Pub Date : 2025-08-01DOI: 10.1109/JMMCT.2025.3593872
Suyash Kushwaha;Chintu Bhaskara Rao;Shamini P R;Sourajeet Roy;Rohit Sharma
In this paper, novel copper graphene heterogeneous interconnect structures are proposed which retain the ease of fabrication while having far better electrical performance when compared to the conventional copper interconnects. In the nanoscale regime, signal integrity (SI) of the copper interconnects degrades significantly. To address the signal integrity issues, these heterogeneous interconnects are developed at 7 nm technology nodes which are further used to make the crossbar arrays for neuromorphic computing. The proposed copper graphene heterogeneous interconnects were designed by stacking the layers of copper and multilayer graphene nanoribbons (MLGNRs) one over the other and a detailed signal integrity analysis is done based on the quantities like the per unit length Resistance, Insertion Loss (IL), Return Loss (RL), eye diagrams, surface charge density and volume current density. The results shows that the proposed interconnects outperformed the copper interconnects based on each and every SI quantity. Finally, in the application example, the best performing heterogeneous interconnects are used to create larger crossbar arrays with sizes 64 × 64, 128 × 128. Further, the key performance matrices such as the delay time, the rise time and the fall time are analyzed and compared with the conventional crossbars made from the copper interconnects. The results in application example proved that the heterogeneous interconnects performs better than the copper interconnects for neuromorphic computing.
{"title":"Performance Enhanced Copper-Graphene Hetero Interconnect Structures in Crossbar Arrays for Neuromorphic Computing","authors":"Suyash Kushwaha;Chintu Bhaskara Rao;Shamini P R;Sourajeet Roy;Rohit Sharma","doi":"10.1109/JMMCT.2025.3593872","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3593872","url":null,"abstract":"In this paper, novel copper graphene heterogeneous interconnect structures are proposed which retain the ease of fabrication while having far better electrical performance when compared to the conventional copper interconnects. In the nanoscale regime, signal integrity (SI) of the copper interconnects degrades significantly. To address the signal integrity issues, these heterogeneous interconnects are developed at 7 nm technology nodes which are further used to make the crossbar arrays for neuromorphic computing. The proposed copper graphene heterogeneous interconnects were designed by stacking the layers of copper and multilayer graphene nanoribbons (MLGNRs) one over the other and a detailed signal integrity analysis is done based on the quantities like the per unit length Resistance, Insertion Loss (IL), Return Loss (RL), eye diagrams, surface charge density and volume current density. The results shows that the proposed interconnects outperformed the copper interconnects based on each and every SI quantity. Finally, in the application example, the best performing heterogeneous interconnects are used to create larger crossbar arrays with sizes 64 × 64, 128 × 128. Further, the key performance matrices such as the delay time, the rise time and the fall time are analyzed and compared with the conventional crossbars made from the copper interconnects. The results in application example proved that the heterogeneous interconnects performs better than the copper interconnects for neuromorphic computing.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"379-387"},"PeriodicalIF":1.5,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904842","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}
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.
{"title":"Enhancing DORT Method Performance in Time-Reversal Microwave Imaging Through Denoising Autoencoder","authors":"Hamed Rezaei;Amir Nader Askarpour;Abdolali Abdipour","doi":"10.1109/JMMCT.2025.3589191","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3589191","url":null,"abstract":"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.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"360-369"},"PeriodicalIF":1.5,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773249","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}
This study examines the computational challenges associated with modeling liver tumors using microwave ablation (MWA), while highlighting the limitations of conventional methods and advocating for the use of MWA in conjunction with artificial intelligence as a more promising approach. The proposed innovative antenna design, which comprises a coaxial line featuring a tapered outer conductor and a dipole antenna, aims to produce a nearly spherical ablation zone without the need for any additional matching network. Capable of operating at both 2.45 GHz and 5.8 GHz with minor structural modifications, it offers flexibility in tumor ablation systems. The research further incorporates and compares the sigmoidal model, a well-established computational method, and a recently developed parametric model for evaluating temperature-dependent properties in modeling the 3-D liver tissue, identifying differences in the ablation zone during MWA. Additionally, since both under and over ablation are major concerns during the MWA procedure, resulting in damage to healthy tissue and tumor recurrence, respectively, this study introduces a Taguchi Artificial Neural Networks (TNN) framework for the prediction of ablation zone in advance, thereby, significantly reducing the number of required training datasets without compromising performance metrics.
{"title":"Optimized Microwave Ablation With a Novel Applicator: Integration of Taguchi Neural Networks for Enhanced Predictive Accuracy of Ablation Zone","authors":"Suyash Kumar Singh;Brij Kumar Bharti;Amar Nath Yadav;Ajay Kumar Dwivedi","doi":"10.1109/JMMCT.2025.3589163","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3589163","url":null,"abstract":"This study examines the computational challenges associated with modeling liver tumors using microwave ablation (MWA), while highlighting the limitations of conventional methods and advocating for the use of MWA in conjunction with artificial intelligence as a more promising approach. The proposed innovative antenna design, which comprises a coaxial line featuring a tapered outer conductor and a dipole antenna, aims to produce a nearly spherical ablation zone without the need for any additional matching network. Capable of operating at both 2.45 GHz and 5.8 GHz with minor structural modifications, it offers flexibility in tumor ablation systems. The research further incorporates and compares the sigmoidal model, a well-established computational method, and a recently developed parametric model for evaluating temperature-dependent properties in modeling the 3-D liver tissue, identifying differences in the ablation zone during MWA. Additionally, since both under and over ablation are major concerns during the MWA procedure, resulting in damage to healthy tissue and tumor recurrence, respectively, this study introduces a Taguchi Artificial Neural Networks (TNN) framework for the prediction of ablation zone in advance, thereby, significantly reducing the number of required training datasets without compromising performance metrics.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"348-359"},"PeriodicalIF":1.5,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739814","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 : 2025-07-10DOI: 10.1109/JMMCT.2025.3587386
Satish Kumar;Gopi Ram;Durbadal Mandal;Rajib Kar
In order to optimize the synthesis of Asymmetric Time-Modulated Circular Antenna Array (ATMCAA) and Symmetric Time-Modulated Circular Antenna Array (STMCAA), this work presents the Novel Particle Swarm Optimization Algorithm (NPSO). Inter-element spacing and uniform current excitation are maintained by regulating the switching time sequence and progressive phase delay of each element. A distinct cost function is developed for each of the two case studies. Using 20- and 36-element examples, several low side-lobe designs synthesized from ATMCAA and STMCAA are compared with traditional circular arrays. Through the manipulation of switching time sequence and progressive phase delay, the cost function is optimized to simultaneously reduce the side-lobe level (SLL) and directivity in ATMCAA and STMCAA. When it comes to antenna array synthesis, NPSO performs better than other algorithms, such as cat swarm optimization and invasive weed optimization. This study demonstrates how effective NPSO is at optimizing antenna arrays in order to improve higher communication reliability and signal quality.
{"title":"Optimal Configuration and Performance Enhancement of Time-Modulated Circular Antenna Arrays","authors":"Satish Kumar;Gopi Ram;Durbadal Mandal;Rajib Kar","doi":"10.1109/JMMCT.2025.3587386","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3587386","url":null,"abstract":"In order to optimize the synthesis of Asymmetric Time-Modulated Circular Antenna Array (ATMCAA) and Symmetric Time-Modulated Circular Antenna Array (STMCAA), this work presents the Novel Particle Swarm Optimization Algorithm (NPSO). Inter-element spacing and uniform current excitation are maintained by regulating the switching time sequence and progressive phase delay of each element. A distinct cost function is developed for each of the two case studies. Using 20- and 36-element examples, several low side-lobe designs synthesized from ATMCAA and STMCAA are compared with traditional circular arrays. Through the manipulation of switching time sequence and progressive phase delay, the cost function is optimized to simultaneously reduce the side-lobe level (SLL) and directivity in ATMCAA and STMCAA. When it comes to antenna array synthesis, NPSO performs better than other algorithms, such as cat swarm optimization and invasive weed optimization. This study demonstrates how effective NPSO is at optimizing antenna arrays in order to improve higher communication reliability and signal quality.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"334-347"},"PeriodicalIF":1.8,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716297","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 : 2025-07-02DOI: 10.1109/JMMCT.2025.3585550
Wen-Tao Bao;Joseph D. Kotulski;Jin-Fa Lee
This paper presents an automatic mesh refinement method designed to accurately capture resonant responses in high-quality factor devices using surface integral equations. To validate the method, a solution-based error estimator is proposed to evaluate solution quality and identify elements requiring local mesh refinement. The sensitivity of the local error distribution to frequencies near numerical resonance is examined. To effectively capture the resonant behavior, an automatic h–refinement strategy, combined with frequency sweeping, is introduced. Numerical experiments on slotted cavities with high-quality factor are provided. In addition, the advantages of the proposed error estimator over the widely used residual error estimator are discussed.
{"title":"Automatic Mesh Refinement Process for High-Quality Factor Resonant Cavities Using the Method of Moments","authors":"Wen-Tao Bao;Joseph D. Kotulski;Jin-Fa Lee","doi":"10.1109/JMMCT.2025.3585550","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3585550","url":null,"abstract":"This paper presents an automatic mesh refinement method designed to accurately capture resonant responses in high-quality factor devices using surface integral equations. To validate the method, a solution-based error estimator is proposed to evaluate solution quality and identify elements requiring local mesh refinement. The sensitivity of the local error distribution to frequencies near numerical resonance is examined. To effectively capture the resonant behavior, an automatic <italic>h</i>–refinement strategy, combined with frequency sweeping, is introduced. Numerical experiments on slotted cavities with high-quality factor are provided. In addition, the advantages of the proposed error estimator over the widely used residual error estimator are discussed.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"324-333"},"PeriodicalIF":1.8,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687766","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 : 2025-07-02DOI: 10.1109/JMMCT.2025.3584998
Reza Ilka;Jiangbiao He;Jingjing Yang;Jose E. Contreras;Carlos G. Cavazos;Weijun Yin
Power transformers serve as indispensable elements in nearly every electrical power system. Ensuring the continuous operation of power transformers is pivotal in maintaining the reliability and safety of the power network. Hotspot temperature (HST) in windings is a key factor that indicates the health condition of a power transformer. To determine the temperature of the transformer windings, it is essential to obtain the temperature distribution inside the transformer. This paper introduces a high-fidelity multi-physics modeling and simulation framework focused on predicting the reliability of large power transformers. The methodology relies on the application of three-dimensional (3D) finite element analysis (FEA) and computational fluid dynamics (CFD). In particular, electromagnetic modeling and simulation using FEA are conducted to calculate transformer losses. Subsequently, a thermal-hydraulic model is established to determine the temperature distribution. More importantly, this is to identify the HST in the transformer windings, which is further utilized to determine the transformer lifetime. Additionally, a sensitivity analysis is carried out to evaluate how the properties of the cooling oil affect both temperature distribution and HST. Finally, experimental results are provided to confirm the multi-physics modeling and simulation results.
{"title":"FEA and CFD Based Multi-Physics Modeling, Simulation, and Validation of Oil-Immersed Power Transformers","authors":"Reza Ilka;Jiangbiao He;Jingjing Yang;Jose E. Contreras;Carlos G. Cavazos;Weijun Yin","doi":"10.1109/JMMCT.2025.3584998","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3584998","url":null,"abstract":"Power transformers serve as indispensable elements in nearly every electrical power system. Ensuring the continuous operation of power transformers is pivotal in maintaining the reliability and safety of the power network. Hotspot temperature (HST) in windings is a key factor that indicates the health condition of a power transformer. To determine the temperature of the transformer windings, it is essential to obtain the temperature distribution inside the transformer. This paper introduces a high-fidelity multi-physics modeling and simulation framework focused on predicting the reliability of large power transformers. The methodology relies on the application of three-dimensional (3D) finite element analysis (FEA) and computational fluid dynamics (CFD). In particular, electromagnetic modeling and simulation using FEA are conducted to calculate transformer losses. Subsequently, a thermal-hydraulic model is established to determine the temperature distribution. More importantly, this is to identify the HST in the transformer windings, which is further utilized to determine the transformer lifetime. Additionally, a sensitivity analysis is carried out to evaluate how the properties of the cooling oil affect both temperature distribution and HST. Finally, experimental results are provided to confirm the multi-physics modeling and simulation results.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"304-314"},"PeriodicalIF":1.8,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597803","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 : 2025-06-27DOI: 10.1109/JMMCT.2025.3583976
P. Agilandeswari;G. Thavasi Raja;R. Rajasekar;R. Parthasarathy
A novel deep learning-based reconfigurable and multifunctional Photonic Crystal Ring Resonator (PCRR) is designed with narrow bandwidth, low insertion loss and ultracompact size for lightwave communication and optical computing applications. The designed coupled nanoring resonator is used to realize four different functions of optical switch, narrow bandpass filter, encoder and XOR gate. The periodic structure of photonic bandgap frequency range is calculated by the Plane Wave Expansion (PWE) technique. The multifunctional nanoscale structure performance parameters of extinction ratio, quality factor and insertion loss are numerically analyzed by Finite-Difference-Time-Domain (FDTD) method. The deep learning algorithm of Long Short Term Memory- Neural Network (LSTM-NN) is used to predict the design parameters with low mean square error and less computation time of 50 seconds. The nanoring resonators is designed with high quality factor of 2566.83, high extinction ratio of 34.87 dB and ultracompact size of 179.20 μm2. Hence, this multifunctional platform is highly appropriate for photonic integrated circuits and optical computing system.
{"title":"Deep Learning-Based Prediction of Multifunctional Photonic Crystal Ring Resonator With Ultra High-Quality Factor","authors":"P. Agilandeswari;G. Thavasi Raja;R. Rajasekar;R. Parthasarathy","doi":"10.1109/JMMCT.2025.3583976","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3583976","url":null,"abstract":"A novel deep learning-based reconfigurable and multifunctional Photonic Crystal Ring Resonator (PCRR) is designed with narrow bandwidth, low insertion loss and ultracompact size for lightwave communication and optical computing applications. The designed coupled nanoring resonator is used to realize four different functions of optical switch, narrow bandpass filter, encoder and XOR gate. The periodic structure of photonic bandgap frequency range is calculated by the Plane Wave Expansion (PWE) technique. The multifunctional nanoscale structure performance parameters of extinction ratio, quality factor and insertion loss are numerically analyzed by Finite-Difference-Time-Domain (FDTD) method. The deep learning algorithm of Long Short Term Memory- Neural Network (LSTM-NN) is used to predict the design parameters with low mean square error and less computation time of 50 seconds. The nanoring resonators is designed with high quality factor of 2566.83, high extinction ratio of 34.87 dB and ultracompact size of 179.20 μm<sup>2</sup>. Hence, this multifunctional platform is highly appropriate for photonic integrated circuits and optical computing system.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"295-303"},"PeriodicalIF":1.8,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144606341","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}
This contribution reports a comprehensive investigation into the development and validation of optimized models for simulating the electronic properties of large-scale graphene-based geometric diodes. Our study incorporates unique features as, for example, a general treatment for the boundary conditions, that include arbitrary impedance constrains for the diode output-terminals. The observed diode-like rectification behavior has its physical origin to be an intrinsic property of in the nonlinear carrier transport partial differential equations with polarity-dependent coefficients in asymmetric geometries. While atomistic methods offer, in principle, high accuracy at the atomic scale, their computational cost renders them impractical for simulating devices with dimensions exceeding a few nanometers. To address this limitation, we have developed an improved drift-diffusion framework that captures the essential physics of charge transport in the non-ballistic limit. Through extensive numerical simulations and new proposed diode topologies, we have investigated the impact of geometric parameters and external bias on the device characteristics. Direct quantitative comparison of independent results, obtained assuming fully coherent and fully diffusive transport in four-terminal diodes, has also been reported. The present model can be effectively used to preliminarily compare different diode geometries and to design/optimize large multi-terminal structures based on graphene.
{"title":"Large-Area Geometric Diodes Based on Asymmetric and Nonlinear Transport in Patterned Graphene","authors":"Davide Mencarelli;Emiliano Laudadio;Heng Wang;Siti Nur Afifa Azman;Martino Aldrigo;Mircea Dragoman;Eleonora Pavoni;Elaheh Mohebbi;Luca Pierantoni","doi":"10.1109/JMMCT.2025.3583441","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3583441","url":null,"abstract":"This contribution reports a comprehensive investigation into the development and validation of optimized models for simulating the electronic properties of large-scale graphene-based geometric diodes. Our study incorporates unique features as, for example, a general treatment for the boundary conditions, that include arbitrary impedance constrains for the diode output-terminals. The observed diode-like rectification behavior has its physical origin to be an intrinsic property of in the nonlinear carrier transport partial differential equations with polarity-dependent coefficients in asymmetric geometries. While atomistic methods offer, in principle, high accuracy at the atomic scale, their computational cost renders them impractical for simulating devices with dimensions exceeding a few nanometers. To address this limitation, we have developed an improved drift-diffusion framework that captures the essential physics of charge transport in the non-ballistic limit. Through extensive numerical simulations and new proposed diode topologies, we have investigated the impact of geometric parameters and external bias on the device characteristics. Direct quantitative comparison of independent results, obtained assuming fully coherent and fully diffusive transport in four-terminal diodes, has also been reported. The present model can be effectively used to preliminarily compare different diode geometries and to design/optimize large multi-terminal structures based on graphene.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"315-323"},"PeriodicalIF":1.8,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11052628","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144640998","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 : 2025-06-13DOI: 10.1109/JMMCT.2025.3579349
Dohun Lee;Ahmad Ramadoni;Jaewook Lee
This study presents a numerical homogenization model to predict the effective nonlinear behavior of highly heterogeneous electropermanent magnet (EPM) composites. EPM composites consist of periodic microstructures composed of both soft and hard ferromagnetic materials (i.e., iron and permanent magnets). EPM composites possess unique ability to self-generate magnetic fields while adjusting them using external current, making them promising for use in electromechanical devices. However, direct numerical analysis of EPM composite structures requires huge computational costs, particularly in nonlinear ranges where electromechanical devices typically operate. This challenge can be alleviated through multiscale analysis using homogenization method. The developed homogenization model is constructed using the energy-based approach, assuming magnetic energy equivalence between heterogeneous and homogeneous media. Specifically, the effective B-H curve of EPM composite is computed by interpolating B-H pairs obtained by solving cell problems through finite element analysis. To validate the proposed homogenization model, three numerical examples including an actuator and a magnetic bearing, are investigated. In each example, the magnetic field distribution, magnetic energy, or magnetic force, along with computational time, of actual EPM heterogeneous structures are compared with those of equivalent structures having homogeneous effective B-H curve. These comparisons confirm the accuracy and computational efficiency of the developed numerical homogenization model.
{"title":"Numerical Homogenization for Nonlinear Multiscale Analysis of Electropermanent Magnet Composites","authors":"Dohun Lee;Ahmad Ramadoni;Jaewook Lee","doi":"10.1109/JMMCT.2025.3579349","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3579349","url":null,"abstract":"This study presents a numerical homogenization model to predict the effective nonlinear behavior of highly heterogeneous electropermanent magnet (EPM) composites. EPM composites consist of periodic microstructures composed of both soft and hard ferromagnetic materials (i.e., iron and permanent magnets). EPM composites possess unique ability to self-generate magnetic fields while adjusting them using external current, making them promising for use in electromechanical devices. However, direct numerical analysis of EPM composite structures requires huge computational costs, particularly in nonlinear ranges where electromechanical devices typically operate. This challenge can be alleviated through multiscale analysis using homogenization method. The developed homogenization model is constructed using the energy-based approach, assuming magnetic energy equivalence between heterogeneous and homogeneous media. Specifically, the effective B-H curve of EPM composite is computed by interpolating B-H pairs obtained by solving cell problems through finite element analysis. To validate the proposed homogenization model, three numerical examples including an actuator and a magnetic bearing, are investigated. In each example, the magnetic field distribution, magnetic energy, or magnetic force, along with computational time, of actual EPM heterogeneous structures are compared with those of equivalent structures having homogeneous effective B-H curve. These comparisons confirm the accuracy and computational efficiency of the developed numerical homogenization model.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"271-282"},"PeriodicalIF":1.8,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367021","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 simulation of carrier transport in power electronic devices imposes stringent requirements on numerical stability, confining the previous methods to low-order schemes. To address this issue, a stabilized higher-order hybridized discontinuous Galerkin method (S-HDG) is proposed, where we decouple the exponentially varying carrier density from the differential operator and project it onto a lower-dimensional equation. Based on the numerical jumps as indicator, an adaptive artificial diffusion term is introduced to dynamically control oscillatory errors and over diffusion during the iterations for solving nonlinear equations. We validate the proposed method to abrupt junction models, demonstrating its high-order accuracy and robustness against severe mesh skewness and curvature. Furthermore, we apply the method to lateral double-diffused MOSFET (LDMOS), a class of typical power electronic devices, achieving good agreement with the industrial-standard FVSG solver in simulating electrical parameters. Notably, our method can offer higher-order convergence and better compatibility with unstructured meshes.
{"title":"A Higher-Order Stabilized Hybridized Discontinuous Galerkin Method for Simulating Semiconductor Devices","authors":"Nian-En Zhang;Dongyan Zhao;Haoqiang Feng;Yin-Da Wang;Yanning Chen;Qi-Chao Wang;Zheng-Wei Du;Yingzong Liang;Fang Liu;Hao Xie;Qiwei Zhan;Wen-Yan Yin","doi":"10.1109/JMMCT.2025.3575845","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3575845","url":null,"abstract":"The simulation of carrier transport in power electronic devices imposes stringent requirements on numerical stability, confining the previous methods to low-order schemes. To address this issue, a stabilized higher-order hybridized discontinuous Galerkin method (S-HDG) is proposed, where we decouple the exponentially varying carrier density from the differential operator and project it onto a lower-dimensional equation. Based on the numerical jumps as indicator, an adaptive artificial diffusion term is introduced to dynamically control oscillatory errors and over diffusion during the iterations for solving nonlinear equations. We validate the proposed method to abrupt junction models, demonstrating its high-order accuracy and robustness against severe mesh skewness and curvature. Furthermore, we apply the method to lateral double-diffused MOSFET (LDMOS), a class of typical power electronic devices, achieving good agreement with the industrial-standard FVSG solver in simulating electrical parameters. Notably, our method can offer higher-order convergence and better compatibility with unstructured meshes.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"283-294"},"PeriodicalIF":1.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524412","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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