Pub Date : 2025-12-17DOI: 10.1109/JMMCT.2025.3644832
{"title":"2025 Index IEEE Journal on Multiscale and Multiphysics Computational Techniques Vol. 10","authors":"","doi":"10.1109/JMMCT.2025.3644832","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3644832","url":null,"abstract":"","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"512-526"},"PeriodicalIF":1.5,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11302050","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-24DOI: 10.1109/JMMCT.2025.3625423
Asha K. Jakhar;Rohit Sharma;Avirup Dasgupta;Sourajeet Roy
In this paper, an artificial neural network (ANN) guided approach is developed for the repeater optimization in multilayer graphene on-chip interconnect networks. The key attribute of the proposed approach is the use of two distinct ANNs to generalize the target objective functions of interconnect networks in terms of (i) the geometrical parameters of the vertical through silicon vias (TSVs) present in the network, and (ii) the design parameters of the fin-shaped field effect transistors (FinFETs) making up the repeaters. The first ANN (ANN1) ensures that for any change in the TSV geometry, the objective functions of the network can be accurately approximated by analytical expressions without the need for laborious SPICE simulations. The second ANN (ANN2) identifies additional tuning parameters of the repeaters besides simply the number and size of the repeaters, leading to better optimization results of the network performance. This enables performing efficient repeater optimizations in the presence of design variability of the TSVs. The generalized target objective functions of the network are then maximized/minimized using a particle swarm optimizer. Multiple numerical examples are presented in the paper to test and validate the proposed ANN guided approach.
{"title":"A Neural Network Guided Approach for Repeater Optimization in Multilayer Graphene On-Chip Interconnect Networks Including TSVs","authors":"Asha K. Jakhar;Rohit Sharma;Avirup Dasgupta;Sourajeet Roy","doi":"10.1109/JMMCT.2025.3625423","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3625423","url":null,"abstract":"In this paper, an artificial neural network (ANN) guided approach is developed for the repeater optimization in multilayer graphene on-chip interconnect networks. The key attribute of the proposed approach is the use of two distinct ANNs to generalize the target objective functions of interconnect networks in terms of (i) the geometrical parameters of the vertical through silicon vias (TSVs) present in the network, and (ii) the design parameters of the fin-shaped field effect transistors (FinFETs) making up the repeaters. The first ANN (ANN<sub>1</sub>) ensures that for any change in the TSV geometry, the objective functions of the network can be accurately approximated by analytical expressions without the need for laborious SPICE simulations. The second ANN (ANN<sub>2</sub>) identifies additional tuning parameters of the repeaters besides simply the number and size of the repeaters, leading to better optimization results of the network performance. This enables performing efficient repeater optimizations in the presence of design variability of the TSVs. The generalized target objective functions of the network are then maximized/minimized using a particle swarm optimizer. Multiple numerical examples are presented in the paper to test and validate the proposed ANN guided approach.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"483-495"},"PeriodicalIF":1.5,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145510231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Spacetime crystals offer unique control over electromagnetic waves, which enables dynamic bandgap engineering dependent on modulation velocity. This article introduces a modified Bragg condition method for rapidly determining bandgap positions in subluminal spacetime crystals. Unlike conventional analytical (e.g., transfer matrix method, Floquet-Bloch theory) and numerical (e.g., FDTD, plane wave expansion) approaches, which demand significant computational resources or complex dispersion analysis, the proposed method leverages constructive interference principles adapted for spatiotemporal periodicity. We derive governing equations that directly relate bandgap frequencies to crystal parameters such as spatial periodicity, refractive indices, and modulation velocity, bypassing exhaustive simulations. Validation by ray-tracing dispersion diagrams and FDTD simulations confirms predictions of the modified Bragg condition method. This Bragg-based approach offers a computationally efficient and physically insightful alternative for rapid bandgap estimation, particularly beneficial for designing dynamic photonic and microwave devices requiring real-time parameter tuning.
{"title":"Determination of Bandgap Position in Subluminal Spacetime Crystal Using Modified Bragg Method","authors":"Seyed Alireza Hosseini;Mohsen Maddahali;Ahmad Bakhtafrouz","doi":"10.1109/JMMCT.2025.3624048","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3624048","url":null,"abstract":"Spacetime crystals offer unique control over electromagnetic waves, which enables dynamic bandgap engineering dependent on modulation velocity. This article introduces a modified Bragg condition method for rapidly determining bandgap positions in subluminal spacetime crystals. Unlike conventional analytical (e.g., transfer matrix method, Floquet-Bloch theory) and numerical (e.g., FDTD, plane wave expansion) approaches, which demand significant computational resources or complex dispersion analysis, the proposed method leverages constructive interference principles adapted for spatiotemporal periodicity. We derive governing equations that directly relate bandgap frequencies to crystal parameters such as spatial periodicity, refractive indices, and modulation velocity, bypassing exhaustive simulations. Validation by ray-tracing dispersion diagrams and FDTD simulations confirms predictions of the modified Bragg condition method. This Bragg-based approach offers a computationally efficient and physically insightful alternative for rapid bandgap estimation, particularly beneficial for designing dynamic photonic and microwave devices requiring real-time parameter tuning.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"466-472"},"PeriodicalIF":1.5,"publicationDate":"2025-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145510229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The accurate computation of electromagnetic scattering from electrically large dielectric layered media with rough surfaces remains a complex challenge, demanding highly efficient computational electromagnetics (CEM) algorithms. This paper presents a novel general local iterative physical optics (gLIPO) algorithm, tailored for the simulation of electromagnetic scattering in dielectric layered media characterized by relatively smooth surface irregularities. The gLIPO algorithm iteratively refines the equivalent local surface currents in accordance with the physical optics (PO) principle at dielectric interfaces, effectively mitigating electromagnetic field discontinuities across the media. Rigorous update equations are derived for both equivalent electric and magnetic surface currents. A series of comprehensive numerical simulations are conducted for four representative scenarios: 1) a single-layer ocean medium at 300 MHz; 2) a single-layer soil medium at 800 MHz; 3) a double-layer ice/ocean medium at 300 MHz; and 4) a tunnel communication scenario at 30 GHz. The results consistently demonstrate that the gLIPO algorithm converges in fewer than five iterations, reducing the maximum relative error in the equivalent surface currents to below $10^{-5}$, benefiting from its linear computational complexity and memory footprint of $O(N)$ . In contrast, the method of moments (MoM) typically requires several dozen iterations, rendering gLIPO approximately an order of magnitude faster, even outperforming the multi-level fast multipole algorithm (MLFMA). Furthermore, gLIPO circumvents the need to compute and store the impedance matrix, as required by MoM, leading to substantial savings in both computational time and memory resources. The gLIPO algorithm offers significant advantages for applications such as large-scale multiple-input multiple-output (MIMO) channel state information (CSI) simulations in 5G and future wireless communication systems, making it a valuable tool for advancing electromagnetic simulation capabilities.
{"title":"General Local Iterative Physical Optics CEM for Layered Dielectrics With Moderately Smooth Rough Surfaces","authors":"Shaolin Liao;Jiong Liang;Chuangfeng Zhang;Qun Li;Jinxin Li;Henry Soekmadji","doi":"10.1109/JMMCT.2025.3620470","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3620470","url":null,"abstract":"The accurate computation of electromagnetic scattering from electrically large dielectric layered media with rough surfaces remains a complex challenge, demanding highly efficient computational electromagnetics (CEM) algorithms. This paper presents a novel general local iterative physical optics (gLIPO) algorithm, tailored for the simulation of electromagnetic scattering in dielectric layered media characterized by relatively smooth surface irregularities. The gLIPO algorithm iteratively refines the equivalent local surface currents in accordance with the physical optics (PO) principle at dielectric interfaces, effectively mitigating electromagnetic field discontinuities across the media. Rigorous update equations are derived for both equivalent electric and magnetic surface currents. A series of comprehensive numerical simulations are conducted for four representative scenarios: 1) a single-layer ocean medium at 300 MHz; 2) a single-layer soil medium at 800 MHz; 3) a double-layer ice/ocean medium at 300 MHz; and 4) a tunnel communication scenario at 30 GHz. The results consistently demonstrate that the gLIPO algorithm converges in fewer than five iterations, reducing the maximum relative error in the equivalent surface currents to below <inline-formula><tex-math>$10^{-5}$</tex-math></inline-formula>, benefiting from its linear computational complexity and memory footprint of <inline-formula><tex-math>$O(N)$</tex-math></inline-formula> . In contrast, the method of moments (MoM) typically requires several dozen iterations, rendering gLIPO approximately an order of magnitude faster, even outperforming the multi-level fast multipole algorithm (MLFMA). Furthermore, gLIPO circumvents the need to compute and store the impedance matrix, as required by MoM, leading to substantial savings in both computational time and memory resources. The gLIPO algorithm offers significant advantages for applications such as large-scale multiple-input multiple-output (MIMO) channel state information (CSI) simulations in 5G and future wireless communication systems, making it a valuable tool for advancing electromagnetic simulation capabilities.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"496-511"},"PeriodicalIF":1.5,"publicationDate":"2025-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145560691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-10DOI: 10.1109/JMMCT.2025.3620570
Raul O. Ribeiro;Guilherme S. Rosa;Rafael A. Penchel;Fernando L. Teixeira
This paper compares the performance of two spectral element method mapping strategies for modeling electromagnetic fields in eccentric coaxial waveguides filled with uniaxially anisotropic media. A well-known cylindrical-based SEM (CSEM) mapping is compared with a novel conformal mapping that transforms the problem into an auxiliary rectangular domain, resulting in a rectangular SEM (RSEM) approach. Numerical results show that while both methods converge similarly for problems with large internal radii, the introduced RSEM offers faster convergence for small internal radii and offsets. Benchmarking against semi-analytical and finite element solutions demonstrates RSEM's superior efficiency and accuracy in solving problems in eccentric cylindrical domains with fewer degrees of freedom.
{"title":"Convergence Analysis of the Spectral Element Method: A Comparative Study of Conformal Mappings for Eccentric Waveguide Modeling","authors":"Raul O. Ribeiro;Guilherme S. Rosa;Rafael A. Penchel;Fernando L. Teixeira","doi":"10.1109/JMMCT.2025.3620570","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3620570","url":null,"abstract":"This paper compares the performance of two spectral element method mapping strategies for modeling electromagnetic fields in eccentric coaxial waveguides filled with uniaxially anisotropic media. A well-known cylindrical-based SEM (CSEM) mapping is compared with a novel conformal mapping that transforms the problem into an auxiliary rectangular domain, resulting in a rectangular SEM (RSEM) approach. Numerical results show that while both methods converge similarly for problems with large internal radii, the introduced RSEM offers faster convergence for small internal radii and offsets. Benchmarking against semi-analytical and finite element solutions demonstrates RSEM's superior efficiency and accuracy in solving problems in eccentric cylindrical domains with fewer degrees of freedom.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"459-465"},"PeriodicalIF":1.5,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-07DOI: 10.1109/JMMCT.2025.3618590
Mohamed Kheir;Kun Qian;Mubashra Nabi;Thomas Ebel
A novel meshless electromagnetic (EM) simulation framework based on Physics-Informed Neural Networks (PINNs), enhanced by the integration of Kolmogorov–Arnold Networks (KANs) is presented. The proposed method addresses both electrostatic and electrodynamic problems governed by Laplace and Helmholtz equations, respectively. A modular and interpretable simulation architecture is developed using KAN-PINNs which enables accurate field learning in multilayered printed circuit boards (PCBs) with spatially varying permittivity. Three canonical structures: an electrostatic box, a parallel-plate transmission line (TL) and a stripline TL are modeled to demonstrate the validity of the method. The results are validated against commercial full-wave solvers showing excellent agreement with normalized root-mean-square errors (RMSE) below 0.1. Moreover, a 4-layer PCB structure is simulated at 100 MHz to demonstrate the method's capability at higher frequencies. For this case, the model achieves a normalized RMSE of 0.153 while reducing simulation time by a factor of three compared to numerical solvers. The proposed framework provides a scalable and fully mesh-free alternative to traditional electromagnetic solvers. This introduces new potential for efficiently simulating complex PCB structures in EMI applications.
{"title":"Modular Meshless Electromagnetic Simulation Using KAN-Based Physics-Informed Neural Networks","authors":"Mohamed Kheir;Kun Qian;Mubashra Nabi;Thomas Ebel","doi":"10.1109/JMMCT.2025.3618590","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3618590","url":null,"abstract":"A novel meshless electromagnetic (EM) simulation framework based on Physics-Informed Neural Networks (PINNs), enhanced by the integration of Kolmogorov–Arnold Networks (KANs) is presented. The proposed method addresses both electrostatic and electrodynamic problems governed by Laplace and Helmholtz equations, respectively. A modular and interpretable simulation architecture is developed using KAN-PINNs which enables accurate field learning in multilayered printed circuit boards (PCBs) with spatially varying permittivity. Three canonical structures: an electrostatic box, a parallel-plate transmission line (TL) and a stripline TL are modeled to demonstrate the validity of the method. The results are validated against commercial full-wave solvers showing excellent agreement with normalized root-mean-square errors (RMSE) below 0.1. Moreover, a 4-layer PCB structure is simulated at 100 MHz to demonstrate the method's capability at higher frequencies. For this case, the model achieves a normalized RMSE of 0.153 while reducing simulation time by a factor of three compared to numerical solvers. The proposed framework provides a scalable and fully mesh-free alternative to traditional electromagnetic solvers. This introduces new potential for efficiently simulating complex PCB structures in EMI applications.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"452-458"},"PeriodicalIF":1.5,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145352081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-24DOI: 10.1109/JMMCT.2025.3613962
Ranjith Kumar R;Parthasarathy Ramanujam
Reinforcement learning (RL) provides a data-driven approach for optimizing design parameters in X and Ku band applications, including radar systems and electromagnetic shielding. Conventional frequency selective surface (FSS) design methods face several challenges such as inefficient optimization and time-consuming iterative processes. To overcome these challenges, an RL-based design optimization is proposed for FSS structures to achieve enhanced selectivity, wider bandwidth, and reduced fabrication complexity. The soft actor-critic (SAC) algorithm, an advanced RL approach, is implemented in the proposed FSS design. The structure features a single-layered square grid pattern with interconnected loops to achieve wide stopband characteristics. The FSS has a guided wavelength of 0.66$lambda _{g}$ × 0.66$lambda _{g}$ × 0.1$lambda _{g}$. The design exhibits a stopband bandwidth of 10.42 GHz, ranging from 7.88 GHz to 18.30 GHz, with a shielding effectiveness (SE) of 68dB and angular stability up to 60$^{circ }$. The equivalent circuit model (ECM) analysis, simulated response, and measured results demonstrate that the SAC-based RL approach outperforms benchmark schemes, achieving the lowest mean squared error (MSE) of 0.2341.
{"title":"Design and Optimization of Wide-Band FSS Using Reinforcement Learning for X and Ku Band Radar Shielding Applications","authors":"Ranjith Kumar R;Parthasarathy Ramanujam","doi":"10.1109/JMMCT.2025.3613962","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3613962","url":null,"abstract":"Reinforcement learning (RL) provides a data-driven approach for optimizing design parameters in X and Ku band applications, including radar systems and electromagnetic shielding. Conventional frequency selective surface (FSS) design methods face several challenges such as inefficient optimization and time-consuming iterative processes. To overcome these challenges, an RL-based design optimization is proposed for FSS structures to achieve enhanced selectivity, wider bandwidth, and reduced fabrication complexity. The soft actor-critic (SAC) algorithm, an advanced RL approach, is implemented in the proposed FSS design. The structure features a single-layered square grid pattern with interconnected loops to achieve wide stopband characteristics. The FSS has a guided wavelength of 0.66<inline-formula><tex-math>$lambda _{g}$</tex-math></inline-formula> × 0.66<inline-formula><tex-math>$lambda _{g}$</tex-math></inline-formula> × 0.1<inline-formula><tex-math>$lambda _{g}$</tex-math></inline-formula>. The design exhibits a stopband bandwidth of 10.42 GHz, ranging from 7.88 GHz to 18.30 GHz, with a shielding effectiveness (SE) of 68dB and angular stability up to 60<inline-formula><tex-math>$^{circ }$</tex-math></inline-formula>. The equivalent circuit model (ECM) analysis, simulated response, and measured results demonstrate that the SAC-based RL approach outperforms benchmark schemes, achieving the lowest mean squared error (MSE) of 0.2341.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"473-482"},"PeriodicalIF":1.5,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145510230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-23DOI: 10.1109/JMMCT.2025.3613377
Vishakha Harlapur;Salil Kulkarni
Thomson coil is a fast-acting electromagnetic actuator, making it a preferred choice for hybrid circuit breakers. Modeling of Thomson coil actuator involves multi-physics analysis consisting of electric circuit, electromagnetism and structural mechanics and is typically carried out using Finite Element Analysis. These simulations are time consuming and therefore not practical during the preliminary design stage or during optimization studies. To address this challenge, a data-driven modeling approach is presented in this paper. First, a set of dimensionless parameters are identified using the Buckingham Pi theorem and then a regression model is developed to establish an approximate relationship between different design variables and the quantity of interest. The use of dimensionless variables not only reduces the number of fitting parameters but also helps to achieve size based scaling. Using the developed model, optimized values of design variables are obtained. This is followed by a sensitivity analysis to evaluate the effect of design parameters on the quantity of interest.
{"title":"Data Driven Modeling and Design Optimization of Thomson Coil Using Dimensionless Parameters","authors":"Vishakha Harlapur;Salil Kulkarni","doi":"10.1109/JMMCT.2025.3613377","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3613377","url":null,"abstract":"Thomson coil is a fast-acting electromagnetic actuator, making it a preferred choice for hybrid circuit breakers. Modeling of Thomson coil actuator involves multi-physics analysis consisting of electric circuit, electromagnetism and structural mechanics and is typically carried out using Finite Element Analysis. These simulations are time consuming and therefore not practical during the preliminary design stage or during optimization studies. To address this challenge, a data-driven modeling approach is presented in this paper. First, a set of dimensionless parameters are identified using the Buckingham Pi theorem and then a regression model is developed to establish an approximate relationship between different design variables and the quantity of interest. The use of dimensionless variables not only reduces the number of fitting parameters but also helps to achieve size based scaling. Using the developed model, optimized values of design variables are obtained. This is followed by a sensitivity analysis to evaluate the effect of design parameters on the quantity of interest.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"443-451"},"PeriodicalIF":1.5,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145315384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-22DOI: 10.1109/JMMCT.2025.3608780
Dan Jiao
{"title":"Editorial: Introducing Explaining the Unexplained","authors":"Dan Jiao","doi":"10.1109/JMMCT.2025.3608780","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3608780","url":null,"abstract":"","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"433-433"},"PeriodicalIF":1.5,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11175564","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145141694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-09DOI: 10.1109/JMMCT.2025.3608139
Mingyu Lu;Charan Litchfield
A 5-MHz sinusoidal signal, a 500-Hz sinusoidal signal, and a DC signal are compared among each other experimentally when they are turned on, after they are established over a piece of long co-axial cable, and when they are turned off. The experimental results do not demonstrate any fundamental differences among the 5-MHz signal, 500-Hz signal, and DC signal in terms of propagation over the co-axial cable. Based on the experimental results, the well-known formulations of AC wave propagation are extended to DC wave propagation. The experimental and theoretical studies of this paper indicate that DC electrical power is transported by electromagnetic wave propagation in practical DC circuits.
{"title":"Is DC Power Transmitted by Electromagnetic Waves?","authors":"Mingyu Lu;Charan Litchfield","doi":"10.1109/JMMCT.2025.3608139","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3608139","url":null,"abstract":"A 5-MHz sinusoidal signal, a 500-Hz sinusoidal signal, and a DC signal are compared among each other experimentally when they are turned on, after they are established over a piece of long co-axial cable, and when they are turned off. The experimental results do not demonstrate any fundamental differences among the 5-MHz signal, 500-Hz signal, and DC signal in terms of propagation over the co-axial cable. Based on the experimental results, the well-known formulations of AC wave propagation are extended to DC wave propagation. The experimental and theoretical studies of this paper indicate that DC electrical power is transported by electromagnetic wave propagation in practical DC circuits.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"434-442"},"PeriodicalIF":1.5,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145141781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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