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SSRN 2023年

作者： Yin, Chunyu Li, Wenxuan Qiu, Xi Luo, Bin Huang, Hongtao Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China Sino-French Institute of Nuclear Energy and Technology Sun Yat-Sen University Zhuhai519082 China

High entropy alloys have become potential candidate materials for high temperature nuclear reactor due to its high strength, high hardness, excellent corrosion resistance and radiation resistance, therefore the compatibility of hydrogen isotopes with HEAs becomes a key issue that has attracted a lot of attentions. The deuterium permeation behavior of the CoCrMnFeNi high entropy alloy after oxidation at 550 °C for 24 h was investigated by gas-phase deuterium permeation testing, SEM, X-ray diffraction methods in this paper. The results show that a dense oxide film with a thickness of about 1μm was formed on the surface of the sample after oxidation. The outer layer of the oxide film is rich in Mn2O3 and the inner layer is rich in Cr2O3. The deuterium permeability of the CoCrMnFeNi sample after oxidation was reduced by an order of magnitude and was 1/7-1/17 times as high as that for the unoxidized one. © 2023, The Authors. All rights reserved.

关键词： Entropy

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Identification of the non-stationarity of extreme temperature events and teleconnections with solar activity and large-scale atmospheric circulation: A case study in the Yangtze River Economic Belt

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Journal of Earth science 2024年

作者： Lin Zhang Jingyun Ling Shengzhi Huang Hongbin Zhan Yi Wu Menggui Jin Qiang Huang State Key Laboratory of Eco-hydraulics in Northwest Arid Region， Xi'an University of Technology College of Design and Engineering， National University of Singapore Yinshanbeilu Grassland Eco-Hydrology National Observation and Research Station， China Institute of Water Resources and Hydropower Research Department of Geology and Geophysics， Texas A&M University， College Station School of Earth System Science， Tianjin University School of Environmental Studies， China University of Geosciences

In recent decades， extreme climate events have become a major problem worldwide. To understand the uncertainty in the response of extreme events to global warming， regional assessments are required for various climatic and geographic regions. The spatiotemporal distribution of extreme temperature events in the Yangtze River Economic Belt (YREB) from 1960 to 2019， including interannual changes and their teleconnections with solar activity and large-scale atmospheric circulation， were analyzed using eight indices of extreme temperature events. Over the past six decades， the climate in the YREB region has seen a warming trend， characterized by an increase in extreme warm events and a decrease in extreme cold events. The extreme temperature indices exhibit strong spatial variability. The warm extremes display a significant upward trend across the YREB， while cold extremes are primarily concentrated in the western part of the region. In recent decades， both warm and cold extremes have significant interannual variations， and these events predominantly oscillate over periods of less than four years. After 1985， the relationship between El Ni?o-Southern Oscillation (ENSO)， Arctic Oscillation (AO)， Pacific Decadal Oscillation (PDO) and extreme temperature events has changed significantly compared with pre-1985， and the direction of the phase angle can determine the positive and negative effects of the two time-series. ENSO， AO and PDO mainly have positive impacts on extreme temperature events， with ENSO and AO exerting greater impacts than PDO. In contrast， solar activity mainly has a negative impact on these events. Furthermore， the notable interdecadal changes in extreme temperature events， especially warm extremes， may be caused by the shift in the PDO phase. Therefore， the results of the study are important for the YREB region to take effective measures to mitigate the potential impacts of human activities on regional warming.

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Study on the Load Following Control of SMR with Flexible Load 5th

Study on the Load Following Control of SMR with Flexible Loa...

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5th International Symposium on Software Reliability, Industrial Safety, Cyber Security and Physical Protection of Nuclear Power Plant, ISNPP 2020

作者： Liu, Ming-Ming Sun, Ao-Di Qiu, Lei-Lei Zhang, Ru Wei, Xin-Yu Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610041 China Key Laboratory of Advanced Nuclear Energy and Technology and Shaanxi Engineering Research Center of Advanced Nuclear Energy Xi’an Jiaotong University Xi’an710049 China

ISBN: (纸本)9789811634550

The load following requirement will be increased greatly while the Small Modular reactor (SMR) is used for isolated island operation mode. In order to improve the load following ability of the system, the flexible load (FL) is presented in this study to follow the electricity load during load follow. The definition of FL is a type of power consuming system that can change the needed power discretionary. For example, the hydrogen manufacture plant, the desalination facility, the district heating system, and other industrial process heat supply system are all FLs. In order to analyze the dynamic characters of the system, pressurized water reactor (PWR) type SMR (comprised with reactor core and once-through steam generator), balance of plant (BOP), and FL are modeled first. Based on these dynamic models, a SMR-FL dynamic simulation program is built in MATLAB/Simulink environment. According to different system characteristics, two types of FL are considered, and the related load allocation control systems are designed. A typical electricity load is used to verify the designed control systems for the two types of FL. The simulation results show that the designed control systems can achieve load following by adjusting the power consuming of FL and maintaining a constant or moderate changing output of SMR. Obviously, this character can make the SMR-FL system more flexible and efficiency. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Control systems

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An Improved Task Planning Method for Unmanned Swarms with Coupled Physical and Logical Constraints

An Improved Task Planning Method for Unmanned Swarms with Co...

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2024 IEEE International Conference on Unmanned systems, ICUS 2024

作者： Chen, Xiubin Zhang, Lei Xu, Fang Yao, Weiran School of Astronautics Harbin Institude of Technology Harbin China Wuhan 2nd Ship Design and Research Institute Wuhan China Marine Military Intelligence Innovation Institute CSSC Systems Engineering Research Institute Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (纸本)9798350384185

Traditional task allocation methods for unmanned swarm systems ignore the effects of actual paths, resulting in estimation accuracy *** paper formulates task planning problem by incorporating physical and logical constraints, and establishes an integrated framework of task allocation and path ***-based search method is used to address path planning with physical constraints.A genetic algorithm is employed to solve multi-traveling salesman allocation problem.A bounded suboptimal optimization, a data dictionary, and an island model are introduced to accelerate the convergence speed of the genetic *** experiments verify that compared to the decoupled task planning methods, the proposed method improves task execution efficiency and remains adaptability to various complex spatial maps. © 2024 IEEE.

关键词： Genetic algorithms

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A Target Trajectory Prediction Method in Air Combat Based on Wavelet-Attention-GRU Under the Frenet Frame

A Target Trajectory Prediction Method in Air Combat Based on...

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Zhang, An Mao, Zeming Xu, Haiyu Fan, Qiucen Bi, Wenhao Yan, Yuwen School of Aeronautics Northwestern Polytechnical University Department of Integrated Technology and Control Engineering Shaanxi Xi'an710072 China Northwestern Polytechnical University National Key Laboratory of Aircraft Configuration Design Shaanxi Xi'an710072 China Shanghai Zhongchuan SDT-NERCCo. Ltd. Department of Mission System Shanghai201114 China

ISBN: (纸本)9781665410205

The target trajectory prediction method can assist pilots in situation awareness and provide support for decision-making to improve the capacity to gain the advantage during high dynamic within-visual-range air combat. Aiming at the problem of traditional methods based on the Cartesian frame, such as the low utilization of training data and the weak generalization, and the low accuracy of the existing time series prediction models, a target trajectory prediction method in air combat based on Wavelet-Attention-GRU under the Frenet frame is proposed. In this method, the air combat features are described via the spatial trajectory curve based on the Frenet frame;the target trajectory prediction model is established by combining the GRU network with the improved multi-head self-attention mechanism by adding wavelet transform. Finally, the one-to-one within-visual-range air combat dataset obtained via the high-fidelity air combat simulator is applied to train and test the trajectory prediction model. © 2024 IEEE.

关键词： Trajectories

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MDDA: A Multi-scene Recognition Model with Multi-dimensional Domain Adaptation 4

MDDA: A Multi-scene Recognition Model with Multi-dimensional...

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4th IEEE International Conference on Electronics technology, ICET 2021

作者： Wan, Naijia Zhang, Changhua Chen, Qian Li, Hao Liu, Xiaobo Wei, Xuedong 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 Science and Technology on Reactor System Design Technology Laboratory Chengdu China

ISBN: (纸本)9781728176734

Optical Character Recognition is widely used in scenarios from license plate recognition, chip detection to text translation. However, in some special scenarios, there are very few data for training or the target datasets are not marked. This paper mainly aims to establish a multi-scene text recognition model that can achieve accurate results even when the target test dataset is not marked. The model reduces the distance between domains at the feature level by using an adversarial loss and flipping the gradient. For the adversarial loss, each letter has a different domain discriminator to align the features at the character level. We also align the source domain features and target domain features in the background. Experimental results show that our model achieves good performance when the training dataset and test dataset have domain shift, and suggest possible scenarios for potential applications. © 2021 IEEE.

关键词： Optical character recognition

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Dynamic failure of aramid paper honeycomb under intermediate strain rate loading

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Thin-Walled Structures 2025年 215卷

作者： Chen, Meiduo Zhang, Xianglin Xu, Songlin Ma, Hao Yuan, Liangzhu Xie, Yushan Zhang, Xiaoman Wang, Pengfei University of Science and Technology of China Department of Modern Mechanics CAS Key Laboratory for Mechanical Behavior and Design of Materials Anhui Hefei230027 China Beijing Institute of Space Long March Vehicle Beijing100076 China National Key Laboratory of Science and Technology on Test Physics and Numerical Mathematics Beijing100076 China

Investigation of the transformation process of failure mechanism for materials and structures under intermediate strain rate loading is of great significance. To achieve intermediate strain rate loading, a novel experimental technique is proposed using a high-speed-rotating eccentric cam to compress the specimen. The particle velocities and the stresses at both ends of the specimen are measured by the velocity interferometer system for any reflector (VISAR) and by the semiconductor strain gauges, respectively. The paper honeycomb specimens with four thicknesses (i.e. 2 mm, 3 mm, 5 mm, and 10 mm) are tested under strain rates ranging from 0.1 to 15 s-1. Local deformation evolution in the specimen is captured based on high-speed photography and analyzed by the digital image correlation method (DIC). The deformation under intermediate strain rate loading is distinguished by higher particle velocity and lower particle acceleration, which is different from those under the static compression (at lower strain rates) and the Split Hopkinson Pressure bar (SHPB) impacting (at higher lower strain rates). Based on the DIC results, the abnormal size effect of specimen 2 mm is due to the competition between in-plane shear failure and out-of-plane buckling. The theoretical model is then established by introducing two main parameters, i.e. the lateral weakening factor ξ and the dynamic parameter k, to describe respectively the effects of in-plane shearing and strain rate on the out-of-plane wall buckling, and the critical stress for specimen buckling is obtained. The results show that the buckling deformation and the half-wave number for buckling are sensitive to the two parameters. This work provides theoretical and experimental references for the study of thin-walled structures under intermediate strain rate. © 2025 Elsevier Ltd

关键词： Fracture mechanics

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Review of Research Advances in CFD Techniques for the Simulation of Urban Wind Environments

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Fluid Dynamics & Materials Processing 2022年第2期18卷 449-462页

作者： Pengfei Ju Mingrui Li 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 School of Energy and Power Engineering Shandong UniversityJinan250061China Shandong Engineering Laboratory for High-Efficiency Energy Conservation and Energy Storage Technology&Equipment Shandong UniversityJinan250061China

Computational fluid dynamics(CFD)has become the main method for the prediction of the properties of the external wind environment in cities and other urban contexts.A review is presented of the existing literature in terms of boundary conditions,building models,computational domains,computational grids,and turbulence *** specific issues,such as the accuracy/computational cost ratio and the exploitation of existing empirical correlations,are also examined.

关键词： Computational fluid dynamics wind environment pre-processing settings

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An interpretable machine learning-based model of turbulent Prandtl number for supercritical CO2 under buoyancy

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Applied Thermal Engineering 2025年 274卷

作者： Zhang, Ruizeng Yang, Zhengwei Liu, Yu Qiu, Qinggang Zhu, Xiaojing Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education Dalian University of Technology Dalian116024 China 703 Research Institute China State Shipbuilding Corporation Harbin150010 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China

Existing studies identify the failure of turbulent heat flux modeling—particularly the constant turbulent Prandtl number (Prt) assumption—as the primary cause of inaccurate heat transfer deterioration (HTD) predictions in supercritical fluids. To address this, we propose a dynamic Prt prediction framework based on interpretable machine learning (ML) to elucidate Prt evolution under buoyancy effects. The model comprises a Prt distribution framework integrating the thermophysical parameter (Pr) and a comprehensive factor fsp that captures system parameter influences, and an ML module that nonlinearly maps multi-parameter effects into fsp, overcoming the limitations of traditional empirical correlations. Results show that the model significantly improves HTD prediction accuracy and reveals that strong buoyancy necessitates a lower Prt to compensate for the turbulent diffusion attenuation. SHAP-based interpretability analysis further quantifies parameter influence hierarchies: heat flux and mass flow rate dominate HTD, inlet temperature, and pressure act independently without interfering with the effects of other parameters on heat transfer, and diameter amplifies the negative effects of heat flux and mass flow rate through synergistic interactions. This study establishes a high-accuracy, mechanically interpretable modeling paradigm for optimizing supercritical systems. © 2025 Elsevier Ltd

关键词： Buoyancy

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Joint DNN Partition and Thread Allocation Optimization for Energy-Harvesting MEC systems

Joint DNN Partition and Thread Allocation Optimization for E...

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design, Automation and Test in Europe Conference and Exhibition

作者： Yizhou Shi Liying Li Yue Zeng Peijin Cong Junlong Zhou School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China National Key Laboratory for Novel Software Technology Nanjing University Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China Key Laboratory of Embedded System and Service Computing (Tongji University) Ministry of Education Shanghai China

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

Deep neural networks (DNNs) have demonstrated exceptional performance, leading to diverse applications across various mobile devices (MDs). Considering factors like portability and environmental sustainability, an increasing number of MDs are adopting energy harvesting (EH) techniques for power supply. However, the computational intensity of DNNs presents significant challenges for their deployment on these resource-constrained devices. Existing approaches often employ DNN partition or offloading to mitigate the time and energy consumption associated with running DNNs on MDs. Nonetheless, existing methods frequently fall short in accurately modeling the execution time of DNNs, and do not consider to use thread allocation for further latency and energy consumption optimization. To solve these problems, we propose a dynamic DNN partition and thread allocation method to optimize the latency and energy consumption of running DNNs on EH-enabled MDs. Specifically, we first investigate the relationship between DNN inference latency and allocated threads and establish an accurate DNN latency prediction model. Based on the prediction model, a DRL-based DNN partition (DDP) algorithm is designed to find the optimal partitions for DNNs. A thread allocation (TA) algorithm is proposed to reduce the inference latency. Experimental results from our test-bed platform demonstrate that compared to four benchmarking methods, our scheme can reduce DNN inference latency and energy consumption by up to 37.3% and 38.5%.

关键词： Energy consumption Instruction sets Heuristic algorithms Artificial neural networks Predictive models Prediction algorithms Inference algorithms Partitioning algorithms Resource management Optimization

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