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Efficient blocked symmetric compressed sparse column method for finite element analysis

Frontiers of Mechanical Engineering 2025年第1期20卷 87-104页

作者： Yingjun WANG Shijie LUO Jinyu GU Yuanfang ZHANG National Engineering Research Center of Novel Equipment for Polymer Processing The Key Laboratory of Polymer Processing Engineering of the Ministry of EducationGuangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced ManufacturingSouth China University of TechnologyGuangzhou 510641China Shien-Ming Wu School of Intelligent Engineering South China University of TechnologyGuangzhou 511442China

In finite element analysis(FEA),optimizing the storage requirements of the global stiffness matrix and enhancing the computational efficiency of solving finite element equations are pivotal *** address these goals,we present a novel method for compressing the storage of the global stiffness matrix,aimed at minimizing memory consumption and enhancing FEA *** method leverages the block symmetry of the global stiffness matrix,hence named the blocked symmetric compressed sparse column(BSCSC)*** also detail the implementation scheme of the BSCSC method and the corresponding finite element equation solution *** approach optimizes only the global stiffness matrix index,thereby reducing memory requirements without compromising FEA computational *** then demonstrate the efficiency and memory savings of the BSCSC method in FEA using 2D and 3D cantilever beams as *** addition,we employ the BSCSC method to an engine connecting rod model to showcase its superiority in solving complex engineering ***,we extend the BSCSC method to isogeometric analysis and validate its scalability through two examples,achieving up to 66.13%memory reduction and up to 72.06%decrease in total computation time compared to the traditional compressed sparse column method.

关键词： finite element analysis global stiffness matrix blocked symmetric property memory reduction isogeometric analysis

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Non-Line-of-Sight Multipath Classification Method for BDS Using Convolutional Sparse Autoencoder with LSTM

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Tsinghua Science and technology 2025年第1期30卷 68-86页

作者： Yahang Qin Zhenni Li Shengli Xie Bo Li Ming Liu Victor Kuzin School of Automation Guangdong University of Technologyand also with Guangdong-Hong Kong-Macao Joint Laboratory for Smart Discrete ManufacturingGuangzhou 510006China School of Automation Guangdong University of TechnologyGuangdong Key Laboratory of IoT Information TechnologyGuangzhou 510006China 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Key Laboratory of Intelligent Information Processing and System Integration of IoTMinistry of EducationGuangzhou 510006China Department of Electronic and Computer Engineering Hong Kong University of Science and TechnologHong Kong 999077China Academician of Russian Engineering Academy Moscow Moscow 125009Russia

Multipath signal recognition is crucial to the ability to provide high-precision absolute-position services by the BeiDou Navigation Satellite System(BDS).However,most existing approaches to this issue involve supervised machine learning(ML)methods,and it is difficult to move to unsupervised multipath signal recognition because of the limitations in signal *** by an autoencoder with powerful unsupervised feature extraction,we propose a new deep learning(DL)model for BDS signal recognition that places a long short-term memory(LSTM)module in series with a convolutional sparse autoencoder to create a new autoencoder ***,we propose to capture the temporal correlations in long-duration BeiDou satellite time-series signals by using the LSTM module to mine the temporal change patterns in the time ***,we develop a convolutional sparse autoencoder method that learns a compressed representation of the input data,which then enables downscaled and unsupervised feature extraction from long-duration BeiDou satellite series ***,we add an l_(1/2) regularizer to the objective function of our DL model to remove redundant neurons from the neural network while ensuring recognition *** tested our proposed approach on a real urban canyon dataset,and the results demonstrated that our algorithm could achieve better classification performance than two ML-based methods(e.g.,11%better than a support vector machine)and two existing DL-based methods(e.g.,7.26%better than convolutional neural networks).

关键词： convolutional sparse autoencoder BeiDou Navigation Satellite System(BDS) long short-term memory(LSTM) multipath classification

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CRL-YOLO: A Comprehensive Recalibration and Lightweight Detection Model for AAV Power Line Inspections

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Wu, Dong Yang, Weijiang Li, Jiechang Du, Kaiyue Li, Linrong Yang, Zhen Guilin University of Technology Key Laboratory of Advanced Manufacturing and Automation Technology The College of Mechanical and Control Engineering Guilin541006 China

In complex backgrounds and under severe interference, due to the relatively small size of insulator defects and dampers, existing object detection algorithms face significant challenges of high miss rates and low detection accuracy in drone-based power line inspections. To address these challenges and achieve accurate, fast detection of insulator defects and dampers, this article proposes a novel anchor-free object detection algorithm named comprehensive recalibration and lightweight-you only look once (CRL-YOLO). This method uses YOLOv8n as the base framework and redesigns three key components: feature extraction, feature fusion, and detection head. First, to address the issue of inadequate feature extraction when processing multiscale and very small objects, a C2f star effective squeeze-excitation (CSE) module was designed to enhance the network's sensitivity to multiscale and small object features, thereby improving feature extraction capabilities. Second, to solve the problem of information loss and feature redundancy during the fusion of different level features in the feature fusion network, a recalibration interaction feature pyramid network (RIF-PNet) is developed. This module enhances the interaction between different level features, enabling more efficient feature fusion. Lastly, considering that shared convolutional kernels can significantly reduce the number of parameters, memory usage, and computational costs, a lightweight unified feature detection head (LUFDH) was proposed to improve the algorithm's applicability to edge computing devices. The experimental results indicate that, compared to the YOLOv8n baseline model, CRL-YOLO improves accuracy, recall (R), and mean average precision (mAP) by 1%, 5%, and 4.3%, respectively, demonstrating its great potential for real-time drone inspections of power transmission lines. © 2025 IEEE.

关键词： Aircraft detection

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Optimization for furnace-assisted laser cladding process parameter of crack-free ceramic-based coating by response surface methodology

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Ceramics International 2025年第9期51卷 11735-11746页

作者： Yong, Zhao Wang, Yunfei Yang, Gaolin Shi, Yuelin Zhang, QunLi Yao, Jianhua College of Mechanical Engineering Zhejiang University of Technology Hangzhou310023 China Key Laboratory of Special Purpose Equipment and Advanced Processing Technology of Ministry of Education Zhejiang University of Technology Hangzhou310023 China Institute of Laser Advanced Manufacturing Zhejiang University of Technology Hangzhou310023 China Zhoushan Dingzun Intelligent Technology Co. LTD Zhoushan316031 China

Ceramic-based coating, recognized as advanced surface treatment material, which is widely utilized across various sectors including aerospace, automotive, and industrial manufacturing. This extensive application is attributed to their remarkable properties such as wear resistance, high-temperature tolerance, and corrosion resistance. However, ceramic phase of the coating experienced excessive residual stress due to rapid cooling and heating effects, during the laser cladding process. Thus, the formation of cracks and pores in the coating is a common issue, posing significant challenge to the preparation of ceramic-based coating. This study employed the response surface methodology to optimize the process parameters of furnace-assisted laser cladding for fabricating 60WC coating on 45# steel substrate. The effects of laser power, scanning rate, powder feeding rate, and preheating temperature on coating height, dilution rate and micro-hardness were investigated comprehensively in order to achieve a crack-free 60WC coating. The results indicate that the synergistic effect of laser scanning speed and preheating temperature is of the utmost significance for attaining crack-free coatings with high hardness. Through the adjustment of these two parameters, a coating featuring high hardness and no cracks can be acquired. And it was determined by RSM that the optimal coating quality was achieved under the following conditions: 2586.13 W laser power, 740.74 mm/min laser scanning speed, 400 °C preheating temperature, and 22.0 g/min powder feeding speed, with no discernible macroscopic or microscopic cracks present. © 2025

关键词： Preheating

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Influence of 3D helical magnetic perturbations on runaway electron generation in J-TEXT tokamak

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Plasma Science and technology 2025年第3期27卷 36-44页

作者： Wei YAN Guinan ZOU Zhongyong CHEN You LI Jiangang FANG Zhifang LIN Zhonghe JIANG Nengchao WANG Bo RAO Yangbo LI Zhengkang REN Chuanxu ZHAO Yu ZHONG Fanxi LIU Yinlong YU Zisen NIE Xun ZHOU Yuan SHENG Yuwei SUN Song ZHOU Xiaoqing ZHANG Zhoujun YANG Zhipeng CHEN Yonghua DING the J-TEXT Team State Key Laboratory of Advanced Electromagnetic Technology International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma PhysicsSchool of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074People’s Republic of China School of Electrical Engineering&Automation Jiangsu Normal UniversityXuzhou 221116People’s Republic of China 不详

A large number of runaway electrons(REs)generated during disruption can cause significant damage to next-generation large-scale *** influence of three-dimensional(3D)helical magnetic perturbations on the suppression of RE generation was explored using a set of 3D helical coils in J-TEXT tokamak,which can excite m/n=-2/2 helical magnetic *** evidence shows that the-2/2 magnetic perturbations caused by the opposite coil current direct plasma toward the high-field side,simultaneously enhancing the magnetic fluctuations,which would enhance the radial loss of REs and even prevent RE *** the other hand,-2/2 magnetic perturbations can also reduce the cooling time during the disruption phase and generate a population of high-energy REs,which can interact with high-frequency magnetic fluctuations and in turn suppress RE *** critical helical coil current was found to correlate with electron density,requiring higher coil currents at higher *** to the statistical analysis of RE generation at different electron densities,the applied-2/2 magnetic perturbations can increase the magnetic fluctuations to the same level at lower electron densities,which can decrease the threshold electron density for RE *** will be beneficial for RE mitigation in future large tokamak devices.

关键词： 3D helical magnetic perturbations runaway electron J-TEXT tokamak

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Enhancing rheology and mechanical properties of DLP 3D-printed Si_(3)N_(4) materials via composition optimization and gas-pressure sintering

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International Journal of Minerals,Metallurgy and Materials 2025年第5期32卷 1220-1233页

作者： Qing Qin Gang Xiong Lin Han Yujuan Zhang Zhen Shen Changchun Ge Institute of Powder Metallurgy and Advanced Ceramics School of Materials Science and EngineeringUniversity of Science and Technology BeijingBeijing 100083China State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and TechnologyInstitute of AutomationChinese Academy of SciencesBeijing 100190China

Digital light processing(DLP)is a crucial additive manufacturing(AM)technique for producing high-precision ceramic *** study aims to optimize the formulation of Si_(3)N_(4)slurry to enhance both its performance and manufacturability in the DLP process,and investigate key factors such as particle size distribution,photopolymer resin monomer ratios,and dispersant types to im-prove the slurry’s rheological *** these optimizations,a photosensitive Si_(3)N_(4)slurry with 50vol%solid content was de-veloped,exhibiting excellent stability,and low viscosity(2.48 Pa·s at a shear rate of 12.8 s^(-1)).The effects of gas-pressure sintering on the material’s phase composition,microstructure,and mechanical properties were further explored,revealing that this technique significantly increases the flexural strength of the green sample from(109±10.24)to(618±42.15)*** sintered ceramics exhibited high hard-ness((16.59±0.05)GPa)and improved fracture toughness((4.45±0.03)MPa·m^(1/2)).Crack trajectory analysis revealed that crack deflec-tion,crack bridging,and the pull-out of rod-likeβ-Si_(3)N_(4)grains,are the main toughening mechanisms,which could effectively mitigate crack *** these mechanisms,crack deflection and bridging were particularly influential,significantly enhancing the frac-ture toughness of the Si_(3)N_(4)***,this research highlights how monomer formulation and gas-pressure sintering strengthen the performance of Si_(3)N_(4)slurry in the DLP three-dimensional printing *** work is expected to provide new insights for fabricat-ing complex Si_(3)N_(4)ceramic components with superior mechanical properties.

关键词： additive manufacturing Si_(3)N_(4)slurry low viscosity pressure sintering

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Potential dependence in electrocatalysis:a theoretical perspective

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Science China Chemistry 2025年第1期68卷 21-25页

作者： Leyu Liu Zhaoming Xia Zeyu Wang Yinjuan Chen Hai Xiao Department of Chemistry Tsinghua UniversityBeijing 100084China Fundamental Science Center of Rare Earths Ganjiang Innovation AcademyChinese Academy of SciencesGanzhou 341119China Key Laboratory of Advanced Catalytic Materials and Technology Advanced Catalysis and Green Manufacturing Collaborative Innovation CenterChangzhou UniversityChangzhou 213164China

Electrocatalysis is a key technology for the new energy era and sustainable development,serving as the interface for interconversion of electrical and chemical energies,which spans a wide spectrum of applications in sustainable energy and environmental *** reactions including electrochemical CO_(2)reduction reaction(eCO_(2)RR),hydrogen evolution reaction(HER),and oxygen evolution/reduction reactions(OER/ORR),hold essential promise for renewable energy technologies as well as complement the biogeochemical carbon and oxygen cycles.

关键词： spectrum interface Electrocatalysis

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Forming limit and failure behavior of fiber metal laminates under low-constraint conditions

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Chinese Journal of Aeronautics 2025年第1期38卷 638-653页

作者： Yao WANG Feng DING Yong LI Yunhua ZHANG Sifa ZHENG Libin ZHAO Ning HU School of Mechanical Engineering Hebei University of TechnologyTianjin 300401China Suzhou Automotive Research Institute(Xiangcheng) Tsinghua UniversitySuzhou 215134China State Key Laboratory of Reliability and Intelligence Electrical Equipment Hebei University of TechnologyTianjin 300130China School of Mechanical Engineering and Automation Beihang UniversityBeijing 100191China Henan Benjie Technology Co. Ltd.Zhengzhou 450003China Key Laboratory of Advanced Intelligent Protective Equipment Technology Ministry of EducationTianjin 300401China Key Laboratory of Hebei Province on Scale-span Intelligent Equipment Technology Hebei University of TechnologyTianjin 300401China

Fiber Metal Laminates(FMLs),as high-performance composite materials,demonstrate exceptional potential in a wide range of applications,such as aeronautical and astronautical ***,the traditional cured FMLs possess complex interlayer stresses and low forming limits,restricting further promotion and application of ***-constraint FMLs exhibit a lower forming resistance and better formability due to no curing during the forming process;however,the formation mechanism and response are not *** paper presents the Forming Limit Diagram(FLD)of low-constraint GLARE(glass fiber reinforced aluminum laminates)based on the forming limit test,and compares it with the conventionally cured laminates to evaluate the differences in the forming *** addition,combined with the analysis of failure mechanism and micro-deformation mechanism of specimens,the influence of different temperatures(20–80℃)and forming states(width)on the deformation performance of laminates is further *** results reveal that the forming limit curve of low-constraint laminates shifts up with the increase of temperature,the forming limit initially increases with the increase of width,then followed by a gradual decrease,and the maximum principal strain of low-constraint laminates is increased by 29% at 80℃ compared to 20℃.The cured laminate has a principal strain range of 0–0.02,while the low-constraint laminates have a principal strain range of 0.03–*** with cured laminates,low-constraint laminates possess a higher forming limit due to the improvement in deformable degree between layers by resin flow and fiber slippage,which enhances their *** study is expected to serve as a reference for establishing forming limit criteria and optimizing forming schemes for low-constraint laminates.

关键词： Fiber Metal Laminates(FMLs) GLARE Low-constraint state Forming limit Failure mechanism

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Physics-informed battery degradation prediction:Forecasting charging curves using one-cycle data

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Journal of Energy Chemistry 2025年第2期101卷 825-836,I0018页

作者： Aihua Tang Yuchen Xu Jinpeng Tian Xing Shu Quanqing Yu Key Laboratory of Advanced Manufacturing Technology for Automobile Parts Ministry of EducationChongqing University of TechnologyChongqing 400054China Department of Electrical and Electronic Engineering and Research Centre for Grid Modernization The Hong Kong Polytechnic UniversityKowloonHong Kong 9997China School of Automotive Engineering Harbin Institute of TechnologyWeihai 264209ShandongChina

Accurately predicting battery degradation is crucial for battery system ***,due to the complexities of aging mechanisms and limitations of historical data,comprehensively indicating battery degradation solely through maximum capacity loss assessment is *** machine learning offers promising solutions,it often overlooks domain knowledge,resulting in reduced accu racy,increased computational burden and decreased ***,this study proposes a method to predict the voltage-capacity(V-Q) curve during battery degradation with limited historical *** process is achieved through two physically interpretable components:a lightweight interpretable physical model and a physics-informed neural *** components incorporate domain knowledge into machine learning to improve V-Q curve prediction performance and enhance *** validation was conducted on 52 batteries of different types under different testing *** proposed method can accurately predict future *** for hundreds of cycles using only one-present-cycle V-Q curve,with root mean square error and mean absolute error basically less than 0.035 Ah and R^(2) basically less than 98.5%.This means that incremental capacity curves can be extracted from the predicted results for a more comprehensive and accurate battery degradation ***,the method can flexibly adjust prediction length and density to cater to the practical needs of long-cycle prediction and data *** study provides a viable method for rapid degradation prediction and is expected to be generalized to in-vehicle implementations.

关键词： battery prediction curves

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Advancements in Poly(ionic liquid) composites with carbon nanomaterials

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advanced Industrial and Engineering Polymer Research 2025年第2期8卷 196-210页

作者： Li, Hui Gao, Jie Li, Zhiyong Zhang, Yan Zhang, Jun Zhang, Shiguo College of Materials Science and Engineering State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha410004 China School of Chemistry and Chemical Engineering Henan Normal University Xinxiang453007 China

Carbon nanomaterials have become essential in modern daily life. Their porous nature and good electrical conductivity are critical for composite applications. However, their inherent van der Waals forces and π-π interactions often result in spontaneous aggregation, which significantly hinders the uniform dispersion of carbon materials in polymer matrices. Establishing interactions between poly(ionic liquid) (PIL) and carbon materials ensures excellent compatibility. Integrating carbon materials with PIL markedly enhances mechanical strength, electrical conductivity, and thermal stability, benefiting the electronics, energy storage, and automotive industries. A thorough understanding of the physical and chemical properties of PILs is crucial for tailoring composite materials to specific applications, enhancing processing capabilities, and boosting performance. This article reviews recent advancements in PIL composites incorporating carbon nanomaterials and outlines future challenges in their development. © 2024 Kingfa Scientific and Technological Co. Ltd.

关键词： Automotive industry

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