Computational Electromagnetic Simulations Research Articles

Antipodal Vivaldi Antenna with Star Trek insignia-based side slot edge for ultra-wideband applications

This article presents a Vivaldi Antipodal Antenna (AVA) with lens and radiating side cavities based on the Star Trek insignia, called Star Trek Side Edge Radiation (STSER-AVA). The objective was to improve parameters to make the radiation of the proposed antenna more directive. To this aim, the development is focused on reducing the squint of the central radiation beam and the side lobe level (SLL), as well as increasing the gain compared to a Conventional AVA. To achieve the objective, using an optimized design. The proposed antenna with or without a lens reached the target with a squint of -2.0 degrees, at 3.90 GHz the antenna with a lens achieved better gain (9.42 dB), but with a greater reduction in SLL of -10.73 dB compared to the lens less antenna. The results were obtained with computational electromagnetic simulations and experimental measurements.

Accurate Modeling of Intelligent Reflecting Surface for Communication Systems

In the conventional sense, a passive intelligent reflecting surface (IRS) is perceived as an ideal phase shifter to the incident signal. It is assumed that the phase of the incident signal can be altered to any desired value without affecting its magnitude. In this paper, we question the veracity of this assumption which forms the basis for the communication model that is widely used in the scientific community. Although there exist rigorous electromagnetic (EM) based models to analyze and design metasurfaces, the same cannot be said about its successor, intelligent reflecting surface. Therefore, we attempt to present an EM-based model that accurately describes intelligent scattering by any arbitrary-shaped IRS. Our objective in this paper is to bridge the gap between the fundamental EM formulation for an IRS and the communication model that accurately captures its functioning. We use Method-of-Moments (MoM), a computational electromagnetic approach to quantify the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">intelligent</i> scattering by an arbitrary-shaped IRS. The proposed theoretical model is then validated with computational EM simulation in Feko. We then adopt the general MoM-based model for a special case where each IRS element is a center-loaded wire. Closed-form expressions for pathloss and beamwidth are derived considering free space propagation. We show analytically and numerically, that the received power predicted by the conventional model vs. what is observed through computational EM simulations can differ by 6 dB. Furthermore, we demonstrate that the impact of optimizing an IRS using the conventional model, where each element is treated as an ideal passive phase shifter, can result in an additional 6 - 8 dB of power loss. As a final remark, we propose correction to the communication model that is currently used for IRS-aided networks when each IRS element is a center-loaded wire.

The effect of body position change on noninvasively acquired intracranial pulse waves

Objective. Craniospinal compliance (CC) is an important metric for the characterization of space-occupying neurological pathologies. CC is obtained using invasive procedures that carry risks for the patients. Therefore, noninvasive methods for acquiring surrogates of CC have been proposed, most recently based on changes in the head’s dielectric properties during the cardiac cycle. Here, we have tested whether changes in body position, which are known to influence CC, are reflected in a capacitively acquired signal (hereinafter referred to as W) originating from dynamic changes of the head’s dielectric properties. Approach. eighteen young healthy volunteers were included in the study. After 10 min in supine position, subjects were tilted head-up (HUT), back to 0° (horizontal, control), and then head-down (HDT). Metrics related to cardiovascular action were extracted from W, including AMP, the peak-to-valley amplitude of the cardiac modulation of W. Computational electromagnetic simulations were performed to probe the association between intracranial volume change and W. Main results. AMP decreased during HUT (0°: 2869 ± 597 arbitrary units (au); +75°: 2307 ± 490 au, P = 0.002) and increased during HDT (−30°: 4403 ± 1428 au, P < 0.0001). The same behavior was predicted by the electromagnetic model. Significance. tilting affects the distribution of CC between cranial and spinal compartments. Cardiovascular action induces compliance-dependent oscillatory changes in the intracranial fluid composition, which causes corresponding variations in the head’s dielectric properties. These manifest as increasing AMP with decreasing intracranial compliance, which suggests that W may contain information related to CC, and that it might be possible to derive CC surrogates therefrom.

A characterization of plasma properties of a heterogeneous magnetized low pressure discharge column

An approach is presented for characterizing heterogeneous magnetized plasma discharge tubes through the scattering of electromagnetic plane waves. Here, we formulate the analytical problem of electromagnetic scattering from a gyrotropic plasma column. The scattering accounts for the heterogeneous composition of the cylindrical discharge plasma and facilitates determining its propensity for gyrotropic scattering, particularly when electron collisional damping may be prevalent. The analytical results are validated using computational simulations. Scattered fields from the magnetized plasma are measured experimentally, and, by comparing the analytical and experimental results, the unknown parameters of the discharge, i.e., characteristic plasma and electron collisional damping frequencies, are determined. The technique is relatively straight-forward to use and removes the need for commercial computational electromagnetic simulations when experimental data on scattering characteristics of such cylindrical discharge plasmas are available.

MaxwellNet: Physics-driven deep neural network training based on Maxwell’s equations

Maxwell’s equations govern light propagation and its interaction with matter. Therefore, the solution of Maxwell’s equations using computational electromagnetic simulations plays a critical role in understanding light–matter interaction and designing optical elements. Such simulations are often time-consuming, and recent activities have been described to replace or supplement them with trained deep neural networks (DNNs). Such DNNs typically require extensive, computationally demanding simulations using conventional electromagnetic solvers to compose the training dataset. In this paper, we present a novel scheme to train a DNN that solves Maxwell’s equations speedily and accurately without relying on other computational electromagnetic solvers. Our approach is to train a DNN using the residual of Maxwell’s equations as the physics-driven loss function for a network that finds the electric field given the spatial distribution of the material property. We demonstrate it by training a single network that simultaneously finds multiple solutions of various aspheric micro-lenses. Furthermore, we exploit the speed of this network in a novel inverse design scheme to design a micro-lens that maximizes a desired merit function. We believe that our approach opens up a novel way for light simulation and optical design of photonic devices.

Cubesat Antenna Analysis and Design: Are you using the right computational electromagnetic tool?

Antenna systems play a critical role in establishing wireless communication links and sustaining remote sensing requirements for Cubesat applications. In addition to the usual antenna design requirements, Cubesat-based spacecrafts impose additional stringent constraints related to the on-board available space, power consumption and development costs. To develop optimal antenna prototypes while considering all these constraints and decrease trial and error related costs, computational electromagnetics (CEM) simulation tools are used. The accuracy of simulation results depends to a great extent on the choice of the appropriate CEM tool for the particular antenna problem to be analyzed; ergo, identifying and answering key questions about design objectives and requirements is necessary for informed decision-making throughout the selection and design processes. However, this could be quite challenging because of existing gaps both in the practitioners’ knowledge about different CEM tools capabilities, limitations, and design know-how. This is especially true for non-specialists such as students and academics involved in student driven Cubesat projects. Therefore, the rationale of this manuscript is to bridge those gaps and clarify some common misconception commonly encountered during the selection and design processes. In that regard, first, an overview of existing antenna configurations commonly used in Cubesat communications is provided. Next, antenna design general workflow is presented. Then, capabilities and limitations of different CEM solving methods are presented. After that, CEM software selection process trade-offs and possible sources of errors are discussed from a practical viewpoint. Finally, a case study of Masat-1 antenna system design is presented as practical example.

Visualization of Plasmonic Couplings Using Ultrafast Electron Microscopy.

Hybrids of graphene and metal plasmonic nanostructures are promising building blocks for applications in optoelectronics, surface-enhanced scattering, biosensing, and quantum information. An understanding of the coupling mechanism in these hybrid systems is of vital importance to its applications. Previous efforts in this field mainly focused on spectroscopic studies of strong coupling within the hybrids with no spatial resolution. Here we report direct imaging of the local plasmonic coupling between single Au nanocapsules and graphene step edges at the nanometer scale by photon-induced near-field electron microscopy in an ultrafast electron microscope for the first time. The proximity of a step in the graphene to the nanocapsule causes asymmetric surface charge density at the ends of the nanocapsules. Computational electromagnetic simulations confirm the experimental observations. The results reported here indicate that this hybrid system could be used to manipulate the localized electromagnetic field on the nanoscale, enabling promising future plasmonic devices.

Low concentration noroxin detection using terahertz spectroscopy combined with metamaterial.

The unreasonable use of antibiotics in poultry breeding has led to the frequent occurrence of antibiotic residues in poultry products, affecting food safety and posing a threat to human health. Accurate and rapid detection of antibiotic drug content is therefore of great significance. In this study, a new metamaterial method based on terahertz (THz) spectroscopy for the detection of the quinolone antibacterial drug noroxin in low concentrations was developed and tested. First, a new metamaterial structure was designed using a computational electromagnetics simulation tool with experimental verification. Three-dimensional full-wave electromagnetic field simulations and measured transmission spectra for the metamaterials were observed. Second, the transmission spectra of photoresists with different thicknesses (0-40µm) on the metamaterials surface were simulated, and the transmission spectra of noroxin thin films of different concentrations on the metamaterial surface were measured. Finally, using a purchased standard sample of noroxin in ethanol (100µg/mL) as the mother liquor, test samples of different concentrations were prepared, and experiments and multivariate data analysis were carried out. The noroxin detection limit for the method presented in this paper was determined as 0.01µg/mL. Thus, the new metamaterial method based on terahertz spectroscopy designed in this study was shown to effectively detect low concentrations of noroxin, providing a theoretical and experimental basis for the rapid detection of quinolone antibiotic residues in food matrices.

Study on a Fast Solver for Poisson’s Equation Based on Deep Learning Technique

Fast and efficient computational electromagnetic simulation is a long-standing challenge. In this article, we propose a data-driven model to solve Poisson’s equation that leverages the learning capacity of deep learning techniques. A deep convolutional neural network (ConvNet) is trained to predict the electric potential with different excitations and permittivity distribution in 2-D and 3-D models. With a careful design of cost function and proper training data generated from finite-difference solvers, the proposed network enables a reliable simulation with significant speedup and fairly good accuracy. Numerical experiments show that the same ConvNet architecture is effective for both 2-D and 3-D models, and the average relative prediction error of the proposed ConvNet model is less than 3% in both 2-D and 3-D simulations with a significant reduction in computation time compared to the finite-difference solver. This article shows that deep neural networks have a good learning capacity for numerical simulations. This could help us to build some fast solvers for some computational electromagnetic problems.

Towards a common vocabulary for describing the accuracy of computational electromagnetics models and comparisons with measurements

Validation and verification activities are essential enablers for the practical application of computational electromagnetics (CEM) models in industrial applications, but these terms are widely confused or merged. Furthermore, concepts such as the accuracy and precision of measurement results are often poorly understood. As model accuracy is most commonly judged against measured results there is a strong case to establish a well-defined vocabulary for describing the accuracy of CEM models that is both consistent with, and complementary to, the existing vocabulary associated with measurements. In order to help clarify the situation, this study identifies the difference between validation and verification in relation to CEM, suggests a mapping between CEM and measurement processes, collates a number of relevant definitions from existing measurement standards, and proposes new and complementary definitions that relate specifically to CEM simulation. It is considered that the proposed vocabulary could help to avoid misunderstandings between the test and modelling domains and eliminate ambiguity in standards relating to CEM validation and verification. In addition, the terminology presented here could also be readily adapted to help develop or clarify similar standards for other physics-based simulation domains, and perhaps even for more general mathematical modelling applications.

3.4/4.0 GHz Tunable Resonant Cavity in SIW Technology Using Metal Post and PIN Diode on a Low-Cost Biasing Network for 5G Applications

This paper presents a dual-band resonant cavity in Substrate Integrated Waveguide (SIW) technology to operate in the range from 3.3 GHz to 4.2 GHz, spectrum considered for the Fifth Generation (5G) network. The cavity was designed to operate at 3.4 GHz and 4.0 GHz. To achieve different states, a jumper and a PIN diode switch are considered as switching elements, connecting and disconnecting the bottom and the upper walls of the SIW resonant cavity through a metal post inserted inside its internal volume. A fitting equation is proposed to predict the maximum resonance frequency caused by the insertion of a single metal post inside the internal volume of the SIW resonant cavity and a new low-cost biasing network is designed on a thin dielectric substrate allocated on the upper wall of the SIW resonant cavity, using transmissions lines and a single capacitor, reducing the final cost and the insertion losses. Good agreement was observed among the fitting equation, computational electromagnetic simulations, and experimental results, validating the proposed methods.

Theory of soliton propagation in nonlinear photonic crystal waveguides.

Propagation of the temporal soliton in Kerr-type photonic crystal waveguide is investigated theoretically and numerically. An expression describing the evolution of the envelope of the soliton based on the full-wave modal analysis, taking into account all space-harmonics, is rigorously obtained. The nonlinear coefficient is derived, for the first time, based on a modification of the refractive indices for each space-harmonic due to the Kerr-type nonlinearity. For illustrating the general formulation and results, we performed extensive computational electromagnetics simulations for the propagation of gap solitons in an experimentally feasible photonic crystal waveguides, endorsing the correctness and usefulness of the proposed formalism.

Metal-Assisted and Microwave-Accelerated Decrystallization of Pseudo-Tophus in Synthetic Human Joint Models.

In this paper, we tested a hypothesis that the metal-assisted and microwave-accelerated decrystallization (MAMAD) technique, based on the combined use of low-power medical microwave heating (MWH) and gold nanoparticles (Au NPs), can be used to decrystallize laboratory-prepared monosodium urate monohydrate crystal aggregate (pseudo-tophus) placed in three-dimensional (3D) synthetic human joint models. To simulate a potential treatment of chronic tophaceous gout using the MAMAD technique, we used three different 3D synthetic human joint models and assessed the percent mass reduction (PMR, i.e., decrystallization) of pseudo-tophus and microwave-induced synthetic skin patch damage after MAMAD sessions (a MAMAD session = 120 s of MWH in the presence of Au NPs). Our three synthetic joint models are: Model 1: Application of seven MAMAD sessions in a closed synthetic joint with a pseudo-bursa containing a pseudo-tophus submerged in a solution of 20 nm Au NPs followed by dehydration of pseudo-tophus after each MAMAD session to assess PMR. Model 2: Application of seven MAMAD sessions in a closed or open synthetic joint with a pseudo-bursa containing a pseudo-tophus submerged in a solution of Au NPs followed by intermittent dehydration of pseudo-tophus after seven MAMAD sessions to assess PMR. Model 3: Application of 18 MAMAD sessions in a rotated closed synthetic joint (three sides are heated separately) with a pseudo-bursa containing a pseudo-tophus submerged in a solution of Au NPs followed by dehydration after every three MAMAD sessions to assess PMR. After a single MAMAD session, pseudo-tophus exposed to MWH and Au NPs had an average PMR of 8.30% (up to an overall PMR of 15%), and microwave-induced damage to the synthetic skin can be controlled by the use of a sacrificial skin sample and by adjusting the duration and the number of the MAMAD sessions. Computational electromagnetic simulations predict a 10% absorption of electric field by the pseudo-tophus placed in the synthetic joint models, which led us to conclude that a medical microwave source with higher power than 20 W can potentially be used with the MAMAD technique.

A Novel Data Segmentation-Based Approach for Validating the Narrowband Radar Data by the Feature Selective Validation Method

More and more electromagnetics analyses need more detailed-level data validation technologies, which can focus on the specific data region. The feature selective validation (FSV) method is a key electromagnetics validation tool, which was adopted in 2008 as the core of 1597.1 standard for validation of computational electromagnetics computer modeling and simulations. However, despite its successful performance for electromagnetic compatibility (EMC) data, it still comes to apply to the validation of narrowband radar data, which, differing from EMC data, is quite problematic. For this reason, this paper proposes a novel approach, which is called segment FSV (S-FSV), to deal with the narrowband radar data. This approach divides the data into several segments, extracts the peak and oscillation regions, allocates an individual importance degree to each segment, and generates validation results for all segments. Finally, the efficiency and feasibility of the proposed approach is corroborated by the statistical results in a narrowband radar data survey. The proposed S-FSV approach is shown to outperform the traditional FSV one in reflecting the expert opinions and to be more suitable for validation of such data.

Functionalizing plasmonic nanoparticles through adding a shell to improve electronic properties of c-Si thin-film solar cells

Embedding plasmonic nanoparticles (p-NPs) inside the solar cell’s active layer is capable of enhancing active layer optical absorption; however, such inclusion has some detrimental effects on the electronic properties of the solar cells. In addition, p-NPs are highly catalytic, their presence enables other non-radiative decay channels besides generation of electron–hole pairs, and the electrons usually get absorbed by these p-NPs. This results in the unfavorable fact that the potential enhancement in the carrier generation rate and the generated current is no longer in line with the enhancement in the optical absorption. In this paper, we propose to functionalize p-NPs by adding a dielectric or semiconductor shell, to passivate the p-NP without deteriorating scattering and/or plasmonic effects. Ag@SiO2 and Ag@TiO2 core–shell p-NPs have been intensely studied using extensive computational electromagnetic simulations to model the spectral response of the active layer’s optical absorption as well as electronic properties as a function of both shell composition and thickness. It is shown that a 5 nm TiO2 shell is apt to optically passivate the p-NP without any reduction in optical absorption, while improving the short circuit current density (J sc ) of the thin-film solar cell by 33.3%.

Notice of Retraction: Review of the Feature Selective Validation Method (FSV). Part I—Theory

It has been. As an automated validation method recommended by the IEEE Standard 1597.1/2, the FSV method has gained broad attention in the practice of computational electromagnetics modeling and simulations. This paper reviews the motivation, evolution, enhancements, and criticisms of the method over this time. The aims of this paper are to give a detailed contextualization of the development of the FSV method itself and to discuss the open questions and possible strategies of the next generation of automated validation methods.

Rapid design and modelling of wideband sinuous antenna reflector feeds through blended rational interpolation

AbstractThis paper describes the design of sinuous antenna reflector feeds using blended rational interpolation. The blended rational interpolation method is developed to interpolate a sparse set of high‐fidelity (HF) data while following the trends of a denser set of low‐fidelity (LF) data. The HF data are obtained by full‐wave computational electromagnetics simulations of the input impedance of a pyramidal sinuous antenna above a ground plane, while the LF data are obtained, at a significantly reduced computational cost, through simulations of a truncated version of the same antenna. Comparisons with other interpolation schemes, both for HF as well as for multifidelity data sets, are presented. It is shown that the blended rational interpolation scheme presented herein yields improved accuracy in most cases. A design example is also presented where a global model of the maximum input reflection coefficient over frequency is built over the design space and thus used to identify the region of acceptable performance. Comparisons with a validation set of HF data resulted in similar results, with the blended rational interpolation model requiring significantly shorter computer simulation time.

Examination of the effectiveness of FF MARS in a CATR through electromagnetic simulation

For more than a decade now, a measurement and post-processing technique involving modal filtering, named mathematical absorber reflection suppression (MARS), has been used very successfully to identify and subsequently extract range reflections in spherical, cylindrical and planar near-field antenna test systems and far-field (FF) and compact antenna test ranges (CATRs). Much of the early work concentrated on verification through experimental testing; however, some additional validation was performed using computational electromagnetic (EM) simulations. These considered first FF and subsequently near-field cases. The recent development of an accurate, flexible EM simulation tool that enables the simulation of `measured' FF pattern data as obtained from using a CATR has, for the first time, permitted the careful verification of the FF-MARS technique for a specified antenna under test (AUT) and CATR combination. This study presents simulated `measured' FF antenna pattern data in the presence of a large scatterer and then verifies the successful extraction of the scattering artefacts. In addition to considering range reflections, feed spill-over is also treated. Results are presented and discussed.

Liquids electrical characterization sensor using a hybrid SIW resonant cavity

AbstractA new sensor based on substrate integrated waveguide (SIW) technology is proposed as an option for liquids electrical characterization. The sensor employs a rectangular waveguide resonant cavity filled with air, with two opposite side walls implemented by closely spaced metallic vias. The resulting structure is a hybrid SIW resonant cavity. The two noncontinuous walls of the hybrid SIW cavity allow the liquid insertion, filling its entire internal volume. The resonance frequency of the hybrid SIW cavity is used to determine the dielectric constant of the liquid to be characterized. A sensor using a hybrid SIW cavity operating in TE101 mode was designed to resonate at 5.9 GHz when filled with air. The sensor was employed to measure the dielectric constant of binary mixtures of distilled water and ethanol. Dielectric constants ranging from 21 to 79 were obtained, corresponding to measured resonance frequencies from 1,247 to 647 MHz, respectively. Good agreement was observed between computational electromagnetic simulation and experimental results. The dependence of the volumetric fraction of ethanol in the binary mixture on the sensor resonance frequency was expressed using a third‐order polynomial approximation.

Comparison of Three-Dimensional Datasets by Using the Generalized n-Dimensional ( n-D) Feature Selective Validation (FSV) Technique

Automatic methods to evaluate the validity of computational electromagnetics computer modeling and simulations have widespread applications. The feature selective validation (FSV) method is a heuristic technique which has been shown to give a broad agreement with a visual assessment for one-dimensional data. As a heuristic technique, extending the dimensionality is an important target for the improvement and development of FSV. One of the major challenges in the development of n -dimensional ( n -D) FSV is the difficulty of obtaining visual assessment results, since, the visual comparison of three- and higher dimensional data is difficult or even impossible. This paper formulates the comparison of 3-D data based on an established generalized n -D-FSV approach. The performance of the approach is investigated by means of the Laboratory for Image and Video Engineering Video Quality Database which provides subjective scores of 150 distorted videos. A statistical evaluation of the relative performance of FSV and other publicly available full-reference video quality assessment algorithms is presented. Further, parameter tuning is performed to improve the agreement of 3-D FSV results and subjective scores. The proposed approach is finally applied to the self-referenced validation of an electromagnetic simulation model to identify and locate the continuous variation of electric field within a region of space.