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Synergia Evaluation of Multi-type Rail Transit Operation Oriented to the Four-Railway-Network Integration 1

6th International Conference on Electrical engineering and Information Technologies for Rail Transportation, EITRT 2023

作者： Liu, Gehui Liu, Ling Liu, Jun Li, Qing Zhang, Huiru Beijing National Railway Research & Design Institute of Signal & Communication Group Co. Ltd. Beijing100070 China Beijing Engineering Technology Research Center of Operation Control System for High Speed Railways Beijing100070 China Beijing Mass Transit Railway Operation Co. Ltd. Beijing100044 China

ISBN: (数字)9789819993116

ISBN: (纸本)9789819993109

The four-railway-network integration is the policy guidance of multi-type rail transit for intensive resource usage, transportation efficiency enhancement, and regional society and economy development. The synergia improvement concerning multi-type rail transit is an important rising of the service level of regional rail transit system and guidance for urbanization progress. Based on the summary of the current status and policy directions of the synergetic development, the concept and key indicators evaluating the degree of synergia are introduced. Four main synergetic patterns are distinguished referring to the typical cases, including independent operation, passenger service integration, cross-line operation, and regional coordination. Detailed patterns and evaluation indicators with respect to the passenger service integration and cross-line operation are further put forward respectively according to the improvement of passenger service and the difficulty of connection implementation. The proposed theoretical methods and indicators provide the firm support and active reference for the synergetic development of multi-type rail transit systems. © Beijing Paike Culture Commu. Co., Ltd. 2024.

关键词： Rails

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Reflectionless spatial beam benders with arbitrary bending angle by introducing optic-null medium into transformation optics

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Chinese Physics B 2021年第3期30卷 242-247页

作者： Fei Sun Yi-Chao Liu Yi-Biao Yang Hong-Ming Fei Zhi-Hui Chen Sai-Ling He Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceCollege of Physics and OptoelectronicsTaiyuan University of TechnologyTaiyuan 030024China National Engineering Research Center for Optical Instruments Center for Optical and Electromagnetic ResearchZhejiang UniversityHangzhou 310058China

By introducing an optic-null medium into the finite embedded transformation,a reflectionless spatial beam bender is designed,which can steer the output beam by a fixed pre-designed angleβfor an arbitrary incident *** bending angleβof the beam bender is determined by the geometrical angle of the device,which can be changed by simply choosing different geometrical *** various bending angles,the designed spatial beam bender can be realized by the same materials(i.e.,an optic-null medium),which is a homogenous anisotropic *** simulations verify the reflectionless bending effect and rotated imaging ability of the proposed beam bender.A reduction model of the optic-null medium is studied,which can also be used for a reflectionless spatial beam bender with a pre-designed bending angle.

关键词： spatial beam benders optic-null medium transformation optics

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Biochar technology cannot offset land carbon emissions in Guangdong province, China

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Carbon research 2024年第1期3卷 1-14页

作者： Wang, Funing Zhou, Wenneng Wang, Xili Zhao, Qing Han, Mengjie State Key Lab of Clean Energy Utilization Institute of Carbon Neutrality State Environmental Protection Engineering Center for Coal-Fired Air Pollution Control Zhejiang University Hangzhou310027 China Jiaxing Research Institute Zhejiang University Jiaxing314000 China Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds School of Ecology Environment and Resources Guangdong University of Technology Guangzhou510006 China Economic & amp Information center Zhejiang310006 China Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies Tsinghua University Beijing100084 China Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management Institute of Eco-environmental and Soil Sciences Guangdong Academy of Sciences Guangzhou510650 China National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China Guangzhou510650 China

As a highly developed region, Guangdong province has substantial industrial emissions. Its subtropical monsoon climate, characterized by abundant hydrothermal conditions, contributes to a substantial biomass potential. The adoption of potential biomass-based carbon dioxide removal (CDR) technologies, such as biochar, presents an opportunity to mitigate emissions and work towards carbon neutrality in the future. However, the current state of the land carbon balance and the CDR potential of biochar in Guangdong province remains unclear. We first calculated the land carbon balance based on inventory data. Then we estimated the CDR potential of biochar derived from agricultural residues, forestry residues, and bioenergy crops cultivated on marginal lands in Guangdong province using life cycle analysis (LCA). Results show that Guangdong province has not yet achieved carbon neutrality, with a net emission (carbon emissions remaining after offsetting by carbon sinks) of 925.63 Tg CO2e (CO2 equivalent, 1Tg = 106 t) in 2021. Emissions from energy consumption account for the highest proportion, contributing 83.8% of total emissions. In the highest biomass utilization scenario, the maximum CDR potential of biochar derived from all biomass types reaches 84.30 Tg CO2e yr-1, which could offset 9.11% of net carbon emissions in Guangdong province. Our findings provide crucial guidance for setting emission reduction targets and implementing effective mitigation strategies in Guangdong province under temperature warming. Graphical Abstract: (Figure presented.) © The Author(s) 2024.

关键词： Carbon capture and utilization

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Machine learning for membrane bioreactor research:principles,methods,applications,and a tutorial

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Frontiers of Environmental Science & engineering 2025年第3期19卷 119-144页

作者： Yizhe Lai Kang Xiao Yifan He Xian Liu Jihua Tan Wenchao Xue Aiqian Zhang Xia Huang Beijing Yanshan Earth Critical Zone National Research Station College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijing 101408China Key Laboratory of Earth System Numerical Modeling and Application University of Chinese Academy of SciencesBeijing 101408China Environmental Chemistry Faculty College of Resources and EnvironmentUniversity of Chinese Academy of SciencesBeijing 101408China State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China Department of Energy Environmentand Climate ChangeSchool of EnvironmentResourcesand DevelopmentAsian Institute of TechnologyP.O.Box 4Klong LuangPathumthani 12120Thailand State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China

Membrane fouling poses a significant challenge to the sustainable development of membrane bioreactor(MBR)technologies for wastewater *** accurate prediction of the membrane filtration process is of great importance for identifying and controlling *** learning methods address the limitations of traditional statistical approaches,such as low accuracy,poor generalization ability,and slow convergence,particularly in predicting complex filtration and fouling processes within the realm of big *** article provides an in-depth exposition of machine learning *** study then reviews advances in MBRs that utilize machine learning methods,including artificial neural networks(ANN),support vector machines(SVM),decision trees,and ensemble *** on current literature,this study summarizes and compares the model input and output characteristics(including foulant characteristics,solution environments,filtration conditions,operating conditions,and time factors),as well as the selection of models and optimization *** modeling procedures of SVM,random forest(RF),back propagation neural network(BPNN),long short-term memory(LSTM),and genetic algorithm-back propagation(GA-BP)methods are elucidated through a tutorial *** simulation results demonstrated that all five methods yielded accurate predictions with R2>***,the existing challenges in the implementation of machine learning models in MBRs were *** is notable that integration of deep learning,automated machine learning(AutoML)and explainable artificial intelligence(XAI)may facilitate the deployment of models in practical engineering *** insights presented here are expected to facilitate the establishment of an intelligent control framework for MBR processes in future endeavors.

关键词： Membrane bioreactor Machine learning Pollutant removal Membrane fouling Model prediction

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Oxidation-induced superelasticity in metallic glass nanotubes

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Nature Materials 2024年第1期23卷 52-57页

作者： Li, Fucheng Zhang, Zhibo Liu, Huanrong Zhu, Wenqing Wang, Tianyu Park, Minhyuk Zhang, Jingyang Bönninghoff, Niklas Feng, Xiaobin Zhang, Hongti Luan, Junhua Wang, Jianguo Liu, Xiaodi Chang, Tinghao Chu, Jinn P. Lu, Yang Liu, Yanhui Guan, Pengfei Yang, Yong Department of Mechanical Engineering College of Engineering City University of Hong Kong Kowloon Tong Hong Kong Institute of Physics Chinese Academy of Sciences Beijing China Songshan Lake Materials Laboratory Dongguan China Beijing Computational Science Research Center Beijing China Department of Material Science and Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Materials Science and Engineering College of Engineering City University of Hong Kong Kowloon Tong Hong Kong College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Department of Mechanical Engineering The University of Hong Kong Pok Fu Lam Hong Kong Department of System Engineering College of Engineering City University of Hong Kong Kowloon Tong Hong Kong

Although metallic nanostructures have been attracting tremendous research interest in nanoscience and nanotechnologies, it is known that environmental attacks, such as surface oxidation, can easily initiate cracking on the surface of metals, thus deteriorating their overall functional/structural properties 1–3. In sharp contrast, here we report that severely oxidized metallic glass nanotubes can attain an ultrahigh recoverable elastic strain of up to ~14% at room temperature, which outperform bulk metallic glasses, metallic glass nanowires and many other superelastic metals hitherto reported. Through in situ experiments and atomistic simulations, we reveal that the physical mechanisms underpinning the observed superelasticity can be attributed to the formation of a percolating oxide network in metallic glass nanotubes, which not only restricts atomic-scale plastic events during loading but also leads to the recovery of elastic rigidity on unloading. Our discovery implies that oxidation in low-dimensional metallic glasses can result in unique properties for applications in nanodevices. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

关键词： Metallic glass

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A Quasi-Parallel Resonant Switched Capacitor DC-DC Converter with Wide Input Voltage Range Regulation and Enhanced Dynamic Performances

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Qi, Jingjing Wu, Xuezhi Sun, Kai Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing100084 China Beijing Jiaotong University National Active Distribution Network Technology Research Center Beijing100044 China

Wide-range and high-efficiency DC-DC converters are in high demand for various applications, such as distributed systems, electric vehicles, and DC buildings. Resonant switched capacitor converters (ReSCC) can achieve soft switching, have small passive device capacity, and exhibit low voltage stress, but the voltage ratio is difficult to be regulated continuously. In this paper, a quasi-parallel resonant switched capacitor DC-DC converter is proposed to satisfy the design requirements, which incorporates a ReSCC with soft-switching and variable voltage ratio, as well as a Buck converter. In addition, a simplified optimal trajectory controller for ReSCC is investigated, which can be combined with PI controller of Buck converter to enhance the load transient of the proposed converter. Moreover, the input voltage feedforward control is implemented with the optimized feedforward coefficient to suppress the input voltage disturbance. The proposed converter can achieve high efficiency and rapid dynamic response over a wide conversion range. The correctness of the theoretical analyses is verified by a 36V∼60V-5V/20A prototype. © 2013 IEEE.

关键词： Capacitor bank

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Significant Wave Height Prediction Based on VMD-SA-MLP-BP

Significant Wave Height Prediction Based on VMD-SA-MLP-BP

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2023 China Automation Congress, CAC 2023

作者： Wu, Yining Zhang, Runfeng Liu, Fang Liu, Zhenzhong Wu, Jianguo Dong, Haonan School of Mechanical Engineering Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education China Yichang Research Institute of Testing Technology Yichang443003 China Tianjin Hanhailanfan Marine Technology Co. Ltd. Tianjin300457 China School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9798350303759

Waves seriously impact port construction, worldwide route planning, military activities, and wave power generation. To improve the accuracy of significant wave height prediction, we proposed a novel prediction method, a multi-layer perceptron combined with a backpropagation adjustment (MLP-BP) prediction model that combines mutation mode decomposition (VMD) and a simulated annealing optimization algorithm (SA). Firstly, we use the variable modulus method to decompose the significant wave height sequence data and transform the wave height sequence into multiple different sub-modes (IMF) to reduce the complexity and non-stationarity of the data. Secondly, the simulated annealing algorithm (SA) is used to optimize the weight and bias of the MLP-BP neural network to find the optimal parameter configuration and improve the performance and generalization ability of the prediction model. Finally, the decomposed sub-modal components of each significant wave height sequence are inserted into the MLP-BP neural network and the predicted values of each element are summed to obtain the final significant wave height prediction. The prediction results of the SSA-MLP-BP, PSO-MLP-BP, SA-MLP-BP, and VMD-SA-MLP-BP were compared and demonstrated that the VMD-SA-MLP-BP model performed best. The MAE, MAPE, MSE, RMSE, and R2 of the prediction evaluation indexes were 0.036 m, 11.7%, 0.004 m2, 0.067 m, and 0.983, respectively, which performed well in predicting significant wave height. © 2023 IEEE.

关键词： Variational mode decomposition

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A MPC-based Planner Applied on a Parallel Wheel-legged Robot for Obstacle Avoidance 25

A MPC-based Planner Applied on a Parallel Wheel-legged Robot...

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Proceedings of the 4th International Conference on Computer, Artificial Intelligence and control engineering

作者： Fei Guo Huan Yu Wanhong Lin Shoukun Wang National Key Laboratory of Human Factors Engineering China Astronaut Research and Training Center Beijing China Institute of Spacecraft System Engineering China Academy of Space Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

ISBN: (纸本)9798400712647

A wheel-legged robot is equipped with Stewart parallel mechanism, constituting a reconfigurable robot which can change its wheelbase, robot body height, and achieve omnidirectional steering. The legged character effectively improves the terrain adaptability, which concerns our planning concentration. We introduced an optimization-based whole-body trajectory planning algorithm to navigate robot in rugged terrain. The planner combines terrain data and stability, allowing lower-level motion generator and controller to operate more efficiently. The Model Predictive control(MPC)-based method updates the footholds and CoG trajectories, which builds upon the support polygon constraints on optimization. The simulations of methodology working in several structure-obstacle scene demonstrated and compared the availability of approach.

关键词： Reconfigurable robot

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A Hybrid Meta-Heuristic Algorithm of Load Balancing for Cloud-based Railway Interlocking system

A Hybrid Meta-Heuristic Algorithm of Load Balancing for Clou...

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International Conference on Intelligent Transportation

作者： Huan Zheng Qihe Zhang Zhiguo Liang Jiacheng Kong Dongdong Wei Yong Yang Ming Chai Haifeng Wang National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China

Cloud-based railway interlocking system is a novel solution for interlocking systems with the development of cloud computing. The load balancing problem caused by imbalanced resources in computing platforms is an essential problem in realizing cloud-based railway interlocking system. Conventional load balancing algorithms focus on makespan, throughput and costs. However, a load balancing algorithm for a cloud-based railway interlocking system should focus on optimizing resource utilization and execution time. To this end, we propose a hybrid meta-heurisite algorithm called Improved Genetic Annealing Algorithm (IGAA). The proposed algorithm can guarantee global optimization ability by using the Metropolis criterion and can converge rapidly due to the parallel searching characteristic of the Genetic Algorithm. Finally, the feasibility and effectiveness of the proposed algorithm are verified by experiments.

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A Distributed Convergent Clock Synchronization Algorithm Based on Exponential Smoothing for Cloud-Based Railway Interlocking system

A Distributed Convergent Clock Synchronization Algorithm Bas...

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International Conference on Intelligent Transportation

作者： Qihe Zhang Shunli Li Zhiguo Liang Jiacheng Kong Dongdong Wei Yong Yang Ming Chai Haifeng Wang National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China

Clock synchronization is one of the essential problems for the cloud-based railway interlocking system, which is related to task processing and information synchronization. To improve the convergence rate and performance of a classical distributed clock synchronization algorithm, this paper proposes an exponential smoothing predictor-based distributed clock synchronization algorithm for the cloud-based railway interlocking system. Firstly, a classical distributed clock synchronization algorithm is conducted to get a convergent clock for distributed computing nodes. Then, to improve the convergence rate and performance, we introduce an exponential smoothing predictor to the classical method. Moreover, the convergence condition and convergence rate of our proposed method were analyzed theoretically. Finally, the simulation results show that the proposed algorithm has a better convergence performance than a classical method and can meet the requirements of a cloud-based railway interlocking system.

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