检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Xing, Yankai Zhang, Guangdou Wang, Baolu Li, Jian Bamisile, Olusola Huang, Qi University of Electronic Science and Technology of China Chengdu China China tobacco guangxi industrial CO. LTD. Guangxi China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China

The fast response and low inertia characteristics of converter-based generation (CBG) lead to a new stability issue that limits the development of renewable energy. The experimental tests validated in this paper confirm that although the grid-forming type converter (GFM) can improve the stability of CBG, the wideband oscillation problems are still risks within different Short-Circuit Ratio (SCR) conditions. This is due to the fact is that, there is no unified and effective way to setting the parameters in existence control strategy. The unsuitable selection of the output and input variable in linearized model of GFM converter leads to a failure of coefficients tuning which brings the instability to the system. In order to optimization parameters tuning process, a benchmark model is adopted in this paper, and the linearization model is updated by selecting suitable variables and detailed with considering the influence of resistance of the converter, etc. Based on this model, the stability margin related to the parameters of system is analyzed. Furthermore, based on this model, in order to consider more dynamics and make the converter controller focus on the topologies and scenarios which lack stabilitythemselves, the different grid scenarios are emulated to design a controller using Deep Reinforcement Learning (DRL) from offline to online to capture more dynamics. That is, the cascaded voltage and current control is tuned by Deep Deterministic Policy Gradient (DDPG) algorithm. Furthermore, the novel grid-forming control structure is proposed based on same algorithm. The validation tests indicate that the proposed strategy provides more essential for the power system stability in various grid conditions. © 2023, The Authors. All rights reserved.

关键词： Topology

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Analysis and Design of Finite Input Inductance Class-E Inverters with Variable Complex Loads

Analysis and Design of Finite Input Inductance Class-E Inver...

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IEEE Workshop on Computers in Power Electronics

作者： Yufei Wang Min Sun Dongsheng Cai Jian Li Qi Huang Siming Pan School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Institute of Electronic and Information Engineering of UESTC in Guangdong Dongguan China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Southwest University of Science and Technology Mianyang China

This paper presents a detailed analysis and design method of the Class-E inverter with finite input inductance under arbitrary complex loads based on the first harmonic approximation. The analytic results show that the inverter can achieve ZVS with a wide range of complex loads with proper resonant network design. The model established allows designers to plot the theoretical ZVS load impedance region for specific design parameters directly in the complex plane. Subsequently a design method for the inverter to achieve high efficiency operation under variable complex loads is developed. This method thus allows the Class-E inverter to be used in an application in which the load resistance varies as well as the reactance. The effectiveness of the proposed method is verified by a 13.56 MHz Class-E inverter prototype.

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Review of Radon and Its Progeny Measurement technology in Environmental Gamma Measurement 1

Review of Radon and Its Progeny Measurement Technology in En...

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1st International Conference on Physics and engineering Mathematics, ICPEM 2020

作者： Zeng, Chenhao Zhou, Jinge Lai, Wanchang Feng, Xiaojie Chen, Jiehao Yu, Yongping College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu Sichuan610059 China Dept. of Military Installation Army Logistical University of PLA Chongqing401311 China

The contribution of radon and its progeny to environmental gamma dose should not be ignored. In recent years, a large number of scholars all over the world have studied the migration behavior of radon and its progeny in the environment, and analyzed their impact on environmental gamma dose. Especially in uranium (thorium) bearing mining areas and other special areas, the influence of radon and its progeny is more prominent, which poses an important challenge to radiation monitoring. This paper summarizes the analysis and processing technology of radon and its progeny in environmental gamma monitoring, and puts forward the research trend and development direction of radon and its progeny analysis technology. © Published under licence by IOP Publishing Ltd.

关键词： Radon

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Charging Properties and Particle Dynamics of Chang’e-5 Lunar Sample in an External Electric Field

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engineering 2024年第11期42卷 267-277页

作者： Junping Gu Xiaoyu Qian Yiwei Liu Qinggong Wang Yiyang Zhang Xuan Ruan Xiangjin Deng Yaowen Lu Jian Song Hui Zhang Yunning Dong Mengmeng Wei Wei Yao Shuiqing Li Weihua Wang Zhigang Zou Mengfei Yang Qian Xuesen Laboratory of Space Technology China Academy of Space TechnologyBeijing 100094China Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Energy and Power EngineeringTsinghua UniversityBeijing 100084China Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education Institute of Nuclear and New Energy TechnologyTsinghua UniversityBeijing 100084China Beijing Institute of Spacecraft System Engineering Beijing 100094China Beijing Orient Institute of Measurement and Test Beijing 100086China Institute of Physics Chinese Academy of SciencesBeijing 100190China College of Engineering and Applied Sciences Nanjing UniversityNanjing 210093China China Academy of Space Technology Beijing 100094China

Facing the challenges of in-situ utilization of lunar regolith resources,applying an external electric field to manipulate lunar particles has become a promising method for space particle control,which mainly depends on the particle charging properties in the applied electric *** the surficial lunar regolith samples brought back from the Moon by the Chang’e-5 mission(CE5 LS),this work successively studied their charging properties,particle dynamics,and their collision damages to aerospace materials under the action of an external electric field in high-vacuum *** results indicated that the charging pro-cess and electrostatic projection of lunar regolith particles under high-vacuum conditions were different from those under atmosphere *** particle diameter range of CE5 LS used in the experiment is 27.7-139.0 *** electric field strength of 3-12 kV·cm^(-1),the charge obtained by CE5 LS is 4.8×10^(-15)-4.7×10^(-13) C and the charge-to-mass ratio is 1.2×10^(-5)-6.8×10^(-4) C·kg^(-1).The CE5 LS is easier to be negatively charged in an external electric ***,significant damages were observed on the target impact surfaces,indicating severe influences of lunar regolith particles on aerospace *** work contributes to a more comprehensive understanding of physical mechanisms controlling the lunar regolith shielding and utilization,and will inspire broad efforts to develop the lunar in-situ engi-neering solutions.

关键词： Chang’e-5 lunar regolith sample Charging properties External electric field Particle dynamics Particle collision

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Nuclide Number Density Prediction in the Lattice Physics Calculation Based on Dynamic Mode Decomposition

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SSRN 2024年

作者： Qin, Shuai Zhang, Qian Zhang, Yunfei Xue, Pengchao Li, Zhuo Laboratory for Advanced Nuclear Energy Theory and Applications Zhejiang Institute of Modern Physics Department of Physics Zhejiang University Zhejiang Hangzhou310027 China Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai201800 China Fundamental Science on Nuclear Safety and Simulation Technology Laboratory College of Nuclear Science and Technology Harbin Engineering University Heilongjiang Harbin150001 China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-sen University Zhuhai519082 China

Burnup analysis in nuclear reactors requires iterative computation of neutron transport and fuel depletion, which is computationally intensive, particularly for large-scale scenarios. This study introduces an innovative approach leveraging the Dynamic Mode Decomposition (DMD) algorithm to predict the temporal evolution of nuclide densities. By identifying and utilizing the DMD modes and eigenvalues from snapshots of nuclide density, this method aims to alleviate the computational demands of the coupled transport and burnup calculations. Firstly, the methodology selects the key reactivity-contributing nuclides to evaluate the correlation between the complexity of the reduced-order model and the precision of predictions. Subsequently, an optimized reduced-order model is employed for forecasting nuclide densities in a pin cell. In most cases, DMD predicts more accurately than traditional quadratic extrapolation methods. Moreover, the DMD algorithm demonstrates commendable accuracy in predicting the nuclide density distribution within a PWR fuel assembly, suggesting its promising potential for reactor burnup analysis applications. © 2024, The Authors. All rights reserved.

关键词： Dynamic mode decomposition

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A Comprehensive Methodology of Field-Oriented Control Design With Parameter Variation Analysis for Interior Permanent Magnet Synchronous Machine Drives

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IEEE Access 2025年 13卷 89524-89541页

作者： Tiago Davi Curi Busarello Abdullah Bubshait Oruganti V. S. R. Varaprasad Abdulhakeem Alsaleem Marcelo Godoy Simões Department of Control Automation and Computation Engineering Federal University of Santa Catarina Florianopolis Brazil Department of Electrical Engineering College of Engineering King Faisal University Al Ahsa Saudi Arabia Smart Transportation Electrification and Energy Research (STEER) Group Department of Electrical Computer and Software Engineering Faculty of Engineering and Applied Science Ontario Tech University Oshawa ON Canada Department of Electrical Engineering College of Engineering Qassim University Buraydah Saudi Arabia School of Technology and Innovations University of Vaasa Vaasa Finland

This paper proposes a comprehensive methodology for Field-Oriented Control (FOC) with parameter variation analysis for Interior Permanent Magnet Synchronous Machines (IPMSM). The modeling approach for an IPMSM is first presented, followed by a step-by-step procedure for designing a vector-controlled strategy. The formulation is based on a dq-rotating reference frame aligned with the rotor shaft position. A key distinction of this methodology from traditional approaches is that the current controller is designed in the time domain based on desired time constants, while the speed control is formulated within a frequency response domain framework. The proposed hybrid approach enables accurate tuning of the Proportional-Integrator (PI) controllers for both current and speed control loops. Additionally, a parameter variation analysis is conducted to enhance the proposed methodology. The validity region for the design procedure is presented, ensuring that for any wide speed variation of the machine, loop gains are properly tuned. One of the main advantages of the proposed methodology is that it provides a fast, reliable, and accurate technique for implementing IPMSM drive systems. Results from a Controller Hardware-in-the-Loop (C-HIL) setup with an external microcontroller are presented. The comprehensive design approach is validated under two different IPMSM parameter sets, demonstrating its effectiveness.

关键词： PI control Stators Tuning Mathematical models Velocity control Rotors Vectors Stator windings Robustness Microcontrollers

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Advancing cancer diagnosis and prognostication through deep learning mastery in breast, colon, and lung histopathology with ResoMergeNet

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Computers in Biology and Medicine 2025年 185卷 109494-109494页

作者： Ejiyi, Chukwuebuka Joseph Qin, Zhen Agbesi, Victor K. Yi, Ding Atwereboannah, Abena A. Chikwendu, Ijeoma A. Bamisile, Oluwatoyosi F. Bakanina Kissanga, Grace-Mercure Bamisile, Olusola O. College of Nuclear Technology and Automation Engineering & Sichuan Industrial Internet Intelligent Monitoring and Application Engineering Research Center Chengdu University of Technology Sichuan Chengdu China Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Life Science University of Electronic Science and Technology of China Chengdu China

Cancer, a global health threat, demands effective diagnostic solutions to combat its impact on public health, particularly for breast, colon, and lung cancers. Early and accurate diagnosis is essential for successful treatment, prompting the rise of Computer-Aided Diagnosis Systems as reliable and cost-effective tools. Histopathology, renowned for its precision in cancer imaging, has become pivotal in the diagnostic landscape of breast, colon, and lung cancers. However, while deep learning models have been widely explored in this domain, they often face challenges in generalizing to diverse clinical settings and in efficiently capturing both local and global feature representations, particularly for multi-class tasks. This underscores the need for models that can reduce biases, improve diagnostic accuracy, and minimize error susceptibility in cancer classification tasks. To this end, we introduce ResoMergeNet (RMN), an advanced deep-learning model designed for both multi-class and binary cancer classification using histopathological images of breast, colon, and lung. ResoMergeNet integrates the Resboost mechanism which enhances feature representation, and the ConvmergeNet mechanism which optimizes feature extraction, leading to improved diagnostic accuracy. Comparative evaluations against state-of-the-art models show ResoMergeNet's superior performance. Validated on the LC-25000 and BreakHis (400× and 40× magnifications) datasets, ResoMergeNet demonstrates outstanding performance, achieving perfect scores of 100 % in accuracy, sensitivity, precision, and F1 score for binary classification. For multi-class classification with five classes from the LC25000 dataset, it maintains an impressive 99.96 % across all performance metrics. When applied to the BreakHis dataset, ResoMergeNet achieved 99.87 % accuracy, 99.75 % sensitivity, 99.78 % precision, and 99.77 % F1 score at 400× magnification. At 40× magnification, it still delivered robust results with 98.85 % accuracy,

关键词： Lung cancer

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Towards in X-Ray Induced Acoustic Imaging for Nasopharyngeal Carcinoma Radiotherapy with a Multidimensional Information Fusion Network

Towards in X-Ray Induced Acoustic Imaging for Nasopharyngeal...

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International Conference on Computer Applications technology (ICCAT)

作者： Xin Jiang Zhi-Chao Chen Zheng Sun Ming-Zhe Liu School of Artificial Intelligence Chongqing University of Technology Chongqing China Department of Radiology Chongqing University Cancer Hospital Chongqing China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China School of Data Science and Artificial Intelligence Wenzhou University of Technology Wenzhou China

ISBN: (数字)9798331539795

ISBN: (纸本)9798331539801

X-ray-induced acoustic computed tomography (XACT) imaging is an emerging noninvasive imaging technique with wide applications in various clinical medicine fields. However, traditional XACT imaging methods often suffer from low imaging quality and increased noise artifacts, particularly notable under sparse sampling conditions. To overcome these challenges, we propose a hybrid supervised reconstruction method based on deep learning. Specifically, we extract and integrate information from XACT thermoacoustic signals and XACT images reconstructed by traditional methods to leverage complementary feature information from both modalities. To adapt to imaging under sparse sampling, we define multiple sparse conditions based on real-world imaging environments and validate them using a real radiotherapy dataset of head and neck cancer patients. The results demonstrate the adaptability of our method to sparse conditions and its capability to enhance XACT imaging quality under such circumstances. Additionally, we validate the feasibility of X-ray thermoacoustic imaging for 3D dose monitoring.

关键词： Deep learning Three-dimensional displays Imaging Feature extraction Acoustics Robustness Radiation therapy Data mining X-ray imaging Image reconstruction

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Design-for-manufacture of a dual-chamber nozzle for hydrodynamic focusing of the Aerosol-on-Demand jet-printhead

Design-for-manufacture of a dual-chamber nozzle for hydrodyn...

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Design, Test, Integration and Packaging of MEMS/MOEMS

作者： Martin Ungerer Ulrich Gengenbach Karanvir Singh Grewal Achim Wenka Ingo Sieber Institute for Automation and Applied Informatics (IAI) Karlsruhe Institiute of Technology (KIT) Karlsruhe Germany Department of Mechanical Engineering Punjab Engineering College Chandigarh India Institute for Micro Process Engineering (IMVT) Karlsruhe Institiute of Technology (KIT) Karlsruhe Germany

In this paper, we present the design of a dual-chamber nozzle (DCN) for a newly developed concept of a printhead for Aerosol-on-Demand (AoD) jet-printing using fluid dynamic modelling and simulation. In this newly developed concept, the ink is atomized inside of the nozzle chamber by ultrasonic excitation. This enables on-demand operation of the printhead. Focusing is achieved by means of a sheath gas and the nozzle geometry. To achieve a collimated aerosol jet, a DCN is advantageous. Computational fluid dynamics (CFD) is used to perform the design layout of a DCN for AoD jet-printing, with the goal of finding a design-for-manufacture.

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Targeted-tuning competitive acidic CO2RR via metalloid antagonism sites

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Materials Today 2025年 83卷 54-63页

作者： Sheng, Beibei Cao, Dengfeng Qi, Zhenghang Shou, Hongwei Xia, Yujian Su, Xiaozhi Chen, Shuangming Wu, Chuanqiang Liu, Hengjie Chimtali, Peter Joseph Chu, Yongheng Liu, Chongjing Wu, Xiaojun Song, Li National Synchrotron Radiation Laboratory CAS Center for Excellence in Nanoscience Key Laboratory of Precision and Intelligent Chemistry School of Nuclear Science and Technology University of Science and Technology of China Hefei230029 China SINOPEC Shanghai Research Institute of Petrochemical Technology Co. Ltd. Shanghai201208 China Engineering Laboratory of Chemical Resources Utilization in South Xinjiang of Xinjiang Production and Construction Corps College of Chemistry and Chemical Engineering Tarim University Alar843300 China School of Chemistry and Materials Science CAS Center for Excellence in Nanoscience and Synergetic Innovation of Quantum Information & Quantum Technology Hefei National Laboratory for Physical Sciences at the Microscale University of Science and Technology of China Hefei230026 China Advanced Light Source Lawrence Berkeley National Laboratory Berkeley CA94720 United States Shanghai Synchrotron Radiation Facility Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai201204 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information Technology Anhui University Hefei230601 China

To mitigate the high separation costs associated with conventional neutral/alkaline electrocatalysis for CO2 reduction reactions (CO2RR), acidic CO2RR offers economic advantages and improved efficiency in CO2 utilization. However, it typically involves the cleavage of M−H bonds at a relatively negative potential, leading to the predominant formation of H2 and poor HCOOH selectivity. Herein, we develop a facile solid-phase thermal diffusion approach to controllably synthesize a novel metalloid-metal single atom alloys (m-SAAs) electrocatalyst Te1Bi with unique metalloid antagonistic sites, thus enabling high-efficient acidic CO2-to-HCOOH conversion. Electrochemical test and operando synchrotron radiation multi-techniques (SRMS) characterization reveal that metalloid Te sites bring steric hindrance effect and blocks *H coupling. Furthermore, it actively adsorbs OH− species as a proton source, allowing for effective separation of protons and electrons in space. Thus, leading to enhanced hydrogenation in acidic CO2RR to produce HCOOH. The flow cell test results demonstrate that the carefully designed Te1Bi catalyst exhibits a milder reaction potential, along with higher HCOOH Faraday efficiency (∼94.5 %) and single-pass carbon efficiency (SPCE, ∼40 %) in acidic media. This work significantly expands the family of SAAs and offers a novel perspective to analyze the regulation of competitive reactions through site-specific modifications for industrial acidic CO2RR. © 2024 Elsevier Ltd

关键词： Synchrotron radiation

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