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Effect of AU Ion Irradiation on Microstructure, Mechanical, and Lead-Bismuth Eutectic Corrosion Properties of Zirconia Coatings with Different Y2o3 Content

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SSRN 2024年

作者： Zhu, Changda Qu, Guofeng Zhou, Mingyang Qiu, Xi Gao, Yang Long, Ziyao Yang, Jijun Key Laboratory of Radiation Physics and Technology of Ministry of Education Institute of Nuclear Science and Technology Sichuan University Chengdu610064 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China

The yttria-stabilized zirconia (YSZ) coatings with 4 ~ 6 mol.% Y2O3 content was irradiated by 6 MeV Au ions with a fluence 6.0[[EQUATION]]1015 ions/cm2. The cubic to monoclinic transformation of ZrO2 is is identified in the Au-irradiated samples. The cavities are observed in the YSZ layer while larger size cavities are found in the 6YSZ layer. LBE corrosion results show that irradiation improves the adhesion and corrosion resistance of the coating due to the fact that irradiation releases the stresses in the coating. Overall, the 4YSZ coating showed the best corrosion resistance and irradiation resistance in the case of heavy ion irradiation. © 2024, The Authors. All rights reserved.

关键词： Yttria stabilized zirconia

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Relaxation and Crystallization of Amorphous Fecraltimo Coatings: Effects on Mechanical Properties and Lead-Bismuth Eutectic Corrosion Resistance

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SSRN 2024年

作者： Yang, Jian Zhou, Mingyang Yang, Jijun Key Laboratory of Radiation Physics and Technology of Ministry of Education Institute of Nuclear Science and Technology Sichuan University Chengdu610064 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610213 China

The microstructure evolution of amorphous FeCrAlTiMo coatings during annealing process, and the effects of structural relaxation and crystallization on its mechanical properties and LBE corrosion resistance are systematically investigated. With increasing annealing temperatures, three coatings with different microstructure, including relaxation and crystallization, could be obtained. The structural relaxation is beneficial to improve the LBE corrosion resistance of the coating, but it is accompanied by the loss of mechanical properties (interface bonding strength and wear resistance). The crystalline coating with multi-phase microstructure of BCC, FCC and HCP ( © 2024, The Authors. All rights reserved.

关键词： Corrosion resistance

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SeaFree-GS: Reconstructing Underwater 3D Scenes With True Appearances

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IEEE Signal Processing Letters 2025年 32卷 2114-2118页

作者： Liu, Shaohua Gao, Ning Fu, Shaowen Zhong, Xiaoqing Li, Hongjue Beihang University School of Astronautics Shenyuan Honors College Beijing100191 China Beihang University School of Astronautics Beijing100191 China Beijing Aerospace Automatic Control Institute Beijing100854 China National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing100854 China China Academy of Space Technology Beijing100094 China Beijing Key Laboratory of System Design for Reusable Launch Vehicle State Key Laboratory of High- Efficiency Reusable Aerospace Transportation Technology China

Reconstructing underwater 3D scenes with accurate appearances is crucial for numerous tasks. However, existing underwater 3D reconstruction methods often fail to restore the true scene appearance due to degradation in underwater images caused by water effects. In this letter, we propose SeaFree-GS, a novel approach leveraging 3D Gaussian Splatting (3DGS) to reconstruct underwater scenes with their true appearances. Specifically, we introduce a Degradation-Aware Dual-Color Modeling strategy, where each Gaussian is assigned an intrinsic color representing the true scene appearance and a viewpoint-dependent degraded color to incorporate water effects. For a given viewpoint, this strategy physically derives the corresponding degraded colors from the intrinsic colors to render the underwater image. To improve reconstruction accuracy, we introduce a Content-Based Loss for selective enhancement of supervision over foreground and background regions, and a Coarse-Grained Depth Loss to enforce additional geometric constraints. Experiments on three datasets demonstrate that SeaFree-GS achieves state-of-the-art performance in Underwater True Appearance Reconstruction, and also performs competitively in Underwater Novel View Synthesis. © 1994-2012 IEEE.

关键词： 3D reconstruction

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design Method of Human-Computer Interactive Interface of MTS Based on DCS of Nuclear Power Plant 5th

Design Method of Human-Computer Interactive Interface of MTS...

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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： Dang, Li-Jun Huang, Jun Ye, Qi Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu Sichuan610213 China

ISBN: (纸本)9789811634550

MTS (maintenance and test software), as an important human-computer interactive tool in DCS of nuclear power plant, plays a crucial role in configuration and management of the engineering applied data, engineering design, system debugging and operational maintenance. With the advent of information age, industrial designers pay more and more attention to interactive design, and user attaches increasing importance to the human-machine interactive experience of products, which puts forward new requirements for the human-machine interactive interface of MTS. This paper takes the human-computer interaction visual design of MTS as the core, through analyzing the human-computer interaction model and requirements of MTS, formulates the overall design scheme of the human-computer interaction system of MTS. According to the overall scheme, a set of human-computer interaction visual design method applied to MTS of DCS in nuclear power plant is proposed. The method and criterion of human-computer interaction design proposed in this paper is very important for the design human-computer interaction of nuclear power plant application software, and also points out the direction of human-computer interaction optimization of MTS mentioned in this paper. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Nuclear power plants

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A Position Probability Prediction Method of Marine Moving Targets for Optimization Search by Satellite

A Position Probability Prediction Method of Marine Moving Ta...

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2024 IEEE International Conference on Control science and systems Engineering, ICCSSE 2024

作者： Zheng, Xiao Peng, Xiaodong Guo, Zhiyuan Qiang, Huimin Zhao, Junbao University of Chinese Academy of Science Laboratory of System Simulation and Concurrent Design Technology National Space Science Center Chinese Academy of Sciences Beijing China Beijing Remote Sensing Information Institute Beijing China

ISBN: (纸本)9798331517199

Marine moving ship target search has great application demand and development prospects in marine surveillance, marine search and rescue, customs anti-smuggling, and other aspects. Satellites are a vital means of searching for marine moving targets. Ground coverage for imaging satellites is relatively limited;the vast marine area makes searching for marine moving ships challenging. Target position prediction, used as the guidance information for satellite detection to reduce the uncertainty of the target position and improve search efficiency, is an essential approach to achieving target optimization search. This paper proposes a target position prediction method based on joint learning of multi-source factors for optimal satellite search of marine moving targets. Firstly, it analyzes the characteristics of marine moving targets and the factors affecting motion. Then, it puts forward the motion prediction model based on a deep neural network, integrating multifactor, like the state of the moving target, environmental attributes such as nautical charts, meteorology and hydrology, and kinematic constraints, to predict the target positional distribution probability. Finally, the target search strategy based on the maximum sum of the distribution probabilities of the satellite coverage area is adopted to improve target detection probability. The experiment results show that the prediction method can realize the target positional distribution probability prediction, reduce the uncertainty search when making the satellite search plan, and improve efficiency. © 2024 IEEE.

关键词： Deep neural networks

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DeepRank: Test Case Prioritization for Deep Neural Networks 35

DeepRank: Test Case Prioritization for Deep Neural Networks

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35th International Conference on Software Engineering and Knowledge Engineering, SEKE 2023

作者： Li, Wei Zhang, Zhiyi Jian, Yifan Liu, Chen Huang, Zhiqiu Collage of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu China School of Marxism Yangzhou University Yangzhou China Ministry Key Laboratory for Safety-Critical Software Development and Verification Nanjing University of Aeronautics and Astronautics Nanjing China

Deep neural networks (DNNs) have been widely used in safety-critical fields such as autonomous driving and medical diagnosis. However, DNNs are easily disturbed to make wrong decisions, which may lead to loss of life or property. Therefore, it is vital to test DNN adequately. In practice, to reveal the incorrect behavior of DNN and improve its robustness, testers usually need massive labeled data to test and optimize DNN. However, labeling test inputs to detect the correctness of DNN predictions is an expensive and time-consuming task that even affects the efficiency of DNN testing. To relieve the labeling-cost problem, we propose DeepRank, a test case prioritization technique based on cross-entropy loss. The key idea of DeepRank is that the higher the loss value of a test case relative to the DNN, the more likely it is to be mispredicted and the more conducive it is to improve the robustness of the DNN through retraining. Therefore, the cross-entropy loss value can be used for test case prioritization. We experimentally validate our approach on two datasets and three DNNs models. The experimental results demonstrate that DeepRank is significantly better than existing test case prioritization methods regarding fault-revealing capability and retraining effectiveness. © 2023 Knowledge systems Institute Graduate School. All rights reserved.

关键词： Deep neural networks

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Active Flow Control of Hydrodynamic Characteristics around a Square Cylinder with Symmetric Synthetic Jets 34th

Active Flow Control of Hydrodynamic Characteristics around a...

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34th International Ocean and Polar Engineering Conference, ISOPE 2024

作者： Ding, Hao Liu, Mingyue Zhou, Jihui Zhu, Shenglong State Key Laboratory of Ocean Engineering Shanghai Jiao Tong University Shanghai China SJTU YaZhou Bay Institude of Deepsea Science and Technology Sanya China System Design Institute of Hubei Aerospace Technology Academy Wuhan China

ISBN: (纸本)9781880653784

To explore the active control method of the square cylinder wake field modification, a self-developed piston-driven synthetic jet actuator is used to generate periodic blowing and suction jets through the slits to affect the external flow field. The flow characteristics around the square cylinder controlled by synthetic jet is experimentally investigated with the force measuring system and Particle Image Velocity (PIV) technique. The statistical fluid forces, the frequency characteristics, and the time-averaged flow flied are compared with different control parameters, i.e. jet exit angle (β), the momentum coefficient (Cμ), and the excitation frequency (f*). With control, dramatic reduction in CLrms (up to 61%) is attained and the corresponding value of CD is 12% at β =45°. Narrower and longer backflow region represents a decrease in flow-induced forces. © 2024 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： Jets

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Application and Practice of Smart Education technology in Blended Teaching of Engineering Drawing Course 24

Application and Practice of Smart Education Technology in Bl...

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9th International Conference on Distance Education and Learning, ICDEL 2024

作者： Xu, Jinyou Tian, He Wang, Xiaofei Xue, Yahong Li, Ling Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin University of Technology China School of Environmental Science and Safety Engineering Tianjin University of Technology Tianjin China

ISBN: (纸本)9798400716805

The expeditious progress of information technology has encouraged the digital enhancement of the educational sector. To remedy the issues of the traditional teaching mode, a blended teaching mode of engineering drawing course has been developed with the use of smart education technology. Based on the Outcomes-based Education ( OBE ), the teaching objectives and teaching contents of the course are reconstructed by using the method of reverse design and forward implementation. By leveraging the synergy of online and offline, virtual and real, and quantitative and qualitative evaluation, a blended teaching approach that is both student-centered and teacher-guided is realized. A course knowledge graph has been built, offering fresh concepts for accomplishing personalized learning for students. The teaching practice shows that the blended teaching mode based on intelligent education has created a multi-dimensional autonomous learning space and personalized learning path for students, which effectively improves the enthusiasm and initiative of students to participate in teaching activities, and also improves the information level of teaching process and management, and promotes the organic integration of teaching and learning. © 2024 ACM.

关键词： Contrastive Learning

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Disorders in fluid filled pipeline structure with elastic helmholtz resonators 29

Disorders in fluid filled pipeline structure with elastic he...

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2022 29th International Conference on Nuclear Engineering, ICONE 2022

作者： Zeng, Qingna Wang, Donghui Zang, Fenggang Zhang, Yixiong Wang, Bihao Yuan, Zhihao Science and Technology on Reactor System Design Technology Laboratory Chengdu610213 China Nuclear Power Institute of China Chengdu610213 China College of Shipbuilding Engineering Harbin Engineering University Harbin150001 China

ISBN: (纸本)9780791886359

This paper studies the influence of hybrid disorders on acoustic transmission characteristic in pipeline with periodic elastic HRs. Band gap structures (BGs) for infinite period are investigated by transfer matrix method and finite element method respectively, and fit well with the corresponding transmission loss (TL) for finite regular periods. By introducing a certain degree of uncertainty level, Interval analysis method is used to convert uncertain parameter problems into two deterministic models. Frequency response function (FRF) for near-periodic structure with single disorder and BGs for quasiperiodic structure with multiple disorders considering cavity radius and periodic length are investigated. The existence of disorders in periodic structure would always reduce attenuation interval and intensity, some disturbance would even change the original acoustic transmission characteristic and excite completely new attenuation zones. The sensitivity of pipeline acoustic vibration transfer characteristic to disorder parameter depends on attenuation mechanism, as for periodic elastic HRs pipeline, acoustic propagation stability is more sensitive to characteristic of locally resonant unit. The work in this paper enriches the stability analysis of pipeline with elastic HRs, which would provide theoretical reference for noise and vibration reduction design in practical engineering applications. © 2022 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Transfer matrix method

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A Transformer-Based Time Series Prediction Model with Contrastive Learning for Nuclear Power system State Monitoring

A Transformer-Based Time Series Prediction Model with Contra...

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Prognostics and system Health Management Conference (PHM-Qingdao)

作者： Pengfei Gou Daiwei Zheng Lei Tang Mengjuan Liu School of Information and Software Engineering University of Electronic Science and Technology of China UESTC Chengdu China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China NPIC Chengdu China

ISBN: (数字)9798350354010

ISBN: (纸本)9798350354027

Prognostics and Health Management (PHM) is currently the mainstream solution for the condition monitoring and maintenance of industrial systems. In PHM, the system condition is monitored by monitoring the operational status parameters of the system to diagnose equipment faults, predict the remaining useful life, etc. Utilizing sequential operational status parameters to complete prediction and classification tasks is usually modeled as a time series processing task. Therefore, a high-performance time series prediction model is crucial for PHM. This paper focuses on the use of time series prediction models to achieve the prediction of key state parameters of the nuclear power system. However, there are still some challenges when directly applying existing time series prediction models to industrial systems. First, obtaining operational data on the nuclear power system is relatively difficult, resulting in a small amount of training data, which causes many models to face the risk of insufficient training or overfitting. Second, most of the existing time series prediction models are composed of high- and low-frequency decoupling modules, while the operational data of nuclear power systems often have fewer high-frequency components, making it difficult for many existing SOTA models to achieve good results. In order to address these challenges, we have developed a Transformer-based time series prediction model with contrastive learning for monitoring the status of nuclear power systems. We evaluated the new model on three nuclear power simulation datasets and four power transformer datasets. The experimental results show that the new model's performance is superior to baseline models. We also proved the effectiveness of our improvement through ablation experiments.

关键词： Training Time series analysis Training data Contrastive learning Predictive models Data models Power systems Power transformers Prognostics and health management Monitoring

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