IEEE Journal on Multiscale and Multiphysics Computational Techniques最新文献

Numerical Homogenization for Nonlinear Multiscale Analysis of Electropermanent Magnet Composites 电永磁复合材料非线性多尺度分析的数值均匀化

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2025-06-13 DOI: 10.1109/JMMCT.2025.3579349

Dohun Lee;Ahmad Ramadoni;Jaewook Lee

{"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}

引用次数: 0

Topological Optimization Framework for the Automated Design of 3D Printable THz Lens Antennas 3D可打印太赫兹透镜天线自动化设计的拓扑优化框架

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2025-04-07 DOI: 10.1109/JMMCT.2025.3558662

Nikolas Hadjiantoni;Dou Feng;Miguel Navarro-Cía;Stephen M. Hanham

{"title":"Topological Optimization Framework for the Automated Design of 3D Printable THz Lens Antennas","authors":"Nikolas Hadjiantoni;Dou Feng;Miguel Navarro-Cía;Stephen M. Hanham","doi":"10.1109/JMMCT.2025.3558662","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3558662","url":null,"abstract":"Electromagnetic topological optimization holds the promise of the fully automated design of electromagnetic structures such as antennas, waveguides, metasurfaces and metamaterials; however, it often yields designs that are incompatible with fabrication processes. In this work, we describe a topological optimization framework that combines structural finite element analysis and electromagnetic finite-difference time-domain simulation to realize fabricable structures which meet specified electromagnetic design objectives. As a demonstration, the framework is applied towards the design of G-band low-profile leaky lens antennas suitable for future 6G communication applications. The 5<inline-formula><tex-math>$lambda _{0}$</tex-math></inline-formula> radius, 2<inline-formula><tex-math>$lambda _{0}$</tex-math></inline-formula> thick leaky lens antenna is compatible with stereolithography 3D printing and displays a realized gain of 23 dBi at 0.2 THz with a low side-lobe level of −20 dB. We foresee the proposed framework being applicable to a wide range of electromagnetic design problems intended for fabrication using additive manufacturing techniques.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"218-226"},"PeriodicalIF":1.8,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900506","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}

引用次数: 0

GPU Accelerated Matrix Solution Using Novel Preconditioner for Three Dimensional Laguerre-FDTD Method 基于新型前置条件的三维Laguerre-FDTD GPU加速矩阵求解

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2025-03-22 DOI: 10.1109/JMMCT.2025.3572490

Yifan Wang;Yiliang Guo;Joshua Corsello;Madhavan Swaminathan

{"title":"GPU Accelerated Matrix Solution Using Novel Preconditioner for Three Dimensional Laguerre-FDTD Method","authors":"Yifan Wang;Yiliang Guo;Joshua Corsello;Madhavan Swaminathan","doi":"10.1109/JMMCT.2025.3572490","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3572490","url":null,"abstract":"Conventionally, the large sparse matrix equation (<inline-formula><tex-math>$Ax=b$</tex-math></inline-formula>) generated by the Laguerre-FDTD method is computed using direct matrix solvers, which is often numerically expensive and computationally slow. In this work, we demonstrate an innovative approach to replace direct matrix solver with an iterative algorithm for the Laguerre-FDTD method. A novel preconditioner, specifically targeted to improve the convergence rate of biconjugate gradient stabilized solver (BiCGSTAB), is derived and implemented in the Laguerre-FDTD method. Compared with the classical Jacobi preconditioner, the proposed preconditioner achieves on average an improvement of more than 1.3× in the convergence rate. To further leverage the computational efficiency, a modified sparse matrix-vector multiplication algorithm is proposed and implemented using a General-Purpose Graphics Processing Unit (GPGPU). The new algorithm ensures that all computations are performed within the GPU, with minimum number of device-to-host data transfer and global memory access. With GPU's accelerated computing capability, the proposed solver achieves more than 5× computational speed up with respect to a high performance CPU-based direct solver on average. In addition, due to the intrinsic memory efficient nature of iterative solver, our approach also shows maximally more than 31× reduction in memory consumption against the direct solver. Various numerical examples are simulated to validate the capability and improvement of the proposed method.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"259-270"},"PeriodicalIF":1.8,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144213617","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}

引用次数: 0

End-to-End Differentiable RCS Optimization on 3D Geometry Based on Physical Optics Method 基于物理光学方法的三维几何端到端可微RCS优化

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2025-03-12 DOI: 10.1109/JMMCT.2025.3569766

Rui Fang;Yu Mao Wu;Hongxia Ye

{"title":"End-to-End Differentiable RCS Optimization on 3D Geometry Based on Physical Optics Method","authors":"Rui Fang;Yu Mao Wu;Hongxia Ye","doi":"10.1109/JMMCT.2025.3569766","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3569766","url":null,"abstract":"The optimization of radar cross section (RCS) is now a significant issue in the designation of military and civilian equipment. Comparing with the expensive material approaches, changing the geometry of an object is a relatively flexible and low-cost way. However, the RCS optimization of large-scale models often faces two major problems: too large optimization space and slow RCS calculation, which caused by increasing geometry parameters and iterative numerical computation, respectively. In addition, secondary problems such as geometric information loss and RCS results lacking of gaurantees always remain even if dimensionality reduction has been carried out for alleviating these two problems. In this paper, we propose a novel end-to-end differentiable RCS optimization framework based on the physical optics (PO) method. The proposed framework utilize the differentiability of the PO method, and realize an efficient and interpretable RCS optimization without dimension reduction. The innovation of this paper lies in the combination of PO method and gradient-based optimization to achieve RCS optimization of large-scale complex 3D geometries. Experiments show that in ordinary 2D scenarios, our method achieves at least 16 times higher efficiency than the mainstream optimization method. Meanwhile, the optimization error of RCS has been reduced by 75.29<inline-formula><tex-math>$%$</tex-math></inline-formula> compared to traditional methods (0.0515vs. 0.2084). We further validate the performance of the framework on more complex tasks such as 3D plane model and analyzed the effectiveness of the overall framework. The proposed optimization method is expected to be widely used in applications such as stealth and aircraft designs.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"246-258"},"PeriodicalIF":1.8,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144196910","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}

引用次数: 0

Fast Well-Conditioned Volume Integral Equation Solver for Analyzing Nonlocal Optical Responses in Quantum Nanostructures 量子纳米结构非局域光响应分析的快速良条件体积积分方程求解器

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2025-03-11 DOI: 10.1109/JMMCT.2025.3550117

Runwei Zhou;Dan Jiao

{"title":"Fast Well-Conditioned Volume Integral Equation Solver for Analyzing Nonlocal Optical Responses in Quantum Nanostructures","authors":"Runwei Zhou;Dan Jiao","doi":"10.1109/JMMCT.2025.3550117","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3550117","url":null,"abstract":"Solid-state spin qubits are one of the candidate platforms for future quantum computers due to their long coherence time and good controllability. However, qubits are susceptible to noise generated from external magnetic fields. In this paper, we present a fast and accurate volume integral equation solver for analyzing local/nonlocal optical responses in quantum nano-electromagnetic gate circuitry. Due to small electric sizes of quantum circuitry, conventional volume integral equation (VIE) solvers suffer from both numerical difficulties and deteriorated accuracy since the underlying numerical system is highly ill-conditioned. To overcome this problem, we introduce a well-conditioned VIE formulation. We further accelerate the VIE solution by transforming the six-dimensional integral arising from the nonlocal constitutive relation to the spectral domain using fast Fourier transform (FFT). The same FFT is also applied to efficiently compute the convolution of Green's function with equivalent volumetric currents. The resultant fast and robust VIE solver has been applied to analyze large-scale 3-D quantum gate devices. Both local and nonlocal optical responses of the devices are captured accurately and efficiently. This work offers a fast and accurate approach to guide the noise control of high-fidelity quantum gate circuitry design.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"209-217"},"PeriodicalIF":1.8,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143761369","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}

引用次数: 0

Internal Loss Analysis and Visualization of 4H-Silicon Carbide Power Diodes: Free Energy Loss Analysis Under the Static Condition 4h -碳化硅功率二极管内部损耗分析与可视化：静态条件下的自由能损耗分析

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2025-03-05 DOI: 10.1109/JMMCT.2025.3567252

Takaya Sugiura

{"title":"Internal Loss Analysis and Visualization of 4H-Silicon Carbide Power Diodes: Free Energy Loss Analysis Under the Static Condition","authors":"Takaya Sugiura","doi":"10.1109/JMMCT.2025.3567252","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3567252","url":null,"abstract":"Loss visualization and analysis of 4H-silicon carbide (4H-SiC) power diodes were performed using the free energy loss analysis (FELA) method that was originally developed for photovoltaic cells. The FELA approach features several advantages, including the direct expression of loss in W/cm<inline-formula><tex-math>$^{2}$</tex-math></inline-formula>, representation of each electron- and hole-induced loss, and internal loss visualization by calculating the free energy at each point. Four 4H-SiC power diodes, including two PiN diodes, a Schottky barrier diode (SBD), and a junction-barrier Schottky diode (JBSD), were evaluated. The PiN diodes exhibited significant Joule losses owing to the inherently high recombination heating associated with these bipolar devices. In contrast, the SBD e<inline-formula><tex-math>$^-$</tex-math></inline-formula>-induced Joule loss, whereas h<inline-formula><tex-math>$^+$</tex-math></inline-formula>-induced Joule and recombination losses were negligible for this unipolar device. The JBSD exhibited <bold>a high allowable current density with</b> low self-heating and was determined to be the best power diode. The FELA visualization of the e<inline-formula><tex-math>$^-$</tex-math></inline-formula>-induced Joule loss of this device revealed that the SBD interface, particularly the p<inline-formula><tex-math>$^+$</tex-math></inline-formula>-region, is the dominant source of Joule loss. Applying FELA to reversed characteristics revealed several insightful device phenomena and which physics were responsible for the loss in different situations.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"227-234"},"PeriodicalIF":1.8,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949153","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}

引用次数: 0

Optimal Preconditioners for Hybrid Direct-Iterative $mathcal {H}$-Matrix Solvers in Boundary Element Methods 边界元法中$mathcal {H}$-矩阵混合直接迭代解的最优预条件

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2025-03-04 DOI: 10.1109/JMMCT.2025.3547827

Omid Babazadeh;Emrah Sever;Jin Hu;Ian Jeffrey;Constantine Sideris;Vladimir Okhmatovski

{"title":"Optimal Preconditioners for Hybrid Direct-Iterative $mathcal {H}$-Matrix Solvers in Boundary Element Methods","authors":"Omid Babazadeh;Emrah Sever;Jin Hu;Ian Jeffrey;Constantine Sideris;Vladimir Okhmatovski","doi":"10.1109/JMMCT.2025.3547827","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3547827","url":null,"abstract":"The paper proposes a new approach to the fast solution of matrix equations resulting from boundary element discretization of integral equations. By hybridizing fast iterative <inline-formula><tex-math>$mathcal {H}$</tex-math></inline-formula>-matrix solvers with a fast direct <inline-formula><tex-math>$mathcal {H}$</tex-math></inline-formula>-matrix preconditioner factorization, we create a framework that can be tuned between the extremes of a direct solver and a unpreconditioned iterative solver. This tuning is largely achieved using a single numerical parameter representing the preconditioner tolerance. A more complicated scheme involving two different tolerances is also briefly considered. The proposed framework is demonstrated on a high-order accurate Locally Corrected Nyström solution of surface integral equations for PEC targets. Examples consider various scattering problems including those featuring strong physical resonances. We show that appropriately choosing the preconditioner tolerance achieves the prescribed solution accuracy with minimal CPU time. Expanding from one to two tolerance parameters further enhances the framework by providing the flexibility to dynamically adjust tolerance, enabling higher compression while maintaining accuracy and fast convergence. This adaptive strategy offers significant potential for optimizing the balance between memory usage and CPU time in the future.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"187-197"},"PeriodicalIF":1.8,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143698349","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}

引用次数: 0

Fast Domain Decomposition Algorithm Using Barycentric Interpolation and Overlapping Subdomains for 3D Multiscale Problems 针对三维多尺度问题使用巴里中心插值和重叠子域的快速域分解算法

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2025-03-04 DOI: 10.1109/JMMCT.2025.3547852

Nils Kielian;Marcus Stiemer

引用次数: 0

One-Stage $ O(N log N)$ Algorithm for Generating Nested Rank-Minimized Representation of Electrically Large Volume Integral Equations 一阶$ O(N log N)$生成电大体积积分方程嵌套秩最小化表示的算法

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2025-02-20 DOI: 10.1109/JMMCT.2025.3544143

Yifan Wang;Dan Jiao

引用次数: 0

Rapid Multi-Objective Antenna Synthesis via Deep Neural Network Surrogate-Driven Evolutionary Optimization 通过深度神经网络替代驱动的进化优化实现快速多目标天线合成

IF 1.8

IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2025-02-20 DOI: 10.1109/JMMCT.2025.3544270

Praveen Singh;Soumyashree S. Panda;Jogesh C. Dash;Bright Riscob;Surya K. Pathak;Ravi S. Hegde

{"title":"Rapid Multi-Objective Antenna Synthesis via Deep Neural Network Surrogate-Driven Evolutionary Optimization","authors":"Praveen Singh;Soumyashree S. Panda;Jogesh C. Dash;Bright Riscob;Surya K. Pathak;Ravi S. Hegde","doi":"10.1109/JMMCT.2025.3544270","DOIUrl":"https://doi.org/10.1109/JMMCT.2025.3544270","url":null,"abstract":"Antenna synthesis is becoming increasingly challenging with tight requirements for C-SWAP (cost, size, weight and power) reduction while maintaining stringent electromagnetic performance specifications. While machine learning approaches are increasingly being explored for antenna synthesis, they are still not capable of handling large shape sets with diverse responses. We propose a branched deep convolutional neural network architecture that can serve as a drop-in replacement for a full-wave simulator (it can predict the full spectral response of reflection co-efficient, input impedance and radiation pattern). We show the utility of such models in surrogate-assisted evolutionary optimization for antenna synthesis with arbitrary specification of targeted response. Specifically, we consider the large shape set defined by the set of 16-vertexes polygonal patch antennas and consider antenna synthesis by specifying independent constraints on return loss, radiation pattern and gain. In contrast to online surrogates, our approach is an offline surrogate that is objective-agnostic; trained once, it can be used over multiple optimizations whereby the model training costs become amortized across multiple synthesis requests. Our approach outperforms evolutionary optimizations relying on full-wave solver-based fitness estimation. Specifically, we report the design, fabrication and experimental characterization of three polygon-shaped patch antennas, each fulfilling different objectives (narrow band, dual-band & wide-band). The reported methodology enables rapid synthesis (in seconds), produces verifiable sound designs and is promising for furthering data-driven design methodologies for electromagnetic wave device synthesis.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"10 ","pages":"151-159"},"PeriodicalIF":1.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594292","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}

引用次数: 0