Pub Date : 2023-01-17DOI: 10.1109/JMMCT.2023.3237699
Mengmeng Li;Yuchenxi Zhang;Zixuan Ma
Planar metasurfaces have been applied in several fields. Near-field coupling is typically neglected in traditional metasurface designs. A numerical modeling method for macrocells that considers near-field couplings between meta-atoms is proposed. A deep neural network (DNN) is constructed to accurately predict the electromagnetic response from different macrocells. Transfer learning is employed to reduce the number of the training datasets. The designed neural network is embedded in the optimization algorithm as an effective surrogate model. Both the deflector and high numerical aperture (NA) metalens are simulated and optimized with our design framework, approximately 30% improvements of efficiencies are achieved.
{"title":"Deep-Learning-Based Metasurface Design Method Considering Near-Field Couplings","authors":"Mengmeng Li;Yuchenxi Zhang;Zixuan Ma","doi":"10.1109/JMMCT.2023.3237699","DOIUrl":"https://doi.org/10.1109/JMMCT.2023.3237699","url":null,"abstract":"Planar metasurfaces have been applied in several fields. Near-field coupling is typically neglected in traditional metasurface designs. A numerical modeling method for macrocells that considers near-field couplings between meta-atoms is proposed. A deep neural network (DNN) is constructed to accurately predict the electromagnetic response from different macrocells. Transfer learning is employed to reduce the number of the training datasets. The designed neural network is embedded in the optimization algorithm as an effective surrogate model. Both the deflector and high numerical aperture (NA) metalens are simulated and optimized with our design framework, approximately 30% improvements of efficiencies are achieved.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49962819","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 : 2023-01-13DOI: 10.1109/JMMCT.2023.3236946
Shutong Qi;Costas D. Sarris
This article presents the coupling of the finite-difference time-domain (FDTD) method for electromagnetic field simulation, with a physics-informed neural network based solver for the heat equation. To this end, we employ a physics-informed U-Net instead of a numerical method to solve the heat equation. This approach enables the solution of general multiphysics problems with a single-physics numerical solver coupled with a neural network, overcoming the questions of accuracy and efficiency that are associated with interfacing multiphysics equations. By embedding the heat equation and its boundary conditions in the U-Net, we implement an unsupervised training methodology, which does not require the generation of ground-truth data. We test the proposed method with general 2-D coupled electromagnetic-thermal problems, demonstrating its accuracy and efficiency compared to standard finite-difference based alternatives.
{"title":"Electromagnetic-Thermal Analysis With FDTD and Physics-Informed Neural Networks","authors":"Shutong Qi;Costas D. Sarris","doi":"10.1109/JMMCT.2023.3236946","DOIUrl":"https://doi.org/10.1109/JMMCT.2023.3236946","url":null,"abstract":"This article presents the coupling of the finite-difference time-domain (FDTD) method for electromagnetic field simulation, with a physics-informed neural network based solver for the heat equation. To this end, we employ a physics-informed U-Net instead of a numerical method to solve the heat equation. This approach enables the solution of general multiphysics problems with a single-physics numerical solver coupled with a neural network, overcoming the questions of accuracy and efficiency that are associated with interfacing multiphysics equations. By embedding the heat equation and its boundary conditions in the U-Net, we implement an unsupervised training methodology, which does not require the generation of ground-truth data. We test the proposed method with general 2-D coupled electromagnetic-thermal problems, demonstrating its accuracy and efficiency compared to standard finite-difference based alternatives.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49962820","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 : 2023-01-12DOI: 10.1109/JMMCT.2023.3236645
Shuzhan Sun;Dan Jiao
In this work, we propose a new split-field domain-decomposition (DD) algorithm. Different from conventional DD methods where interface fields are treated as a whole and shared in common between adjacent subdomains, we split the field on the interface into $m$ components, where $m$ is the number of subdomains sharing the interface, and solve one component of the interface field in each subdomain. The resultant numerical scheme allows for each subdomain to be directly solved in a decoupled manner, and meanwhile captures the global coupling among subdomains iteratively with fast and guaranteed convergence. Numerical simulations of large-scale electromagnetic structures such as integrated circuits and packages demonstrate the accuracy and efficiency of the proposed DD algorithm, and the resultant parallel solver.
{"title":"Split-Field Domain Decomposition Parallel Algorithm With Fast Convergence for Electromagnetic Analysis","authors":"Shuzhan Sun;Dan Jiao","doi":"10.1109/JMMCT.2023.3236645","DOIUrl":"https://doi.org/10.1109/JMMCT.2023.3236645","url":null,"abstract":"In this work, we propose a new split-field domain-decomposition (DD) algorithm. Different from conventional DD methods where interface fields are treated as a whole and shared in common between adjacent subdomains, we split the field on the interface into \u0000<inline-formula><tex-math>$m$</tex-math></inline-formula>\u0000 components, where \u0000<inline-formula><tex-math>$m$</tex-math></inline-formula>\u0000 is the number of subdomains sharing the interface, and solve one component of the interface field in each subdomain. The resultant numerical scheme allows for each subdomain to be directly solved in a decoupled manner, and meanwhile captures the global coupling among subdomains iteratively with fast and guaranteed convergence. Numerical simulations of large-scale electromagnetic structures such as integrated circuits and packages demonstrate the accuracy and efficiency of the proposed DD algorithm, and the resultant parallel solver.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49981536","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}
Nowadays, materials to protect equipment from unwanted multispectral electromagnetic waves are needed in a broad range of applications including electronics, medical, military and aerospace. However, the shielding materials currently in use are bulky and work effectively only in a limited frequency range. Therefore, nanostructured materials are under investigation by the relevant scientific community. In this framework, the design of multispectral shielding nanomaterials must be supplemented with proper numerical models that allow dealing with non-linearities and being effective in predicting their absorption spectra. In this study, the electromagnetic response of metal-oxide nanocrystals with multispectral electromagnetic shielding capability has been investigated. A numerical framework was developed to predict energy bands and electron density profiles of a core-shell nanocrystal and to evaluate its optical response at different wavelengths. To this aim, a finite element method software is used to solve a non-linear Poisson's equation. The numerical simulations allowed to model the optical response of $mathbf {ITO}$ - $mathbf {In_{2}O_{3}}$ core-shell nanocrystals and can be effectively applied to different nanotopologies to support an enhanced design of nanomaterials with multispectral shielding capabilities.
{"title":"Numerical Study of the Optical Response of $text{ITO}$-${text{In}_{{2}}{text O}_{{3}}}$ Core-Shell Nanocrystals for Multispectral Electromagnetic Shielding","authors":"Nicola Curreli;Matteo Bruno Lodi;Michele Ghini;Nicolò Petrini;Andrea Buono;Maurizio Migliaccio;Alessandro Fanti;Ilka Kriegel;Giuseppe Mazzarella","doi":"10.1109/JMMCT.2023.3235750","DOIUrl":"https://doi.org/10.1109/JMMCT.2023.3235750","url":null,"abstract":"Nowadays, materials to protect equipment from unwanted multispectral electromagnetic waves are needed in a broad range of applications including electronics, medical, military and aerospace. However, the shielding materials currently in use are bulky and work effectively only in a limited frequency range. Therefore, nanostructured materials are under investigation by the relevant scientific community. In this framework, the design of multispectral shielding nanomaterials must be supplemented with proper numerical models that allow dealing with non-linearities and being effective in predicting their absorption spectra. In this study, the electromagnetic response of metal-oxide nanocrystals with multispectral electromagnetic shielding capability has been investigated. A numerical framework was developed to predict energy bands and electron density profiles of a core-shell nanocrystal and to evaluate its optical response at different wavelengths. To this aim, a finite element method software is used to solve a non-linear Poisson's equation. The numerical simulations allowed to model the optical response of \u0000<inline-formula><tex-math>$mathbf {ITO}$</tex-math></inline-formula>\u0000-\u0000<inline-formula><tex-math>$mathbf {In_{2}O_{3}}$</tex-math></inline-formula>\u0000 core-shell nanocrystals and can be effectively applied to different nanotopologies to support an enhanced design of nanomaterials with multispectral shielding capabilities.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/7274859/10003074/10013664.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49962821","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 : 2023-01-03DOI: 10.1109/JMMCT.2022.3233944
Dinshaw S. Balsara;Costas D. Sarris
There is a great need to solve CED problems on adaptive meshes; referred to here as AMR-CED. The problem was deemed to be susceptible to “long-term instability” and parameterized methods have been used to control the instability. In this paper, we present a new class of AMR-CED methods that are free of this instability because they are based on a more careful understanding of the constraints in Maxwell's equations and their preservation on a single control volume. The important building blocks of these new methods are: 1) Timestep sub-cycling of finer child meshes relative to parent meshes. 2) Restriction of fine mesh facial data to coarser meshes when the two meshes are synchronized in time. 3) Divergence constraint-preserving prolongation of the coarse mesh solution to newly built fine meshes or to the ghost zones of pre-existing fine meshes. 4) Electric and magnetic field intensity-correction strategy at fine-coarse interfaces. Using examples, we show that the resulting AMR-CED algorithm is free of “long-term instability”. Unlike previous methods, there are no adjustable parameters. The method is inherently stable because a strict algorithmic consistency is applied at all levels in the AMR mesh hierarchy. We also show that the method preserves order of accuracy, so that high order methods for AMR-CED are indeed possible.
{"title":"A Systematic Approach to Adaptive Mesh Refinement for Computational Electrodynamics","authors":"Dinshaw S. Balsara;Costas D. Sarris","doi":"10.1109/JMMCT.2022.3233944","DOIUrl":"https://doi.org/10.1109/JMMCT.2022.3233944","url":null,"abstract":"There is a great need to solve CED problems on adaptive meshes; referred to here as AMR-CED. The problem was deemed to be susceptible to “long-term instability” and parameterized methods have been used to control the instability. In this paper, we present a new class of AMR-CED methods that are free of this instability because they are based on a more careful understanding of the constraints in Maxwell's equations and their preservation on a single control volume. The important building blocks of these new methods are: 1) Timestep sub-cycling of finer child meshes relative to parent meshes. 2) Restriction of fine mesh facial data to coarser meshes when the two meshes are synchronized in time. 3) Divergence constraint-preserving prolongation of the coarse mesh solution to newly built fine meshes or to the ghost zones of pre-existing fine meshes. 4) Electric and magnetic field intensity-correction strategy at fine-coarse interfaces. Using examples, we show that the resulting AMR-CED algorithm is free of “long-term instability”. Unlike previous methods, there are no adjustable parameters. The method is inherently stable because a strict algorithmic consistency is applied at all levels in the AMR mesh hierarchy. We also show that the method preserves order of accuracy, so that high order methods for AMR-CED are indeed possible.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49981637","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 : 2023-01-01DOI: 10.1109/JMMCT.2024.3355900
{"title":"2023 Index IEEE Journal on Multiscale and Multiphysics Computational Techniques Vol. 8","authors":"","doi":"10.1109/JMMCT.2024.3355900","DOIUrl":"https://doi.org/10.1109/JMMCT.2024.3355900","url":null,"abstract":"","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10405364","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139494253","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 : 2023-01-01DOI: 10.1109/JMMCT.2023.3346472
Costas Sarris
In July 2023, the IEEE Journal on Multiphysics and Multiscale Computational Techniques (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.
{"title":"Editorial The Year of the Impact Factor","authors":"Costas Sarris","doi":"10.1109/JMMCT.2023.3346472","DOIUrl":"https://doi.org/10.1109/JMMCT.2023.3346472","url":null,"abstract":"In July 2023, the \u0000<sc>IEEE Journal on Multiphysics and Multiscale Computational Techniques</small>\u0000 (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.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10399976","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139473656","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 : 2022-12-20DOI: 10.1109/JMMCT.2022.3230732
Boyuan Zhang;Dong-Yeop Na;Dan Jiao;Weng Cho Chew
An efficient numerical solver for the A - $Phi$ formulation in electromagnetics based on discrete exterior calculus (DEC) is proposed in this paper. The A - $Phi$ 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 A equation and the $Phi$ equation. The A - $Phi$ 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 A - $Phi$ solver is inherently stable, free of spurious solutions and can capture highly complex structures efficiently. In this paper, the background knowledge about the A - $Phi$ formulation and DEC is introduced, as well as technical details in implementing the DEC A - $Phi$ solver with different boundary conditions. Numerical examples are provided for validation purposes as well.
{"title":"An A-$Phi$ Formulation Solver in Electromagnetics Based on Discrete Exterior Calculus","authors":"Boyuan Zhang;Dong-Yeop Na;Dan Jiao;Weng Cho Chew","doi":"10.1109/JMMCT.2022.3230732","DOIUrl":"https://doi.org/10.1109/JMMCT.2022.3230732","url":null,"abstract":"An efficient numerical solver for the \u0000<bold>A</b>\u0000-\u0000<inline-formula><tex-math>$Phi$</tex-math></inline-formula>\u0000 formulation in electromagnetics based on discrete exterior calculus (DEC) is proposed in this paper. The \u0000<bold>A</b>\u0000-\u0000<inline-formula><tex-math>$Phi$</tex-math></inline-formula>\u0000 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 \u0000<bold>A</b>\u0000 equation and the \u0000<inline-formula><tex-math>$Phi$</tex-math></inline-formula>\u0000 equation. The \u0000<bold>A</b>\u0000-\u0000<inline-formula><tex-math>$Phi$</tex-math></inline-formula>\u0000 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 \u0000<bold>A</b>\u0000-\u0000<inline-formula><tex-math>$Phi$</tex-math></inline-formula>\u0000 solver is inherently stable, free of spurious solutions and can capture highly complex structures efficiently. In this paper, the background knowledge about the \u0000<bold>A</b>\u0000-\u0000<inline-formula><tex-math>$Phi$</tex-math></inline-formula>\u0000 formulation and DEC is introduced, as well as technical details in implementing the DEC \u0000<bold>A</b>\u0000-\u0000<inline-formula><tex-math>$Phi$</tex-math></inline-formula>\u0000 solver with different boundary conditions. Numerical examples are provided for validation purposes as well.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49962816","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 : 2022-12-20DOI: 10.1109/JMMCT.2022.3230664
Christopher K. Pratt;John C. Young;Robert J. Adams;Stephen D. Gedney
This article presents a boundary integral equation formulation for the prediction of electrostatic fields, potentials, and currents in regions comprising piecewise-homogeneous electrolytes. The integral equation is formulated in terms of the boundary electric potentials and normal electric current densities and is discretized using the locally corrected Nyström method. The method is validated by comparison to analytic solution data for both linear and nonlinear canonical problems. Solution convergence is investigated with respect to mesh discretization and basis order.
{"title":"Boundary Integral Equation Method for Electrostatic Field Prediction in Piecewise-Homogeneous Electrolytes","authors":"Christopher K. Pratt;John C. Young;Robert J. Adams;Stephen D. Gedney","doi":"10.1109/JMMCT.2022.3230664","DOIUrl":"https://doi.org/10.1109/JMMCT.2022.3230664","url":null,"abstract":"This article presents a boundary integral equation formulation for the prediction of electrostatic fields, potentials, and currents in regions comprising piecewise-homogeneous electrolytes. The integral equation is formulated in terms of the boundary electric potentials and normal electric current densities and is discretized using the locally corrected Nyström method. The method is validated by comparison to analytic solution data for both linear and nonlinear canonical problems. Solution convergence is investigated with respect to mesh discretization and basis order.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49962817","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 : 2022-12-16DOI: 10.1109/JMMCT.2022.3229963
Hongliang Li;Philip T. Krein;Jian-Ming Jin
A nonlinear electromagnetic (EM)-thermal coupled solver is developed for modeling ferromagnetic materials widely used in electric motors. To accurately predict machine performance, the time-domain finite element method is employed to solve this multiphysics problem. By adopting the nonlinear B-H models to account for hysteresis effects, magnetic core losses are computed as the major sources of power dissipation for magnetic materials. The resulting temperature change is then obtained and its effect on the magnetic properties is subsequently evaluated. Due to different time scales of EM field variations and heat transfer processes, different time step sizes are adopted to enhance the simulation speed. During thermal time marching, the EM solver is invoked adaptively based on material property changes, and EM losses are calculated and updated through extrapolation, resulting in an efficient EM-thermal coupling scheme. Numerical examples are presented to validate the accuracy and capabilities of the proposed EM-thermal co-simulation framework.
{"title":"Electromagnetic-Thermal Modeling of Nonlinear Magnetic Materials","authors":"Hongliang Li;Philip T. Krein;Jian-Ming Jin","doi":"10.1109/JMMCT.2022.3229963","DOIUrl":"https://doi.org/10.1109/JMMCT.2022.3229963","url":null,"abstract":"A nonlinear electromagnetic (EM)-thermal coupled solver is developed for modeling ferromagnetic materials widely used in electric motors. To accurately predict machine performance, the time-domain finite element method is employed to solve this multiphysics problem. By adopting the nonlinear B-H models to account for hysteresis effects, magnetic core losses are computed as the major sources of power dissipation for magnetic materials. The resulting temperature change is then obtained and its effect on the magnetic properties is subsequently evaluated. Due to different time scales of EM field variations and heat transfer processes, different time step sizes are adopted to enhance the simulation speed. During thermal time marching, the EM solver is invoked adaptively based on material property changes, and EM losses are calculated and updated through extrapolation, resulting in an efficient EM-thermal coupling scheme. Numerical examples are presented to validate the accuracy and capabilities of the proposed EM-thermal co-simulation framework.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49962815","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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