Noise Spectrum Research Articles

The transport of self-propelled ellipsoidal particles confined in 2D smooth corrugated channel

Directed transport of self-propelled ellipsoidal particles confined in a smooth corrugated channel with asymmetric potential and Gaussian colored noise is investigated. Effects of the channel, potential and colored noise on the system are discussed. Large noise intensity in the x-axis direction inhibits the transport in [Formula: see text] and [Formula: see text] directions. The directed transport speed [Formula: see text] has a maximum with increasing noise intensity in the y-axis direction. Proper size of the bottleneck is good for the directed transport of the ellipsoidal particles, but large or small size of bottleneck inhibits this directed transport. The transport reverse phenomenon appears with increasing load and self-propelled speed. Confined spherical particle is easier to produce directed transport than confined needlelike ellipsoid particle.

Aerodynamic noise analysis of tilting rotor in edgewise flow conditions

This paper presents a comprehensive experimental analysis of the noise characteristics of an isolated tilt-rotor system under edgewise flight conditions. The investigation explores the effect of rotor tilt on noise and aerodynamics using flow velocity, thrust, and far-field noise measurements. Flow field results show that as the tilting angles vary, there is a change in speed over the rotor blade surface, which influences vortex formation and wake attributes. The far-field noise spectra revealed a significant decrease in sound pressure level with increasing tilt angle, predominantly evident in both the high-amplitude tonal peaks and the broadband signal within the low-to-mid frequency range. The directivity patterns of the overall sound pressure level also demonstrated a reduction in magnitude with the tilting of the rotor. This reduction was observed consistently across all top-plane observation points, with a monopole directivity trend. Meanwhile, in the side plane array, the decrease was primarily evident above the plane of rotation with a dipole directivity pattern. The radiation direction at which the minimum sound pressure level occurs was identified near the rotation plane, irrespective of the tilt angle. Furthermore, the time-dependent noise analyses revealed dominant and persistent signal characteristics at the blade passing frequency, whereas the mid-frequency range exhibited more intermittent behaviour, and the high-frequency range indicated transient characteristics.

Mechanistic study of noise source and propagation characteristics of flow noise of a submarine

Flow noise, part of hydrodynamic noise, significantly impacts the stealth capabilities of submarines. Investigating the noise source location and formation mechanism of flow noise is crucial for enhancing submarine stealth performance. This study uses large eddy simulation to examine the evolution of vortex structure in the SUBOFF submarine. The propagation of far-field noise from dipole and quadrupole noise sources of the SUBOFF is calculated, by rationally constructing a permeable integral surface in conjunction with the Ffowcs-Williams and Hawkings and “Collapsing-Sphere” formulations. The numerical results for both flow and acoustic fields are consistent with experimental data and previous numerical findings. Sail and rudder are the predominant dipole noise sources, due to turbulence effects from vortex shedding. The permeable integral surface effectively captures the quadrupole noise source. The quadrupole noise in the 2 kHz frequency range contributes 17 % to 26 % of the total noise energy. The location of the quadrupole noise source and its generation mechanism is explored, through the evolution of the vortex structure and the Lamb vector amplitude. Approximate scaling laws for far-field dipole and quadrupole noise spectra are given, thus illustrating the general laws in the frequency domain of the far-field noise.

Peculiarities of the SCLC Effect in Gate‐All‐Around Silicon Nanowire Field‐Effect Transistor Biosensors

AbstractHigh‐quality liquid gate‐all‐around (LGAA) silicon nanowire (NW) field‐effect transistor (FET) biosensors are fabricated and studied their properties in 1 mm phosphate‐buffered saline solution with pH = 7.4 using transport and noise spectroscopy. At small VDS, the conventional current behavior of FET with a linear dependence on voltage is registered in the output current‐voltage (I‐VM) characteristics with M = 1. At drain‐source voltage VDS > 0.6 V, the I‐V characteristics with stronger power M are revealed. It is shown that the current in LGAA NW FETs follows current proportional to voltage in power M = 4 dependence on small liquid gate voltages. Transport and noise spectroscopy analyses demonstrate that the obtained results are associated with the space‐charge‐limited current (SCLC) effect. Moreover, a strong two‐level random telegraph signal (RTS) is found in the region corresponding to SCLC at VDS values exceeding 0.6 V. The RTS related to single trap phenomena results in a well‐resolved Lorentzian component of noise spectra. The results demonstrate that the SCLC and two‐level RTS phenomenon are correlated effects. They should be taken into account during the development of single‐trap‐based devices, including biosensors.

Aerodynamic noise and its reduction of the marine gas turbine air exhaust system.

The aerodynamic noise of pipelines is an important part of the noise of a ship's system. This paper conducted numerical investigations on the flow and acoustic characteristics of the marine gas turbine exhaust system. The near-field and far-field acoustic characteristics of the internal flow noise of the exhaust system are calculated by employing the Möhring's sound analogy method. In addition, the far-field acoustic characteristics of the external jet flow noise of the exhaust system are calculated by employing the stochastic noise generation and radiation (SNGR) method. Two kinds of protrusions are added to the main nozzle outlet to achieve noise reduction. The internal sound field of the marine exhaust system is dominated by low frequency sound sources, which are more obvious as the exhaust mass flow rate decreases. As for the external sound field of the marine exhaust system, the peak frequency of the far-field noise spectrum decreases with the decrease in the exhaust mass flow rate. The eight periodic protrusions perform better in reducing the internal aerodynamic noise of the exhaust system, while the five aperiodic protrusions perform better in reducing the external jet noise of the exhaust system.

A study on the hydroacoustic characterisation of a cavitating propeller by dynamic adaptive mesh refinement technique

Underwater radiated noise (URN) of a marine propeller has received significant interest in recent decades due to its implications on marine fauna. Therefore, an accurate prediction of URN at an early stage of the propeller design is becoming imperative. This study presents a numerical investigation into the noise prediction of a marine propeller, including cavitation and a comparison with experimental test results obtained from the URN database from the King's College D (KCD) standard propeller series. Amongst the propellers tested in the series, the member KCD-193 was chosen to scrutinise in this study due to the significant variance of the cavitation types experienced by this propeller member and consequent characteristic variations observed in its URN spectral response. Numerical URN predictions of different flow conditions, represented by the advance coefficient and cavitation number, were conducted to investigate their effects on the noise spectrum. These predictions were compared with the experimental results to enable interpretation of the impact of various aspects of the simulation on URN prediction accuracy. In this investigation, one of the most prominent noise sources, tip-vortex cavitation (TVC), was identified as a critical aspect that needs to be captured by the numerical simulations for accurate URN predictions using CFD simulations. The influence of TVC on the spectrum was observed to be significant. The inception and stable presence of TVC dominated the frequency response of the broadband hump. In order to address this, a systematic adaptive mesh refinement strategy was implemented based on the vortex criterion to solve the flow characteristics in the propeller slipstream accurately. To further complement this task, a correlation between the cavitation bubble growth and collapse phenomenon by the sensitivity of the broadband hump on the spectrum was established based on the experimental results. The central frequency of the broadband hump was observed to vary with the advance coefficient and cavitation number. The reduction in the cavitation number resulted in a shift of this hump towards lower frequencies. The URN level of the hump decreased slightly in the high frequency by the reduction in the advance coefficient and the developing cavitation, demonstrating the cushioning effect on the spectrum. An accurate assessment of the noise spectrum, as far as numerical predictions are concerned, particularly on the broadband hump frequency bandwidth, was directly associated with the resolution of the TVC.

Wavelet Analysis of Differential TEC Measurements Obtained Using LOFAR

AbstractRadio interferometers used to make astronomical observations, such as the LOw Frequency ARray (LOFAR), experience distortions imposed upon the received signal due to the ionosphere as well as those from instrumental errors. Calibration using a well‐characterized radio source can be used to mitigate these effects and produce more accurate images of astronomical sources, and the calibration process provides measurements of ionospheric conditions over a wide range of length scales. The basic ionospheric measurement this provides is differential Total Electron Content (TEC, the integral of electron density along the line of sight). Differential TEC measurements made using LOFAR have a precision of <1 mTECu and therefore enable investigation of ionospheric disturbances which may be undetectable to many other methods. We demonstrate an approach to identify ionospheric waves from these data using a wavelet transform and a simple plane wave model. The noise spectra are robustly characterized to provide uncertainty estimates for the fitted parameters. An example is shown in which this method identifies a wave with an amplitude an order of magnitude below those reported using Global Navigation Systems Satellite TEC measurements. Artificially generated data are used to test the accuracy of the method and establish the range of wavelengths which can be detected using this method with LOFAR data. This technique will enable the use of a large and mostly unexplored data set to study traveling ionospheric disturbances over Europe.

Measuring Community Response to Noise-Factors Affecting the Results of Annoyance Surveys.

Social surveys are conducted to determine how annoyed people are in a certain noise situation. The results are typically presented as exposure-response curves showing the percentage of the area population that are highly annoyed as a function of the noise exposure level. It is a well-known fact that the survey results are not only dependent on the accumulated noise exposure, DNL, DENL, or similar, but also on various other factors such as maximum levels, exposure patterns, noise spectra, etc. A re-analysis of previously reported surveys shows that the results are also, to a large extent, dependent on survey-specific factors like the wording of the annoyance questions, how the questionnaires are presented, response scales, methods of scoring highly annoyed, etc. This paper discusses and quantifies the influence of such factors and suggests ways of comparing results from surveys that have been conducted according to different protocols and different analysis methods.

Colored Noise in PPO: Improved Exploration and Performance through Correlated Action Sampling

Proximal Policy Optimization (PPO), a popular on-policy deep reinforcement learning method, employs a stochastic policy for exploration. In this paper, we propose a colored noise-based stochastic policy variant of PPO. Previous research highlighted the importance of temporal correlation in action noise for effective exploration in off-policy reinforcement learning. Building on this, we investigate whether correlated noise can also enhance exploration in on-policy methods like PPO. We discovered that correlated noise for action selection improves learning performance and outperforms the currently popular uncorrelated white noise approach in on-policy methods. Unlike off-policy learning, where pink noise was found to be highly effective, we found that a colored noise, intermediate between white and pink, performed best for on-policy learning in PPO. We examined the impact of varying the amount of data collected for each update by modifying the number of parallel simulation environments for data collection and observed that with a larger number of parallel environments, more strongly correlated noise is beneficial. Due to the significant impact and ease of implementation, we recommend switching to correlated noise as the default noise source in PPO.

Simulating the Effect of Environmental Change on Evolving Populations.

This study uses evolutionary simulations to explore the strategies that emerge to enable populations to cope with random environmental changes in situations where lifetime learning approaches are not available to accommodate them. In particular, it investigates how the average magnitude of change per unit time and the persistence of the changes (and hence the resulting autocorrelation of the environmental time series) affect the change tolerances, population diversities, and extinction timescales that emerge. Although it is the change persistence (often discussed in terms of environmental noise color) that has received most attention in the recent literature, other factors, particularly the average change magnitude, interact with this and can be more important drivers of the adaptive strategies that emerge. Moreover, when running simulations, the choice of change representation and normalization can also affect the outcomes. Detailed simulations are presented that are designed to explore all these issues. They also reveal significant dependences on the associated mutation rates and the extent to which they can evolve, and they clarify how evolution often leads populations into strategies with higher risks of extinction. Overall, this study shows how modeling the effect of environmental change requires more care than may have previously been realized.

Enhancing Arabic Sign Language Interpretation: Leveraging Convolutional Neural Networks and Transfer Learning

In a world essentializing communication for human connection, the deaf community encounters distinct barriers. Sign language, their main communication method is rich in hand gestures but not widely understood outside their community, necessitating interpreters. The existing solutions for sign language recognition depend on extensive datasets for model training, risking overfitting with complex models. The scarcity of details on dataset sizes and model specifics in studies complicates the scalability and verification of these technologies. Furthermore, the omission of precise accuracy metrics in some research leaves the effectiveness of gesture recognition by these models in question. The key phases of this study are Data collection, Data preprocessing, Feature extraction using CNN and finally transfer learning-based classification. The purpose of utilizing CNN and transfer learning is to tap into pre-trained neural networks for optimizing performance on new, related tasks by reusing learned patterns, thus accelerating development and improving accuracy. Data preprocessing further involves resizing of images, normalization, standardization, color space conversion, augmentation and noise reduction. This phase is capable enough to prune the image dataset by improving the efficiency of the classifier. In the subsequent phase, feature extraction has been performed that includes the convolution layer, feature mapping, pooling layer and dropout layer to obtain refined features from the images. These refined features are used for classification using ResNet. Three different datasets are utilized for the assessment of proposed model. The ASL-DS-I Dataset includes a total of 5832 images of hand gestures whereas, ASL-DS-II contains 54,049 images and ASL-DS-III dataset includes 7857 images adopted from specified web links. The obtained results have been evaluated by using standard metrics including ROC curve, Precision, Recall and F-measure. Meticulous experimental analysis and comparison with three standard baseline methods demonstrated that the proposed model gives an impressive recognition accuracy of 96.25%, 95.85% and 97.02% on ASL-DS-I, ASL-DS-II and ASL-DS-III, respectively.

Aerodynamic investigation of the turbulent flow past a louvered-fin-and-tube automotive heat exchanger

Turbulent flow past a radiator contributes to noise emission when interacting with a downstream cooling fan. This study examines turbulent flow characteristics downstream of a radiator, focusing on turbulence production, dissipation, non-homogeneity, and anisotropy. We assess turbulence models based on isotropy and homogeneity for noise prediction in real applications. Results show significant non-homogeneity due to the radiator grid’s wakes, extending downstream to a region where the fan would be located. Flow in this region trends toward isotropy, especially when considering a downstream circularly-holed wood panel mimicking the flow contraction caused by a fan casing. The radiator core’s fins and louvers break down vortical structures more than generating large eddies, as reported in studies involving heat exchangers with larger gaps between cooling pipes. The von Kármán turbulence model approximates the experimental spectrum, but caution is needed with rapid flow acceleration. This investigation enhances our understanding of turbulence characteristics in the vicinity of radiators with implications for noise spectrum prediction and modeling in such systems.

Acoustic performance evaluation of railway boundary walls using a computational fluid dynamics-based simulation approach.

Railway noise has become a significant concern for trackside residents due to increased volume of high-speed passenger and freight train traffic. To address this, active measures, such as reducing noise at the source, and passive measures, such as installing noise barriers along the transmission path, are widely being used. In urban areas, railway boundary walls are constructed to prevent encroachments of railway lands and to avoid pedestrian trespassing of railway tracks. This study aims to evaluate the effectiveness of such a boundary wall for reducing noise and proposes an improved alternative through computational fluid dynamics (CFD) simulations. Various noise barriers with different geometry, shape, and surface materials were simulated and validated with the field conditions based on a rectangular wall of height 2.75 m. Noise attenuation was evaluated by measuring railway noise spectra at different positions, including 0.5 m in front and behind the barrier and at the facade of the residential area. The insertion loss based on field measurements for a rectangular barrier of height 2.75 m was observed to be 5.2 dBA. The simulation results indicated a positive correlation between barrier height and insertion loss, with a maximum attenuation of 17 dBA achieved with a barrier of height 6 m. The most effective noise barrier for reducing railway noise was a T-shaped barrier with a height of 6 m and a projection length of 2 m, with an insertion loss of 22 dBA. This study recommends constructing the barrier with soft materials on its surface to reflect and absorb sound waves effectively. These findings have potential implications for urban planners and policymakers in designing effective noise barriers in residential areas near railway lines.

Phase modulation by quantum gates of two microwave pulses in the framework of spin-boson model

As one of the most successful platforms of quantum control, trapped ions can be modulated by sequential microwave pulses to realize high-fidelity quantum logic gates, and dephasing noise may lead to invalidation of phase locking. In this work, we utilize the Dirac–Frenkel time-dependent variational approach with Davydov ansatz to simulate spin echo dynamics in the framework of spin-boson model. As the essential modulation parameters, pulse duration and waiting time have been comprehensively investigated to optimize the phase gates by two microwave pulses. We find that, as spin orientation undergoes periodic changes, the phase difference by acting one and two pulses exhibits spontaneous locking following time evolution, which indicates the robustness of the quantum phase gates. Spectrum of the environmental noise that is appropriate for the phase locking is also determined.

Towards a rapid-distortion theory model of turbulent flow for wind noise within an impermeable windscreen

Current models for the wind noise reduction (WNR) of microphone windscreens in atmospheric turbulence generally work under the assumption of a homogeneous surface pressure averaging theorem. Under this theorem, the surface pressures should average in such a way that the noise spectrum at low wavenumbers relative to the windscreen dimension should approach that of an unscreened microphone. Contrasting this, experiments have actually observed a significant WNR at these wavenumbers. In this work, we examine a Rapid Distortion Theory model for linking turbulent distortion to the unsteady pressure received inside the windscreen. The theoretical background and underlying assumptions of Rapid Distortion Theory are examined in detail [R. Zamponi, et al., J. Fluid Mech. 915:A27 (2021)], then results for the case of an impermeable cylinder are presented. Future work on the project involving both theoretical development and experimental verification are then discussed.

Dispersion complexity-entropy curves: An effective method to characterize the structures of nonlinear time series.

The complexity-entropy curve (CEC) is a valuable tool for characterizing the structure of time series and finds broad application across various research fields. Despite its widespread usage, the original permutation complexity-entropy curve (PCEC), which is founded on permutation entropy (PE), exhibits a notable limitation: its inability to take the means and amplitudes of time series into considerations. This oversight can lead to inaccuracies in differentiating time series. In this paper, drawing inspiration from dispersion entropy (DE), we propose the dispersion complexity-entropy curve (DCEC) to enhance the capability of CEC in uncovering the concealed structures within nonlinear time series. Our approach initiates with simulated data including the logistic map, color noises, and various chaotic systems. The outcomes of our simulated experiments consistently showcase the effectiveness of DCEC in distinguishing nonlinear time series with diverse characteristics. Furthermore, we extend the application of DCEC to real-world data, thereby asserting its practical utility. A novel approach is proposed, wherein DCEC-based feature extraction is combined with multivariate support vector machine for the diagnosis of various types of bearing faults. This combination achieved a high accuracy rate in our experiments. Additionally, we employ DCEC to assess stock indices from different countries and periods, thereby facilitating an analysis of the complexity inherent in financial markets. Our findings reveal significant insights into the dynamic regularities and distinct structures of these indices, offering a novel perspective for analyzing financial time series. Collectively, these applications underscore the potential of DCEC as an effective tool for the nonlinear time series analysis.

Effect of correlation time of combustion noise on early warning indicators of thermoacoustic instability.

In this paper, we analyze the effects of finite correlation time (noise color) of combustion noise on noise-induced coherence and early warning indicators (EWIs) via numerical and experimental studies. We consider the Rijke tube as a prototypical combustion system and model combustion noise as an additive Ornstein-Uhlenbeck process while varying noise intensity and correlation time. We numerically investigate corresponding effects on coherence resonance and multi-fractal properties of pressure fluctuations. Subsequently, we experimentally validate results and elucidate the influence of noise color and intensity on trends in coherence resonance and multi-fractal measures that can be expected in a practical scenario using an electroacoustic simulator. We find that the coherence factor, which quantifies the relative contribution of coherent oscillations in a noisy signal, increases as the system approaches the thermoacoustic instability-irrespective of the correlation time. It works at most levels of combustion noise (except for too low and too high noise levels). The Hurst exponent reduces as the system approaches thermoacoustic instability only when the correlation time is small. These results have implications on the prediction and monitoring of thermoacoustic instability in practical combustors.

Wide-band fluctuations of solar active regions probed with SHARP magnetograms

Context. The power spectra of the fluctuation noise of the solar active region (AR) areas and magnetic fluxes sequentially observed in time contain information about their geometrical features and the related fundamental physical processes. These spectra are analysed for five different ARs with various magnetic field structures. Aims. The goal of this work is to detect the characteristic properties of the Fourier and wavelet spectra evaluated for the time series of the fluctuating areas and radial magnetic fluxes of the active regions. Accordingly, this work gathers information on the properties of noise in the different cases considered. Methods. The AR area and radial magnetic flux time series were built using SHARP magnetogram datasets that cover nearly the entire time of the ARs’ transits over the solar disk. Then we applied Fourier and wavelet analyses to these time series using apodization and detrendization methods for the cross-comparison of the results. These methods allow for the detection and removal of the artefact data edge effects. Finally, we used a linear least-squares fitting method for the obtained spectra on a logarithmic scale to evaluate the power-law slopes of the fluctuation spectral power versus frequency (if any). Results. According to our results, the fluctuation spectra of the areas and radial magnetic fluxes of the considered ARs differ from each other to a certain extent, both in terms of the values of the spectral power-law exponents and their frequency bands. Conclusions. The characteristic properties of the fluctuation spectra for the compact, dispersed, and mixed-type ARs exhibit noticeable discrepancies amongst each other. It is plausible to conclude that this difference might be related to distinct physical mechanisms responsible for the vibrations of the AR areas and/or radial magnetic fluxes.

Long‐Term Variability of Mean Winds and Planetary‐Scale Waves Around Venusian Cloud Top Observed With Akatsuki/UVI

AbstractSince December 2015, Ultraviolet Imager (UVI) onboard Akatsuki has been observing Venus clouds at the wavelengths of 283 and 365 nm. Horizontal winds near the cloud top derived from the UVI images over ∼7 earth years are analyzed to elucidate spatial and temporal variability of the superrotation and planetary‐scale waves. Zonal winds averaged over the analysis period are asymmetric with respect to the equator, being faster in the southern hemisphere. This asymmetry varied temporarily and was occasionally reverted. Comparison of the winds from the two wavelengths suggests that it is uncertain whether the asymmetry is in the wind distribution or in the sensing altitude for winds. Mean zonal winds representing the superrotation exhibited broad low‐frequency variability with spectra resembling the red noise spectra. This is indicative of the presence of internal variability rather than responses to periodical external forcing. Planetary‐scale waves with zonal‐wavenumber 1 at periods around 4 and 5 days, which have been interpreted as equatorial Kelvin and Rossby waves, respectively, are quantified. While the ∼5‐day waves have nearly constant frequencies, the ∼4‐day waves have variable phase speeds that follow the superrotation speed. This result indicates that the ∼5‐day waves are likely to extend over a large depth below the cloud top and that the ∼4‐day waves are likely to be confined near the cloud top. Their possible generation mechanism through the coupling of Kelvin and Rossby waves is discussed. This study further reports wind variability of 10 to 15‐day periodicity, thermal‐tide structure, and comparison with minor species observations.

Wind noise due to flow induced around a windscreen in large-scale turbulence

Turbulent wind noise on microphones is a ubiquitous problem for sound measurement and recording outdoors. Windscreens, such as open-cell foam spheres, are effective at reducing wind noise. The unsteady pressure sources induced on the windscreen surface must contribute less noise on average than the stagnation pressure on a bare microphone, or windscreens would not be effective. To quantify this noise reduction mechanism, a model is presented for the unsteady pressure within an impermeable windscreen of arbitrary shape immersed in an initially isotropic turbulent flow. Only turbulent scales larger than the windscreen are considered, which contribute the most intense low-frequency band of the noise spectrum in most practical situations. The inhomogeneous velocity field around the windscreen is modeled in terms of an induced irrotational blocking field that meets the kinematic boundary condition. The interior pressure is expressed as a convolution of the surface pressure field with a filter function in wavevector space. The wind noise wavevector spectrum is then shown to be only a function of the inflow isotropic velocity spectrum and the windscreen shape. Solutions are obtained for the pressure frequency spectrum within a spherical windscreen for a von Kármán turbulence model and compared with prior results in literature.