Prediction Of Acoustic Field Research Articles

Prediction of one-dimensional acoustic field with axial temperature gradient using neural networks

The study of sound propagation inside the ducts finds extensive application in aerospace, automobiles, speech, and biomedical sectors. This paper presents a neural network-based formulation to estimate the acoustic field inside a uniform duct with temperature gradient along the axial direction. The governing differential equation is derived from the momentum, energy, and state equations. The acoustic field is approximated with a feedforward neural network, and the problem is converted to an unconstrained optimization problem using the trial solution method. The training process is performed using the L-BFGS optimizer and the sine activation function. The acoustic field inside the duct is predicted up to 2000 Hz for linear and exponential temperature profiles. The predicted results are in good agreement with those obtained from the traditional Range-Kutta solver with a maximum relative error of 0.1%. Furthermore, the classical Helmholtz equation without the temperature gradient is solved using the developed neural network formulation. Using these results, a comparative study is conducted to understand the effect of the temperature gradient on the acoustic field inside the duct.

Kriging-based accelerated prediction of frequency spectrum and acoustic field around rotating sources

The computational cost of predicting sound radiated from rotating sources is mainly affected by three parameters, i.e., the number of frequencies, source points and field points. The key of reducing the prediction cost of sound radiated from rotating sources is to reduce the times of integral calculation invoked in multi-frequency and combination of multi-source-field points. In view of the above engineering background, this paper employs a frequency-domain integral prediction method combined with a Kriging interpolation model to accelerate acoustic prediction. Three numerical cases are performed to validate the effectiveness of the above method in accelerating prediction of the frequency spectrum and acoustic field around rotating sources. The research also provides recommendations on the distribution characteristics of the initial sampling points and the method of adding sampling points.

Numerical prediction of mean flow and acoustic field of a supersonic impinging jet

The three-dimensional turbulent mean flow and acoustic field of a supersonic jet impinging on a solid plate is studied computationally using the general purpose CFD code Ansys Fluent. A pressure-based coupled solver formulation with the second order weighted central-upwind spatial discretization is applied to compute transient solutions. Cold and hot jet thermal conditions are considered. Mean flow characteristics are investigated by a steady-state modeling approach. Acoustic radiation of impingement tones is simulated using a transient time-domain formulation. The effects of turbulence in steady-state are modeled by the SST k-ω turbulence model. The Wall-Modeled Large-Eddy Simulation (WMLES) model is applied to compute transient solutions. The near-wall mesh on the impingement plate is fine enough to resolve the viscosity-affected near-wall region all the way to the laminar sublayer. Nozzle-to-plate distance is parameterized in the model for automatic re-generation of the mesh and results. Steady-state predictions of hover lift loss and mean jet velocity distributions are compared with experimental data, and favorable agreement is reported. The transient solution reproduces the mechanism of impingement tone generation by the interaction of large scale vortical structures with the impingement plate. The acoustic near-field is directly resolved by Computational Aeroacoustics (CAA) to accurately propagate impingement tone waves to near-field microphone locations. Calculated impingement tone frequencies and sound pressure levels agree with experimental values.

Research on underwater acoustic field prediction method based on physics-informed neural network

In the field of underwater acoustic field prediction, numerical simulation methods and machine learning techniques are two commonly used methods. However, the numerical simulation method requires grid division. The machine learning method can only sometimes analyze the physical significance of the model. To address these problems, this paper proposes an underwater acoustic field prediction method based on a physics-informed neural network (UAFP-PINN). Firstly, a loss function incorporating physical constraints is introduced, incorporating the Helmholtz equation that describes the characteristics of the underwater acoustic field. This loss function is a foundation for establishing the underwater acoustic field prediction model using a physics-informed neural network. The model takes the coordinate information of the acoustic field point as input and employs a fully connected deep neural network to output the predicted values of the coordinates. The predicted value is refined using the loss function with physical information, ensuring the trained model possesses clear physical significance. Finally, the proposed prediction model is analyzed and validated in two dimensions: the two-dimensional acoustic field and the three-dimensional acoustic field. The results show that the mean square error between the prediction and simulation values of the two-dimensional model is only 0.01. The proposed model can effectively predict the distribution of the two-dimensional underwater sound field, and the model can also predict the sound field in the three-dimensional space.

Physics based sparsity level determination for acoustic scattered far-field prediction.

Sparse reconstruction using the equivalent source method has shown promise in acoustic field prediction from near-field measurements. The sparsity level of the representation coefficients needs to be known or estimated. In this letter, for scattered far-field prediction, the lower bound of sparsity level is derived from the effective rank of the far-field transfer matrix and used as a pre-set hyperparameter for orthogonal matching pursuit. The minimum number of measurements is then determined under the compressed sensing theory. Simulated and tank data show the effectiveness of this approach, which combines physical propagation and compressed sensing and is easy to implement.

Acoustic Field Prediction Method and Simulation Research Based on Acoustic Field Geometric Average Theory

In order to meet the capability requirements of submarine radiated noise acoustic field prediction in free field and improve the detection and anti-detection capabilities, this paper proposes an acoustic field prediction method based on the geometric average theory of acoustic field. According to the measured self-noise information, a global search method is used. By calculating the average energy of the spherical, the extended compensation for different point distances is achieved, so as to predict the radiation noise at different distances. Through simulation experiments, it is found that the method proposed in this paper has a fast calculation speed, and the acoustic field prediction accuracy is high.

Fast prediction of aerodynamic noise induced by the flow around a cylinder based on deep neural network

Accurate and fast prediction of aerodynamic noise has always been a research hotspot in fluid mechanics and aeroacoustics. The conventional prediction methods based on numerical simulation often demand huge computational resources, which are difficult to balance between accuracy and efficiency. Here, we present a data-driven deep neural network (DNN) method to realize fast aerodynamic noise prediction while maintaining accuracy. The proposed deep learning method can predict the spatial distributions of aerodynamic noise information under different working conditions. Based on the large eddy simulation turbulence model and the Ffowcs Williams–Hawkings acoustic analogy theory, a dataset composed of 1216 samples is established. With reference to the deep learning method, a DNN framework is proposed to map the relationship between spatial coordinates, inlet velocity and overall sound pressure level. The root-mean-square-errors of prediction are below 0.82 dB in the test dataset, and the directivity of aerodynamic noise predicted by the DNN framework are basically consistent with the numerical simulation. This work paves a novel way for fast prediction of aerodynamic noise with high accuracy and has application potential in acoustic field prediction.

Interval Analysis of Interior Acoustic Field with Element-By-Element-Based Interval Finite-Element Method

This paper presents an element-by-element-based interval finite-element method (EBE-IFEM) for the uncertain interior acoustic field prediction with uncertain-but-bounded parameters. The interval dynamic matrices and loads vectors are assembled with the element-by-element (EBE) strategy, and decomposed into diagonalization forms additionally. Then the interval dynamic equation can be rewritten as iterative enclosure form, and finally are analyzed by both Rump’s method and the Neumaier-Pownuk method in the comparative discussion. Meanwhile, numerical examples are calculated with the interval perturbation finite-element method (IPFEM), modified interval finite-element method (MIPFEM), and Monte Carlo simulation. The numerical results demonstrate that the solution by the EBE-IFEM shows more accurate and more stable than other cross-references, when evaluating the intervals of sound pressure response in interior acoustic field.

Investigation on different time-harmonic models using FEM for the prediction of acoustic pressure fields in a pilot-scale sonoreactor

In this study, the performance of three different acoustic pressure models were evaluated by comparing the predicted pressure field with sonochemiluminescence data. The nonlinear Helmholtz model showed the best agreement in terms of antinode and pressure magnitude predictions. The linear Helmholtz model was found to overpredict the antinodes and acoustic pressure magnitudes in the reactor due to the lack of attenuation mechanisms. Results showed that the antinode locations predicted by the monodisperse Commander and Prosperetti model at constant bubble density was highly dependant on the specified bubble fraction. A new approach was proposed, which involved tuning the bubble fraction of the model using wavelength measurements from sonochemiluminescence results. Simulation results using this new approach showed promising agreement to experimental observations. The proposed method can be a simple and efficient way to tune acoustic pressure simulations for systems that forms uniform standing waves, which can then be useful for sonoreactor design.

Impedance models for single and two degree of freedom linings and correlation with grazing flow duct testing

Presented here is the development of a predictive model for impedance of single-degree-of-freedom (SDOF) and two-degree-of-freedom (2DOF) acoustic linings that is suitable for the design stage of suppression of inlet noise for turbo-fan engines. It is required that over a probable range of lining physical parameters and operating conditions the impedance spectrum is predicted with accuracy sufficient to support a lining design process and assessment of achievable attenuation. The starting point is a published impedance model for SDOF linings that primarily focuses on the transfer impedance of conventional and micro-perforate face sheets with grazing flow. This is expanded here to include 2DOF linings, introducing new issues related to transfer impedance of the inserted septum. Problems addressed are related to the septum insertion process that can change thickness, hole diameter and open area ratio of the uninstalled septum, and introduce blockage. Required empiricism is discussed and models for face sheet and septum-in-core transfer impedance are derived, applicable to a specific range of sheet thickness, hole diameter, and open area ratio. Manufacturing processes considered are mechanical drilling in the case of the carbon fiber laminate face sheet that is conventional perforate, and laser drilling in the case of the epoxy film micro-perforate septum material. Benchmarking is carried out by comparison of acoustic field predictions, using the proposed lining model in an FEM propagation code, with measured data from a grazing flow duct facility. Test samples include SDOF and 2DOF linings, including cases with three segments, each with distinct physical properties. Example results of comparisons are shown to highlight the fidelity of the impedance model over a frequency range compatible with the grazing flow duct geometry.

Corrigendum to “A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval Parameters”

Corrigendum to “A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval Parameters”

Time domain model and experimental validation of non-contact surface wave scanner

This paper presents a time-domain model for the prediction of acoustic field in an air-coupled, non-contact, ultrasonic surface wave scanner, which includes an air-coupled Emitter, the Propagation space, and an air-coupled Receiver (EPR). The computation is divided into three steps, with each step being modeled in the time domain by its spatio-temporal transfer function. The latter are then used in turn, to find the pulse response of the overall system.The model takes the finite size of the aperture receiver, the attenuation in both air and the tested solid sample, as well as the electric response of the emitter-receiver set he into account. The attenuation is characterized by a causal time-domain Green’s function, allowing wideband attenuation of a lossy medium, obeying the power law αω=α0ωη,0⩽η⩽2, to be used. The model is implemented numerically using a Discrete Representation approach. It is then validated quantitatively by comparing the predicted acoustic field with experiment. The prediction error for three typical field features, the system’s impulse response, the on-axis field distribution, and the directivity pattern, is globally smaller than 3%.In order to obtain this high level of accuracy in the model, the parameters characterizing the solid sample used during the experiment were measured experimentally, with a specifically developed experimental setup.Overall, the proposed model is approximately 100 times faster than 3D FEM with an equivalent spatio-temporal resolution. In parallel, a simplified model is proposed, which neglects the attenuation in air and assumes the emitter inclination angle to be perfectly adjusted. This approach makes it possible to further shorten the computational time by a factor of about ten, whilst maintaining good accuracy. Thanks to its computational efficiency, the proposed model can be used to formulate various recommendations concerning the scanner settings, in particular the inclination angles of the emitter and receiver, and their distance from the sample.

Prediction of fluid flow and acoustic field of a supersonic jet using vorticity confinement.

In this study, the numerical simulation of the fluid flow and acoustic field of a supersonic jet is performed by using high-order discretization and the vorticity confinement (VC) method on coarse grids. The three-dimensional Navier-Stokes equations are considered in the generalized curvilinear coordinate system and the high-order compact finite-difference scheme is applied for the space discretization, and the time integration is performed by the fourth-order Runge-Kutta scheme. A low-pass high-order filter is applied to stabilize the numerical solution. The non-reflecting boundary conditions are adopted for all the free boundaries, and the Kirchhoff surface integration is utilized to obtain the far-field sound pressure levels in a number of observer locations. Comparisons of the jet mean flow and jet aeroacoustics results with the other numerical and experimental data at similar flow conditions are made and show a reasonable agreement. The study shows that the proposed solution methodology based on the high-order compact finite-difference scheme in conjunction with the VC method can reasonably predict the near-field flow and the far-field noise of high Reynolds number jets with a fairly coarser grid than that used in the large eddy simulations and, thus, the computational cost can be significantly decreased.

Absorption scaling theory applied to an energy-intensity boundary element method for prediction of broadband acoustic fields in enclosures

Insight into the acoustic energy distribution in enclosures is gained by applying Absorption Scaling Theory. Broadband high-frequency acoustic fields within 3D rectangular enclosures are modeled with an energy-intensity boundary element method (EIBEM) that replaces the enclosure boundary with a distribution of broadband uncorrelated directional intensity sources to simulate either diffuse or specular reflection. Assuming a highly reflective enclosure, the boundary panel strengths are expanded in a power series with the spatially-averaged absorption as a small parameter. For diffuse reflection fields, where the theory is well developed, a matrix formulation is derived for each of the expansion coefficients that must be solved in sequential order. The leading order term in the expansion is inversely proportional to the scaling parameter and estimates the average level inside the enclosure, the next term gives spatial variation independent of average absorption level, while higher order terms account for the spatial variation of energy due to the distribution of absorption and the location of sources. For a highly reflective enclosure, only a few terms are needed to accurately predict the mean-square pressures. Similar behavior is demonstrated for specular reflection using numerical simulations. Applications include theoretical and empirical enclosure design and assessment, and solving the inverse problem.

Modeling high frequency broadband acoustic fields inside rectangular and cylindrical enclosures using an energy-intensity boundary element method

Accurate prediction of high frequency broadband acoustic fields inside enclosures with curved boundaries typically requires time consuming frequency-by-frequency numerical techniques. A quick solution is developed for general enclosure shapes using an energy-intensity boundary element method, previously tested for rectangular geometries and now extended to cylinders with flat or spherical endcaps. Derived from first principles, which are reviewed, the approach uses uncorrelated spreading energy-intensity boundary sources to directly solve for the steady-state mean-square pressures. The enclosure boundary is discretized into radiating panels that account for interior energy transfer and satisfy prescribed reflection and absorption boundary conditions. Half-space orthogonal spherical harmonics serve as basis functions to emulate both diffuse and specular reflections. Panel interactions are calculated by an energy-accurate quadrature technique and studied for curved boundaries. Computationally intensive benchmark solutions are developed for verification. A fully correlated Helmholtz solution is derived for the cylindrical enclosure using a novel internal scattering approach to calculate high frequency pressure, and numerically integrated over a third-octave band. Comparisons between the fully correlated solution and the energy method for enclosures of various aspect ratios reveal excellent agreement. Simulations are also presented contrasting interesting behavioral differences between diffuse and specular reflection fields.

Broadband noise prediction using large eddy simulation and a frequency domain method

A new LES-acoustic analogy method for accurate flow and broadband noise prediction is proposed. A frequency domain method for the generalized Lighthill acoustic analogy theory is derived in detail and the final equations for code is provided which can help to bridge the gap between the flow field prediction and the acoustic field prediction for those who are interested in acoustic results but lack of acoustic prediction ability. The hybrid method (LES and acoustic analogy method) for broadband noise prediction is validated using the rod-airfoil interaction problem. Both flow field results and acoustic field results are compared with experimental results and other numerical results in detail. The flow field results agree very well with the experimental results and other numerical results. The predicted acoustic results and experimental results also reach good agreement both in far field acoustic pressure Power Spectral Density (PSD) and noise directivity. The method developed in the paper proves to be an effective tool for broadband noise prediction. In addition, the different span correction methods for the acoustic pressure spectrum are also discussed.

A New Uncertain Analysis Method for the Prediction of Acoustic Field with Random and Interval Parameters

For the frequency response analysis of acoustic field with random and interval parameters, a nonintrusive uncertain analysis method named Polynomial Chaos Response Surface (PCRS) method is proposed. In the proposed method, the polynomial chaos expansion method is employed to deal with the random parameters, and the response surface method is used to handle the interval parameters. The PCRS method does not require efforts to modify model equations due to its nonintrusive characteristic. By means of the PCRS combined with the existing interval analysis method, the lower and upper bounds of expectation, variance, and probability density function of the frequency response can be efficiently evaluated. Two numerical examples are conducted to validate the accuracy and efficiency of the approach. The results show that the PCRS method is more efficient compared to the direct Monte Carlo simulation (MCS) method based on the original numerical model without causing significant loss of accuracy.

Effect of pintle on the acoustic field and stability factors of a solid-propellant rocket motor with variable pintle thruster

The acoustic modes and combustion instability within a solid rocket combustion chamber are predicted and analyzed in the presence of a movable pintle in the nozzle. The prediction of acoustic field is performed with a commercial finite element method code, and a combustion instability diagnosis is conducted with the classical acoustic analysis by investigating the stability factors (alphas). The effect of pintle position on the acoustic modes is analyzed by comparing the acoustic modes of cylindrical chambers with and without a pintle. A stability integral and alphas survey is carried out between the annular type chamber (resulting from the presence of the pintle) and the cylindrical chamber. Emphasis is placed on the changes in the nozzle throat area and on their respective stability integral when pintle position varies. The stability behavior according to the presence of the pintle is analyzed using two major driving and damping factors. The stability analysis reveals that the acoustic mode with the pintle is more sensitive to the fourth longitudinal mode compared with the acoustic mode without the pintle. Meanwhile, other modes show analogous acoustic fields, and the second mode is highly dependent on pintle position.

Evidence-theory-based analysis for the prediction of exterior acoustic field with epistemic uncertainties

Evidence theory has a strong ability to handle the epistemic uncertainty, based on which the uncertain parameters with limited information can be conveniently treated. In this paper, a numerical method is developed to predict the exterior acoustic field with epistemic uncertainties based on evidence theory. In order to alleviate the computational cost, the interval analysis technique is adopted to acquire the approximate frequency response amplitude bounds for each focal element, and the corresponding formulations of interval perturbation analysis for exterior acoustic field prediction are deduced. Inspired by the probability theory, the mean value, standard deviation and cumulative distribution are used to describe the distribution characteristics of evidence variables. Two numerical examples are given to illustrate the feasibility and effectiveness of the present method.

An interval perturbation method for exterior acoustic field prediction with uncertain-but-bounded parameters

This paper proposes two interval analysis methods, called the first-order interval parameter perturbation method (FIPPM) and the modified interval parameter perturbation method (MIPPM), for use in exterior acoustic field prediction when there are uncertainties in both the material properties and the external load. Interval variables are used to quantitatively describe the uncertain parameters in the face of limited information. The conventional first-order Taylor expansion and perturbation terms are employed in the FIPPM, while the MIPPM introduces modified Taylor series to approximate the non-linear interval matrix and vector. The high-order terms of the Neumann expansion are retained to calculate the interval matrix inverse. A numerical example is given by comparing the results with a Monte Carlo simulation to demonstrate the feasibility and effectiveness of the proposed methods at evaluating the sound pressure ranges in an exterior acoustic field.