Wave Propagation Model Research Articles

2D Modeling of Wave Propagation in Shallow Water by the Method of Characteristics

2D Modeling of Wave Propagation in Shallow Water by the Method of Characteristics

High-brightness holographic projection.

We propose a holographic projection system that achieves high image quality, brightness, and light efficiency. Using a novel, to the best of our knowledge, light-efficiency loss function, we are able to concentrate more light on the projection region and improve display brightness compared with conventional projectors. Leveraging emerging artificial intelligence-driven computer-generated holography and camera-in-the-loop calibration techniques, we learn a holographic wave propagation model using experimentally captured holographic images and demonstrate state-of-the-art light reallocation performance with high image quality.

Tsunami Wave Characteristics from the 1674 Ambon Earthquake Event Based on Landslide Scenarios

This study focuses on understanding the historical tsunami events in Eastern Indonesia, specifically the Banda Sea region, by extracting information from the limited and challenging-to-interpret historical records. The oldest detailed account of a tsunami in Indonesia dates back to 1674, documented in the book Waerachtigh Verhael Van de Schlickelijcke Aerdbebinge by Rumphius. The study aims to comprehend the primary source of the tsunami and analyze its characteristics to facilitate future tsunami risk reduction. The methodology includes collecting topography and bathymetry data, conducting landslide scenario analysis, employing a two-layer wave propagation model, and performing spectral analysis. The study utilizes comprehensive datasets, investigates potential landslide scenarios, simulates tsunami propagation, and analyzes frequency characteristics using the fast Fourier transform. The 1674 event yielded a runup height of approximately 50–100 m, whereas this study underestimated the actual runup. To illustrate the tsunami wave along the bay’s coastline, a Hovmöller diagram was employed. By analyzing the Hovmöller diagram, the power spectral density was computed, revealing five prominent period bands: 6.96, 5.16, 4.1, 3.75, and 3.36 min. The integration of these components provides a rigorous approach to understanding tsunami dynamics and enhancing risk assessment and mitigation in the study area.

Frequency-Domain Reverse-Time Migration with Analytic Green's Function for the Seismic Imaging of Shallow Water Column Structures in the Arctic Ocean.

Seismic oceanography can provide a two- or three-dimensional view of the water column thermocline structure at a vertical and horizontal resolution from the multi-channel seismic dataset. Several seismic imaging methods and techniques for seismic oceanography have been presented in previous research. In this study, we suggest a new formulation of the frequency-domain reverse-time migration method for seismic oceanography based on the analytic Green's function. For imaging thermocline structures in the water column from the seismic data, our proposed seismic reverse-time migration method uses the analytic Green's function for numerically calculating the forward- and backward-modeled wavefield rather than the wave propagation modeling in the conventional algorithm. The frequency-domain reverse-time migration with analytic Green's function does not require significant computational memory, resources, or a multifrontal direct solver to calculate the migration seismic images as like conventional reverse-time migration. The analytic Green's function in our reverse-time method makes it possible to provide a high-resolution seismic water column image with a meter-scale grid size, consisting of full-band frequency components for a modest cost and in a low-memory environment for computation. Our method was applied to multi-channel seismic data acquired in the Arctic Ocean and successfully constructed water column seismic images containing the oceanographic reflections caused by thermocline structures of the water mass. From the numerical test, we note that the oceanographic reflections of the migrated seismic images reflected the distribution of Arctic waters in a shallow depth and showed good correspondence with the anomalies of measured temperatures and calculated reflection coefficients from each XCDT profile. Our proposed method has been verified for field data application and accuracy of imaging performance.

Physics‐based wave propagation model assisted vehicle localisation in tunnels

AbstractConnected and autonomous vehicles systems can provide a safe and convenient transportation solution through wireless communication between vehicles and roadside communication infrastructure. The vehicle's ability to establish its location plays an important role in such systems. This article presents an efficient localisation framework by combining physics‐based wireless propagation models and fingerprint localisation algorithms. To that end, a parabolic wave equation (PWE)‐based wireless channel simulator is utilised to obtain the direction of arrival (DOA) values that construct the fingerprint dataset. A detailed procedure on how to obtain the DOA information using PWE, as well as analysis and guidelines on the selection of the key parameters of the localisation framework are provided. Numerical results are compared with theoretical data in terms of accuracy, and the selection of parameters during the localisation process is investigated in actual road tunnel cases. Besides, various numbers of wireless access points and schemes of fingerprinting algorithms have been studied, showing the capability of the proposed approach to be employed for the pre‐design of wireless communication systems.

How Ultrasonic Pulse-Echo Techniques and Numerical Simulations Can Work Together in the Evaluation of the Elastic Properties of Glasses

This paper presents the numerical simulation of the ultrasonic wave transmittance utilizing the elastodynamic finite integration technique (EFIT). With this methodology, it is possible to simulate the propagation of the ultrasound in a medium with a relatively low computational cost. The capability of this technique for determining the elastic properties of fluorophosphate and the aluminosilicate glasses is described in detail. The elastic constants of the glasses were calculated from the theoretically predicted longitudinal and transversal sound velocities and compared with the corresponding experimental data. Furthermore, the calculated and experimental elastic properties of the fluorophosphate and aluminosilicate glasses were correlated with the structural peculiarities of these glasses. This simulation technique is also suitable for unveiling the existence of possible defects in the glasses by comparing the experimental and simulation data. The EFIT technique is shown to be a very useful tool in order to provide fast and easy-to-acquire data regarding also the structural characteristics of various glassy systems. This can be used in conjunction with other spectroscopic techniques which can prove to be extremely useful for the non-destructive testing of vitreous materials. The latter can prove very important when vitreous materials used in optical or optoelectronic applications need continuous monitoring in order to ensure their optimum operation and functionality with limited intervention. The main contribution of this paper is the treatment of numerical time-domain modeling of 2D acoustic wave propagation in a viscoelastic medium by implementing the elastodynamic finite integration technique (EFIT).

Simple two-layer dispersive models in the Hamiltonian reduction formalism

A Hamiltonian reduction approach is defined, studied, and finally used to derive asymptotic models of internal wave propagation in density stratified fluids in two-dimensional domains. Beginning with the general Hamiltonian formalism of Benjamin (1986 J. Fluid Mech. 165 445–74) for an ideal, stably stratified Euler fluid, the corresponding structure is systematically reduced to the setup of two homogeneous fluids under gravity, separated by an interface and confined between two infinite horizontal plates. A long-wave, small-amplitude asymptotics is then used to obtain a simplified model that encapsulates most of the known properties of the dynamics of such systems, such as bidirectional wave propagation and maximal amplitude travelling waves in the form of fronts. Further reductions, and in particular devising an asymptotic extension of Dirac’s theory of Hamiltonian constraints, lead to the completely integrable evolution equations previously considered in the literature for limiting forms of the dynamics of stratified fluids. To assess the performance of the asymptotic models, special solutions are studied and compared with those of the parent equations

Surrogate modeling of time-domain electromagnetic wave propagation via dynamic mode decomposition and radial basis function

This work introduces an ‘equation-free’ non-intrusive model order reduction (NIMOR) method for surrogate modeling of time-domain electromagnetic wave propagation. The nested proper orthogonal decomposition (POD) method, as a prior dimensionality reduction technique, is employed to extract the time- and parameter-independent reduced basis (RB) functions from a collection of high-fidelity (HF) solutions (or snapshots) on a properly chosen training parameter set. A dynamic mode decomposition (DMD) method, resulting in a further dimension reduction of the NIMOR method, is then used to predict the reduced-order coefficient vectors for future time instants on the previous training parameter set. The radial basis function (RBF) is employed for approximating the reduced-order coefficient vectors at a given untrained parameter in the future time instants, leading to the applicability of DMD method to parameterized problems. A main advantage of the proposed method is the use of a multi-step procedure consisting of the POD, DMD and RBF techniques to accurately and quickly recover field solutions from a few large-scale simulations. Numerical experiments for the scattering of a plane wave by a dielectric disk, by a multi-layer disk, and by a 3-D dielectric sphere nicely illustrate the performance of the NIMOR method.

Deep compression network for enhancing numerical reconstruction quality of full-complex holograms.

The field of digital holography has been significant developed in recent decades, however, the commercialization of digital holograms is still hindered by the issue of large data sizes. Due to the complex signal characteristics of digital holograms, which are of interferometric nature, traditional codecs are not able to provide satisfactory coding efficiency. Furthermore, in a typical coding scenario, the hologram is encoded and then decoded, leading to a numerical reconstruction via a light wave propagation model. While previous researches have mainly focused on the quality of the decoded hologram, it is the numerical reconstruction that is visible to the viewer, and thus, its quality must also be taken into consideration when designing a coding solution. In this study, the coding performances of existing compression standards, JPEG2000 and HEVC-Intra, are evaluated on a set of digital holograms, then the limitations of these standards are analyzed. Subsequently, we propose a deep learning-based compression network for full-complex holograms that demonstrates superior coding performance when compared to the latest standard codecs such as VVC and JPEG-XL, in addition to JPEG2000 and HEVC. The proposed network incorporates not only the quality of the decoded hologram, but also the quality of the numerical reconstruction as distortion costs for network training. The experimental results validate that the proposed network provides superior objective coding efficiency and better visual quality compared to the existing methods.

Deriving Vocal Fold Oscillation Information from Recorded Voice Signals Using Models of Phonation.

During phonation, the vocal folds exhibit a self-sustained oscillatory motion, which is influenced by the physical properties of the speaker's vocal folds and driven by the balance of bio-mechanical and aerodynamic forces across the glottis. Subtle changes in the speaker's physical state can affect voice production and alter these oscillatory patterns. Measuring these can be valuable in developing computational tools that analyze voice to infer the speaker's state. Traditionally, vocal fold oscillations (VFOs) are measured directly using physical devices in clinical settings. In this paper, we propose a novel analysis-by-synthesis approach that allows us to infer the VFOs directly from recorded speech signals on an individualized, speaker-by-speaker basis. The approach, called the ADLES-VFT algorithm, is proposed in the context of a joint model that combines a phonation model (with a glottal flow waveform as the output) and a vocal tract acoustic wave propagation model such that the output of the joint model is an estimated waveform. The ADLES-VFT algorithm is a forward-backward algorithm which minimizes the error between the recorded waveform and the output of this joint model to estimate its parameters. Once estimated, these parameter values are used in conjunction with a phonation model to obtain its solutions. Since the parameters correlate with the physical properties of the vocal folds of the speaker, model solutions obtained using them represent the individualized VFOs for each speaker. The approach is flexible and can be applied to various phonation models. In addition to presenting the methodology, we show how the VFOs can be quantified from a dynamical systems perspective for classification purposes. Mathematical derivations are provided in an appendix for better readability.

Study on predictability of ocean wave fields based on marine radar measurement data

In this study, the predictability of ocean wave fields is considered based on marine radar measurement data. Phase-resolved components obtained by applying 3D FFT-based reconstruction to a sequence of radar images are utilized for wave field prediction, and two different prediction approaches are introduced: (i) snapshot data-based prediction through the adjustment of the frequency and phase of each component, and (ii) spatiotemporal data-based prediction through the data assimilation for reconstructed wave fields. Furthermore, the time evolution of a predictable zone is derived for different shapes of measurement domains including rectangular and ring-shaped domains. To validate the proposed wave propagation modeling method, numerical simulations are conducted on synthetic radar images created by reflecting geometrical shadowing effects, and the prediction accuracy is examined in relation to the derived predictable zone. Lastly, the forecasting performance, which is represented by the predictable time range at a radar location, is discussed with respect to the prediction techniques, specifications of the reconstruction domain, and moving measurements.

Numerical Study on the Dynamic Propagation Model of Cracks from Different Angles under the Effect of Circular Hole Explosion

A dynamic disturbance will induce cracks around the tunnel in tunnel blasting or shield construction. To investigate the overall stability of cracks with various angles during a fixed borehole (round hole explosion) blasting, models containing an individual crack with different angles were introduced for simulation research. The research set up a thin sheet model with a length of 350 mm and a width of 150 mm, with a 7 mm diameter hole and a pre-existing crack of 75 mm and 5 mm in the middle. The evolution of the stress wave propagation model and the crack propagation model were simulated using the AUTODYN software. And in this study, the theory of stress wave is used to creatively explain the dynamic load under the action of formation and reasons for the danger zone. The results indicate that pre-existing cracks from different angles will have an impact on the blast hole and the new cracks generated around itself. At 45–90°, pre-existing cracks will direct reflected stress waves to promote some cracks around the hole to have faster growth rates than others, and these special cracks with faster growths and longer lengths will more easily connect with the free surface or other cracks, resulting in overall instability. And these conditions are consistent with the prediction made by the stress wave propagation simulation study. The research results have certain guiding significance for the stability analysis and hazardous area prediction of tunnel blasting with existing cracks.

Numerical analysis of Plastic Perforated Panel for Acoustic Protection

Acoustic protection is an important aspect in various industrial, commercial and residential applications. In order to reduce the transmission of noise, perforated panels are frequently used as a barrier. The present study aims to conduct a numerical analysis of plastic perforated panels for acoustic protection. The study employed a finite element method (FEM) approach and focused on the propagation of acoustic waves through perforations of varying diameters (30 mm, 40 mm, 50 mm, 60 mm, 70 mm and 90 mm) and at different frequencies (250 Hz, 500 Hz, 1000 Hz and 1500 Hz). The numerical analysis was conducted using the finite element software ANSYS. This work offers numerical analysis models of acoustic wave propagation, which can be used by those interested in similar problems, for different environments, in closed or open spaces. The results showed that the perforation diameter and frequency play a crucial role in the performance of the plastic perforated panels as an acoustic barrier. The results of the author�s research pointed out that the plastic materials can be used successfully in the construction of acoustic barriers. Next to it, the findings of this study can provide valuable insights for engineers and designers in the selection and optimization of plastic perforated panels for acoustic protection applications.

A Comprehensive Prediction Model for VHF Radio Wave Propagation by Integrating Entropy Weight Theory and Machine Learning Methods

In order to improve the prediction accuracy and robustness of radio wave propagation in the very high-frequency (VHF) band, we proposed a combination prediction model (hereinafter referred to as CPM) based on the entropy weight theory and the machine learning method. The improved entropy weight method is used to determine the initial weights of recommendation ITU-R P.1546 and ITU-R P.2001 in the combination prediction model based on the systematic analysis of the prediction performance of the two ITU-R models. Furtherly, we modeled the weight mapping using the machine learning method. The statistical comparison shows that the prediction accuracy and robustness of the proposed model are better than ITU-R P.1546 and P.2001 models, in which the root mean square error (RMSE) of path loss is reduced by 3.56dB and 7.35dB, respectively. In addition, the relative error (RE) of path loss is reduced by 0.0157 dB and 0.0255 dB, respectively, corresponding to a 40.53% and 52.62% reduction in the RE of path loss. The above research can provide basic support for the regional assimilation of radio propagation prediction methods.

Level set-based shape optimization of deformable structures for achieving desired sound transmission and reflective responses

In this paper, we propose a level set-based shape optimization method for acoustic wave propagation problems with a deformable structure. First, we propose a mathematical model for acoustic wave propagation with a deformed structure based on coordinate transformation and the Eulerian approach. Next, we formulate the shape optimization problem and perform sensitivity analysis based on the shape derivative concept. We then construct an optimization algorithm based on the framework of a level set-based shape and topology optimization method. Finally, we provide two-dimensional optimization examples that demonstrate the effectiveness of our proposed method in providing optimized designs with desired functionality, while considering the structural deformation.

Theoretically derived pore geometry in carbonates using the extended biot theory

Carbonates typically display a large scatter in velocity-porosity cross plots that is caused by the difference in stiffness that the highly variable pore geometry produces in carbonate rocks at a given porosity. In recent years, digital image analysis (DIA) made it possible to capture objective, quantifiable parameters of the pore geometry to explain the scatter in carbonate velocity-porosity cross plots. The geometrical parameters most influential for acoustic velocity are Perimeter over Area (measuring the complexity of the pore space) and Dominant Size (measuring pore sizes as equivalent diameter). Most theoretical models of acoustic wave propagation in porous media, however, do not incorporate those geometrical characteristics of the natural pore spaces? In contrast, the frame flexibility and coupling factors (fk and γk) embedded in the Extended Biot Theory capture the geometrical characteristics using poroelastic data. Here, these theoretically derived parameters are tested and validated with experimental data. In 95 limestone samples, Extended Biot Theory parameters fk and γk can be derived reliably from measured acoustic data. Both parameters correlate well to Perimeter over Area (r = 0.702, p < 0.0001), and Dominant Size (r = 0.792, p < 0.0001) derived using digital image analysis of thin section photographs. These correlations confirm the existence and the strength of the relationship between theoretical parameters from the Extended Biot Theory and quantitative pore geometry parameters. Thus, this study illustrates that: (1) estimating porosity from acoustic data can be substantially improved by incorporating information on quantitative pore space geometry; and (2) in cases where good estimates of porosity are available (e.g. from well-log data or seismic with extensive well control) quantitative pore geometric characteristics can be estimated directly from acoustic data. These quantitative pore geometry characteristics can be used to estimate permeability indirectly from acoustic data. For example, permeability estimates based on a Kozeny-Carman type function incorporating geometrical information derived from the topological Extended Biot Theory parameters fk and γk, yield a statistically significant, high Pearson correlation coefficient of r = 0.713 (p < 0.0001).

Determining the Deformation Characteristics of Railway Ballast by Mathematical Modeling of Elastic Wave Propagation

The article solves the problem of theoretically determining the deformable characteristics of railway ballast, considering its condition through mathematical modeling. Different tasks require mathematical models with different levels of detail of certain elements. After a certain limit, excessive detailing only worsens the quality of the model. Therefore, for many problems of the interaction between the track and the rolling stock, it is sufficient to describe the ballast as a homogeneous isotropic layer with a vertical elastic deformation. The elastic deformation of the ballast is formed by the deviation of individual elements; the ballast may have pollutants, the ballast may have places with different levels of compaction, etc. To be able to determine the general characteristics of the layer, a dynamic model of the stress–strain state of the system based on the dynamic problem of the theory of elasticity is applied. The reaction of the ballast to the dynamic load is modeled through the passage of elastic deformation waves. The given results can be applied in the models of the railway track in the other direction as initial data regarding the ballast layer.

A multi-objective approach for location and layout optimization of wave energy converters

Wave Energy Converters (WECs) have been increasingly installed in various coastal regions due to the higher energy density of waves than other renewable sources. Regarding coastal regions’ high potential, it is remarkably better to emplace multiple devices concerning a layout of the arrays with different configurations. Although WECs can capture the highest energy in hotspots, the location for installing these devices must be optimized. Purposefully, the wave propagation model, SWAN, was first employed respected to stochastic wind data to assess the wave energy potential and compute the annual energy production (AEP). The Latin Hypercube Sampling (LHS) technique was used to generate samples. Finally, the optimal location and layout of the arrays were determined through the multi-objective optimization (MOOP) algorithm, NSGA-III, based on SWAN’s sequential outputs. The optimized layouts contained arrays with 4-, 8-, and 16-devices with regard to devices’ initial state. Almost 20 hotspots were located by solving the Pareto-front. It was found that the best arrangement for the 4-device arrays is linear. However, the optimal arrangement of the 8- and 16-device arrays widely varies and depends on the AEP of the region. Nevertheless, it seems best to position the 16-device array in a diagonal layout with one to three rows.

Plenty of accurate, explicit solitary unidirectional wave solutions of the nonlinear Gilson–Pickering model

This paper proposes abundant accurate wave solutions that represent the plasma wave propagation based on crystal lattice theory and physicochemical characterization. The Gilson–Pickering ([Formula: see text]) model is analytically and numerically solved by two recent techniques. This model is a basic unidirectional wave propagation model that describes the prorogation of waves in crystal lattice theory and plasma physics. The investigated model has a deep connection with some nonlinear evolution equations under specific values of its parameters, such as the Fuchssteiner–Fokas–Camassa–Holm ([Formula: see text]) equation, the Rosenau–Hyman ([Formula: see text]) equation, and the Fornberg–Whitham ([Formula: see text]) equation. The Sardar sub-equation and He’s variational iteration techniques are employed to construct novel and accurate solitary wave solutions of the handled model. The obtained solutions are explained through some distinct graphs in contour, three-, two-dimensional. The research value is explained by comparing our results with some recently published studies. The employed methods show their simple, direct, effectiveness and their ability for handling many nonlinear evolution equations.

Performance of old and new mass‐lumped triangular finite elements for wavefield modelling

AbstractFinite elements with mass lumping allow for explicit time stepping when modelling wave propagation and can be more efficient than finite differences in complex geological settings. In two dimensions on quadrilaterals, spectral elements are the obvious choice. Triangles offer more flexibility for meshing, but the construction of polynomial elements is less straightforward. The elements have to be augmented with higher‐degree polynomials in the interior to preserve accuracy after lumping of the mass matrix. With the classic accuracy criterion, triangular elements suitable for mass lumping up to a polynomial degree 9 were found. With a newer, less restrictive criterion, new elements were constructed of degree 5–7. Some of these are more efficient than the older ones. To assess which of all these elements performs best, the acoustic wave equation is solved for a homogeneous model on a square and on a domain with corners, as well as on a heterogeneous example with topography. The accuracy and runtimes are measured using either higher‐order time stepping or second‐order time stepping with dispersion correction. For elements of polynomial degree 2 and higher, the latter is more efficient. Among the various finite elements, the degree‐4 element appears to be a good choice.