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Burnup performance analysis for candidate materials of the LWR accident tolerant control rod 14

Burnup performance analysis for candidate materials of the L...

14th International Nuclear Fuel Cycle Conference, GLOBAL 2019 and Light Water reactor Fuel Performance Conference, TOP FUEL 2019

作者： Liu, Yong Li, Mancang Yu, Yingrui Xiao, Peng Wang, Xingbo Zhang, Bin Wang, Dongyong Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China 328# Section 1 Changshun Avenue Chengdu China

The accident tolerant fuel (ATF) is considered to be one of the most advanced concepts to improve the safety of light water reactors (LWRs). The accident tolerant control rod (ATCR) is a significant aspect in the ATF concept. The melting temperature of traditional LWR control rod (CR) materials, such as silver-indium-cadmium (AIC) alloy, is too low to endure the high temperature under several accident conditions. Consequently, varieties of candidate materials for control rod have been proposed in the previous researches because of the outstanding characters of high-temperature behavior, as well as reactivity worth, stability in coolant water and so on. In this paper, the burnup performance of the sesquioxides of the rare-earth elements (RE2O3) and the hafnia (Hf) are analyzed and compared to the traditional AIC control rod. Two parameters are chosen to reveal the burnup performance of the candidate control rod materials, the initial control rod reactivity worth and the stability of the control rod reactivity worth along with the assembly burnup. The candidate-material control rods and the AIC control rod are placed in the ATF assembly with the same conditions, and the assembly is depleted to sufficient burnup. Numerical results indicate that Eu2O3, Dy2O3, Sm2O3 and Hf are excellent ATCR materials compared to AIC. The initial control rod reactivity worth of these materials is not less than that of AIC, and the burnup stability is outstanding, especially Eu2O3 and Dy2O3 Copyright © GLOBAL 2019 - International Nuclear Fuel Cycle Conference and TOP FUEL 2019 - Light Water reactor Fuel Performance *** rights reserved.

关键词： Hafnium oxides

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Joint Entity and Relation Extraction Based on Prompt Learning and Multi-channel Heterogeneous Graph Enhancement

Joint Entity and Relation Extraction Based on Prompt Learnin...

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International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Haiqing Lv Xiaohui Han Peipei Wang Wenbo Zuo Jing Guo Lijuan Xu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan China Quan Cheng Laboratory Jinan China Information Research Institute Qilu University of Technology (Shandong Academy of Sciences) Jinan China

ISBN: (数字)9798331509712

ISBN: (纸本)9798331509729

Joint extraction of entity and relation is crucial in information extraction, aiming to extract all relation triples from unstructured text. However, current joint extraction methods face two main issues. Firstly, they rarely consider the semantic information of entity and relation labels, leading to models that fail to fully understand and utilize the rich semantics in these labels, thereby limiting their performance. Secondly, although table-filling methods are widely used, they focus only on the start or end positions and ignore deep interactions between tables, relying solely on word-level information. To address these issues, we propose the P-MHE framework based on prompt learning and multi-channel heterogeneous graph enhancement. First, we use prompt templates to construct semantic nodes for entity and relation type labels, initializing them along with words as nodes in a heterogeneous graph. We iteratively fuse these semantic nodes through a message-passing mechanism to obtain node representations suitable for entity and relation extraction tasks. Secondly, we design a multi-channel heterogeneous graph to model node relationships from different perspectives, enhancing feature interactions among different types of nodes. Finally, we aggregate the semantic node information of entity and relation type labels after iteration, constructing separate decoding tables for each entity and relation type to better adapt to their respective characteristics. We evaluated our model on four public datasets. Experimental results show that P-MHE outperforms existing models on multiple public datasets. Extensive additional experiments further validate the effectiveness of our model.

关键词： Training Adaptation models Limiting Fuses Semantics Natural languages Information retrieval Feature extraction Data mining Iterative decoding

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A novel paper-based electrowetting device using cellulose paper and paraffin wax 26

A novel paper-based electrowetting device using cellulose pa...

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26th International Conference on Miniaturized systems for Chemistry and Life sciences, MicroTAS 2022

作者： Li, He Yan, Zhibin Jin, Mingliang Zhou, Guofu Shui, Lingling Guangdong Provincial Key Laboratory of Optical Information Materials and Technology Institute of Electronic Paper Displays South China Academy of Advanced Optoelectronics South China Normal University Guangzhou510006 China Defense Key Disciplines Lab of Novel Micro-nano Devices and System Technology Chongqing University Chongqing400044 China School of Information and Optoelectronic Science and Engineering South China Normal University Guangzhou510006 China Guangdong Shunde Innovative Design Institute Guangdong Foshan528318 China

ISBN: (纸本)9781733419048

Paper-based microfluidic devices based on continuous-flow (μPAD) and electrowetting on dielectric (EWOD), have attracted increasing attention due to their low cost and excellent liquid handling capability. Here, we report a novel paper-based EWOD devices fabricated with the cellulose paper as substrate and paraffin wax as dielectric layer, which have been widely used in μPAD. Two methods are proposed to fabricate paraffin wax layer, including melting and spray-coating. Under DC electric field, the spray-coating-based devices show larger contact angle changes but with smaller hysteresis than the melting-based one. Our study opens up a new way for fabrication of the hybrid paper-based microfluidic device in the future. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized systems for Chemistry and Life sciences. All rights reserved.

关键词： Wetting

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Study on the thermal-mechanical performance of SiC composites cladding under multiple conditions

Study on the thermal-mechanical performance of SiC composite...

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2020 International Conference on Nuclear Engineering, ICONE 2020, collocated with the ASME 2020 Power Conference

作者： Yin, Chunyu Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China No.328 section 1 changshun avenue Chengdu China

ISBN: (纸本)9780791883761

SiC has become a candidate cladding material of Accident Tolerant Fuels (ATF) due to its excellent irradiation stability and corrosion resistance. However, because SiC is a ceramic material with low toughness, brittle failure is a significant concern. In order to improve the toughness, SiC fiber is required to manufacture multi-layer SiC composites. But the current performance model or analysis tool is not available for SiC composites cladding due to its obviously difference with Zr alloy cladding. On one side, Finite element method was used in this paper to analyze the performance of SiC composites cladding under operation conditions which include normal, transient conditions and LOCA conditions;on the other side, this paper gives the performance of the SiC composites with two layers under multiple operating conditions. The result showed that the temperature was stable and the maximum hoop stress was reached at about 70d under normal condition. The power ramp can increase the cladding temperature and has visible influence on the stress distribution. The hoop stress of the cladding reversed under LOCA condition. The tensile hoop stress on the outer surface significantly increased, which caused the obvious increase of failure probability of monolithic SiC, and the failure probability of SiC layer is significantly increased. The conclusion of the analysis has guiding significance for the theoretical design of SiC composites. Copyright © 2020 ASME.

关键词： Silicon carbide

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One-Pot Synthesis of Tetraarylpyrrolo[3,2-b]pyrrole Dopant-Free Hole-Transport Materials for Inverted Perovskite Solar Cells

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Chinese Journal of Chemical Physics 2021年第2期34卷 217-226,I0002页

作者： Liang-sheng Duan Quan-ping Wu Yuan-yuan Xu Hui Wang Zhe Sun Yu Chen Song Xue School of Materials Science and Engineering Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical SystemSchool of Mechanical EngineeringTianjin University of TechnologyTianjin 300384China

Four organic smallmolecule hole transport materials(D41, D42,D43 and D44) of tetraarylpyrrolo[3,2-b]pyrroles were prepared. They can be used without doping in the manufacture of the inverted planar perovskite solar cells. Tetraarylpyrrolo[3,2-b]pyrroles are accessible for one-pot synthesis.D42, D43 and D44 possess acceptor-π-donor-π-acceptor structure, on which the aryl bearing substitutes of cyan, fluorine and trifluoromethyl, respectively. Instead, the aryl moiety of D41 is in presence of methyl with a donor-π-donor-π-donor structure. The different substitutes significantly affected their molecular surface charge distribution and thin-film morphology, attributing to the electron-rich properties of fused pyrrole ring. The size of perovskite crystalline growth particles is affected by different molecular structures,and the electron-withdrawing cyan group of D42 is most conducive to the formation of large perovskite grains. The D42 fabricated devices with power conversion efficiency of17.3% and retained 55% of the initial photoelectric conversion efficiency after 22 days in dark condition. The pyrrolo[3,2-b]pyrrole is efficient electron-donating moiety for hole transporting materials to form good substrate in producing perovskite thin film.

关键词： Pyrrole[3,2-b]pyrrole Hole-transporting materials Organic small molecules Dopant-free Perovskite solar cells

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Semi-Supervised Clustering Framework for Fine-grained Scene Graph Generation 39

Semi-Supervised Clustering Framework for Fine-grained Scene ...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Yang, Jiarui Wang, Chuan Zhang, Jun Wu, Shuyi Jinjing, Zhao Liu, Zeming Yang, Liang Shanghai Key Lab of Intell. Info. Processing School of Computer Science Fudan University China Shanghai Collaborative Innovation Center on Intelligent Visual Computing China Institute of Information Engineering CAS China School of Computer Science and Technology Beijing JiaoTong University China Guangdong Provincial Key Lab of Intell. Info. Processing & Shenzhen Key Lab of Media Security Shenzhen University China Information Research Center of Military Science PLA Academy of Military Science China National Key Laboratory of Science and Technology on Information System Security China School of Computer Science and Engineering Beihang University China School of Artificial Intelligence Hebei University of Technology China

ISBN: (纸本)157735897X

Scene Graph Generation (SGG) aims to detect all objects and identify their pairwise relationships existing in the scene. Considering the substantial human labor costs, existing scene graph annotations are often sparse and biased, which result in confusion training with low-frequency predicates. In this work, we design a Semi-Supervised Clustering framework for Scene Graph Generation (SSC-SGG) that uses the sparse labeled data to guide the generation of effective pseudo-labels from unlabeled object pairs, thus enriching the labeled sample space, especially for low-frequency interaction samples. We approach from the perspective of clustering, reducing the problem of confirmation bias in a self-training manner. Specifically, we first enhance the model’s robustness to feature extraction via prototype-based clustering, aggregating different relationship augmented features onto the same prototype. Secondly, we design a dynamic pseudo-label assignment algorithm based on a mini-batch, which adjusts the detection sensitivity to different frequency samples from the historical assignment. Finally, we conduct joint training on the pseudo-labels and the labeled data. We conduct experiments on various SGG models and achieve substantial overall performance improvements, demonstrating the effectiveness of SSC-SGG. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Effect of residual pore on the performance of UN kernel TRISO particle fuel 14

Effect of residual pore on the performance of UN kernel TRIS...

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14th International Nuclear Fuel Cycle Conference, GLOBAL 2019 and Light Water reactor Fuel Performance Conference, TOP FUEL 2019

作者： Liu, Shichao Chen, Ping Zhou, Yi Pang, Hua Xi, Yong Tang, Changbing Zhao, Yanli Qiu, Xi Guo, Zixuan Nuclear power institute of China Science and Technology on Reactor System Design Technology Laboratory Changshun Stress No.1 Chengdu Sichuan610200 China

The thermal-mechanical performance of uranium nitride (UN) tri-isotropic (TRISO) particle with residual pore used in Light Water reactor (LWR) was investigated. The effect of pore size and location on the performance of inner dense pyrolytic carbon (IPyC) layer, SiC layer and outer dense pyrolytic carbon (OPyC) layer was studied. The dimensional changes, fission gas release and internal pressure of the fuel particle layers were calculated. Residual pore size can affect the stress distribution of coated layers obviously. The residual pore especially the big ones may be the source of cracks on the SiC layer, which can break or loss the capacity of SiC layer. Residual pore location has little influence on the stress distribution of the coated layer. In order to maintain the fission retention capacity of TRISO particle, the big residual pore should be avoided during fabrication process. Copyright © GLOBAL 2019 - International Nuclear Fuel Cycle Conference and TOP FUEL 2019 - Light Water reactor Fuel Performance *** rights reserved.

关键词： Silicon carbide

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MFCLIP: Multi-modal Fine-grained CLIP for Generalizable Diffusion Face Forgery Detection

arXiv

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arXiv 2024年

作者： Zhang, Yaning Wang, Tianyi Yu, Zitong Gao, Zan Shen, Linlin Chen, Shengyong Jinan250353 China Nanyang Technological University 50 Nanyang Ave Block N 4 639798 Singapore School of Computing and Information Technology Great Bay University Dongguan523000 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China Jinan250014 China The Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin300384 China Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518129 China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518060 China

The rapid development of photo-realistic face generation methods has raised significant concerns in society and academia, highlighting the urgent need for robust and generalizable face forgery detection (FFD) techniques. Although existing approaches mainly capture face forgery patterns using image modality, other modalities like fine-grained noises and texts are not fully explored, which limits the generalization capability of the model. In addition, most FFD methods tend to identify facial images generated by GAN, but struggle to detect unseen diffusion-synthesized ones. To address the limitations, we aim to leverage the cutting-edge foundation model, contrastive language-image pre-training (CLIP), to achieve generalizable diffusion face forgery detection (DFFD). In this paper, we propose a novel multi-modal fine-grained CLIP (MFCLIP) model, which mines comprehensive and fine-grained forgery traces across image-noise modalities via language-guided face forgery representation learning, to facilitate the advancement of DFFD. Specifically, we devise a fine-grained language encoder (FLE) that extracts fine global language features from hierarchical text prompts. We design a multi-modal vision encoder (MVE) to capture global image forgery embeddings as well as fine-grained noise forgery patterns extracted from the richest patch, and integrate them to mine general visual forgery traces. Moreover, we build an innovative plug-and-play sample pair attention (SPA) method to emphasize relevant negative pairs and suppress irrelevant ones, allowing cross-modality sample pairs to conduct more flexible alignment. Extensive experiments and visualizations show that our model outperforms the state of the arts on different settings like cross-generator, cross-forgery, and cross-dataset evaluations. Copyright © 2024, The Authors. All rights reserved.

关键词： Alignment

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Mofs-Derived Cu/Carbon Membrane as Bi-Functional Catalyst: Improving Catalytic Activity in Detection and Degradation of Pfoa Via Regulation of Reactive Cu Species

SSRN

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SSRN 2023年

作者： Hou, Chen Chen, Fang Cheng, Daozhen Zou, Shengyang Wang, Jianzhi Shen, Mengxia Wang, Yang College of Bioresources Chemical and Materials Engineering Shaanxi University of Science and Technology Shaanxi Provincial Key Laboratory of Papermaking Technology and Specialty Paper Development Key Laboratory of Paper Based Functional Materials of China National Light Industry National Demonstration Center for Experimental Light Chemistry Engineering Education Xi’an710021 China Key Laboratory for Green Chemical Process of Ministry of Education Hubei Key Laboratory for Novel Reactor and Green Chemistry Technology Hubei Engineering Research Center for Advanced Fine Chemicals School of Chemical Engineering and Pharmacy Wuhan Institute of Technology Wuhan430073 China

Developing bi-functional materials to simultaneously detect and degrade persistent pollutant perfluorooctanoic acid (PFOA) is of significant importance for environmental and human health. In this study, a copper-based mimic enzyme colorimetric detecting sensor coupling with solar photo-electro-Fenton degradation (SPEF) system was built based on Cu/carbon nanofiber (CNF-Cu/C) membrane. Self-supporting flexible CNF-Cu/C membrane was successfully prepared by solvothermal method with further secondary seed growth and in-situ thermal reduction. Based on calcination temperature regulation, the obtained CNF-Cu/C membrane derived from MOFs/polyacrylonitrile (HKUST/PAN) membrane was characterized by 3D carbon fiber network dispersed with porous carbon skeleton embedded copper species, which exhibited good dispersibility, cycling stability and excellent electrical conductivity. With excellent peroxidase-like activity, CNF-Cu/C can rapidly detect PFOA based on the inhibition of color reaction of tetramethylbenzidine (TMB) with detection limit of 0.133 μM. Furthermore, CNF-Cu/C also exhibited outstanding optical properties and oxygen redox reaction (ORR) activity, and the removal efficiency of PFOA in Cu-SPEF system reached 98.22% within 180 min under optimal conditions. Based on the results of free radical quenching experiment, EPR experiment and HPLC-MS experiments, the degradation mechanism and degradation path of PFOA by SPEF system were further speculated. © 2023, The Authors. All rights reserved.

关键词： Membranes

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Attention-Guided Multi-scale Interaction Network for Face Super-Resolution

arXiv

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arXiv 2024年

作者： Wan, Xujie Li, Wenjie Gao, Guangwei Lu, Huimin Yang, Jian Lin, Chia-Wen The Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210046 China Key Laboratory of Artificial Intelligence Ministry of Education Shanghai200240 China The Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100080 China The School of Automation Southeast University Nanjing210096 China The School of Computer Science and Technology Nanjing University of Science and Technology Nanjing210094 China The Department of Electrical Engineering National Tsing Hua University Hsinchu30013 Taiwan

Recently, CNN and Transformer hybrid networks demonstrated excellent performance in face super-resolution (FSR) tasks. Since numerous features at different scales in hybrid networks, how to fuse these multi-scale features and promote their complementarity is crucial for enhancing FSR. However, existing hybrid network-based FSR methods ignore this, only simply combining the Transformer and CNN. To address this issue, we propose an attention-guided Multi-scale interaction network (AMINet), which contains local and global feature interactions as well as encoder-decoder phases feature interactions. Specifically, we propose a Local and Global Feature Interaction Module (LGFI) to promote fusions of global features and different receptive fields' local features extracted by our Residual Depth Feature Extraction Module (RDFE). Additionally, we propose a Selective Kernel Attention Fusion Module (SKAF) to adaptively select fusions of different features within LGFI and encoder-decoder phases. Our above design allows the free flow of multi-scale features from within modules and between encoder and decoder, which can promote the complementarity of different scale features to enhance FSR. Comprehensive experiments confirm that our method consistently performs well with less computational consumption and faster inference. Copyright © 2024, The Authors. All rights reserved.

关键词： Decoding

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