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SSRN 2023年

作者： Xu, Wei Tang, Longchang Zhao, Ningkang Ouyang, Kun Zeng, Chang Liu, Xiaojing He, Xiaoqiang College of Smart Energy Shanghai Jiao Tong University Shanghai200240 China Shanghai200240 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610041 China

Surface modification is of critical interest to enhance boiling heat transfer in terms of heat transfer coefficient or critical heat flux (CHF), which is significantly affected by distinct surface morphology and wettability and it can improve the efficiency and safety of equipment. Furthermore, actual service environment may cause severe corrosion to the processed structured surfaces while its consequence on boiling heat transfer is still obscure. In this research, comprehensive researches are conducted to unravel corrosive effect on metallic samples made of stainless steel (SS) and Inconel materials with microstructures. Different constructions (i.e., microgroove, microcavity and micropillar array) and characteristic dimensions (~20, 50 μm) of microstructure, various duration time (up to 300 days) and pH values (~7.0 to 8.5) of corrosive environment are compared thoroughly. Conclusions can be drawn that not all microstructures can enhance pool boiling heat transfer characteristics, especially in terms of CHF values. More importantly, CHF value of SS microgroove sample firstly increases from 60.94 to 94.09 W·cm-2 in 50 days, then decreases to 47.77 W·cm-2 in 300 days, which can be attributed to competition result between formation of hierarchical micro/nano structure with enhancing wicking capability and chemistry condition with increasing contact angle. In addition, distinct bubble dynamics during pool boiling is also analyzed. The insights obtained from this article can be used to guide surface modification method and to reveal evolvement rule of engineered metallic surface in highly corrosive and harsh boiling heating transfer environment. © 2023, The Authors. All rights reserved.

关键词： Corrosive effects

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Larger Recovery Strain in a Conisi Alloy Due to Enhanced Reversibility of FccHcp Martensitic Transformation

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SSRN 2023年

作者： Liao, Qi Wang, Dian Yang, Xiao He, Wei Yang, X. Peng, H.B. Wen, Y.H. School of Mechanical Engineering Sichuan University Chengdu China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu China School of of Mechanical Engineering Hebei University of Technology Tianjin China School of Manufacturing Science & Engineering China

It is not clear how coherent ordered nanoparticles affect characteristics of FCCHCP martensitic transformation in disordered alloys. In this paper, the precipitations of coherent ordered nanoparticles and their effects on the FCCHCP martensitic transformation were systematically investigated in a solution-treated Co24Ni6Si shape memory alloy. The results showed that both the coherent ordered L12 structured and L11 structured nanoparticles could precipitate even in the solution-treated Co24Ni6Si alloy followed by water quenching. The L12 structured nanoparticles strongly hindered the occurrence of stress-induced HCP martensitic transformation and its reverse transformation, but their hindrance dramatically reduced with the decrease of size when below 1.5 nm. The coherent ordered nanoparticles did not convert the nonthermoelastic FCCHCP martensitic transformation to the thermoelastic ones owing to absence of group-subgroup relation between the parent phase and martensite. A maximal recovery strain of 6.7% was obtained after only aging at 1073 K for 1 min. This value was 1~2% higher than the reported maximal ones in conventional FeMnSi-based alloys subjected to complicated thermomechanical treatments. The enhanced reversibility of HCP martensitic transformation could account for this larger recovery strain by the ultrafine coherent ordered L12 structured nanoparticles. © 2023, The Authors. All rights reserved.

关键词： Martensitic transformations

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An Improved Method for Underwater Image Super-Resolution and Enhancement 4

An Improved Method for Underwater Image Super-Resolution and...

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4th IEEE International Conference on Electronics technology, ICET 2021

作者： Li, Hao Zhang, Changhua Wan, Naijia Chen, Qian Wang, Donghun Song, Danrong University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu China University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu China Technology Laboratory Nuclear Power Institute of China Science and Technology on Reactor System Design Chengdu China

ISBN: (纸本)9781728176734

Underwater object detection and recognition are still challenging because of the degradation caused by the complex underwater imaging environment and lighting conditions. Aiming at the problems of the simultaneous enhancement and super-resolution (SESR), a method with single image super-resolution and enhancement of underwater imagery is proposed. Firstly, an underwater image super-resolution algorithm is proposed to remove blurring, and then an end-to-end underwater image enhancement network is used to compensate for color casts and produce natural color enhancement images. In addition, we verify the effectiveness of the proposed model through qualitative analysis and quantitative experiments and compare the performance with several state-of-the-art models, which show that the proposed method performs better. © 2021 IEEE.

关键词： Image enhancement

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Two-dimensional CuO nanosheets-induced MOF composites and derivatives for dendrite-free zinc-ion batteries

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纳米研究（英文版） 2023年第5期16卷 6881-6889页

作者： Guoqiang Yuan Yang-Yi Liu Jun Xia Yichun Su Wenxian Wei YinBo Zhu Yang An HengAn Wu Qiang Xu Huan Pang School of Chemistry and Chemical Engineering Yangzhou UniversityYangzhou 225002China School of Chemistry and Chemical Engineering Yangzhou UniversityYangzhou 225002China School of Electrical Engineering Engineering Technology Research Center of Optoelectronic Technology ApplianceTongling UniversityTangling 244061China CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern MechanicsCAS Center for Excellence in Complex System MechanicsUniversity of Science and Technology of ChinaHefei 230027China Department of Materials Science and Engineering SUSTech Academy for Advanced Interdisciplinary StudiesSouthern University of Science and TechnologyShenzhen 518055China

Uncontrollable dendrite growth and side reactions resulting in short operating life and low Coulombic efficiency have severely hindered the further development of aqueous zinc-ion batteries(AZIBs).In this work,we designed to grow zeolitic imidazolate framework-8(ZIF-8)uniformly on CuO nanosheets(NSs)and prepared carbon-coated CuZn alloy NSs(CuZn@C NSs)by calcination under H2/Ar *** reflected by extended X-ray absorption fine structure(EXAFS),density functional theory(DFT),and in-situ Raman,the Cu-Zn and Zn-N bonds present in CuZn@C NSs act as zincophilic sites to uniformly absorb Zn ions and inhibit the formation of Zn *** the same time,CuZn@C NSs hinder the direct contact between zinc anode and electrolyte,preventing the occurrence of side *** impressively,the symmetric cells constructed with CuZn@C NSs anodes exhibited excellent zinc plating/exfoliation performance and long life cycle at different current densities with low voltage *** addition,low polarization,high capacity retention,and long cycle life over 1000 cycles at 5 A·g-1 were achieved when CuZn@C NSs were used as anodes for CuZn@C/V2O5 full cells.

关键词： two-dimensional CuO nanosheet metal-organic frameworks (MOFs)-based composites carbon-coated CuZn alloy nanosheets dendrite-free zinc-ion battery

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Semantic Segmentation of Substation Scenes Using Attention-Based Model 4

Semantic Segmentation of Substation Scenes Using Attention-B...

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4th IEEE International Conference on Electronics technology, ICET 2021

作者： Chen, Qian Zhang, Changhua Li, Hao Wan, Naijia Wang, Donghui Xu, Bin University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu China University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu China Nuclear Power Institute of China Science and Technology on Reactor System Design Technology Laboratory Chengdu China

ISBN: (纸本)9781728176734

Inspection robots are widely used in transformer substation for inspection tasks. In order to complete the task, the robots need to understand and recognize road scenes. However, the transformer substation contains lots of similar and small equipment, which are difficult to recognize. To address this problem, we propose a semantic segmentation model to recognize road scenes. Specifically, our proposed model discriminates the equipment by leveraging multi-view method. We use attention mechanism to strengthen the relationship between pixels that belong to an individual category. Compared with previous methods, our approach achieves a good performance in a new dataset from a transformer substation and shows robustness in recognizing equipment of transformer substation. © 2021 IEEE.

关键词： Roads and streets

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Modeling and Program Development of Supercritical CO2 Sub-Channel Based on Modelica Language

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SSRN 2023年

作者： Guo, Jia Ming, Yang Zhao, Fulong Fang, Huawei Yin, Jingwei Tian, Ruifeng College of Nuclear Science and Technology Harbin Engineering University Harbin150001 China Heilongjiang Provincial Key Laboratory of Nuclear Power System & Equipment Harbin Engineering University Harbin150001 China Key Laboratory of Nuclear Reactor System Design Technology of China Nuclear Power Research and Design Institute Chengdu610000 China

Small nuclear reactor (SMR) system has many advantages, including low construction cost, short construction period and fast economic benefits. SMR has broad prospects in power supply in remote areas, small power grids, low-temperature heating, nuclear hydrogen production, seawater desalination, nuclear powered ships, etc. In order to study the hydraulics and thermal parameters of supercritical carbon dioxide as coolant in SMR, this paper developed a supercritical carbon dioxide reactor sub-channel analysis program based on Modelica language. Based on the sub-channel analysis method, the reactor coolant flow channel is divided in several control bodies, then the program calculates hydraulics and thermal parameters of each control body. In order to verify the correctness of the model and program, sub-channel program will calculate the axial temperature distribution, radial temperature distribution, coolant flow rate and power level under steady-state conditions. Then compare these calculations with KAIST MMR in Korea. In the transient characteristic analysis, this paper will analyze the reactor power increase, reactivity insertion and coolant flow loss accident, then evaluate the safety performance of the reactor. This paper relies on theoretical modeling and program development method, studying the sub-channel thermal hydraulic characteristics of steady-state and transient conditions, which provides theoretical reference and program support for the study of transient response characteristics and safety characteristics of supercritical carbon dioxide reactor. © 2023, The Authors. All rights reserved.

关键词： Temperature distribution

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Interactive Cloud Detection Based on Dynamic Mode Decomposition

Interactive Cloud Detection Based on Dynamic Mode Decomposit...

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2024 International Conference on Information technology, Data science, and Optimization, I-DO 2024

作者： Li, Yilong Yang, Lu Qiu, Xiaobin Bi, Chongke Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China Tianjin Key Laboratory for Oceanic Meteorology and Tianjin Institute of Meteorological Science Tianjin China Tianjin University Tianjin China

ISBN: (纸本)9798400709180

Cloud detection can address data quality and analytical accuracy issues caused by cloud cover in satellite imagery, significantly enhancing image usability. Existing cloud detection methods still have the problem of detecting a certain amount of ground and sea surface as clouds, as well as some cloud regions that are missed, resulting in a decrease in the accuracy of cloud detection. Aiming at the above problems, an interactive cloud detection method based on Dynamic Mode Decomposition is proposed. Based on the fact that clouds are constantly moving, the dynamic mode decomposition can be utilized to detect the characteristics of moving objects, and the dynamic clouds are detected, avoiding the detection of the ground and sea surface as clouds. Although static clouds rarely appear, to ensure the robustness of the algorithm, we design an interactive static cloud detection algorithm for the users, which solve the problem of missed detection and further improves the accuracy of cloud detection. To assess the effectiveness of the algorithm, the four different types of clouds of floccus, undulatus, vortex clouds, and stratocumulus are detected, the experimental outcomes demonstrate the effectiveness and robustness of the algorithm. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Dynamic mode decomposition

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Numerical Study on the Impact Characteristics of a Single Molten Lead Bismuth Droplet on Water

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SSRN 2024年

作者： Lin, Yue Zhang, Dalin Chen, Yutong Zhang, Xisi Deng, Jian Du, Peng Tian, Wenxi Qiu, Suizheng Su, Guanghui Department of Nuclear Science and Technology State Key Lab. of Multiphase Flow in Power Engineering Shaanxi Key Lab. of Advanced Nuclear Energy and Technology Xi’an Jiaotong University No.28 Xianningxilu Beilinqu Shaanxi Xi’an710049 China Institute of Reactor Engineering Technology China Institute of Atomic Energy Beijing102413 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Sichuan Chengdu610213 China

As an important link in the possible occurrence of steam explosions, the interaction between molten materials and coolant is of great significance for safety analysis in severe accidents of nuclear reactors. This study is based on the two-dimensional multiphase and multi-component fluid dynamics code ACENA to model the process of single molten lead bismuth droplet impacting a water tank and obtain the velocity changes of the molten droplet as it moves through the water tank. Furthermore, a sensitivity analysis of relevant factors such as the heat transfer area fraction and drag coefficient of the droplet is carried out. To verify models in ACENA, the computation results are compared to experimental data. It is demonstrated that the overall trend of the velocity curve acquired by the ACENA code during the interaction between a molten lead bismuth droplet and water is consistent with the experimental results. The droplet falling velocity increases with the increase in droplet temperature when the temperature of water is the same, and the droplet falling velocity increases with the increase of water temperature at the same droplet temperature. The simulation results by ACENA code for MFCI are in good agreement with experiments which verifies the accuracy of relevant models in ACENA. It can provide an effective means for safety analysis of nuclear reactors in China. © 2024, The Authors. All rights reserved.

关键词： Drops

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Few-shot gearbox fault diagnosed based on meta-learning and time convolution network

Few-shot gearbox fault diagnosed based on meta-learning and ...

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2022 Chinese Automation Congress, CAC 2022

作者： Dai, Yuan Ou, Yanghui Hu, Junwei Ping, Zuowei Xu, Xinghua Zhang, Yong Wuhan University of Science and Technology School of Information Science and Engineering Wuhan China Wuhan Second Ship Design and Research Institute Wuhan China Naval University of Engineering National Key Laboratory of Science and Technology on Vessel Integrated Power System Wuhan China

ISBN: (纸本)9781665465335

In order to resolve the problem that the traditional fault diagnosis methods can not accurately diagnose under complex working conditions and few fault data, a fault diagnosis method based on meta-learning and time convolution network (TCN) is proposed in this paper. Firstly, Ensemble Empirical Mode Decomposition-Independent Component Analysis (EEMDICA) is used to denoise the original signals under different working conditions, and the acquired signals are randomly sampled to form meta tasks according to the meta-learning protocol. Through the TCN model training, the priori knowledge is obtained by optimizing the initialization parameters. The knowledge is used to improve accuracy in unforeseen condition tasks. Finally, simulation experiments are carried out on the gearbox dataset. The results indicate that the method has advantages in solving the fault classification problem of few shot gearbox under complex working conditions. © 2022 IEEE.

关键词： Empirical mode decomposition

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TICNet: Three-Branch Real-Time Semantic Segmentation Network with Intensive Compensation of Railway Track Scenes 5

TICNet: Three-Branch Real-Time Semantic Segmentation Network...

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5th International Conference on Machine Learning and Computer Application, ICMLCA 2024

作者： Bai, Yiwen Yang, Lu Zhang, Lei Song, Yajing School of Transportation Science and Engineering Beihang University Beijing102206 China School of Mechanical Engineering Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Tianjin300384 China Traffic Control Technology Co. Ltd. Beijing China

ISBN: (纸本)9798331530334

With the rapid development of railway traffic system, real-time semantic segmentation plays a crucial role in railway track scene monitoring. However, most of the existing methods use lightweight convolution to reduce the computational complexity, which results in reduced accuracy. To solve this problem, this paper proposes a real-time semantic segmentation network called TICNet, which is specifically used for accurate segmentation of railway track scenes. TICNet uses a novel three-branch structure designed for efficient feature extraction and accurate segmentation. Results on the RailSem19 dataset show that TICNet has a segmentation accuracy of 62.36% mIoU with an inference speed of 81.2 FPS, which is significantly better than many existing methods. © 2024 IEEE.

关键词： Semantic Segmentation

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