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Fracture behaviour of fibre-reinforced composite materials subjected to shear loading: An experimental and numerical study

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International Journal of Lightweight Materials and Manufacture 2023年第1期6卷 108-116页

作者： Liu, Haibao Zhou, Jin Kong, Xiangshao Li, Shipeng Centre for Aeronautics School of Aerospace Transport and Manufacturing Cranfield University CranfieldMK43 0AL United Kingdom School of Mechanical Engineering Xi'an Jiaotong University Shaanxi Xi'an710049 China Departments of Naval Architecture Ocean and Structural Engineering School of Transportation Wuhan University of Technology Hubei Wuhan430063 China Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education Tianjin University Tianjin300350 China

Compared to fibre-dominated behaviour, a response dominated by the matrix under shear loading can considerably limit the load-bearing capability and restrict the utilisation of composite materials. It is therefore practically significative to understand the shear response of composite materials. This paper presents a detailed experimental and numerical investigation on the fracture behaviour of composite laminates subjected to shear-dominated loading. Composite specimen with a lay-up of [(0/90)4/0]S are tested using the V-Notched Rail (VRS) shear test method. Subsequently, the Scanning Electron Microscope (SEM) investigation is also conducted on the fracture surfaces of the tested specimens to get insights into the damage mechanisms due to shear loading. In addition, a high-fidelity computational damage model is developed to predict the shear fracture behaviour of fibre-reinforced composites. Simulation results, including loading response, strain distribution and shear fracture, well correlated with experimental results, which demonstrates the predictive capability of the developed elastic-plastic damage model. © 2022 The Authors

关键词： Finite element method

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Multi-objective Optimization of Repulsive Force Actuator for Vacuum Circuit Breaker 30

Multi-objective Optimization of Repulsive Force Actuator for...

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30th International Symposium on Discharges and Electrical Insulation in Vacuum, ISDEIV 2023

作者： Li, Peiyuan Liu, Xiaoming Chen, Hai Jiang, Wentao Zhou, Yongjie Hebei University of Technology State Key Laboratory of Reliability and Intelligence of Electrical Equipment Tianjin China Tiangong University School of Control Science and Engineering Tianjin China Shanghai Qiteng Electric Co. Ltd. Shanghai China

ISBN: (纸本)9784886864369

The fast DC vacuum switch driven by repulsive force actuator is the key equipment for the control and protection of the new energy power system. Its operating speed directly determines the interruption time of the DC vacuum switch. This paper takes fast 400V DC vacuum switch as the research object, studies the dynamic output characteristics, establishes the finite element numerical analysis model of electromagnetic repulsive force actuator, simulates and analyzes the influence of opening capacitors and charging voltage on the dynamic performance of fast switching. Moreover, the multi-objective artificial jellyfish optimizer is applied to design the repulsive force actuator. Based on the optimized 400V DC vacuum switch, the dynamic output performance of the fast switch has been obtained and analyzed. And the numerical simulation results show that the dynamic motion characteristics and energy conversion efficiency of the fast switch can be improved within 2.0ms. © 2023 IEEJ.

关键词： Electric circuit breakers

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Principal Trotter Observation Error with Truncated Commutators

arXiv

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arXiv 2024年

作者： Li, Langyu Institute of Cyber-system and Control College of Control Science and Engineering Zhejiang University Hangzhou310027 China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China

Hamiltonian simulation is one of the most promising applications of quantum computers, and the product formula is one of the most important methods for this purpose. Previous related work has mainly focused on the worst-case or average-case scenarios. In this work, we consider the simulation error under a fixed observable. Under a fixed observable, errors that commute with this observable become less important. To illustrate this point, we define the observation error as the expectation under the observable and provide a commutativity-based upper bound using the Baker–Campbell–Hausdorff formula. For highly commuting observables, the simulation error indicated by this upper bound can be significantly compressed. In the experiment with the Heisenberg model, the observation bound compresses the Trotter number by nearly half compared to recent commutator bounds. Additionally, we found that the evolution order significantly affects the observation error. By utilizing a simulated annealing algorithm, we designed an evolution order optimization algorithm, achieving further compression of the Trotter number. The experiment on the hydrogen molecule Hamiltonian demonstrates that optimizing the order can lead to nearly half the reduction in the Trotter number. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum computers

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Designing Electronic Structures of Multiscale Helical Converters for Tailored Ultrabroad Electromagnetic Absorption

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Nano-Micro Letters 2025年第1期17卷 439-455页

作者： Zhaobo Feng Chongbo Liu Xin Li Guangsheng Luo Naixin Zhai Ruizhe Hu Jing Lin Jinbin Peng Yuhui Peng Renchao Che Key Laboratory of Jiangxi Province for Persistent Pollutants Control and Resources Recycle School of Environmental and Chemical EngineeringNanchang Hangkong UniversityNanchang 330063People’s Republic of China School of Physics and Materials Nanchang UniversityNanchang 330031People’s Republic of China Key Laboratory of Nondestructive Testing Ministry of EducationNanchang Hangkong UniversityNanchang 330063People’s Republic of China Laboratory of Advanced Materials Shanghai Key Lab of Molecular Catalysis and Innovative MaterialsAcademy for Engineering and TechnologyFudan UniversityShanghai 200438People’s Republic of China

Atomic-scale doping strategies and structure design play pivotal roles in tailoring the electronic structure and physicochemical property of electromagnetic wave absorption(EMWA)***,the relationship between configuration and electromagnetic(EM)loss mechanism has remained ***,drawing inspiration from the DNA transcription process,we report the successful synthesis of novel in situ Mn/N co-doped helical carbon nanotubes with ultrabroad EMWA *** calculation and EM simulation confirm that the orbital coupling and spin polarization of the Mn–N4–C configuration,along with cross polarization generated by the helical structure,endow the helical converters with enhanced EM *** a result,HMC-8 demonstrates outstanding EMWA performance,achieving a minimum reflection loss of−63.13 dB at an ultralow thickness of 1.29 *** precise tuning of the graphite domain size,HMC-7 achieves an effective absorption bandwidth(EAB)of 6.08 GHz at 2.02 mm ***,constructing macroscale gradient metamaterials enables an ultrabroadband EAB of 12.16 GHz at a thickness of only 5.00 mm,with the maximum radar cross section reduction value reaching 36.4 dB *** innovative approach not only advances the understanding of metal–nonmetal co-doping but also realizes broadband EMWA,thus contributing to the development of EMWA mechanisms and applications.

关键词： Metal-nonmetal co-doping 3d-2p orbital coupling Spin polarization Helical structure Broadband EM wave absorption

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A Proactive-Reactive Approach for Dynamic Hybrid Berth Allocation Problem Considering Vessels Arrival Delay

A Proactive-Reactive Approach for Dynamic Hybrid Berth Alloc...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Pengfei Yang Lei Cai Wenjing Guo Wenfeng Li School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan China State Key Laboratory of Maritime Technology and Safety Wuhan University of Technology Wuhan China

Dynamic Berth Allocation Problem (DBAP) is an essential problem in container terminal operations. Most studies focus on discrete or continuous berths in DBAP. However, affected by the geographical conditions, the mixture of discrete and continuous berths which are called hybrid berths often appear in real port container terminals. Moreover, the arrival time of vessels is often fluctuant due to the influence of environmental factors. To solve such a Dynamic Hybrid Berth Allocation Problem (DHBAP) under vessels' arrival delay, this study develops a proactive-reactive approach. Specifically, we establish a mixed-integer programming model with a buffer as the proactive strategy to obtain a baseline schedule. Then, we propose a hybrid berth reactive strategy (HBRS) to adjust the baseline schedule for vessels that are delayed. To get a better solution in a short time, a genetic algorithm is designed. We verify the effectiveness of the proposed HBRS by comparing it with the most commonly used right-shift strategy. Experimental results show that the longer the buffer is, the better the robustness of the model is, but the total time of the vessel in terminals will also increase. Compared with the right-shift strategy, the proposed HBRS can obtain an allocation plan with similar robustness in a shorter total time of the vessel in terminals.

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A Method for Automatic Identification of Natural Fracture Based on Machine Learning: A Case Study on the Dahebian Block of the Liupanshui Basin in Guizhou Province 13th

A Method for Automatic Identification of Natural Fracture Ba...

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13th International Field Exploration and Development Conference, IFEDC 2023

作者： Zhao, Wei-Guang Sang, Shu-Xun Cheng, De-Qiang Han, Si-Jie Zhou, Xiao-Zhi Zhang, Jin-Chao Zhao, Fu-Ping School of Resources and Geosciences China University of Mining and Technology Xuzhou221116 China Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Controland Utilization China University of Mining and Technology Xuzhou221008 China Carbon Neutrality Institute China University of Mining and Technology Xuzhou221008 China Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou221116 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Key Laboratory of Coalbed Methane Resources and Reservoir Formation Process Ministry of Education China University of Mining and Technology Xuzhou221116 China Key Laboratory of Unconventional Natural Gas Evaluation and Development in Complex Tectonic Areas Ministry of Natural Resources Guiyang550009 China Guizhou Engineering Research Institute of Oil & Gas Exploration and Development Guiyang550009 China

ISBN: (纸本)9789819702718

Natural fractures are effective storage spaces and important seepage channels for oil and gas reservoirs. Accurately identifying natural fractures in reservoirs is crucial for the exploration and development of oil and gas resources. This article combines conventional and imaging logging data and uses machine learning to automatically identify natural fractures in reservoirs. The fracture labels of conventional logging come from imaging logging. Conventional logging data is decomposed through multi-scale wavelet to extract components that reflect fracture information, and further build the original data set. The AdaBoost model is trained based on a modified dataset of balanced samples for automatic fractures recognition in logging. The research results indicate that the approximate component and high-frequency component reflect the fluctuation of the formation and noise information respectively, and have little impact on the reservoir fractures identification;The medium frequency component can reflect the characteristic information of fractures and can be used for model training;After hyper-parameter optimization, the AdaBoost model has high accuracy and generalization ability, and can still accurately identify the types and distribution of natural fractures from the actual unbalanced logging data. This research has important guiding significance for the accurate characterization and construction of reservoir. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Wavelet transforms

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A Novel Variable Impedance PM Machines with Separated Fault Tolerant Ring

A Novel Variable Impedance PM Machines with Separated Fault ...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Runyu Wang Xinggang Fan Dawei Li Ronghai Qu Yongtao Peng Xiaopeng Zhao State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China National Key Laboratory of Science and Technology on Aircraft Control AVIC Xi’an Flight Automatic Control Research Institute Xi’an China

This paper aims to analyze and design a novel variable impedance permanent magnet (PM) machine with separated fault tolerant ring for high reliability applications. The proposed topology automatically changes from low impedance to ultra-high impedance under turn-to-turn short-circuit without complex fault diagnosis and control strategies. First, the topology of the variable impedance PM machine is introduced. Then, the magnetic field distribution of the separate fault tolerant ring under health and fault is analyzed to qualitatively reveal the fault tolerance principle. Finally, a turn-to-turn short-circuit model considering the core saturation effect is developed for investigating the mechanism of fault tolerance performance improvement. It is found that the short-circuit current and torque ripple after the fault of the variable impedance machines are significantly lower than those of the conventional ones.

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UAV Obstacle Avoidance Algorithm Based on Priori Artificial Potential Field and PID-ADRC Hybrid control

UAV Obstacle Avoidance Algorithm Based on Priori Artificial ...

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第42届中国控制会议

作者： Keqing Guo Hui Wang Heting Wang Daoguang Tang School of Aerospace Engineering Beijing Institute of Technology Beijing Key Laboratory of UAV Autonomous Control Beijing Institute of Technology School of Electrical and Control Engineering North University of China

Aiming at the obstacle avoidance problem of Unmanned Aerial Vehicles(UAV) in practical application,this paper proposes a UAV trajectory obstacle avoidance algorithm based on Priori Artificial Potential Field(P-APF),while using PID and Active Disturbance Rejection control(ADRC) for obstacle avoidance control of *** view of the problems that the classical artificial potential field algorithm is easy to fall into local minima and the trajectory is tortuous,this paper analyzes the boundary repulsion potential field function in the actual scene and corrects the trajectory in advance based on the priori *** at the problems of nonlinear and sensitive to disturbance of the UAV system,a hybrid position and attitude tracking control method based on the cascade PID-ADRC is *** simulation results show that after adding white noise disturbance,the UAV can still avoid obstacles and reach the specified target position smoothly,and its attitude tracking is fast and stable with good anti-disturbance capability.

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A Novel Intelligent Online Fire Monitoring Approach for Underground Pipe Galleries

A Novel Intelligent Online Fire Monitoring Approach for Unde...

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Data Driven control and Learning Systems (DDCLS)

作者： Yongjing Wang Chenying Wen Zheren Zhu Xinming Zhang Zhihuan Song Zugang Zhu Xueer Fan The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou Hangzhou Underground Pipeline Development Co. Ltd Hangzhou

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Underground pipe galleries are constructed beneath urban areas, providing pathways for the installation of various municipal pipelines. These galleries help protect pipelines and efficiently utilize underground space, serving as a significant facilitator for the construction of smart cities. Due to the confined space inside the galleries and the simultaneous presence of multiple pipelines, there is a potential safety hazard of fire incidents. To ensure the safe operation of pipelines, online monitoring and timely warning of fire incidents are valuable tasks. Current traditional computer vision and machine learning approaches for object detection often experience slow response time. Therefore the You Only Look Once (YOLO) series due to its fast response time, has become a popular method in real-time detection. Nonetheless, YOLOv8 still suffer from information fusion problems. In response to this issue, this paper proposed YOLOH algorithm, which improves YOLOv8 by employing the Gather-and-Distribute (GD) mechanism for intelligent online monitoring of fire incidents in underground pipe galleries. Finally, the effectiveness of YOLOH was validated using a combination of publicly available fire datasets and simulated fire datasets in underground pipe galleries. The YOLOH attains a 63.2 mAP, surpassing the YOLOv8-N baseline by +2.15 mAP.

关键词： YOLO Machine learning algorithms Smart cities Pipelines Propagation losses Real-time systems Neck

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Multi-Agent Q-Value Mixing Network with Covariance Matrix Adaptation Strategy for the Voltage Regulation Problem

Multi-Agent Q-Value Mixing Network with Covariance Matrix Ad...

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第42届中国控制会议

作者： Yiwen Wang Senlin Zhang Meiqin Liu Shanling Dong Ronghao Zheng College of Electrical Engineering Zhejiang University National Key Laboratory of Industrial Control Technology Zhejiang University

control and optimization of power systems typically involves schemes that utilize optimal power flow techniques and comprehensive modeling of various electrical components. However, the extensive integration of renewable energy sources and distributed energy resources makes it difficult to obtain accurate models, making the traditional model-based approaches more challenging. In this paper, we propose a Covariance Matrix Adaptation Q-value network mixing method(CMAQMIX), which is a novel model-free multi-agent reinforcement learning method that combines the advantages of Covariance Matrix Adaptation Evolution Strategy and the Q-value network mixing method to solve the problem of continuous action space. We establish a new multi-agent voltage regulation environment based on CityLearn framework to test the CMAQMIX method. The results show that our proposed method outperforms the Independent Proximal Policy Optimization method and can give immediate action response without the complete domain knowledge of the power system.

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