Modeling Of Electromagnetic Wave Propagation Research Articles

An Efficient and Accurate Algorithm for Electromagnetic Wave Propagation Modeling Based on Wavelet Transforms

An Efficient and Accurate Algorithm for Electromagnetic Wave Propagation Modeling Based on Wavelet Transforms

Thermal Effects of Electromagnetic Energy on Skin in Contact with Metal: A Numerical Analysis

It has been well recognized that interactions between electromagnetic fields and metals are very strong. The consequence of human tissue in contact with metal, when subjected to an alternating electromagnetic field, is an increase in tissue temperature, which results from metals absorbing the energy obtained through induction. However, the electromagnetic induction characteristics and tissue energy absorbed caused by various electromagnetic field exposure conditions have not been well understood. A computational model was developed and employed in this study to assess the temporal and spatial temperature increases in skin due to contact with a highly conductive metallic plate while subjected to a high-intensity electromagnetic field. The effects of plate material, plate thickness, coil distance, and exposure time on temperature increase in the skin were computationally investigated. The electromagnetic and temperature distributions in skin layers during exposure to electromagnetic fields were achieved using models of electromagnetic wave propagation and an unsteady bioheat transfer. The modeling approach used indicates that the plate thickness, plate material, coil distance, and exposure time have a significant impact on the temperature change in the skin. The most important parameter was found to be the metal type. Iron has the greatest effect on skin temperature increase when subjected to external electromagnetic induction. These results allow the researchers to estimate more precisely the exposure limits for induction coils.

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.

A Comparative Study of Rough Sea Surface and Evaporation Duct Models on Radio Wave Propagation

Microwave and millimeter-wave propagations near the sea surface are greatly affected by the vertical atmospheric refractivity profile and the sea surface. To accurately simulate or predict the performance of ship radar systems, the evaporation duct model and rough sea surface models are usually incorporated into the parabolic equation to model electromagnetic wave propagation. The Paulus-Jeske (PJ) model and Naval Postgraduate School (NPS) model are the most widely used to make the vertical atmospheric refractivity profile, and the roughness sea surface is modeled with the effective reflection coefficient of the rough surface or the generation of the rough sea surface. There are four widely used rough sea surface approximations called Ament, Miller-Brown, Shadowed, and Hybrid for rough sea surface modeling. In this study, numerical simulation is first used to compare the different rough sea surface modeling methods. Then, evaporation duct measurement data and C-band propagation experimental data are used to compare the evaporation duct models and the four rough sea surface models that are combined with evaporation duct models for propagation loss prediction. The simulation results show that the shadowing of radio waves by the rough sea surface and sea surface structure are important factors affecting the transmission of radio waves in evaporation ducts, and the difference in the path loss predicted by different rough sea surface approximations may exceed 10 dB at the same location. In particular, the frequency and wind speed will increase. In addition, the experimental data show that the evaporation duct can be better diagnosed using different evaporation duct models at different atmospheric stabilities. When the air-sea temperature difference is positive, the PJ evaporation duct is recommended; otherwise, the NPS model is better, and the results of the Shadowed and Hybrid rough sea surface models are in better agreement with the observations.

Path Loss and Auxiliary Communication Analysis of VANET in Tunnel Environments

Vehicular ad hoc network (VANET) communications face severe fading problems due to the signal reflections and diffractions within tunnels. Unlike the open road, the space of a tunnel is very limited, so VANET communication performance in a tunnel is seriously affected. In the process of signal transmission, the reflected signal is symmetrical with the incident signal after it is reflected by the road and the wall. In this paper, we establish a mathematical model of path loss for V2V (Vehicle-to-Vehicle) communication based on the principle of signal reflection symmetry in tunnels and considering several factors, such as the tunnel surface and the color of the tunnel wall. In addition, we use cooperative communication to form a virtual multiple-input multiple-output (V-MIMO) system, to improve the communication quality in tunnels. In the proposed system, the OBU (On-Board-unit) and RSU (Road-Side-Unit) share each other’s antennas, so that wireless cooperative communication can be employed, without increasing the number of antennas in a one-way tunnel. Therefore, this multipath fading internal electromagnetic wave propagation model can be used to improve performance. A deep reinforcement learning algorithm was used to solve the pairing problem to obtain a more accurate OBU and RSU pair, to form a V-MIMO system. Here, the RSU is regarded as an agent and interacts with the OBU in the tunnel. The optimal strategy was learned in a real-time changing simulation environment, and the experiment verified the convergence of the algorithm. The simulation results showed that, compared with the Q-learning based scheme, the optimal matching algorithm based on V-MIMO and a DQN (Deep Q-network) could effectively reduce the probability of transmission outages and improve the communication efficiency in tunnels.

Non-destructive detection of thin micro-defects in glass reinforced polymer composites using a terahertz electro–magnetic wave based on a convolution neural network

This study presents a non-destructive evaluation (NDE) method that utilizes a convolutional neural network (CNN) based terahertz (THz) signal processing to quantitively distinguish overlapping signals from micro-defects in glass fiber reinforced polymer (GFRP) composites. Theoretical electro–magnetic wave propagation models for describing the propagation of the THz signal into the GFRP composite were devised considering the interaction of THz with the micro-defects in the GFRP composite. THz signals were simulated with respect to the thickness of the defects, and transformed into two-dimensional (2D) spectrograms using a short-term Fourier transform (STFT). The converted 2D-STFT images were used to train the CNN deep learning model to classify the size and thickness of the defects. A probability map of the classification of the defect thickness was derived from the trained CNN deep learning model. Using the probability map based on the CNN model, the depth and size of the micro-defects thinner than 20 μm inside the GFRP composites could be successfully differentiated with 95% accuracy. This research proposes a promising approach for analyzing micro-defects in composite materials by quantitatively evaluating the extent of signal overlap, going beyond the traditional approach of training the model based solely on the signal.

Deep Learning-Based Localization with Urban Electromagnetic and Geographic Information

There is a growing demand for localization of illegal signal sources, aiming to guarantee the security of urban electromagnetic environment. The performance of traditional localization methods is limited due to the non-line-of-sight (NLOS) propagation and sparse layouts of sensors. In this paper, a deep learning-based localization method is proposed to overcome these issues in urban scenarios. Firstly, a model of electromagnetic wave propagation considered with geographic information is proposed to prepare reliable datasets for intelligent cognition of urban electromagnetic environment. Then, this paper improves an hourglass neural network which consists of downsampling and upsampling layers to learn the propagation features from sensing data. The core modules of VGG and ResNet are, respectively, utilized as feature extractors in downsampling. Moreover, this paper proposes a weighted loss function to expand the attention on position features, in order to improve the performance of localization with sparse layouts of sensors. Representative numerical results are discussed to assess the proposed method. ResNet-based extractor performs more efficiently than VGG-based extractor, and the proposed weighted loss function increases the localization accuracy by more than 50%. Additionally, the established geographic model supports qualitative and quantitative evaluation of the robustness with varied degree of NLOS propagation. Compared with other deep learning-based algorithms, the proposed method presents the more robust and superior performance under severe NLOS propagation and sparse sensing conditions.

Synthetic modeling and field GPR survey to understand the near-surface deformation induced by coseismic groundwater dynamics following the 2019 Mirpur earthquake in Pakistan

The Mirpur earthquake of Mw 5.8 on 24 September 2019 severely damaged villages in the epicentral area. The earthquake-triggered ground dynamics produced widespread liquefaction features on the surface (e.g., fractured road structure and sand boils) and in the shallow subsurface (e.g., elevated groundwater table, fractures, and sand dikes). Due to complexity of liquefaction-induced deformation and timing of field surveys, the structural and hydrogeologic features that develop in the near surface during seismic events are often poorly resolved on ground-penetrating-radar (GPR) profiles. To track and delineate the internal architecture and coseismic changes in groundwater levels and/or pressures due to liquefaction, a GPR survey was carried out soon after the Mirpur earthquake. The sudden pore water pressure changes in the shallow aquifer system caused a rise in the water table via upward groundwater movement and fracturing followed by rapid infiltration. This cascade phenomenon has adverse effects on soil, water resources, civil infrastructure, and public health and safety. To better understand induced changes in the physical properties of road infrastructure and the shallow subsurface, we performed synthetic modeling of electromagnetic wave propagation by employing the finite-difference time-domain method. Based on the available information at multiple scales (borehole and geophysical), subsurface physical models representing the most common and important coseismic features were considered for synthetic modeling. Likewise, synthetic tests of paved road were conducted to simulate the radar response of structural discontinuities (fractures) developed at different angles. To validate synthetic results by identifying a similar dynamic response of the induced hydrogeologic changes in the form of coseismic liquefaction features, a field GPR survey was conducted. Our results clearly demonstrate that the GPR technique is a potential candidate for hydrogeophysical detection and characterization of features of interest in the case of paved roads as well as agricultural and residential areas. Additionally, the successful application of GPR proves it to be a cost-effective, high-resolution, and speedy tool for better assessment of hydrogeologic hazard, socioeconomic consequences, and mitigation in the Mirpur area. The proposed approach may find applications in other seismically active regions around the world.

Finite-difference time-domain analysis of ELF radio wave propagation in the spherical Earth–ionosphere waveguide and its validation based on analytical solutions

Abstract. The finite-difference time-domain (FDTD) model of electromagnetic wave propagation in the Earth–ionosphere cavity was developed under assumption of an axisymmetric system, solving the reduced Maxwell equations in a 2D spherical coordinate system. The model was validated on different conductivity profiles for the electric and magnetic field components for various locations on Earth along the meridian. The characteristic electric and magnetic altitudes, phase velocity, and attenuation rate were calculated. We compared the results of numerical and analytical calculations and found good agreement between them. The undertaken FDTD modeling enables us to analyze the Schumann resonances and the propagation of individual lightning discharges occurring at various distances from the receiver. The developed model is particularly useful when analyzing ELF measurements.

A predictive 6G network with environment sensing enhancement: From radio wave propagation perspective

In order to support the future digital society, sixth generation (6G) network faces the challenge to work efficiently and flexibly in a wider range of scenarios. The traditional way of system design is to sequentially get the electromagnetic wave propagation model of typical scenarios firstly and then do the network design by simulation offline, which obviously leads to a 6G network lacking of adaptation to dynamic environments. Recently, with the aid of sensing enhancement, more environment information can be obtained. Based on this, from radio wave propagation perspective, we propose a predictive 6G network with environment sensing enhancement, the electromagnetic wave propagation characteristics prediction enabled network (EWaveNet), to further release the potential of 6G. To this end, a prediction plane is created to sense, predict and utilize the physical environment information in EWaveNet to realize the electromagnetic wave propagation characteristics prediction timely. A two-level closed feedback workflow is also designed to enhance the sensing and prediction ability for EWaveNet. Several promising application cases of EWaveNet are analyzed and the open issues to achieve this goal are addressed finally.

Attenuation Characteristics and Time Delay of PD Electromagnetic Wave Propagation in GIS Systems

Modeling of electromagnetic wave propagation inside a gas-insulated switchgear structure can be helpful for understanding and improving the utilization of partial discharge detection by providing information to help determine more optimal positioning of ultra-high frequency sensors. This paper studies the effect of insulating spacers, L- and T-type structures on electromagnetic wave propagation by simulating the time dependent wave propagation behavior for these arrangements within a gas-insulated switchgear busbar geometry. The attenuation characteristics and time delays produced by spacers, L- and T-type structures for partial discharge electromagnetic wave propagation behavior are presented. Emphasis is placed on comparison of attenuation characteristics and time delay between different observation points along the busbar both before and after the 90° bends formed by L- and T-type structures. Moreover, a comparative analysis of the radial electric field at the gas-insulated switchgear tank and its rate of change with time is also conducted. The paper demonstrates that if the location of the ultra-high frequency sensor is chosen appropriately based on knowledge of the physical structures, the attenuation effects introduced by L- and T-type structures could be reduced.

Physics-informed Supervised Residual Learning for Electromagnetic Modeling

In this paper, we propose a non-stationary iterative physics-informed supervised residual learning scheme (NSIP-ISRL) as a general framework for modeling electromagnetic wave propagation in inhomogeneous medium. NSIPISRL is based on the residual neural network (ResNet) that maps the residuals of matrix equation to the update of solutions [1]. It incorporates the concept of non-stationary iterative method, in which physical principles are embedded in the solution process through matrix-vector multiplication. NSIPISRL is applied to solve 2D volume integral equations in order to model electromagnetic wave interaction with lossy scatterers. The results show that NSIPISRL has a good accuracy and a strong generalization ability. The trained network can be applied to various scenarios with different scatterers, different incident angles, and different frequencies and still maintain a good accuracy.

Experimental research on the interaction between electromagnetic wave and plasma

The basis of plasma stealth technology is the attenuation of electromagnetic waves by plasma. In this study, the calculation principle of the finite-difference time-domain (FDTD) method is introduced and a FDTD time–space coupling model of electromagnetic wave propagation in plasma is established. The time-domain variation characteristics of electromagnetic waves entering the plasma are analyzed. The plasma parameter distribution under different conditions obtained using the COMSOL fluid mechanics model is introduced into the FDTD model. The plasma reflectivity measurement experiment was carried out in a microwave anechoic chamber, and the influence of different experimental conditions on the plasma reflectivity was analyzed. The variation of reflectivity under different plasma parameter distributions is obtained. The results show that increasing electron density and plasma thickness and enhanced plasma distribution uniformity are beneficial for improving the attenuation effect of plasma on electromagnetic waves. These results provide a reference for the inductively coupled plasma parameter distribution in a closed quartz cavity, which provides a basis for the plasma to attenuate the electromagnetic waves.

Theoretical Analyses and Experimental Research on Transmission of Electromagnetic Wave Passing through Concrete Materials Surface

Simplified theoretical model of electromagnetic wave propagation on concrete materials surface is established first by only considering the normal incidence case. In order to investigate the impact of concrete component to the wave transmission, concrete materials specimens with different composite were casted, which were tested by electromagnetic pulse testing method. Study shows that the transmission rate is only relevant with the concrete materials relative dielectric parameter. The greater relative dielectric constant, the smaller transmission rate in materials surface is. Among all this concrete casting components, unit volume water content has the most obvious influence on transmission rate. To change the transmission rate of electromagnetic wave, it is necessary to control the unit volume water content in concrete materials design process.

A Review of Grid-Based, Time-Domain Modeling of Electromagnetic Wave Propagation Involving the Ionosphere

The ionosphere plays a critical role in many electromagnetics applications, ranging from long-distance communications to geolocation and satellite communications. As a result, it is of paramount importance to have accurate models of the impact of the ionosphere on electromagnetic wave propagation. Numerous approaches have been suggested over the years to address this problem, including ray tracing, mode theory, and grid-based methods. This paper summarizes the development and applications of grid-based, time-domain methods for predicting electromagnetic wave propagation in the ionosphere. The advantage of these models is their ability to account for detailed inhomogeneities of the ionosphere as well as their ability to model wideband sources and realistic source waveforms (such as lightning strikes). First, different classes of ionospheric algorithms are provided, along with how the required ionospheric parameters are obtained. Second, an overview of the grid-based, time-domain models that have been used to simulate electromagnetic propagation in the ionosphere are described, ranging from 2-D and 3-D FDTD models to FETD and DGTD approaches. Finally, a list of key applications of these models is provided.

Two Approaches for Modeling ELF Wave Propagation in the Earth-Ionosphere Cavity With Day-Night Asymmetry

In this article, we introduce a lesser-known analytical treatment and a new numerical approach to model electromagnetic wave propagation in the lowest part of the extremely low-frequency (ELF) band (<; 100 Hz) that takes into consideration the day-night asymmetry of the Earth-ionosphere cavity. We present numerical tests showing that the two models produce practically the same output, i.e., the relative difference between them is less than 0.4%. Our result is an important step toward inferring the distribution and intensity of global lightning activity based on the Schumann resonance (SR) measurements, which is the main objective of our work.

Solution of Maxwell’s Equations for Nonrectangular Electromagnetic Applications

The use of a fourth-order modified Runge–Kutta (MRK) scheme on a transformed coordinate system with Maxwell’s equations for nonrectangular domains and applications is presented. Maxwell’s equations are the governing equations for modeling electromagnetic wave propagation involving scattering, radiating structures, transmission lines, radar, biomedical applications, and nondestructive testing. Because of complex geometries in most problems where the material boundaries are not parallel to the grid axis, the application of finite differencing schemes in physical coordinates becomes nonviable. Therefore, by transforming the arbitrary-shaped structures to a uniform rectangular grid, numerical schemes and boundary conditions can be easily implemented. Numerical results for four cases are presented in this paper. Accuracy of the scheme has been established by comparing numerical results with the exact solution and error distribution plots. In the third case, scattering from the lossless and the lossy square cylindrical dielectric device where the plane wave source is injected using the total-field–scattered-field technique has been investigated. The results are compared with the results obtained from the benchmark finite difference time domain scheme. Lastly, the application of the numerical model to simulate scattering from curved boundaries has been presented in the fourth example.

Integrated Application of GPR and Ultrasonic Testing in the Diagnostics of a Historical Floor.

The paper presents the results of integrated ground penetrating radar (GPR) and ultrasonic testing (UT) measurements conducted on a historical floor in St. Nicholas’ Church, Gdańsk, Poland. The described inspection was the first stage of the technical state assessment of the building. The aim of the study was the detection of underfloor air gaps, which were observed in a few trial pits. The condition of the ground under the floor was determined by localizing other inclusions such as rubble, human remains, brick walls and pipes. To identify the phenomenon of electromagnetic and ultrasonic wave propagation within the air gap, laboratory tests were conducted on physical models consisting of two concrete slabs stacked on top of each other and gradually moved apart to simulate a slot of varying thickness. The conducted research was supported by the numerical models of electromagnetic wave propagation. The obtained results showed that the integration of the GPR and UT methods provided an effective imaging of the floor and the area under it. Ultrasonic testing was proved to be a good technique for identifying air voids, while the GPR method allowed detecting concentrated anomalies and determining the degree of ground homogeneity under the floor.

Impact of ionization rate on the transmission of electromagnetic wave in realistic plasma

A self-consistent calculation model of hypersonic fluid and electromagnetic wave (EM) propagation around a vehicle was used for radio frequency (RF) blackout prediction. First, the plasma flow around the RAMC-II vehicle at an altitude of 61 km was calculated using the finite-volume method with a newly developed unstructured grid solver. The electron number density around the RAMC-II vehicle shows good agreement with the flight test data and NASA data. Then, the effect of chemical reaction ionization rate on the plasma flow is studied, which shows that the electron number density decreases with the decrease in the chemical reaction ionization rate. Finally, based on the influence of the chemical reaction ionization rate on plasma flow, the transmission properties of the electromagnetic wave in realistic plasma at different chemical reaction ionization rates were investigated. The numerical results show that the signal loss of EM waves decreases with the decrease in the ionization rate. The ionization rate is reduced by 25 times, and the electromagnetic wave signal loss is reduced by approximately 30 dB. Based on the study, a scheme to reduce the electron number density around the vehicle by reducing the ionization rate of the chemical reaction, thereby reducing the signal loss of the electromagnetic wave, can be considered to mitigate the RF blackout.

The Conformal Finite-Difference Time-Domain Simulation of GPR Wave Propagation in Complex Geoelectric Structures

The finite-difference time-domain (FDTD) method adopts the most popular numerical model simulating ground penetrating radar (GPR) wave propagation in an underground structure. However, a staircase approximation method is usually adopted to simulate the curved boundary of an irregular object in the FDTD and symplectic partitioned Runge-Kutta (SPRK) methods. The approximate processing of rectangular mesh parameters will result in calculation errors and virtual surface waves for irregular targets of an underground structure. In this paper, we examine transverse mode (TM) electromagnetic waves with numerical models of electromagnetic wave propagation in geoelectric structures with conformal finite-difference time-domain (CFDTD) method technology in which the effective dielectric parameters are used to accurately simulate the dielectric surface and to absorb waves at the edges of the grid. The third orders of the transmission boundary are used in this paper. Additionally, three complex geocentric models of inclined layered media, spherical media, and three-layered pavement model with structural damages are set up for simulation calculations, then we carry out the actual radar wave detection in a laboratory as the fourth numerical example. Comparison of simulated reflectance waveform of FDTD, symplectic partitioned Runge-Kutta (SPRK), and CFDTD methods shows that at least 50% of the virtual waves can be reduced by using the proposed algorithm. Wiggle diagrams of FDTD and CFDTD methods show that much of the virtual waves have been reduced, and the radar image is clearer than before. This provides a method for the detection of complex geoelectric and layered structures in actual engineering.