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SSRN 2025年

作者： Li, Ning Yibo, Zhang Xu, Yawei Li, Jing School of Chemistry and Chemical Engineering South China University of Technology Guangzhou510641 China National Key Laboratory of Spacecraft Thermal Control Beijing Institute of Spacecraft System Engineering Beijing100086 China South China University of Technology Zhuhai Institute of Modern Industrial Innovation Zhuhai519000 China

In the space environment, the heat dissipation of spacecraft primarily relies on thermal radiation. To reduce the weight of spacecraft, it is necessary to replace the existing copper radiators with aluminum ones. However, aluminum radiators have a lower emissivity, which results in suboptimal heat dissipation performance. Therefore, enhancing the emissivity of aluminum radiators is crucial for improving their heat dissipation performance. This study investigates the rapid (100 s) reduction of graphene oxide (GO) into low-defect reduced graphene oxide (mRGO) using Joule heating for 100 seconds, followed by non-covalent modification to further enhance its dispersion in water. By incorporating modified reduced graphene oxide (mRGO) as the primary filler in an aqueous epoxy resin emulsion and using 3-aminopropyltriethoxysilane (APTES) to enhance the adhesion between the coating and the aluminum substrate, a composite Graphene/Epoxy coating (GEC) with high emissivity and strong adhesion was successfully prepared. Experimental results demonstrate that the coating containing 4 wt% mRGO filler exhibits the optimal heat dissipation efficiency (24.15%) and significantly enhances the infrared emissivity of the substrate (up to 0.93). This coating exhibits excellent thermal stability and strong adhesion, providing a novel approach for thermal management in space radiators. © 2025, The Authors. All rights reserved.

关键词： Aluminum coatings

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UGNA-VPR: A Novel Training Paradigm for Visual Place Recognition Based on Uncertainty-Guided NeRF Augmentation

arXiv

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arXiv 2025年

作者： Shen, Yehui Zhang, Lei Li, Qingqiu Zhao, Xiongwei Wang, Yue Lu, Huimin Chen, Xieyuanli College of Intelligence Science and Technology National University of Defense Technology China Faculty of Robot Science and Engineering Northeastern University China School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University China SIASUN Robot& Automation Co. Ltd China School of Computer Science Fudan University China

Visual place recognition (VPR) is crucial for robots to identify previously visited locations, playing an important role in autonomous navigation in both indoor and outdoor environments. However, most existing VPR datasets are limited to single-viewpoint scenarios, leading to reduced recognition accuracy, particularly in multi-directional driving or feature-sparse scenes. Moreover, obtaining additional data to mitigate these limitations is often expensive. This paper introduces a novel training paradigm to improve the performance of existing VPR networks by enhancing multi-view diversity within current datasets through uncertainty estimation and NeRF-based data augmentation. Specifically, we initially train NeRF using the existing VPR dataset. Then, our devised self-supervised uncertainty estimation network identifies places with high uncertainty. The poses of these uncertain places are input into NeRF to generate new synthetic observations for further training of VPR networks. Additionally, we propose an improved storage method for efficient organization of augmented and original training data. We conducted extensive experiments on three datasets and tested three different VPR backbone networks. The results demonstrate that our proposed training paradigm significantly improves VPR performance by fully utilizing existing data, outperforming other training approaches. We further validated the effectiveness of our approach on self-recorded indoor and outdoor datasets, consistently demonstrating superior results. Our dataset and code have been released at https://***/nubot-nudt/UGNA-VPR. Copyright © 2025, The Authors. All rights reserved.

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Numerical Investigation into the Transient Behavior of the Spike-Type Rotating Stall for a Transonic Compressor Rotor

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Fluid Dynamics & Materials processing 2022年第3期18卷 761-773页

作者： Pengfei Ju Fangfei Ning Zhiting Tong Jingying Wang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education(Tianjin University of Technology) Tianjin300384China Research Institute of Aero-Engine Beihang UniversityBeijing100191China National Key Laboratory of Science and Technology on Aero-Engine Aero-Thermodynamics School of Energy and Power EngineeringBeihang UniversityBeijing100191China School of Energy and Power Engineering Shandong UniversityJinan250061China Shandong Engineering Laboratory for High-Efficiency Energy Conservation and Energy Storage Technology&Equipment Shandong UniversityJinan250061China

In this paper,a numerical investigation into a spike-type rotating stall process is carried out considering a transonic compressor rotor(the NASA Rotor 37).Through solution of the Unsteady Reynolds-Averaged Navier-Stokes(URANS)equations,the evolution process from an initially circumferentially-symmetric near-stall flow field to a stable stall condition is simulated without adding any artificial *** the near-stall operating point,periodic fluctuations are present in the overall flow of the ***,the blockage region in the channel periodically shifts from middle span to the *** fluctuating condition does not directly lead to stall,while the full-annulus calculation eventually evolves to ***,a kind of“early disturbance”feature appears in the dynamic signals,which propagates forward ahead of the rotor.

关键词： Transonic compressor spike stall numerical simulation early disturbance dynamic signal

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Hierarchy-based extended CBBA for multi-robot task assignment

Hierarchy-based extended CBBA for multi-robot task assignmen...

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Chinese Automation Congress (CAC)

作者： Jiajun Liu Weiguo Xia Fuqiang Li Peng Wang China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology China

This paper studies the task assignment problem of a multi-robot system with complex constraints including the robot speed limit, the task execution time window constraints, the arrival time, the trip cost, and different priorities of the tasks. A new bidding function is then designed for each robot. Based on the k-means algorithm, a hierarchy-based extended consensus-based bundle algorithm (CBBA) is proposed to find the optimal solution for the task allocation problem. Finally, simulation examples are presented to show the feasibility of the proposed algorithm and comparisons with existing algorithms show that the proposed algorithm can reduce the task assignment time with guaranteed reward values.

关键词： Costs Automation Heuristic algorithms Numerical simulation Time factors Resource management Multi-robot systems

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Research on Cardiac Medical Image Segmentation Based on an Improved U-Net Model

Research on Cardiac Medical Image Segmentation Based on an I...

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Image processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Yuqing Wu Jun Wang Rui Wang Jian Wang Kecheng Zhou Xiaoxin Zhang School of Computer Science and Technology Shenyang University of Chemical Technology Key Laboratory of Industrial Intelligence Technology on Chemical Process Liaoning Province Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Department of Emergency Zhongyi Northeast International Hospital Co. Ltd. Shenyang China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

This paper presents a cardiac MRI image segmentation model based on an improved U-Net architecture. Accurate segmentation of cardiac MRI images is critical for the diagnosis and treatment of cardiovascular diseases, yet existing U-Net models exhibit limitations in handling complex cardiac structures and multi-scale features. To address these challenges, this paper proposes two key enhancements. First, we propose a Multi-Dimensional Context Attention module, designed to improve the integration of global and local information within the skip connections, thereby enhancing segmentation accuracy for intricate cardiac structures. Furthermore, we propose a Reverse Feature Modulation module, which generates reverse masks and dynamically adjusts feature weights across different classes using adaptive weighting, effectively mitigating class imbalance issues in multi-class segmentation tasks and improving focus on difficult-to-segment regions. Experimental results demonstrate that the proposed model outperforms the standard U-Net on the ACDC dataset, achieving significant improvements in evaluation metrics such as the Dice coefficient. These enhancements underscore the model's efficacy and robustness in complex cardiac image segmentation tasks, offering new technical support for automated cardiovascular disease diagnosis.

关键词： Image segmentation Accuracy Magnetic resonance imaging Computational modeling Modulation Context awareness Robustness Medical diagnosis Cardiovascular diseases Context modeling

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Cooperative neural-adaptive fault-tolerant output regulation for heterogeneous nonlinear uncertain multiagent systems with disturbance

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Science China(Information Sciences) 2021年第7期64卷 181-192页

作者： Shanling DONG Guanrong CHEN Meiqin LIU Zheng-Guang WU College of Electrical Engineering Zhejiang University Department of Electrical Engineering City University of Hong Kong National Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang University Institute for Advanced Study Chengdu University

This paper investigates the cooperative output regulation problem for heterogeneous nonlinear uncertain multiagent networked systems subject to actuator failure, bounded matched or mismatched disturbances or disturbances produced by a given linear exosystem. Accurate information about nonlinearity,actuator failure and disturbance may be completely unknown. First, a distributed finite-time observer is designed to estimate the dynamics of the exosystem on a finite-time interval over a communication ***, a neural-adaptive control protocol is proposed. It is shown that(i) closed-loop multiagent systems are asymptotically stable, with output synchronization errors that tend to zero in the absence of mismatched disturbance, and(ii) the states of the closed-loop multiagent systems and the output synchronization errors are bounded in the presence of mismatched disturbance. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control strategy.

关键词： cooperative output regulation actuator failure matched/mismatched disturbance distributed finite-time observer neural-adaptive control

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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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Chinese control Conference (CCC)

作者： Yiwen Wang Senlin Zhang Meiqin Liu Shanling Dong Ronghao Zheng College of Electrical Engineering Zhejiang University Hangzhou China National Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China

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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UWIA-AODV: Improved Ad-Hoc On-Demand Distance Vector Routing Protocol for Underwater Acoustic Sensor Networks

UWIA-AODV: Improved Ad-Hoc On-Demand Distance Vector Routing...

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Chinese control Conference (CCC)

作者： Xueyi Wang Meiqin Liu Senlin Zhang Shanling Dong National Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China College of Electrical Engineering Zhejiang University Hangzhou China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China

In the past a few years, underwater acoustic networks have developed as a powerful technique used for variety of applications. Ad-Hoc On-Demand Distance Vector (AODV) is a popular and effective routing protocol, while it is not suitable for underwater usage due to the features of underwater acoustic channel such as low data rate, long delay, limited bandwidth and energy. In this paper, we propose an improved AODV based on implicit acknowledgement which employs broadcast features of nodes to overhear packets and retransmit those that fail to be transmitted. In addition, residual energy is considerded for energy balancing. Finally, the in-field experiment results shows that our proposed protocol can select the route with more residual energy for energy balancing. And our proposed protocol also outperforms AODV in terms of throughput and packet discovery ratio. So it is more suitable for underwater scenarios that require high transmission reliability.

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Recent advancements in graphene adsorbents for wastewater treatment:Current status and challenges

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Chinese Chemical Letters 2020年第10期31卷 2525-2538页

作者： MD Faysal Hossain Nasrin Akther Yanbo Zhou State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process East China University of Science and TechnologyShanghai 200237China National Engineering Laboratory for Industrial Wastewater Treatment East China University of Science and TechnologyShanghai 200237China

From emerging pollutants to emerged threat,researchers are continuously looking for promising technologies for wastewater *** has been identified as the most convenient approach for treating wastewater at low-cost and with ***,graphene and its derivatives have gained heightened attention as novel adsorbents because of their unique molecular structure and outstanding physicochemical *** metals,dyes,polycyclic aromatic hydrocarbons(PAHs)and other pollutants,which are widely concerned recently,all show different adsorption *** functional groups,resonating and delocalizedπ-electron system of graphene derivatives lead to the formation of various adsorptive interactions i.e.,π-πinteractions,electrostatic interactions,Hbonding,*** these venomous pollutants,and quarantine them in *** pristine form of graphene subsidiaries tends to exhibit low sorption efficiency due to high propensity of agglomeration,lack of selectivity,hydrophobicity and difficulty in phase separation a fter ***,designing of efficient graphene composites through the surface modification with numerous functional groups,polymers or nanoparticles is an ongoing *** graphene composites are increasingly reported,but the fate of pollutants and adsorption mechanisms are still far to be fully *** review summarizes the recent progresses in the application of graphene-based adsorbents for eliminating a wide range of organic and inorganic pollutants from wastewater.A critical explanation is provided on the synthesis of graphene adsorbents,systematic adsorption and desorption mechanisms along with their pollutant removal performances under different experimental conditions.A brief perspective on upcoming research needs and challenges involved in the designing of high-quality graphene-based adsorbents are highlighted.

关键词： Wastewater Adsorption Graphene composites Interaction mechanism Regeneration

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Co3o4@Mn-Ni(Oh)2 Core-Shell Heterostructure for Hybrid Supercapacitor Electrode with High Utilization

SSRN

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SSRN 2023年

作者： Wang, Guosheng Ding, Yingjie Xu, Zhihua Wang, Geming Li, Zhikun Yan, Zhaoxiong Hubei Key Laboratory of Industrial Fume and Dust Pollution Control Jianghan University Wuhan430056 China School of Environment and Health Jianghan University Wuhan430056 China Provincial Key Laboratory of Plasma Chemistry and Advanced Materials Wuhan Institute of Technology Wuhan430073 China

It is of great importance to rationally design and fabricate electrode materials with high utilization and unexceptionable re-cycling performance in energy storage device including supercapacitors (SCs). Herein, Mn-doped Ni(OH)2 nanosheets with oxygen vacancies in-situ grow on the Co3O4 nanobelts on carbon cloth (CC) to form a core-shell heterostructure (Co3O4@Mn-Ni(OH)2/CC). The obtained Co3O4@Mn-Ni(OH)2/CC electrode has an outstanding specific capacity of 313.4 mA h g–1 (1128.4 C g–1 or 2051.6 F g–1) at 1 A g–1, ca. 6.4 times that of the Ni(OH)2/CC electrode (48.9 mA h g–1). The hybrid supercapacitor (HSC) constructed by activated carbon (AC) and Co3O4@Mn-Ni(OH)2/CC displays a marvelous energy density of 65.5 W h kg−1 at 800 W kg−1, and 93.0% of the capacity retention over 10000 repeated charging/discharging cycles at 5 A g–1, superior to the Co3O4@Ni(OH)2/CC//AC HSC (36.5%) and Mn-Ni(OH)2/CC//AC HSC (53.9%). The results of the characterizations and density functional theory (DFT) calculation show that the Mn-doping and subsequent induced oxygen vacancies promote the conductivity, and inhibit the irreversible phase transition of Ni(OH)2 during the charging/discharging process which contributes to the long-time cycling stability of the electrode. Moreover, the core-shell heterostructure fosters the exposure of active sites and reduces the charge transfer resistance due to the interfacial interaction. This work provides some insight into the rational design and fabrication of electrode materials with high utilization in SCs. © 2023, The Authors. All rights reserved.

关键词： Nickel compounds

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