Electromagnetic Model Research Articles

Transformer electromagnetic modelling based on DC hysteresis measurement

Transformer electromagnetic modelling based on DC hysteresis measurement

Variable resolution machine learning optimization of antennas using global sensitivity analysis.

The significance of rigorous optimization techniques in antenna engineering has grown significantly in recent years. For many design tasks, parameter tuning must be conducted globally, presenting a challenge due to associated computational costs. The popular bio-inspired routines often necessitate thousands of merit function calls to converge, generating prohibitive expenses whenever the design process relies on electromagnetic (EM) simulation models. Surrogate-assisted methods offer acceleration, yet constructing reliable metamodels is hindered in higher-dimensional spaces and systems with highly nonlinear characteristics. This work suggests an innovative technique for global antenna optimization embedded within a machine-learning framework. It involves iteratively refined kriging surrogates and particle swarm optimization for generating infill points. The search process operates within a reduced-dimensionality region established through fast global sensitivity analysis. Domain confinement enables the creation of accurate behavioral models using limited training data, resulting in low CPU costs for optimization. Additional savings are realized by employing variable-resolution EM simulations, where low-fidelity models are utilized during the global search stage (including sensitivity analysis), and high-fidelity ones are reserved for final (gradient-based) tuning of antenna parameters. Comprehensive verification demonstrates the consistent performance of the proposed procedure, its superiority over benchmark techniques, and the relevance of the mechanisms embedded into the algorithm for enhancing search process reliability, design quality, and computational efficiency.

Electromagnetic responses on microstructures of duplex stainless steels based on 3D cellular and electromagnetic sensor finite element models

Electromagnetic responses on microstructures of duplex stainless steels based on 3D cellular and electromagnetic sensor finite element models

Electromagnetic Modeling of Superconducting Bulks in Applied Time-Varying Magnetic Field

An integrodifferential model formulated in terms of the electric vector potential is developed for the 3D numerical modeling of the electromagnetic field in superconducting bulks, for AC losses evaluation. The Newton Raphson method is applied to accelerate the convergence. The model is validated on a benchmark. The comparison results show the accuracy of the model and its performances in terms of computation time compared to classical approaches.

Self-powered actively-controlled lateral suspensions of high-speed trains using energy-regenerative electromagnetic damper and model predictive control

Self-powered actively-controlled lateral suspensions of high-speed trains using energy-regenerative electromagnetic damper and model predictive control

Research on path planning in UAV-assisted emergency communication

The rapid development of UAV communication technology makes it have application potential in wireless systems. However, for the optimization problem of UAV base station providing communication for ground personnel in the disaster area under special natural disasters, traditional deep reinforcement learning is used. Algorithms cannot solve such problems well. This article proposes the AD3QN algorithm combined with the attention mechanism, which can communicate with disaster victims on the ground better and more quickly, providing better information collection for rescue missions and completing the task of communication optimization. In the mission simulation environment, in order to make the environment more realistic, we innovatively designed the ground user distribution model, air-to-ground communication model, and electromagnetic interference model. Finally, the effect of the proposed algorithm is evaluated by comparing different deep reinforcement learning algorithms. The results show that the algorithm we proposed can provide communication services faster and has higher practicability in terms of algorithm.

Integral equation based wellbore preconditioner for 3D electromagnetic response modeling

Modeling subsurface controlled-source electromagnetic (CSEM) responses using the finite-element (FE) method is challenging in the presence of highly conductive wellbore casing. The very large conductivity contrast between the casing and the host formation leads to increased computation time and potentially unstable solutions. We address this difficulty by preconditioning an FE solver with an integral equation (IE) primary solution that captures the CSEM response of a realistic-sized steel wellbore casing. Our hybrid IE-FE approach determines the primary field using 2D integral-equation forward modeling and then interpolates the IE-computed solution onto the nodes. Then using an existing FE simulator, we solve for the secondary electric and magnetic fields. This approach removes the need for an ultra-fine FE mesh around the wellbore, thereby improving FE solution stability while greatly reducing FE computation time. Our method is illustrated by modeling the CSEM responses of idealized fluid-bearing zones.

Assessing the Impact of DC Bipole Configuration on the Lightning Performance of a HVDC Transmission Line in terms of Backflashover

This work presents a discussion on the influence of both the polarity and position of the phase conductors (DC poles) of a double circuit 500 kV HVDC transmission line (TL) on lightning overvoltages developed across their line insulator strings and the corresponding lightning performance in terms of backflashover, considering computational simulations with the Hybrid Electromagnetic Model (HEM) and the Leader Progression Model (LPM). Several polarity arrangements of the DC poles were considered and their influence on the probability of backflashover occurrence due to negative downward lightning was assessed for tower-footing grounding impedances varying from 10 to 100 Ω. The study indicates the worst lightning performances for configurations B, C1 and D2, with critical current and backflashover probability varying from 96 to 49 kA and from 4% to 26%, respectively. These results show the importance of both the position and polarity of the phase conductors and tower-footing grounding impedance to define the HVDC TL performance, indicating the TL configurations with the lower phases with positive polarity as the one with worst lightning performance in terms of backflashover.

A novel impact approach based on electromagnetic loading technology: A case study on CFRP/Al riveted structures

To investigate the mechanical response and damage behavior of aircraft fuselage composite structures under out-of-plane impact loads more efficiently and flexibility, this paper proposed a novel impact approach and testing platform based on inductive coils to yield electromagnetic impact force. The influence of system key parameters on the electromagnetic loading waveforms were analyzed using an electromagnetic field finite element model. Single/repeated impact tests on CFRP/aluminium alloy (Al) riveted structures were conducted at different voltages (energies) based on this approach. The results indicate that the electromagnetic impact (EMI) approach exhibits significant advantages in both variable strain rate loading and continuous impact loading scenarios. This device can efficiently achieve multi-point and multiple impact loading. The electromagnetic impact forces with various amplitudes and pulse-widths can be accurately obtained by altering voltage and capacitance values, which can demonstrate the good experimental consistency of such test approach. Besides, with this test method, the load threshold for damage formation can be clearly defined: once the impact force exceeds the damage threshold load, the delamination area of the CFRP laminates expand as the impact energy increases. Note that when the provided out-of-plane impact load is slightly higher than the damage threshold load by changing the voltage, significant delamination damage may suddenly manifest in any one impact event of the repeated impacts.

A 3D Continuous-Space Electromagnetic Channel Model for 6G Tri-Polarized Multi-User Communications

A 3D Continuous-Space Electromagnetic Channel Model for 6G Tri-Polarized Multi-User Communications

Simulation of the electromagnetic scattering characteristics in inductively coupled plasma array for aircraft stealth

Abstract In this paper, an electromagnetic model of an inductively coupled plasma (ICP) array is developed to investigate its electromagnetic transmission characteristics under varying discharge conditions. The reliability of the model is enhanced by basing plasma parameters on simulation results from a fluid dynamics model. Electromagnetic simulations analyze the reflection spectrum of the inductively coupled plasma array, revealing the modulation mechanism of the plasma array. Findings indicate that as excitation power increases, the attenuation peak of the ICP array shifts to higher frequencies, and the attenuation bandwidth widens. By employing different power levels for the two layers in the Inductively Coupled Plasma (ICP) process, the array can achieve effective stealth performance with lower power consumption. Adjusting plasma discharge parameters to match specific scenarios enables the proposed plasma array to achieve varied modulation effects, expanding its potential applications in aircraft stealth.

γ-Cascade V4: A semi-analytical code for modeling cosmological gamma-ray propagation

Since the universe is not transparent to gamma rays with energies above around one hundred GeV, it is necessary to account for the interaction of high-energy photons with intergalactic radiation fields in order to model gamma-ray propagation. Here, we present a public numerical software for the modeling of gamma-ray observables. This code computes the effects on gamma-ray spectra from the development of electromagnetic cascades and cosmological redshifting. The code introduced here is based on the original γ-Cascade, and builds on it by improving its performance at high redshifts, introducing new propagation modules, and adding many more extragalactic radiation field models, which enables the ability to estimate the uncertainties inherent to EBL modeling. We compare the results of this new code to existing Monte Carlo electromagnetic transport models, finding good agreement within EBL uncertainties.

Review of 3D electromagnetic modeling and inversion for mineral exploration

Many mineral deposits have low resistivity. This property makes the electromagnetic (EM) method a very useful tool for mineral exploration. In the past few decades, the application of EM exploration technologies has been reviewed by many researchers. However, most reviews focused on EM exploration methods, the development of equipment, or their applications. Three-dimensional forward modeling and inversions are high-accuracy EM interpretation techniques in which great progress has been made in recent years in mineral exploration. We review the development of EM technology for mineral exploration with a focus on 3D EM forward modeling, inversion technology, and its applications. We first briefly introduce the EM methods for mineral exploration. Next, we give a comprehensive review of 3D EM forward modeling, inversion, and data interpretation, with special attention paid to the development of EM theory and applications in mineral exploration. We hope this review can promote the application of 3D EM numerical simulation and inversion in mineral exploration.

RF coil design strategies for improving SNR at the ultrahigh magnetic field of 10.5T.

Toward pushing the boundaries of ultrahigh fields for human brain imaging, we wish to evaluate experimentally achievable SNR relative to ultimate intrinsic SNR (uiSNR) at 10.5T, develop design strategies toward approaching the latter, quantify magnetic field-dependent SNR gains, and demonstrate the feasibility of whole-brain, high-resolution human brain imaging at this uniquely high field strength. A dual row 16-channel self-decoupled transmit (Tx) and receive (Rx) array was developed for 10.5T using custom Tx/Rx switches. A 64-channel receive-only array was built to fit into the 16-channel Tx/Rx array. Electromagnetic modeling and experiments were used to define safe operational power limits. Experimental SNR was evaluated relative to uiSNR at 10.5T and 7T. The 64-channel Rx array alone captured approximately 50% of the central uiSNR at 10.5T, while an identical array developed for 7T captured about 76% of uiSNR at 7T. The 16-channel Tx/80-channel Rx configuration brought the fraction of uiSNR captured at 10.5T to levels comparable to the 64-channel Rx array at 7T. SNR data displayed an approximate dependence over a large central region when evaluated in the context of uiSNR. Whole-brain, high-resolution -weighted and T1-weighted anatomical and gradient-recalled-echo BOLD-EPI functional MRI images were obtained at 10.5T for the first time with such an advanced array. We demonstrated the ability to approach the uiSNR at 10.5T over the human brain, achieving large SNR gains over 7T, currently the most commonly used ultrahigh-field platform. Whole-brain, high-resolution anatomical and EPI-based functional MRI data were obtained at 10.5T, illustrating the promise of greater than 10T fields in studying the human brain.

The influence of eyelashes on electric field distribution and absorbed power density in the cornea under millimeter-wave exposure.

As millimeter wave (MMW) technology, particularly in fifth-generation (5G) devices, gains prominence, there is a crucial need for comprehensive electromagnetic (EM) models of ocular tissues to understand and characterize EM exposure conditions accurately. This study employs numerical modeling to investigate the interaction between MMW and the cornea, aiming to characterize EM field distributions and absorption within an anatomically accurate eye model while considering the influence of eyelashes. Using the finite-difference time-domain (FDTD) method, we conduct simulations of EM radiation interactions from 20.0 to 100.0 GHz with a human eye model. Moreover, we analyze the temperature distribution increase within the eye model using a thermal sensor in XFdtd, employing a scheme based on the finite difference (FD) method. Our findings reveal a nonuniform distribution of the EM field, particularly intensified in corneal regions adjacent to eyelashes and eyelids. Despite similar EM field patterns, the presence or absence of eyelashes has minimal impact on temperature differences. However, the study highlights increased radiation absorption by the eyelid's epidermis at 100.0 GHz, reducing the rise in the cornea's temperature.

Electromagnetic fields transformation in UWB infinite antenna arrays in the cluster excitation mode

Infinite ultra-wideband (UWB) arrays of TEM horns and Vivaldi antennas were considered. At the first stage we used an array model in the quasi-periodic excitation mode in the form of a Floquet channel. It was implemented in the HFSS electromagnetic modeling system. At the second stage the array parameters in the cluster excitation mode were determined using the calculated scattering matrix of the Floquet channel. Two clusters of TEM horns and Vivaldi antennas were analyzed. They were finite along one coordinate and infinite along the other. It was investigated how the cluster size, frequency, amplitude distribution of exciting waves, scanning in the sector of angles affect the shape of the amplitude-phase distribution of the field in the array aperture. It was shown that the field distribution in the emitting aperture may differ significantly from the distribution of exciting waves at the inputs of the array elements. An explanation of this effect based on the representation of the field in the array in the form of a superposition of its eigen waves was proposed.

Modelling and optimization of TPMLMs with slotted stators based on Bayesian DNN

AbstractThe Permanent Magnet Linear Motor (TPMLM) is widely used in different industrial fields. TPMLMs with slots and iron cores have high power density, but their thrust fluctuations and copper losses are significant. Due to the nonlinearity and saturation of magnetic circuits, their electromagnetic models are complex and the accuracy of numerical methods is very inferior. Substantially accurate modelling is crucial for motor optimisation design. In this paper, a data‐driven modelling method based on Bayesian optimisation deep neural network (DNN) is proposed to improve the accuracy of the electromagnetic field. The finite element (FE) modelling under different structural parameters is analysed and provides a training dataset for DNN. Then, a multi‐objective optimisation problem for the slotted TPMLM is carried out based on the multi‐objective black hole algorithm. Compared to the original design, the average thrust of TPMLM increased by 49.37%, the thrust fluctuation percentage decreased by 9.59%, and the coil copper consumption percentage decreased by 2.64%. The results show that the improved DNN model has very high modelling accuracy, providing a new way for motor design and optimisation.

Three-dimensional airborne electromagnetic forward modeling based on multiscale hexahedral finite-element method

Slow forward modeling is the main factor that restricts the practical use of three-dimensional (3D) inversion and interpretation of airborne electromagnetic (AEM) data. To improve the modeling efficiency in 3D AEM, we propose a new multiscale finite-element (MsFE) method based on unstructured hexahedral meshes. Compared with the traditional 3D AEM forward modeling, the main advantage of our newly developed method is that it can simulate complex underground structures in the earth quickly. Since we can fit the earth's topography or the anomalous bodies underground using a small number of hexahedral grids, we can quickly model them using MsFE. The main idea of the MsFE forward modeling method is to construct an interpolation operator between a coarse and a dense mesh and use the interpolation operator to map the conventional FE coefficient matrix to the MsFE coefficient matrix and thus reduce the number of unknowns in the modeling process. This will vastly reduce the scale of the linear equations system. We validate our method by simulating a typical mountain peak model and demonstrate its effectiveness by simulating numerous synthetic models and a model from Voisey Bay's Ovoid sulfide deposit, Canada.

PreSCAN: A Comprehensive Review of Pre-Silicon Physical Side-Channel Vulnerability Assessment Methodologies

Physical side-channel attacks utilize power, electromagnetic (EM), or timing signatures from cryptographic implementations during operation to retrieve sensitive information from security-critical devices. This paper provides a comprehensive review of these potent attacks against cryptographic hardware implementations, with a particular emphasis on pre-silicon leakage assessment methodologies. We explore the intricacies of cryptographic algorithms, various side-channel attacks, and the latest mitigation techniques. Although leakage assessment techniques are widely adopted in the post-silicon phase, pre-silicon leakage assessment is an emerging field that addresses the inherent limitations of its post-silicon counterpart. We scrutinize established post-silicon techniques and provide a detailed comparative analysis of pre-silicon leakage assessment across different abstraction levels in the hardware design and verification flow. Furthermore, we categorize and discuss existing pre-silicon power and electromagnetic modeling techniques for leakage detection and mitigation that can be integrated with electronic design automation (EDA) tools to automate security assessments. Lastly, we offer insights into the future trajectory of physical side-channel leakage assessment techniques in the pre-silicon stages, highlighting the need for further research and development in this critical area of cybersecurity.

Quantum mechanical effects in plasmonic sub-nanometer cavities formed by a tip and substrate structure

Enhancing local field intensity through light field compression is one of the core issues in surface plasmon-enhanced spectroscopy. The theoretical framework for the nanostructure composed of a tip and a substrate has predominantly relied on classical electromagnetic models, ignoring the electron tunneling effect. In this paper, we investigate the plasmonic near-field characteristics in the sub-nanometer cavity formed by the tip and the substrate using a quantum-corrected model. Additionally, we analyze the local electric field and Raman enhancement when hexagonal boron nitride (h-BN) monolayer is used as a decoupling layer for the nanocavity. The results indicate that classical electromagnetic theory fails to accurately describe the plasmonic electric field in smaller sub-nanometer gaps. When the gap is reduced to 0.32 nm, the quantum-corrected model shows that the local electric field in the sub-nanometer cavity is significantly reduced due to the tunneling current, aligning more closely with experimental results. Moreover, adding a high-barrier h-BN layer effectively prevents the occurrence of tunneling current, allowing for a strong local electric field even when the gap is less than 0.32 nm. The calculated maximum Raman enhancement reaches up to 15 orders of magnitude. Our research results provide a deep understanding of quantum mechanical effects in tip-enhanced spectroscopy systems, enabling the potential applications based on quantum plasmons in nanocavity.