ACES Publication Search
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| Title: | ACES Journal January 2025 Cover |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 1967 KB |
| Title: | ACES Journal January 2025 Front/Back Matter |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 254 KB |
| Title: | ACES Journal January 2025 Full |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 16150 KB |
| Title: | Semantic Segmentation on FDFD-generated Wideband Radar Images of Potential Shooters |
| Abstract: | This paper presents a deep learning model for fast and accurate radar detection and pixel-level localization of large concealed metallic weapons on pedestrians walking along a sidewalk. The considered radar is stationary, with a multi-beam antenna operating at 30 GHz with 6 GHz bandwidth. A large modeled data set has been generated by running 2155 2D-FDFD simulations of torso cross sections of persons walking toward the radar in various scenarios. |
| Author(s): | M. Asri, A. Morgenthaler, C. M. Rappaport |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 2896 KB |
| Title: | An Electromagnetic Scattering Mechanism Recognition Method Based on Deep Learning |
| Abstract: | In this paper, we proposed a data-driven deep learning (DL) method to recognize various electromagnetic (EM) scattering mechanisms. With appropriate training data containing different EM scattering mechanisms, the proposed network can accurately recognize the EM scattering mechanisms of complex models. Numerical experiments show that the DL network architecture is effective for both vertical polarization and horizontal polarization scattered field, and the average relative recognition error of the proposed method is less than 5%. This paper shows that deep neural networks have a good learning capacity for EM scattering mechanism recognition. This provides a research strategy for solving EM scattering mechanism identification in more complex EM environments. |
| Author(s): | X. Liu, K. Zheng, J. Li |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 1654 KB |
| Title: | Zigzag Antenna Design Based on Machine Learning |
| Abstract: | In this paper, we propose the design of a zigzag antenna using machine learning (ML) techniques. We trained the deep neural network that was to be employed for the ML model using training data, after which we evaluated the maturity of the trained model using mean squared error and R-squared metrics. Next, we utilized random search in conjunction with the trained model to derive a design of the optimal zigzag antenna having good impedance matching characteristics.We then validated the applicability of the ML techniques in antenna design based on the agreement between measured and simulated reflection coefficients. |
| Author(s): | J. Y. Park, J. Choo |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 856 KB |
| Title: | Miniaturized Flat Archimedean Spiral Antenna |
| Abstract: | This paper presents the design and tests of a miniaturized flat Archimedean spiral antenna. The antenna has two gold Archimedean spiral arms on the surface of a thick alumina cylinder. This cylindrical substrate has an outer diameter of 1.1 mm and a thickness of 0.52 mm. These reduced dimensions make the presented antenna at least an order of magnitude smaller than any previous planar Archimedean spiral antenna reported in the literature. This small antenna can be used for communication in small devices, wireless power transmission for implantable sensors, microrobots and other micro applications. Despite its reduced size, the antenna has a relatively low resonant frequency, which was measured at 4.9 GHz. The characteristic length of the antenna can be reported as only 0.018λ. The design and simulations of the fundamental parameters of the antenna are presented, showing a uniform radiation pattern. Also, the manufacturing process is described. Seven prototypes of the antenna have been manufactured and their reflection coefficient was measured. The tests showed good agreement with simulations. The repeatability of the measurements and the reliability of the fabrication process are demonstrated. |
| Author(s): | M. Fernandez-Munoz, N. Munoz-Mateos, R. Sanchez-Montero, P. L. Lopez-Espi, J. A. Martinez-Rojas, E. Diez-Jimenez |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 3241 KB |
| Title: | Convolutional Neural Networks Aided Reinforcement Learning for Accelerated Optimization of Antenna Topology |
| Abstract: | A machine learning (ML) framework is proposed to achieve the automatic and rapid optimization of antenna topologies. A convolutional neural network (CNN) is utilized as a surrogate model (SM) and is combined with reinforcement learning (RL) algorithms. Specifically, the RL agent interacts with simulation software to learn. Data accumulated from electromagnetic (EM) simulations are used to train the SM. The CNNbased SM predicts antenna performance based on the topology of the antenna. Subsequently, the SM replaces EM simulations within the RL training environment. The RL agent interacts with the CNN-based SM to search for the optimal topology. This approach significantly reduces dependence on time-consuming EM simulations. To validate the effectiveness of the optimization method, a center-fed microstrip patch antenna is optimized. Simulation results demonstrate that, compared to other optimization methods, impedance bandwidth is improved, while the number of simulation samples and optimization time are significantly reduced. |
| Author(s): | J. Dou, H. Gong, S. Wei, H. Chen, Y. Chen, T. Shen, J. Song |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 1964 KB |
| Title: | Accurate Measurement of Wake Height Caused by Target Motion using Millimeter-wave Radar |
| Abstract: | This study explores the feasibility of using millimeter-wave radar to observe ship wake wave heights on the water surface and proposes an accurate measurement method based on Frequency-Modulated Continuous Wave (FMCW) radar to detect water surface elevation changes caused by ship motion. By acquiring electromagnetic echo signals from the water surface using millimeter-wave radar and applying interference principles, high-precision measurements of water surface elevation changes are achieved. We conducted numerical simulations of the ship wake using computational fluid dynamics (CFD) based on an actual ship model and performed wake wave height measurements using high-resolution radar parameters. By comparing the radar measurement data with those from a capacitive wave height meter, the effectiveness of the AWR2243 FMCW millimeter-wave radar in measuring wake wave heights induced by ship motion was validated. Timefrequency analysis of the wake wave height using wavelet transform indicated that the primary frequency of the wake diffusion wave generated by the experimental ship model’s movement was around 2 Hz. The experimental results demonstrate that FMCW millimeter-wave radar can achieve high-precision water surface wave height measurements. The radar’s application in oceanic target wake observation has great potential, providing new technical means for ship monitoring, marine scientific research, and ocean environmental monitoring. |
| Author(s): | Y. Jia, Y. Gong, L. Zhai, Y. Liu, X. Zhang |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 18500 KB |
| Title: | Investigating the Distribution of Induced Electric Field Generated by Double Square Semicircle Coil in Transcranial Magnetic Stimulation |
| Abstract: | Transcranial magnetic stimulation (TMS) is a physical technique that modulates the human brain nervous system and can be used as a non-invasive treatment for neurological diseases. To address the problem of poor focusing performance of TMS coils, this study first designs a new coil geometry, Double Square Semicircle (DSS) coil, based on traditional coil stimulation characteristics. Second, this study uses the Sim4Life finite element simulation software to compare the stimulation characteristics of DSS coil and six traditional coils under the head model, proving that the induced electric field generated by DSS coil has high-focusing performance. Third, this paper explores the effects of four physical parameters - the distance between the human brain model and the coil, different stimulation directions, coil size and coil bending angle - on the spatial distribution of the induced electric field. After the above simulation experiments, the optimal design scheme of DSS coil is found. Experimental results show that, compared with several traditional coils, the focusing effect can be improved by up to 77.49%, proving that DSS is a highfocusing performance TMS coil, which is suitable for future TMS high-precision treatment needs. |
| Author(s): | Y. Wang, Z. Li, J. Li, H. Zhang, E. Gong, L. Shi |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 1974 KB |
| Title: | Comparison of an Induction Switched Reluctance Machine with an Interior Permanent Magnet Machine using Finite Element Method |
| Abstract: | An induction switched reluctance machine (ISRM) is a novel electrical machine which benefits from high torque and power density. The innovation is based on optimization of the flux path in the machine, using short circuit windings on the rotor. This leads to a high-grade electromechanical energy conversion process, higher torque density compared to other electrical machines, short flux path, and low core loss. ISRM offers superior performance in terms of higher torque density and can be applied to a broad range of applications, including electric, hybrid electric, and plug-in hybrid vehicles (EV/HEV/PHEV). In this paper, a 12/10 ISRM is presented. The model of the machine was simulated using the finite element (FE) method, and the results are compared with an interior permanent magnet machine (IPM) which has been designed for EV application. The results of our investigations indicate that the proposed geometry offers superior performance in terms of higher torque and efficiency. |
| Author(s): | M. Daneshi, M. Abbasian, M. Delshad |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 1513 KB |
| Title: | Magnetic Field Analysis of Trapezoidal Halbach Permanent Magnet Linear Synchronous Motor Based on Improved Equivalent Surface Current Method |
| Abstract: | This paper proposes an improved analytical method to calculate the two-dimensional air gap magnetic field (AGMF) of the permanent magnet array in trapezoidal Halbach permanent magnet linear synchronous motors. The influence of the trapezoidal magnet bottom angle a, equivalent width coefficient aw, height coefficient ah and air gap height coefficient ag on the amplitude and harmonic distortion rate of the air gap central magnetic field is analyzed. Based on the equivalent surface current method (ESCM), an improved equivalent algorithm based on trapezoidal side length is proposed for the trapezoidal Halbach permanent magnet array (THPMA). The equivalent analytical formula of two-dimensional air gap flux density is derived and verified by the finite element method (FEM). Results show that the improved equivalent surface current method (IESCM) is convenient and accurate and is suitable for magnetic field calculation of irregular magnetic poles with arbitrary section shape. Analysis shows that, compared with a rectangular magnet, when the bottom angle a of the magnet is greater than 90°, AGMF can obtain the maximum peak value of magnetic flux density (Bpeak) and the minimum total harmonics distortion of magnetic flux density (THDB). |
| Author(s): | B. Li, J. Zhang, X. Zhao, Z. Miao, H. Dong, H. Li |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 2017 KB |
| Title: | 3-D Analytical Predictions of Surface-inset Axial Flux Machines with Different Halbach Arrangements |
| Abstract: | A three-dimensional (3-D) analytical model with a high computational efficiency is proposed for a surface-inset axial flux machine (SIAFM). Accounting for the air-gap fringing field, the proposed 3-D analytical model is used to compute the magnetic field in the SIAFMs with conventional, Hat- and T-shaped Halbach arrangements. Based on the linear superposition method, the 3-D scalar potential equations for different regions with boundary condition equations are obtained. On this basis, the air-gap magnetic field and electromagnetic parameters can be derived. To demonstrate the advantages, the optimization performance of the Tshaped Halbach machine model is compared with that of conventional and Hat-shaped Halbach machine models. The prediction indicates that the optimized T-shaped Halbach machine model has the greatest electromagnetic torque. Finally, a 3-D finite element analysis (FEA) validates the 3-D analytical predictions. |
| Author(s): | Y. Ni, C. Liu, B. Xiao, Y. Lin |
| File Type: | Journal Paper |
| Issue: | Volume: 40 Number: 1 Year: 2025 |
| Download Link: | Click here to download PDF File Size: 1296 KB |