves from the North Atlantic Ocean with respect to body waves from sources in the Southern Hemisphere. Thus, this ratio can be used as a proxy to identify time periods where body waves are significant in the noise wavefield.

Identification of Multiple Noise Sources Improves Estimation of Neural Responses across Stimulus Conditions.

Most models of neural responses are constructed to reproduce the average response to inputs but lack the flexibility to capture observed variability in responses. The origins and structure of this variability have significant implications for how information is encoded and processed in the nervous system, both by limiting information that can be conveyed and by determining processing strategies that are favorable for minimizing its negative effects. Here, we present a new modeling framework that incorporates multiple sources of noise to better capture observed features of neural response variability across stimulus conditions. We apply this model to retinal ganglion cells at two different ambient light levels and demonstrate that it captures the full distribution of responses. Further, the model reveals light level-dependent changes that could not be seen with previous models, showing both large changes in rectification of nonlinear circuit elements and systematic differences in the contributions of different noise sources under different conditions.