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International Conference on the Computation of Electromagnetic Fields (COMPUMAG)

作者： Yusuke Sakamoto Yihao Xu Bingnan Wang Tatsuya Yamamoto Yuki Nishimura Mitsubishi Electric Research Laboratories Cambridge MA USA Advanced Technology R&D Center Mitsubishi Electric Corporation Amagasaki Hyogo Japan Mechanical and Industrial Engineering Northeastern University Boston MA USA

This paper proposes a surrogate model for the rapid evaluation of electric machine designs, based on a neural network combined with a semi-analytical subdomain model. Although both physical-based analytical approaches and data-driven approaches have been proposed to construct surrogate models, which can be significantly faster than numerical finite-element simulations, issues still remain. On one hand, simplifications in analytical approaches often cause inaccuracy, especially in the prediction of highly nonlinear phenomena such as cogging torque of permanent magnet synchronous motors; on the other hand, data-driven approaches often require a large amount of training data to achieve high accuracy. In our proposed method, the performance of the electric machine is initially approximated by using a semi-analytical subdomain method, and this initial prediction is used as an input of a neural network, together with other design variables, to obtain the final prediction. We test the method to predict the cogging torque of surface-mounted permanent magnet motors. With this physics-assisted neural network (PANN) approach, we can predict cogging torque with good accuracy, which cannot be achieved with only physical-based model; the prediction accuracy is also much improved compared with conventional neural networks, especially when the size of the training dataset is small.

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Tandem Neural Networks for Electric Machine Inverse design

Tandem Neural Networks for Electric Machine Inverse Design

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IEEE International Conference on Electric Machines and drives (IEMdC)

作者： Yihao Xu Bingnan Wang Yusuke Sakamoto Tatsuya Yamamoto Yuki Nishimura Toshiaki Koike-Akino Ye Wang Mechanical and Industrial Engineering Northeastern University Boston MA USA Mitsubishi Electric Research Laboratories (MERL) Cambridge MA USA Advanced Technology R&D Center Mitsubishi Electric Corporation Amagasaki Japan

In electric motor design tasks, multiple design goals often need to be placed on a single motor, and multi-objective optimization plays a significant role. Trade-offs and Pareto front searching are needed, as these design goals or responses cannot be optimized concurrently due to their interdependent nature. However, tuning the motor parameters in the iterative optimization process is typically ineffective and heavily dependent on the expertise of the engineers due to the large number of time-consuming finite-element simulations required to evaluate each motor design candidate. In this paper, we propose an inverse design approach for electric machines based on a tandem neural network, which can effectively provide desired motor design candidates for various design targets without iteration. The one-to-many mapping problem can be avoided by the tandem neural network, which constructs loss functions based on the responses of the generated motor designs. The proposed intelligent design strategy is generally applicable for the design tasks of different types of electric motors.

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Compact, Hybrid Slot-dipole-Monopole Wi-Fi 7 Antenna for Slim-Bezel Notebook Applications

Compact, Hybrid Slot-Dipole-Monopole Wi-Fi 7 Antenna for Sli...

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Asia-Pacific Conference on Microwave

作者： M. Idrees Magray Saou-Wen Su Jui-Han Lu Antenna Design Department Advanced EM & Wireless Comm R&D Center ASUSTek Computer Inc Taipei Taiwan Department of Electronic Communication Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan

A hybrid slot-dipole-monopole antenna is demonstrated that is suitable for Wi-Fi 7 notebook applications. The design consists of an open slot, a coupled strip resonator, and a T-shaped feed, created on the two layers of the substrate. The open slot is able to operate in the 2.4 GHz (2400-2484 MHz) wireless local area network (WLAN) band. The coupled strip resonator and the T-shape feed together generate two resonant dipole-monopole modes that cover the 5 GHz (5150-5825 MHz) and 6 GHz (5925-7125 MHz) WLAN bands respectively. The design is simple in structure and occupies a compact size of $4.6 \mathrm{~mm} \times 15 \mathrm{~mm}$ (approximately $0.037 \lambda \times 0.120 \lambda$ at 2.4 GHz), which can find practical applications in slim-bezel notebook computers.

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Multi-Objective Motor design Optimization with Physics-Assisted Neural Network Model

Multi-Objective Motor Design Optimization with Physics-Assis...

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IEEE International Conference on Electric Machines and drives (IEMdC)

作者： Yusuke Sakamoto Yihao Xu Bingnan Wang Tatsuya Yamamoto Yuki Nishimura Mitsubishi Electric Research Laboratories (MERL) Cambridge MA USA Mechanical and Industrial Engineering Northeastern University Boston MA USA Advanced Technology R&D Center Mitsubishi Electric Corporation Amagasaki Japan

Electric machine design optimization tasks typically require a large number of time-consuming simulations using finite-element analysis (FEA) to iteratively evaluate the design candidates. Various surrogate modeling techniques have been investigated in order to speed up the design optimization process. In recent years, machine learning based surrogate models are explored, due to their advantages including extraordinary capability in learning highly nonlinear functions. However, typical neural network based machine learning models require a large amount of training data and long training time. In this paper, we propose a multi-objective optimization (MOO) scheme for electric machine design, using a physics-assisted neural network (PANN) as surrogate model. In the PANN method, a semi-analytical subdomain physics model is used to estimate the performance of the electric machine, and this calculated result is used as the input of a neural network, in addition to other design parameters. We show that PANN can achieve the same accuracy with significantly less training data, as compared with neural networks relying solely on data. The hybrid model also shows improved accuracy with the subdomain based physics model alone. We apply the PANN surrogate model to speed up the electric machine MOO by replacing the iterative FEA based optimization process. The Pareto front solutions obtained by the proposed method are further validated with FEA with good accuracy.

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Cell-type continuous electromagnetic radiation system generating millimeter waves for active denial system applications

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defence technology（防务技术） 2022年第10期18卷 1895-1913页

作者： Sun-Hong Min Ohjoon Kwon Matlabjon Sattorov Seontae Kim In-Keun Baek Seunghyuk Park ranjan Kumar Barik Anirban Bera dongpyo Hong Seonmyeong Kim Bong Hwan Hong Chawon Park Sukhwal Ma Minho Kim Kyo Chul Lee Yong Jin Lee Han Byul Kwon Young Joon Yoo Sang Yoon Park Gun-Sik Park Korea Institute of Radiological and Medical Sciences(KIRAMS) Seoul01812South Korea Institute for Basic Science Center for Axion and Precision Physics ResearchDaejeon34141South Korea Center for THz-Driven Biomedical Systems Department of Physics and AstronomyCollege of Natural SciencesSeoul National UniversitySeoul08826South Korea Center for Applied Electromagnetic Research Advanced Institute of Convergence TechnologySuwonGyeonggi-do16229South Korea R&D Department Seoul-TeracomInc.Suwon16229South Korea Mechatronics R&D Center Samsung Electronics Co.Ltd.Hwasung18448South Korea Hanwha Corporation Gumi730-030South Korea Council of Scientific and Industrial Research Central Electronics Engineering Research InstitutePilani333031India Home Economics Education/Biosystems and Biomedical Sciences Korea UniversitySeoul02841South Korea Current affiliation of Seontae Kim:Young IN ACE 1 F60Anyangcheondong-roDongan-guAnyang-siGyeonggi-do14042South Korea.

The cell-type continuous electromagnetic radiation system is a demonstration device capable of generating high-power millimeter electromagnetic waves of a specific wavelength and observing their effects on living *** irradiates a biological sample placed in a 30×30×50 cm^(3)cell with electromagnetic waves in the 3.15-mm-wavelength region(with an output of≥1 W)and analyzes the temperature change of the sample.A vacuum electronic device-based coupled-cavity backward-wave oscillator converts the electron energy of the electron beam into radiofrequency(rF)energy and radiates it to the target through an antenna,increasing the temperature through the absorption of rF energy in the *** system causes pain and ultimately reduces combat power.A cell-type continuous electromagnetic radiation system consisting of four parts—an electromagnetic-wave generator,a highvoltage power supply,a test cell,and a system controller—generates an rF signal of≥1 W in a continuous waveform at a 95-GHz center frequency,as well as a chemical solution with a dielectric constant similar to that of the skin of a living *** increase of 5°C lasting approximately 10 s was confirmed through an experiment.

关键词： Millimeter waves Terahertz waves Coupled-cavity backward wave oscillator(CCBWO) Cell-type continuous electromagnetic radiation Active denial system(AdS) directed-energy weapon(dEW)

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Comparison of Learning-based Surrogate Models for Electric Motors

Comparison of Learning-based Surrogate Models for Electric M...

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International Conference on the Computation of Electromagnetic Fields (COMPUMAG)

作者： Yihao Xu Bingnan Wang Yusuke Sakamoto Tatsuya Yamamoto Yuki Nishimura Mitsubishi Electric Research Laboratories Cambridge MA USA Mechanical and Industrial Engineering Northeastern University Boston MA USA Advanced Technology R&D Center Mitsubishi Electric Corporation Amagasaki Hyogo Japan

Multi-objective optimization is frequently employed in electric motor design, where iterative numerical simulations are required to evaluate a large number of design candidates. A trial-and-error design methodology like this is very time-consuming. In this paper, we propose learning-based surrogate models that use trained deep neural networks (NNs) to accomplish the rapid evaluation of motor designs. A motor design candidate can be described with either a list of geometrical parameters of the motor design, or a colored image of the motor cross-section. different deep learning models can be constructed with either parameter-based input or image-based inputs. Our analysis reveals that deep convolutional neural networks (CNNs) utilizing image-based inputs exhibit a higher degree of predictive accuracy for more intricate responses, such as cogging torque, in comparison to models employing parameter-based inputs, albeit at the cost of increased training time.

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distributed Aperture Coherent Synthesis Method based on Two-stage Compensation

Distributed Aperture Coherent Synthesis Method based on Two-...

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Signal, Information and data Processing (ICSIdP), IEEE International Conference on

作者： Zhongwei Liu dongming Zhou rongrong Xiang Jie Chen Tianhang Wu Tianyu ding Xiaochuan Liu Hongwei Gao School of Electronic and Information Engineering Beihang University Beijing China Radar Research Lab School of Information and Electronics Beijing Institute of Technology Beijing China Department of Data Technology and Application Beijing Institute of Computer Technology and Application Beijing China Radar R&D Center Beijing Institute of Radio Measurement Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

To solve the problem that it is difficult to accurately estimate the coherent parameters of distributed aperture radar under the condition of low signal-to-noise ratio, a distributed coherent synthesis method based on two-stage compensation is proposed in this paper. This method utilizes prior information such as system layout, beam pointing, and inertial navigation station location to perform coarse alignment of echoes at the first stage in time, and then uses cross-correlation method to estimate coherent parameters of delay and phase within a small range, and perform precise compensation of time and phase at the second stage, so as to realize the coherent synthesis of multiple radar echoes. Experimental results show that the proposed method can effectively realize distributed coherent synthesis processing under low signal-to-noise ratio.

关键词： Accuracy Layout radar Inertial navigation Apertures data processing radar signal processing delays Signal to noise ratio

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Metamaterial-Inspired Antenna for Wi-Fi 7 Operation in Wireless Local Area Network Bands

Metamaterial-Inspired Antenna for Wi-Fi 7 Operation in Wirel...

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Asia-Pacific Conference on Microwave

作者： Saou-Wen Su M. Idrees Magray Jui-Han Lu Antenna Design Department Advanced EM & Wireless Comm R&D Center ASUSTek Computer Inc Taipei Taiwan Department of Electronic Communication Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan

A metamaterial-inspired antenna is proposed that utilizes an artificial mu-negative (MNG) transmission line (TL) to incorporate the zeroth-order resonance (ZOr) into WiFi 7 operation in the 2.4/5/6 GHz wireless local area network (WLAN) bands. The antenna comprises a meta-structured loop with periodically loaded series interdigital capacitors and a parasitic shorted strip, all formed on the same substrate layer in a coplanar structure. The 2.4 and 6 GHz WLAN bands are produced by the parasitic strip and the close-form loop strip, respectively, which are of typical right-handed antennas. The 5 GHz band caused by the ZOr mode, where the permeability is zero, can be adjusted by the series capacitance in the unit cell. The total antenna size is 5.4 mm $\times 19.6$ mm only. In this work, the design applied to notebook computers for the upcoming Wi-Fi 7 operation is also demonstrated. Both numerical and experimental results validate our proof-of-concept design.

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reliability-Based Sizing of Electric Propulsion System for Turboelectric Aircraft

Reliability-Based Sizing of Electric Propulsion System for T...

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Annual Conference of Industrial Electronics Society

作者： Yebin Wang Chung-Wei Lin Huazhen Fang Tomoki Takegami Mitsubishi Electric Research Laboratories Cambridge MA USA Department of Mechanical Engineering University of Kansas Lawrence KS USA Advanced Technology R&D Center Mitsubishi Electric Corporation Amagasaki City Japan

Aviation industry is moving towards more electric aircraft, where both non-propulsive and propulsive loads are electrified. While bringing in various benefits, electric propulsion system (EPS) introduces extra complexity and weight to aircraft, as well as raises the reliability concern. New design and analysis tools are required to size the EPS while meeting stringent reliability requirements. This paper investigates how to consolidate readability into the EPS sizing process and makes two-fold contributions. First, a probabilistic algorithm is proposed to assess the reliability of the EPS admitting a directed acyclic graph topology. The algorithm reduces the directed acyclic graph to a layered tree, which simplifies the calculation of joint probability of nodes in each layer. Second, we formulate the reliability-based EPS sizing as an integer nonlinear programming problem, where the reliability requirements are posed as constraints. Preliminary simulation validates the proposed method.

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Post-radiation effects of core pumped monolithic holmium-doped silica fibre lasers

Post-radiation effects of core pumped monolithic holmium-dop...

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Specialty Optical Fibres 2023

作者： Theodosiou, A. Koutsokeras, L. Ioannou, A. Stancalie, A. Negut, C.d. Aubrecht, J. Peterka, P. Constantinides, G. Kalli, K. Lumoscribe LTD Anthipoloxagou Georgiou M. Savva 12 Paphos8201 Cyprus Cyprus University of Technology Saripolou 33 Limassol3036 Cyprus Department of Mechanical Engineering and Materials Science and Engineering Cyprus University of Technology Limassol Cyprus National Institute for Laser Plasma and Radiation Physics Center for Advanced Laser Technology Măgurele077125 Romania "Horia Hulubei" National Institute for R&D in Physics and Nuclear Engineering 30 Reactorului St. MagureleRO-077125 Romania Institute of Photonics and Electronics The Czech Academy of Sciences Chaberska 57 182 51 Kobylisy 8 Prague Czech Republic

ISBN: (数字)9781510662674

ISBN: (纸本)9781510662667

We present our recent studies regarding the influence of ionized radiation when a monolithic Holmium fibre laser was exposed under a total dose of 350 Gy of γ-radiation. Since fibre lasers have many uses for space applications, it is important to study the robustness and the effects caused by ionized radiation. The optical fibre laser was characterized before and after the exposure using spectrum analysis and raman spectrometry while the variations were quantified. Moreover, the fibre laser response and the FBG mirrors' temperature response were analyzed. · © 2023 SPIE.

关键词： Fiber lasers

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