In this paper, we develop a new one-stage <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ O(N \log N)$</tex-math></inline-formula> algorithm to generate a rank-minimized <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {H}^{2}$</tex-math></inline-formula>-representation of electrically large volume integral equations (VIEs), which significantly reduces the CPU run time of state-of-the-art algorithms for completing the same task. Unlike existing two-stage algorithms, this new algorithm requires only one stage to build nested cluster bases. The cluster basis is obtained directly from the interaction between a cluster and its admissible clusters composed of real or auxiliary ones that cover all interaction directions. Furthermore, the row and column pivots of the resultant low-rank representation are chosen from the source and observer points in an analytical way without the need for numerically finding them. This further speeds up the computation. Numerical experiments on a suite of electrically large 3D scattering problems have demonstrated the efficiency and accuracy of the proposed new algorithm.

We investigate the impact of noise on time-reversal imaging and propose an approach that significantly enhances the detection of objects in noisy environments. Our method involves the decomposition of the time-reversal operator at a single frequency, known for its sensitivity to noise. We utilize a specific autoencoder architecture to denoise the generated dataset from a multi-static data matrix (MDM), effectively separating the signal sub-space from the noise sub-space, even at low signal-to-noise ratios (SNRs) ranging from -5 dB to high levels of SNR. This dataset is generated by simulating scatterers mounted at various locations within a two-dimensional (2D) grid, each with different SNRs.

Numerical electromagnetic computations must often accommodate random geometric representations while handling biological tissues, and engineered components with manufacturing tolerances. Meshless time-domain radial point interpolation method (RPIM) offers advantages to quantitatively analyze such geometric uncertainties using polynomial chaos expansion (PCE). Formulations for geometric uncertainties may require variations in mesh or node distribution for each analyzed sample, leading to high computational requirement for re-meshing. The proposed geometric stochastic RPIM (G-SRPIM) overcomes this with a single domain model by expressing the shape function matrix of RPIM in a stochastic framework. The uncertainty is quantified in G-SRPIM through a novel way by which its random support domain moment matrices are organized in a block structure, and inverted using Schur's complement and Neumann approximation, exploiting the underlying symmetry. The proposed method is validated by analyzing a parallel plate waveguide with a slit exhibiting random variations, a realistic 3D bio-electromagnetic problem involving a section of human head, and an iris filter with random variations in its iris dimensions. Standard deviation upto 45% of the average inter-node distance is tested without jeopardizing the stability. The accuracy of our approach is compared with Monte-Carlo (MC) simulations on a deterministic RPIM using the Kolmogorov-Smirnov (KS) test. Additionally, results are compared with MC simulation on CST<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\text{\text{®}}}$</tex-math></inline-formula> Studio Suit 2018<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\text{™}}$</tex-math></inline-formula> and stochastic collocation (SC). The proposed method exhibits superior execution time compared to SC and MC-based non-intrusive implementations, underscoring its efficiency and reliability in handling geometric uncertainties in microwave components.

Mutual-coupling effects are of utmost importance in the development of high-frequency circuits and systems. However, it is a common practice to ignore those couplings when establishing equivalent circuit models. Neglecting these couplings leads to inaccurate circuit modelling. Therefore, it becomes imperative to account for mutual couplings in the development of accurate equivalent circuit models. This work presents a holistic process for synthesizing the equivalent circuit model of an electromagnetic (EM) field structure that incorporates mutual couplings of varying orders. The proposed high-order framework begins by developing equivalent circuit models for each individual transmission line discontinuity within the target circuit. Subsequently, the mutual couplings of different orders are extracted in a step-by-step manner. Throughout this process, full-wave EM simulations are deployed, along with a circuit parameter extraction method that utilizes de-embedded circuit responses. By combining these techniques, a comprehensive and accurate equivalent circuit model is generated, enabling a detailed analysis of the target field model structure, and facilitating a deeper understanding of its electrical and magnetic behavior and performance. This paper utilizes a three-step microstrip discontinuity structure and a thirdorder parallel coupled microstrip filter as examples for theoretical and experimental demonstration of the proposed technique.

Solving the coupled partial differential equations (PDEs) that govern the dynamics of multiphysics systems is both important and challenging. Existing numerical methods such as the finite element method (FEM) are known to be computationally intensive, while machine learning techniques, like the physics-informed neural network (PINN), often falter when modeling complex systems or processes over long timescales. To overcome these limitations, we propose a new framework “Drift-Correcting Multiphysics Informed Neural Network” (DC-MPINN), specifically designed to solve coupled multiphysics problems efficiently over extended timescales–without sacrificing accuracy. This new method introduces an architecture for temporal domain decomposition that corrects drift of conserved quantities, as well as a composite loss function that allows solving coupled multiphysics problems. We demonstrate the superior performance of DC-MPINN over traditional FEM approaches in several benchmark problems. This approach represents a step forward in multiphysics computational techniques, enhancing our ability to understand and predict the behavior of physical processes across various disciplines.

This article considers an electro-thermo-geometrical Multiphysics analysis of electromagnetic compatibility (EMC) resonance problem solution by using bandpass (BP) type negative group delay (NGD) equalization method. The rectangular cavity electric model based on EMC frequency domain S-parameter analysis is introduced. The unfamiliar BP-NGD function is specified in order to size the lumped electrical components of the suitable RLC-network based topology. The BP-NGD equalization principle is described including the Multiphysics synoptic analysis by means of electro- thermo-geometrical approach of the problem. The BP-NGD equalization methodology is proposed. The feasibility study of the EMC resonance equalization method is validated by considering a proof-of-concept constituted by 232.9×28×3.8 cm-size rectangular cavity. The BP-NGD active circuit is designed as equalizer by using RLC-series network. The EMC solution is verified by the BP-NGD POC specified by −4 ns NGD value at 0.644 MHz center frequency stating resonance effect reduction with 1-dB flatness. Furthermore, time-domain signal integrity (SI) analysis confirms the EMC cavity resonance resolution by showing output delay, over/under shoot reduction and also input-output cross correlation improvement from 89% to 99%.

This index covers all technical items-papers, correspondence, reviews, etc.-that appeared in this periodical during 2023, and items from previous years that were commented upon or corrected in 2023. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index.

An efficient numerical solver for the <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</b> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Phi$</tex-math></inline-formula> formulation in electromagnetics based on discrete exterior calculus (DEC) is proposed in this paper. The <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</b> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Phi$</tex-math></inline-formula> formulation is immune to low-frequency breakdown and ideal for broadband and multi-scale analysis. The generalized Lorenz gauge is used in this paper, which decouples the <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</b> equation and the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Phi$</tex-math></inline-formula> equation. The <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</b> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Phi$</tex-math></inline-formula> formulation is discretized by using the DEC, which is the discretized version of exterior calculus in differential geometry. In general, DEC can be viewed as a generalized version of the finite difference method, where Stokes' theorem and Gauss's theorem are naturally preserved. Furthermore, compared with finite difference method, where rectangular grids are applied, DEC can be implemented with unstructured mesh schemes, such as tetrahedral meshes. Thus, the proposed DEC <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</b> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Phi$</tex-math></inline-formula> solver is inherently stable, free of spurious solutions and can capture highly complex structures efficiently. In this paper, the background knowledge about the <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</b> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Phi$</tex-math></inline-formula> formulation and DEC is introduced, as well as technical details in implementing the DEC <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">A</b> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\Phi$</tex-math></inline-formula> solver with different boundary conditions. Numerical examples are provided for validation purposes as well.

In July 2023, the <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IEEE Journal on Multiphysics and Multiscale Computational Techniques</small> (J-MMCT) reached an important milestone, obtaining its first Impact Factor (2.3). The Impact Factor confirmed the position of the Journal as one of the leading publications dedicated to the latest advances in computational electromagnetics with an emphasis on methods for multiscale and multiphysics problems. This is the result of hard work and consistent efforts of everyone involved with J-MMCT, from founding Editor-in-Chief Prof. Qing-Huo Liu to all Editorial Board and Steering Committee members to date.

Electric arc discharges in low–voltage (LV) or medium–voltage (MV) power distribution devices can cause significant pressure rise. For example, a high amplitude pressure peak can damage the housing of a LV circuit breaker initiating cracks during short circuit interruption. In case of larger deformations or creation of additional gaps, the impact of the geometric changes on the pressure rise cannot be neglected. This paper describes a new three–codes–coupling approach, wherein a magneto–hydrodynamics (MHD) model consisting of a fluid– flow solver and an electromagnetic solver are coupled with a structural dynamics solver to build a complex co–simulation model. This model can predict the deformation of structures under the influence of arcing pressure. The applicability of the model was tested with a setup, where an electric arc is ignited inside an arc chamber that has a flexible plate on one side. Predicted pressure rise and displacement results are in good agreement with test data. In a more complex setup, this approach was applied to model the bending of a flexible baffle plate in the venting path of a LV circuit breaker during short circuit interruption. Additional challenges such as contact motion and pre–stress analysis were resolved.