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Mechanical performance of stiffened CFRP panel cured via magnetic particle-induced in-situ heating

Fuhe Cailiao Xuebao/Acta Materiae Compositae Sinica 2025年第5期42卷 2528-2536页

作者： Xu, Yurong Hu, Xiafen Sun, Ao Liang, Jiqiu Wu, Dan Hao, Lei Wei, Junjie Li, Yichao School of Aerospace Engineering Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Advanced Aerospace Propulsion Technology System Design Institute of Hubei Aerospace Technology Academy Wuhan430040 China

With the development trend of large and complexity of carbon fiber reinforced polymer (CFRP) structures, the conventional oven or autoclave molding method exposes problems such as size limitation, long fabrication time, low energy utilization, uneven curing, etc., and there is an urgent need to explore new composite molding method. In this paper, a new fabrication method to cure CFRP based on electromagnetic induction in-situ heating was investigated by using Mn-Zn ferrite as a heating carrier. The heating characteristics, mechanical properties and porosity of stiffened CFRP panels with two kinds of complex layups, T-shape and I-shape, were investigated, and comparative analyses were carried out with the counterpart specimens cured by an oven. The results show that the induction method can achieve in-situ, uniform, temperature-controlled and lay-up angle independent heating and curing for both two types panels. Under the condition of 13wt% Mn-Zn ferrite addition and 5.5 h induction heating, the flexural stiffness of the T-shaped panel is increased by 5.2% and the maximum load is increased by 11.2% compared to the oven-formed specimen under the same curing time. The buckling load of the I-beam reinforced panel increases by 3.3% compared to the oven-molded specimen. However, the porosity of the two types of panels increase slightly by 0.4% and 0.3%. The results obtained in this paper provide important guidance for the engineering application of electromagnetic induction curing process in the fabrication of CFRP composite structures. © 2025 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.

关键词： Machinability

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Cybersecurity Risk Assessment of Nuclear Svdu Based on Attack Tree

SSRN

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SSRN 2025年

作者： Wu, Yanqun Wang, Junfeng Ma, Quan Liu, Mingxing Chen, Meiyuan College of Computer Science Sichuan University Chengdu610065 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610000 China

The nuclear power SVDU in nuclear power plants is an important component of the nuclear reactor protection system. With the complete digitalization of the reactor protection system, the risks of cybersecurity attacks have significantly increased. This paper proposes a safety risk assessment method based on an attack tree model to analyze the risk status of the nuclear power SVDU and assess its risk level and security level. Firstly, the typical information security threats faced by nuclear power SVDU are analyzed. Subsequently, an attack tree model of the system is constructed based on the STRIDE model, with four security attributes assigned to the leaf nodes of the tree with reference to the CVSS4.0 system and multi-attribute utility theory. These attributes are quantified through level scoring, and the risk probability of the leaf nodes is calculated using entropy weighting. The risk probability of the root node is then obtained based on the dependency relationship between nodes. Finally, the security risk rating of nuclear power SVDU is obtained. Experimental results demonstrate that the method in this paper more accurately identifies high-risk security threats, predicts possible attack paths, and provides a basis for security protection strategy selection. © 2025, The Authors. All rights reserved.

关键词： reactor shielding

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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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Enhancing Routing Performance Through Trajectory Planning With DRL in UAV-Aided VANETs

IEEE Transactions on Machine Learning in Communications and ...

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IEEE Transactions on Machine Learning in Communications and Networking 2025年 3卷 517-533页

作者： Chen, Jingxuan Huang, Dianrun Wang, Yijie Yu, Ziping Zhao, Zhongliang Cao, Xianbin Liu, Yang Quek, Tony Q. S. Oliver Wu, Dapeng Beihang University School of Electronic and Information Engineering Beijing100191 China State Key Laboratory of CNS/ATM Beijing100191 China Nanyang Technological University School of Computer Science and Engineering Nanyang Avenue 639798 Singapore Singapore University of Technology and Design Information System Technology and Design Pillar Somapah Rd 487372 Singapore Yonsei University Yonsei Frontier Laboratory Seoul03722 Korea Republic of City University of Hong Kong Department of Computer Science Kowloon Hong Kong

Vehicular Ad-hoc Networks (VANETs) have gained significant attention as a key enabler for intelligent transportation systems, facilitating vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. Despite their potential, VANETs face critical challenges in maintaining reliable end-to-end connectivity due to their highly dynamic topology and sparse node distribution, particularly in areas with limited infrastructure coverage. Addressing these limitations is crucial for advancing the reliability and scalability of VANETs. To bridge these gaps, this work introduces a heterogeneous UAV-aided VANET framework that leverages uncrewed aerial vehicles (UAVs), also known as autonomous aerial vehicles, to enhance data transmission. The key contributions of this paper include: 1) the design of a novel adaptive dual-model routing (ADMR) protocol that operates in two modes: direct vehicle clustering for intra-cluster communication and UAV/RSU-assisted routing for inter-cluster communication;2) the development of a modified density-based clustering algorithm (MDBSCAN) for dynamic vehicle node clustering;and 3) an improved UAV trajectory planning method based on a multi-agent soft actor-critic (MASAC) deep reinforcement learning algorithm, which optimizes network reachability. Simulation results reveal that the UAV trajectory optimization method achieves higher network reachability ratios compared to existing approaches. Also, the proposed ADMR protocol improves the packet delivery ratio (PDR) while maintaining low end-to-end latency. These findings demonstrate the potential to enhance VANET performance, while also providing valuable insights for the development of intelligent transportation systems and related fields. © 2025 The Authors.

关键词： Vehicular ad hoc networks

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Variable stiffness design optimization of fiber-reinforced composite laminates with regular and irregular holes considering fiber continuity for additive manufacturing

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Chinese Journal of Aeronautics 2025年第3期38卷 334-354页

作者： Yi LIU Zunyi DUAN Chunping ZHOU Yuan SI Chenxi GUAN Yi XIONG Bin XU Jun YAN Jihong ZHU School of Mechanics Civil Engineering&ArchitectureNorthwestern Polytechnical UniversityXi’an 710072China Research&Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen 518063China Key Lab for Airborne Hi-performance Electro-magnetic Window RISACJinan 130012China School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China State Key Laboratory of Structural Analysis for Industrial Equipment Department of Engineering MechanicsInternational Research Center for Computational MechanicsDalian University of TechnologyDalian 116024China State IJR Center of Aerospace Design and Additive Manufacturing MIIT Lab of Metal Additive Manufacturing and Innovative DesignNorthwestern Polytechnical UniversityXi’an 710072China

Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples cons

关键词： Variable stiffness composite laminates Discrete material interpolation scheme Normal distribution fiber optimization Discrete fiber continuous filtering strategy Additive manufacturing of composite laminates

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NO reduction by carbon-based gases based on coal gasification fractions:NO reduction intermediate identification and kinetic analysis

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Frontiers of Environmental science & Engineering 2025年第3期19卷 175-189页

作者： Xiang Zhang Jian Tian Tanghui Hu Guangyong Yue Xianlong Liu Wen Zhou Xiaohong Liu Xinye Wang Ministry-of-Education Key Laboratory for the Green Preparation and Application of Functional Materials Hubei Engineering Research Center for Green Industrialization Technology of Industrial WasteSchool of Materials Science and EngineeringHubei UniversityWuhan 430062China Hubei Huda Tianshu New Energy Materials Industrial Research and Design Institute Co. Ltd.Wuhan 430062China Wuhan Tianshu Dust Removal Equipment Co. Ltd.Wuhan 430062China Engineering Laboratory for Energy System Process Conversion&Emission Control Technology of Jiangsu Province School of Energy and Mechanical EngineeringNanjing Normal UniversityNanjing 210042China

Combining pulverized coal gasifiers with cement kiln production is promising for application in low-cost and efficient NO *** paper presents a pulverized coal gasifier catalytic denitration technique and investigates the homogeneous reduction(by CO and CH_(4))and heterogeneous catalytic reduction(by coke,CaO,MgO,and Fe_(2)O_(3))of NO.A combination of Chemkin simulations and fixed-bed experiments is used to elucidate the reaction pathways and key intermediates of NO reduction by carbon-based *** addition,the activation energies for different catalyst combinations were analyzed via reaction *** results demonstrate that the presence of small amounts of O_(2) inhibits NO reduction by CO but promotes NO reduction by CH_(4).The NCO·radical is essential for the NO reduction process,and the generation of this radical depends on the CH_(4) cleavage intermediate and O·*** and Fe_(2)O_(3) exhibit more significant catalytic effects on NO reduction by carbon-based gases than the other catalysts *** presence of a small amount of O_(2) in the reacting gas mixtures facilitates the NO reduction *** activation energy is reduced to 1.02 kJ/mol,and the NO conversion reaches 99.80%when the catalyst is C+CaO+MgO+Fe_(2)O_(3) and the gas composition is CO+CH_(4)+O_(2).This work provides theoretical support and data recommendations for the use of pulverized coal gasifiers for the denitrification of cement kilns.

关键词： Carbon-based gas Catalytic denitration Coke Kinetic analysis Reaction mechanism

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Deep learning-based dual monitoring system for power forecasting and fault detection in nuclear power applications

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Energy and AI 2025年 20卷

作者： Lyu, Mingzhe Gong, Helin Chen, Zhang Wang, Jiangyu Zhong, Mingxiao Wang, Zhiyong Li, Qing Pan, Zefei School of Mathematical Sciences University of Electronic Science and Technology of China Chengdu611731 China Shanghai Zhangjiang Institute of Mathematics Shanghai201203 China Paris Elite Institute of Technology Shanghai Jiao Tong University Shanghai200240 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610041 China CNNP Operation Maintenance Technology Co. Ltd Hangzhou311215 China

Monitoring key parameters in nuclear power plant control rooms is critical, as human errors can result in severe safety and operational consequences. This study proposes a hybrid framework for power prediction and fault detection that integrates multi-head self-attention mechanisms with long short-term memory networks, combined with a dual-monitoring system. The framework is evaluated using real-time data from two pressurized water reactor units (Units 5 and 6) under four realistic operational scenarios. In the most informative case, the model achieves a 56.6% reduction in root mean square error and a 36.8% reduction in mean absolute error, with a coefficient of determination (R2) of 0.9924—significantly outperforming the next-best benchmark. For fault diagnosis, the dual-monitoring system reduces the false negative rate to 18.73% and improves recall to 81.27%, demonstrating strong anomaly detection under complex conditions. By combining short-term fluctuation sensitivity with long-term trend stability, the proposed approach offers a robust and generalizable solution for intelligent monitoring. These findings advance the development of artificial intelligence–enhanced systems for secure and efficient operation of critical energy infrastructure. © 2025 The Authors

关键词： Deep learning

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Magnitude,distribution and temporal trend of nitrous oxide emissions from China's natural soils over 1980–2022

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science China Earth sciences 2025年第4期68卷 1074-1085页

作者： Songbai HONG Zimeng LI Mingsong TANG Fa LI Yitong YAO Yanzi YAN Mingzhu HE Xuhui WANG Hui ZENG Shilong PIAO School of Urban Planning and Design Shenzhen Graduate SchoolPeking UniversityShenzhen518055China Key Laboratory of Earth Surface System and Human-Earth Relations Ministry of Natural Resources of ChinaShenzhen Graduate SchoolPeking UniversityShenzhen518055China Institute of Carbon Neutrality Sino-French Institute for Earth System ScienceCollege of Urban and Environmental SciencesPeking UniversityBeijing100871China Department of Earth System Science Stanford UniversityStanfordCA94305USA Division of Geological and Planetary Sciences California Institute of TechnologyPasadenaCA91125USA Department of Soil and Environment Swedish University of Agricultural SciencesUppsala75007Sweden Joint International Research Laboratory of Catastrophe Simulation and Systemic Risk Governance Beijing Normal UniversityZhuhai519087China School of National Safety and Emergency Management Beijing Normal UniversityZhuhai519807China

Soils represent the largest contributor to global nitrous oxide(N_(2)O)***,current research efforts predominantly focus on N_(2)O emissions from agricultural soils,while studies on N_(2)O emissions from natural soils,another significant source,remain *** this study,we explored the magnitude,spatiotemporal dynamics,and drivers of N_(2)O emissions from China's natural soils over the period 1980–2022 via machine learning and a compiled novel dataset of 319 field *** results revealed that the N_(2)O flux per unit area was generally higher in the southeast compared to the northwest,and higher in forests than in *** spatial and biome heterogeneity was strongly regulated by local hydrothermal conditions and nitrogen *** averaged N_(2)O emissions over the study period were 646.2±27 Gg N_(2)O yr^(-1),with approximately equivalent contributions from forests and ***,there exhibited a significant and increasing trend from 1980 to 2022,with a rate of 2.7 Gg N_(2)O yr^(-2).Such an increase was primarily driven by the expansion of forested area and elevated nitrogen *** data-driven study presents a long-term and gridded estimate of N_(2)O emissions from China's natural soils,emphasizing the need for future research on changes of greenhouse gas emissions induced by land use change and nitrogen deposition.

关键词： Nitrous oxide Spatiotemporal dynamics Nitrogen deposition Forests Grasslands Data-driven estimates

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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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A numerical method for predicting bursting strength of composite rocket motor case considering filament winding process-induced stress

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Chinese Journal of Aeronautics 2025年第2期 509-522页

作者： Jiqiu LIANG Fei ZHAO Dan WU Anxin DING Hubei Key Laboratory of Advanced Aerospace Propulsion Technology System Design Institute of Hubei Aerospace Technology Academy School of Materials Science and Engineering Wuhan University of Technology State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology

A numerical method to predict the bursting strength of filament wound composite rocket motor case is proposed here. This method can evaluate the longitudinal stress evolution of each composite layer as impregnated filaments with fiber tension are wound layer by layer, and consider the effects of accumulated stress and deformation during filament winding on the bursting strength of composite case. Taking ?520 mm composite cases as a case study, the filament-winding-processinduced stress and deformation as well as progressive damage behavior are numerically predicted,followed by a comparison with experimental results. The numerical results show that the predicted bursting pressures for composite cases manufactured on the mandrels with and without a flexible component are 14.20 MPa and 21.40 MPa, respectively. These values exhibit slight deviation from the measured pressures of 13.50 MPa and 21.57 MPa. Moreover, the predicted damage locations,situated respectively in the dome and cylinder, agree well with the experimental observation. These observations indicate that use of flexible component reduces the load-bearing capacity of the ***, it validates the reliability and accuracy of the proposed numerical method in predicting the bursting strength of composite cases.

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