Noise Field Research Articles

Experimental Investigation on Transmission of Sound in To Metallic Enclosures During Static Firing Tests Of Solid Rocket Motor

Satellite launch vehicle during lift-off generates intense dynamic environment mainly the acoustic noise, which in turn acts on the nearby launch pad systems. Reliable operation of these launch pad ground systems needs to be ensured by safeguarding against these dynamic loads with adequate protection measures. For future launch vehicle programs where the launch turnaround time is a crucial aspect, sensitive systems like ground check-out electronic packages are planned to be placed adjacent to the launch vehicle mounting pedestal on the launch pad to ensure minimal time for preparation. The enclosures housing these electronic packages needs to be configured to minimize the transmission of acoustic levels being imposed from the lift-off induced noise. In the present work, an experimental investigation is carried out on acoustic transmission characteristics of metallic enclosures of different material and thickness during the static firing tests of solid rocket motors. Acoustics generated from the supersonic jet noise has a wide frequency band from 100 to 10,000 Hz with sound power peaking near 1,000 Hz. The electronic components and packages, which are generally vulnerable to the high frequency noise, need to be protected from this lift-off induced acoustics. The enclosures are placed in the far field of this jet noise and the transmission loss measurements are obtained. Variation of transmission loss with material and thickness of the enclosures are studied with specific attention to the internal acoustic modes and the coincidence phenomena. Subsequently, the enclosures treated with acoustic blankets of different thickness are investigated to verify its influence on internal acoustic modes and also the additional reduction in transmission of sound in the dominant frequency band of supersonic jet noise.

Phase-Slip Based SQUID Used as a Photon Switch in Superconducting Quantum Computation Architectures

The photon storage time in a superconducting coplanar waveguide (CPW) resonator is contingent on the loaded quality factor, primarily dictated by the input and output capacitance of the resonator. The phase-slip based superconducting quantum interference device (PS-SQUID) comprises two phase-slip (PS) junctions connected in series with a superconducting island in between. The PS-SQUID can manifest nonlinear capacitance behavior, with the capacitance finetuned by the gate voltage to minimize the impact of magnetic field noise as much as possible. By substituting the coupling capacitance of the CPW resonator with the PS-SQUID, the loaded quality factor of the resonator can be changed by three orders, thus, we get a microwave photon switch in superconducting quantum computation architectures. Furthermore, by regulating the loaded quality factors, the coupling strength between the CPW and superconducting quantum circuits can be controlled, enabling the ability to manipulate stationary qubits and flying qubits.

New robust remote reference estimator using robust multivariate linear regression

SUMMARY The solution of the remote reference method, a frequently used technique in magnetotelluric (MT) data processing, can be viewed as a product of the two-input–multiple-output relationship between the local electromagnetic field and the reference field at a remote station. By applying a robust estimator to the two-input–multiple-output system, one can suppress the influence of outliers in the local magnetic field as well as those in the local electric field based on regression residuals. Therefore, this study develops a new robust remote reference estimator with the aid of robust multivariate linear regression. By applying the robust multivariate regression S-estimator to the multiple-output system, the present work derives a set of equations for robust estimates of the transfer function, noise variances, and the scale of the Mahalanobis distance simultaneously. The noise variances are necessary for the multivariate analysis to normalize the residuals of dependent variables. The Mahalanobis distance, a distance measure for multivariate data, is a commonly used indicator of outliers in multivariate statistics. By updating those robust estimates iteratively, the new robust remote reference estimator seeks the transfer function that minimizes the robust scale estimate of the Mahalanobis distance. The developed estimator can avoid bias in the MT transfer function even if there are significant noises in the reference magnetic field and handle outlying data more robustly than previously proposed robust remote reference estimators. The authors applied the developed method to a synthetic data set and real-world data. The test results demonstrate that the developed method downweights outliers in the local electric and magnetic fields and gives an unbiased transfer function.

Construction Noise Reduction Research on Rail Transit Projects: A Case Study in China

With the advancement of China’s construction industry and the rapid pace of urbanization, there has been heightened concern about and demand for improved construction environments. Rail transit projects commonly experience noise levels that exceed standard limits, resulting in a significant challenge posed by construction noise pollution. This issue not only disrupts the normal operations of construction sites but also profoundly impacts the mental well-being, auditory health, and nervous system of both construction workers and nearby residents. Consequently, effectively addressing construction noise pollution has emerged as a pressing issue. This study systematically reviewed domestic and international construction noise standards, integrating field research and noise monitoring data from construction sites. It provided a detailed analysis of the sources and hazards of construction noise and explored the source and propagation characteristics of construction noise from rail transit projects. The feasibility of controlling construction noise from various perspectives was investigated. Finally, the study analyzed the causes of construction noise exceeding standard limits, proposed layout strategies and control methods tailored to the stages of construction, and offered comprehensive noise control recommendations, culminating in a complete control process. This study fills a gap in research related to construction noise for rail transit projects, provides a valuable foundation for developing construction noise control objectives, and offers practical guidance on the implementation of measurement and control methods. These insights will help advance the field of construction noise control and management, and provide valuable insights for similar domestic rail transit projects.

Effects of system parameters on a single-beam synthetic gradiometer with a dual-cell structure.

We report a single-beam synthetic gradiometer operated in the spin-exchange-relaxation free (SERF) regime, using the structure of two separate atomic vapor cells spaced 2 cm apart. To improve the capability of the gradiometer in suppressing the common-mode magnetic field noise, we are aiming at investigating the effects of the system parameters on the gradiometer common-mode rejection ratio (CMRR). The mathematical expression for the relationship between the gradiometer CMRR and the two variables including the linewidth ratio and the pumping factor ratio is constructed for the first time, to our knowledge. This means that the CMRR can be optimized by controlling the linewidth and the pumping factor, which is easy to implement in the operation process. As a result, a CMRR of 246 is achieved and a gradiometer sensitivity of 4.5 fT/cm/Hz1/2 is also measured. This method provides a theoretical and experimental basis for the automated operation of gradiometers, and the gradiometer system performance can be tuned to a desired state by simply controlling the linewidth and the incident light intensity.

Numerical Simulation Analysis of the Correlation between Hydrodynamic Noise of Hydraulic Turbines and Defects in Runner Blades

To investigate the hydrodynamic noise characterization of hydraulic turbines with runner blade defects, this article establishes the intact machine model and three kinds of models with runner blade defects. Using the Computational Fluid Dynamic (CFD) and Computational Acoustic (CA) hybrid simulation computational methods, the hydrodynamic noise field of the hydraulic turbine is numerically simulated, and the results of the acoustic near field and acoustic far field are shown. 1. The double-row leaf grille and the runner are the primary sound source areas of the hydraulic turbine, and the intensity of sound radiation from these areas is positively correlated with the degree of runner blade defects. 2. As the runner blade defects develop, the sound power level (SWL) increases more significantly in the guide vanes near the nose of the spiral case in the double-row leaf grille. The most pronounced increase in the SWL is observed at the defective craters on the runner blades. 3. The frequency of the defective noise signal is primarily concentrated in the low-frequency band. The dominant frequency amplitude associated with runner blade defects increases and rises after the occurrence of defects. Secondary frequency changes are also observed, and the location of these changes varies at different receiving points.

Research on the unsteady flow field and aerodynamic noise characteristics in the circular space of ultra-high-speed elevators

Due to the non-streamlined blunt body shape of the elevator car, intense aerodynamic loads and noise are generated in the annular space when the elevator operates at high speed in a narrow hoistway. This article uses large-eddy simulation and Curle acoustic theory to establish a numerical model of the wellbore flow field under different guiding shapes of the elevator car. First, the mechanism of action between the flow guide shape, vortex characteristics, and aerodynamic load was studied, and the influence of operating speed on aerodynamic load under different flow guide shapes was analyzed. Second, the distribution and spectral characteristics of noise in the annular space under different flow guide shapes were studied from the near field and far field scales. Finally, it can be concluded that increasing the guide surface can significantly reduce the pressure difference between the upper and lower parts of the car, weakening the separation of the tail airflow. The number of guide surfaces, installation position, and vertex offset significantly impact drag and lateral force, with the optimal reduction of 34.65% and 57.6%, respectively. The maximum sound source intensity of near-field noise is mainly concentrated at the arc transition in the upper part of the annular space, and the frequency is mainly concentrated in the range of 500–1000 Hz. The sound pressure level is linearly related to the logarithm of the longitudinal distance, and the noise attenuation speed becomes faster with the increase in the number of guiding surfaces.

A Nonstationary Stochastic Rainfall Generator Conditioned on Global Climate Models for Design Flood Analyses in the Mississippi and Other Large River Basins

AbstractExisting stochastic rainfall generators (SRGs) are typically limited to relatively small domains due to spatial stationarity assumptions, hindering their usefulness for flood studies in large basins. This study proposes StormLab, an SRG that simulates precipitation events at 6‐hr and 0.03° resolution in the Mississippi River Basin (MRB). The model focuses on winter and spring storms caused by water vapor transport from the Gulf of Mexico—the key flood‐generating storm type in the basin. The model generates anisotropic spatiotemporal noise fields that replicate local precipitation structures from observed data. The noise is transformed into precipitation through parametric distributions conditioned on large‐scale atmospheric fields from a climate model, reflecting spatial and temporal nonstationarity. StormLab can produce multiple realizations that reflect the uncertainty in fine‐scale precipitation arising from a specific large‐scale atmospheric environment. Model parameters were fitted monthly from December–May, based on storms identified from 1979 to 2021 ERA5 reanalysis data and Analysis of Record for Calibration (AORC) precipitation. StormLab then generated 1,000 synthetic years of precipitation events based on 10 CESM2 ensemble simulations. Empirical return levels of simulated annual maxima agree well with AORC data and show an overall increase in 1‐ to 500‐year events in the future period (2022–2050). To our knowledge, this is the first SRG simulating nonstationary, anisotropic high‐resolution precipitation over continental‐scale river basins, demonstrating the value of conditioning such stochastic models on large‐scale atmospheric variables. StormLab provides a wide range of extreme precipitation scenarios for design floods in the MRB and can be further extended to other large river basins.

Large eddy simulation for jet noise characteristics of liquid rocket engine with guide groove

The study of jet noise characteristics of liquid rocket engines is a prerequisite for evaluating the noise level of rockets and effectively controlling the noise. To obtain the effect of engine operating and structural parameters on jet noise, the Large Eddy Simulation combined with the FW-H integration method is applied for the scaled engine with guide groove under different chamber pressures and nozzle expansion ratios. The simulation results show that the noise field distribution of the jet with a guide groove is highly symmetrical and has obvious directivity. The noise caused by jet impingement on the guide groove is strongly correlated to the distribution of high vorticity regions. Remarkably, higher chamber pressure leads to longer potential jet length, higher noise sound pressure levels, and greater enhancement effect of impact on noise. However, the frequency spectral characteristics are basically invariant. When the chamber pressure is constant, the increment of the nozzle expansion ratio in a certain range results in lower noise peak frequency and weaker impact effect.

An optically pumped magnetic gradiometer for the detection of human biomagnetism

We realise an intrinsic optically pumped magnetic gradiometer based on non-linear magneto-optical rotation. We show that our sensor can reach a gradiometric sensitivity of 18 fT cm−1Hz−1 and can reject common mode homogeneous magnetic field noise with up to 30 dB attenuation. We demonstrate that our magnetic field gradiometer is sufficiently sensitive and resilient to be employed in biomagnetic applications. In particular, we are able to record the auditory evoked response of the human brain, and to perform real-time magnetocardiography in the presence of external magnetic field disturbances. Our gradiometer provides complementary capabilities in human biomagnetic sensing to optically pumped magnetometers, and opens new avenues in the detection of human biomagnetism.

Protecting the Quantum Coherence of Two Atoms Inside an Optical Cavity by Quantum Feedback Control Combined with Noise-Assisted Preparation

We propose a theoretical scheme to enhance quantum coherence and obtain steady-state coherence by combining quantum feedback control and noise-assisted preparation. We investigate the effects of quantum-jump-based feedback control and noise field on the quantum coherence and excited-state population between two atoms inside an optical cavity where a noise field drives one, and the other is under quantum feedback control. It is found that steady quantum coherence can be achieved by adding an external noise field, and the quantum feedback can prolong the coherence time with partial suppression of the spontaneous emission of atoms. In addition, we study the influence of the joint action of quantum feedback and noise-assisted preparation on quantum coherence and show that the combined action of feedback control and noise-assisted preparation is more effective in enhancing steady coherence. The findings of our research offer some general guidelines for improving the steady-state coherence of coupled qubit systems and have the potential to be applied in the realm of quantum information technology.

The Tail Characteristics of Several Asymmetric Distributions and Their Applications in the Field of Financial Data Modelling and Machine Learning

Asymmetric distributions play a pivotal role in various fields, including finance, machine learning, and artificial intelligence. In finance, asymmetric distributions, characterized by negative skewness, peakedness, heavy tails, and asymmetric fluctuations, provide a more accurate representation of financial data. These distributions are particularly useful in capturing the complex behavior of assets and risk management. In the field of machine learning, data disturbance, noise, outliers and other disturbances will have a negative impact on the performance and reliability of the model, asymmetric distributions offer a valuable tool for describing the tail behavior of noise and interference. This is crucial in designing more robust machine learning models that can handle outliers and noise effectively. Additionally, when dealing with unbalanced data classification, asymmetric distributions can be leveraged by adjusting the decision threshold of classifiers or employing specialized loss functions. In this paper, the asymptotic tail ratio behavior of probability density function(pdf) and cumulative distribution function (cdf) of three asymmetric distributions (asymmetric Laplace, generalized Logistic and asymmetric normal distribution) and Student-t distribution were considered respectively under some regular conditions. The detailed characteristics of these asymmetric tails will have a profound impact on the fields of financial data analysis, artificial intelligence, and unbalanced classification.

Least-squares reverse time migration of simultaneous sources with deep-learning-based denoising

Least-squares reverse time migration (LSRTM) is currently one of the most advanced migration imaging techniques in the field of geophysics. It uses least-squares inversion to fit the observed data, resulting in high-resolution imaging results with more accurate amplitudes and better illumination compensation than conventional reverse time migration (RTM). However, noise in the observed data and the Born approximation forward operator can result in high-wavenumber artifacts in the final imaging results. Moreover, iteratively solving LSRTM leads to one or two orders of computational cost higher than conventional RTM, making it challenging to apply extensively in industrial applications. Simultaneous source acquisition technology can reduce the computational cost of LSRTM by reducing the number of wavefield simulations. However, this technique also can cause high-wavenumber crosstalk artifacts in the migration results. To effectively remove the high-wavenumber artifacts caused by these issues, simultaneous source and deep learning are combined to speed up LSRTM as well as suppress high-wavenumber artifacts. A deep residual neural network (DR-Unet) is trained with synthetic samples, which are generated by adding field noise to synthesized noise-free migration images. Then, the trained DR-Unet is applied on the gradient of LSRTM to remove high-wavenumber artifacts in each iteration. Compared to directly applying DR-Unet denoising to LSRTM results, embedding DR-Unet denoising into the inversion process can better preserve weak reflectors and improve denoising effects. Finally, the proposed LSRTM method is tested on two synthetic data sets and a land data set. The tests demonstrate that the proposed method can effectively remove high-wavenumber artifacts, improve imaging results, and accelerate convergence speed.

Acoustical Holography and Coherence-Based Noise Source Characterization of an Installed F404 Engine

Understanding the acoustic source characteristics of supersonic jets is vital to accurate noise field modeling and jet noise reduction strategies. This paper uses advanced, coherence-based partial field decomposition methods to characterize the acoustic sources in an installed, supersonic GE F404 engine. Partial field decomposition is accomplished using an equivalent source reconstruction via acoustical holography. Bandwidth is extended through the application of an array phase-unwrapping and interpolation scheme. The optimized-location virtual reference method is used. Apparent source distributions and source-related partial fields are shown as a function of frequency. Local maxima are observed in holography reconstructions at the nozzle lipline, distinct in frequency and space. The lowest-frequency local maximum may relate to noise generated by large-scale turbulence structures in the convectively subsonic region of the flow. Other local maxima are correlated primarily with Mach wave radiation originating from throughout the shear layer and into the fully mixed region downstream of the potential core tip. Source-elucidating decompositions show that the order and behavior of the decomposition lend to the local maxima being related to distinct subsources. Between the local maxima, however, there may be a combination of sources active, which is likely the cause of the spatiospectral lobes observed in other full-scale, supersonic jets.

Effects of Stochastic Magnetic Noise on the SERF Co‐Magnetometer

AbstractStochastic magnetic field noise has a non‐negligible negative impact on the performance of quantum precision measurement instruments such as spin‐exchange relaxation‐free (SERF) co‐magnetometer in terms of sensitivity and stability. Conventional magnetic field error analysis and suppression methods are not applicable to stochastic magnetic field noise. In this paper, a stochastic model of the SERF co‐magnetometer is proposed to analyze the mechanism of stochastic magnetic field noise. The mean and covariance propagation model of the SERF co‐magnetometer is given based on the stochasticity model and statistical principles. The analysis of simulation experiments reveals that reducing the longitudinal electron spin polarization can somewhat reduce the standard deviation of the system output caused by stochastic magnetic field noise. And the atomic ensembles are most resistant to stochastic magnetic field noise when the electron spin polarization strongly couples with the nuclear spin polarization. Finally, the experiments verified the above conclusions. In conclusion, this paper provides theoretical and experimental support for analyzing and suppressing the effect of stochastic magnetic field noise on the SERF co‐magnetometer, which is of great significance for improving the sensitivity and stability of the measurement.

Advancements in wideband source localization with an acoustic vector sensor line array

A method is presented for localizing wideband acoustic sources using an array of acoustic vector sensors (AVS). The method focuses on leveraging the lack of correlation between acoustic pressure and particle velocity in the underwater environmental noise field. Coherent processing is introduced in the signal processing stage to suppress noise components in the observed data. By employing a focused transform that maps various frequency components of the wideband signal into the same signal subspace, an asymptotically unbiased Direction of Arrival (DOA) estimation is achieved using a multidimensional subspace method. A concise expression for the Cramér-Rao Bound (CRB) on the estimation errors is provided within the framework of the wideband multi-vector-sensor model. The performance of the proposed method for localizing sources is assessed through simulation and experimental data analysis. The research indicates that coherent processing effectively suppresses isotropic components in background noise, the proposed method achieves a lower estimation error, closer to the CRB, compared to the scalar array counterpart under identical signal-to-noise ratio (SNR) conditions.

Phase Transition Temperatures of a Nematic Liquid Crystal in the Presence of Noise and DC Fields

Phase Transition Temperatures of a Nematic Liquid Crystal in the Presence of Noise and DC Fields

Optimal Design and Development of Magnetic Field Detection Sensor for AC Power Cable.

The state detection of power cables is very important to ensure the reliability of the power supply. Traditional sensors are mostly based on electric field detection. The operation is complex, and its efficiency needs to be improved. This paper optimizes the design and development of the magnetic field detection sensor for AC power cables. First, through the establishment of the magnetic field sensor model, it is determined that permalloy is the material of the magnetic core, the optimal aspect ratio of the magnetic core is 20, and the ratio of coil length to core length is 0.3. Second, the coil-simulation model is established, and it is determined that the optimal number of turns of the coil is 11,000 turns, the diameter of the enameled copper wire is 0.08 mm, and the equivalent magnetic field noise of the sensor is 0.06 pT. Finally, the amplifying circuit based on negative magnetic flux feedback is designed, the sensor is assembled, and the experimental circuit is built for the sensitivity test. The results show that the sensitivity of the magnetic field sensor is 327.6 mV/μT. The sensor designed in this paper has the advantages of small size, high sensitivity, ease of carry, and high reliability.

THE REDUCTION OF GEOMAGNETIC DATA FOR THE TERRITORY OF LATVIA TO THE EPOCH 2021.5

The article describes the sources of geomagnetic data, the reduction of geomagnetic data for the territory of Latvia to the epoch 2021.5, the history of previous magnetic observations in Latvia, the information available in the State Geodetic Network database and the information available in the World Geomagnetism Data Centre. The sequence of absolute measurements is described in detail. To visualise the changes in the magnetic declination value in the territory of Latvia, a 2021.5 year declination fluctuation has been created using ArcGIS Pro. The declination values in Latvia range from 6.68° to 10°, the inclination values range from 71.089° to 72.245° and the total magnetic field values from 51100 nT to 52594 nT. The values obtained for the magnetic field components refer to a magnetically clean environment, and there can be, and are, differences in the natural conditions in the Latvian territory, in natural anomalous locations and in locations with artificially high magnetic field noise (e.g. in cities, near railways, near high voltage lines, etc.). In the Latvian network, points have been selected in locations where the magnetic noise is minimal, as this is the technological process for building such stations. Magnetic observatories are even stricter, so the data coming from the observatories reflect the natural magnetic field without the influence of magnetic anomalies. The reduced magnetic field values and their representation on a map can be used for aeronautical navigation, military applications, identification of local magnetic anomaly sites or search for magnetically clean environments.

Measuring forces in a 2D multi-contact system using the virtual fields method: Principle, simulations and experimental application to a three-particle system

This paper proposes an experimental approach to measure contact forces in a two-dimensional system composed of cylindrical particles using the Virtual Fields Method (VFM). This identification method relies on the knowledge of the strain distribution in the particles forming the discrete medium. Synthetic strain data provided by a finite element model (with added noise) were first used as input data for the identification procedure. It is shown that if the mechanical response of the constitutive material is known, the contact forces applied to a particle can be identified, since they are proportional to a weighted average of the strain components, the weights being the virtual strain components. Various strategies were tested to propose kinematically admissible fields for the virtual displacement. Identification technique robustness was studied with respect to various sources of error, such as noise in the strain field, missing data along the boundaries, and a possible spurious shift between real and virtual fields. An experimental application was then performed on a three-particle system subjected to confined compression by processing strain maps obtained using Localized Spectrum Analysis (LSA) for each particle. In addition to the VFM equations, particle equilibrium and Newton's third law of motion were taken into account to propose a relevant strategy for processing the experimental data. The results open up prospects for applications to granular materials composed of numerous particles.