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Dual-function artificial CA/PVP interlayer for protect Zn anode on improving uniform Zn2+ ion deposition

Electrochimica Acta 2025年 535卷

作者： Fan, Lanlan Zhang, Xiangguo Deng, Junwen Cao, Lei Jiangxi Provincial Key Laboratory for Simulation and Modelling of Particulate Systems International Institute for Innovation Jiangxi University of Science and Technology Nanchang330013 China

Aqueous Zn-ion batteries (ZIBs) have come into the public's view because of their low cost, high theoretical capacity and safety. However, uncontrollable dendrite growth on the Zn anode surface is the key reason restricting the long-cycle stability of ZIBs. Herein, a highly water-soluble polyvinylpyrrolidone and cellulose acetate (CA/PVP) interlayer was used to enhance the lifespan of battery cycles and provide excellent suppression of dendrite growth and side reaction generation. On the one hand, the water-soluble PVP can swell in the electrolyte, forming local electrolyte gelation on the surface of the Zn anode, balancing the transmission of Zn2+ flow. On the other hand, the synergistic effect of carbon based (C = O) and hydroxyl groups (-OH) in the interlayer can facilitate the desolvation of hydrated Zn2+. Furthermore, C = O complexes with Zn2+ ions can increase the hydrophilicity of the Zn anode, reduce interfacial impedance and further optimize Zn2+ transport kinetics. Subsequently, the Zn||Zn symmetric battery, constructed with a CA/PVP interlayer, is capable of sustaining a prolonged cycling performance exceeding 1000 h at a current density of 0.1 mA cm-2/0.05 mAh cm-2. At the same time, the CA/PVP3%@Zn full cell demonstrate 94 % of capacity retention after 300 cycles at 0.5 A g-1. The successful construction of artificial interfacial layers provides an attractive strategy for the development of high-performance aqueous ZIBs. © 2025

关键词： Aqueous Zn ion batteries Cycle stability Dual-function Interlayer Zn dendrite

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Bit Bounce Detection for Drilling Process Based on Multi-Feature Graph and Graph Convolutional Network

Bit Bounce Detection for Drilling Process Based on Multi-Fea...

引用

Annual Conference of Industrial Electronics Society

作者： Peng Zhang Wenkai Hu Weihua Cao Min Wu Jiandong Wang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao Shandong Province China

Prompt detection of bit bounce can prevent serious incidents and is of great importance for safe and efficient deep geological drilling. In the early stage of bit bounce, signal changes are relatively weak. In addition, there are differences in the topological relationships of samples at different time instances in normal state and bit bounce. These factors present a challenge to timely and accurate bit bounce detection. Therefore, this paper proposes a bit bounce detection method based on multi-feature graph and graph convolution networks. A multi-feature graph construction method using process variables, mean value, Mahalanobis distance, and Euclidean distance is proposed, and a two-layer graph convolutional network is designed to realize deep feature extraction and incident detection. The effectiveness and superiority of the proposed method are demonstrated by a real drilling industrial case.

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Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation

arXiv

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arXiv 2022年

作者： Fan, Siqi Zhu, Fenghua Feng, Zunlei Lv, Yisheng Song, Mingli Wang, Fei-Yue The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Tsinghua University Beijing China The College of Computer Science and Technology Zhejiang University Hangzhou China

Pseudo supervision is regarded as the core idea in semi-supervised learning for semantic segmentation, and there is always a tradeoff between utilizing only the high-quality pseudo labels and leveraging all the pseudo labels. Addressing that, we propose a novel learning approach, called Conservative-Progressive Collaborative Learning (CPCL), among which two predictive networks are trained in parallel, and the pseudo supervision is implemented based on both the agreement and disagreement of the two predictions. One network seeks common ground via intersection supervision and is supervised by the high-quality labels to ensure a more reliable supervision, while the other network reserves differences via union supervision and is supervised by all the pseudo labels to keep exploring with curiosity. Thus, the collaboration of conservative evolution and progressive exploration can be achieved. To reduce the influences of the suspicious pseudo labels, the loss is dynamic re-weighted according to the prediction confidence. Extensive experiments demonstrate that CPCL achieves state-of-the-art performance for semi-supervised semantic segmentation. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Distributed Active Disturbance Rejection Control of Multiple Mobile Robots for Online Workload Partition

Distributed Active Disturbance Rejection Control of Multiple...

引用

Chinese Automation Congress (CAC)

作者： Xin Li Chao Zhai Hehong Zhang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan Campus School of Automation Wuhan China School of Computer and Data Science Fuzhou University Fuzhou China

Considering the actual multi-agent coverage process, the motion trajectories are seriously affected by disturbances and noise. In this paper, a cooperative control method based on active disturbance rejection controller (ADRC) for multiple mecanum-wheeled robots (MWMR) is proposed to improve its robustness. In particular, to suppress the total disturbances during the running of each robot and reduce large computation and observation cost of high order ADRC, a reduced-order cascaded ADRC (RC-ADRC) is proposed. Moreover, distributed controller is proposed to track the expected trajectories of multiple mecanum-wheeled robots under disturbances. Compared with the proposed RC-ADRC based cooperative control scheme and PID based cooperative control one, the favorable motion trajectory tracking performance is obtained. simulation results verify the superiority of the method.

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Fuzzy Logic Model for Predicting the Heat Index

arXiv

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arXiv 2022年

作者： Uzoukwu, Nnamdi Purqon, Acep Computational Science The Faculty of Mathematics and Natural Science Bandung Institute of Technology Jl. Ganesha No. 10 Bandung40132 Indonesia Physics of the Earth and Complex Systems Laboratory The Faculty of Mathematics and Natural Science Bandung Institute of Technology Jl. Ganesha No. 10 Bandung40132 Indonesia

A fuzzy inference system was developed for predicting the heat index from temperature and relative humidity data. The effectiveness of fuzzy logic in using imprecise mapping of input to output to encode interconnectedness of system variables was exploited to uncover a linguistic model of how the temperature and humidity conditions impact the heat index in a growth room. The developed model achieved an R2 of 0.974 and a RMSE of 0.084 when evaluated on a test set, and the results were statistically significant (F1,5915 = 222900.858, p © 2022, CC BY-NC-SA.

关键词： Forecasting

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An Interacting-Multiple-Model Method for Tracking a Hypersonic Glide Target

An Interacting-Multiple-Model Method for Tracking a Hyperson...

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Chinese Control and Decision Conference, CCDC

作者： Jingshuai Huang Hongbo Zhang Shang Wu Guojian Tang Weimin Bao National University of Defense Technology College of Aerospace Science and Engineering Changsha China Science and Technology on Complex Aviation Systems Simulation Laboratory Beijing

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

In terms of tracking a hypersonic glide target (HGT), a tracking method is proposed based on interacting-multiple-model (IMM). Target tracking mainly contains two missions: system modeling and choosing filtering algorithm. First, a tracking system is established composed of state and measurement equations on basis of ground-based radar measuring. The Singer model is used to represent the unknown aerodynamic acceleration. Then, to enhance model adaptation of the tracking method, three-model interacting filter is constructed with maneuver-frequency adaption based on unscented Kalman filter (UKF). Through tracking a flight trajectory generated by Gauss Pseudospectral Method, the effectiveness of the proposed method is validated and the multiple-model is superior to the single-model.

关键词： Target tracking Radar tracking Electronic mail Kalman filters Adaptation models Mathematical model Aerospace engineering

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Unmanned Marine Emergency Response System technology

Unmanned Marine Emergency Response System Technology

引用

2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Zhang, Hongli Song, Yuanyun Chen, Chao Chu, Xianying Beijing Aerospace Technology Research Institute Beijing China Aviation Systems Simulation Laboratory Science and Technology on Complex Beijing China

ISBN: (纸本)9781728137926

With the global climate change, the frequency and destructiveness of emergencies in the coastal areas worldwide have increased in recent years. The rapid response of the existing equipment and means is insufficient. It is urgent to improve response speed for marine research, disaster investigation, marine rescue, maritime surveillance and other maritime emergencies. With the development of high-speed civil aircraft technology, the high-speed UAV platform can form an unmanned emergency response system, taking advantage of fast arrival, wide coverage and flexibility. The simulation shows that the unmanned emergency system has outstanding advantages compared with the existing subsonic UAV, and can effectively execute emergency marine missions. © 2019 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Synchronization of Diverse Agents via Phase Analysis

arXiv

引用

arXiv 2022年

作者： Wang, Dan Chen, Wei Qiu, Li Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Department of Mechanics and Engineering Science State Key Laboratory for Turbulence and Complex Systems Peking University Beijing100871 China

In this paper, the synchronization of heterogeneous agents interacting over a dynamical network is studied. The edge dynamics can model the inter-agent communications which are often heterogeneous by nature. They can also model the controllers of the agents which may be different for each agent or uniform for all the agents. Novel synchronization conditions are obtained for both cases from a phase perspective by exploiting a recently developed small phase theorem. The conditions scale well with the network and reveal the trade-off between the phases of node dynamics and edge dynamics. We also study the synchronizability problem which aims to characterize the allowable diversity of the agents for which controllers can be designed so as to achieve synchronization. The allowable diversity is captured in terms of phase conditions engaging the residue matrices of the agents at their persistent modes. Controller design algorithms are provided for the cases of agent-dependent and uniform controllers, respectively. Copyright © 2022, The Authors. All rights reserved.

关键词： Synchronization

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A Novel Two-Stream Model for Human Motor Characteristics Learning

A Novel Two-Stream Model for Human Motor Characteristics Lea...

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IEEE International Conference on Robotics and Biomimetics

作者： Tian-Yu Xiang Xiao-Hu Zhou Xiao-Liang Xie Shi-Qi Liu Hong-Jun Yang Zhen-Qiu Feng Jian-Long Hao Zeng-Guang Hou The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The school of Information Shanxi University of Finance and Economics Taiyuan China The CAS Center for Excellence in Brain Science and Intelligence Technology Beijing China The Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology Taipa Macau

ISBN: (纸本)9781665481106

Electroencephalogram (EEG) is one of the most pop-ular sources for learning human motor characteristics. However, most current methods only consider its temporal features and overlook spatial information. This paper proposes a novel two-stream model based on spatial and temporal features to learn human motor characteristics from EEG signals. The spatial stream is analyzed by graph neural networks (GNN) to extract the relationship among different channels. Adjacent matrices can be learned through the training process, unlike pre-defined ones used in other GNN-based EEG analysis methods. The temporal stream is processed with mixed convolution structures, which consist ID convolution, depthwise convolution, and separable convolution. The features of two streams are fused with fully-connected neural networks for human motor characteristics learning. Experimental results show the proposed model can achieve the accuracy of 0.684/0.709 (four classes motor imagery) in subject-independent/dependent schemes, demonstrating the promising for it used in brain computer interface (BCI) scenarios.

关键词： Training Convolution Computational modeling Biological system modeling Streaming media Brain modeling Electroencephalography

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Study on Effects of Operation Parameters on Ventilation Performances for a Floor-Standing Air Conditioner

SSRN

引用

SSRN 2022年

作者： Dianyu, E. Tan, Cong Li, Jing Liu, Sida Zhou, Zongyan Cui, Jiaxin Yi, Lei Jiangxi Provincial Key Laboratory for Simulation and Modelling of Particulate Systems Jiangxi University of Science and Technology Nanchang330013 China International Institute for Innovation Jiangxi University of Science and Technology Nanchang330013 China ARC Research Hub for Computational Particle Technology Department of Chemical and Biological Engineering Monash University VIC3800 Australia

The floor-standing air conditioners (FSACs) have been widely used in civil and office buildings because of its advantages of high cooling/heating capacity and easy installation. The major challenge of FSACs is to meet the requirements of thermal comfort and indoor air quality (IAQ) while the operation energy consumption should be minimized. This study extensively examines the effects of some key operation parameters on the FSAC performance using validated computational fluid dynamics (CFD) method. The operation parameters include controllable supply vane angle, supply air velocity, supply air temperature, and uncontrollable outdoor weather condition. The main ventilation performance is assessed by indices such as predicted mean vote (PMV), predicted percent dissatisfied (PPD), draught rate (DR), local mean age of air (LMAA), and energy consumption (P system ). The relative importance of the operation parameters for each ventilation performance index is identified through evaluating the individual effects of the operation parameters on the ventilation performance. By comparing the individual effects and combined effects of the operation parameters on the ventilation performance, it is found that the variations of PMV, PPD, DR, LMAA and P system caused by the combined effects can be accounted by the corresponding most important operation parameters by 90.6%, 97.4%, 77.1%, 95.1% and 79.2%, respectively. Additionally, the outdoor weather conditions do not significantly affect DR, PPD and LMAA, but can shift PMV to uncomfortable levels. Finally, the constant-air-volume (CAV) system is recommended for FSACs during the steady stage and a simplified and optimized operation strategy is proposed. © 2022, The Authors. All rights reserved.

关键词： Sensitivity analysis

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