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Chinese Chemical Letters 2024年第6期35卷 502-506页

作者： Chaozheng He Pei Shi Donglin Pang Zhanying Zhang Long Lin Yingchun Ding department of Chemistry and Chemical engineering Liaocheng UniversityLiaocheng 252059China Henan Key Laboratory of Materials on Deep-Earth engineering School of Materials Science and EngineeringHenan Polytechnic UniversityJiaozuo 454000China School of Materials Science and engineering Henan Polytechnic UniversityJiaozuo 454000China department of Basic Medicine North Sichuan Medical CollegeNanchong 637000China

Single atom catalysts(SACs)have been in the forefront of catalysts research because of their high efficiency and low cost and provide new ideas for development of renewable energy conversion and storage ***,the relationship between the intrinsic properties of materials such as lattice thermal conductivity and catalysis remains to be *** this work,the lattice thermal conductivity of BN and graphene was calculated by Sheng *** addition,the adsorption properties of 3d-TM(TM=V,Cr,Mn,Fe,Co,Ni)on BN and graphene were investigated using first-principles methods,and it was found that Ni atom can form relatively stable SACs compared to other *** molecular dynamics(MD)simulation and migration barrier of Ni loaded on BN and graphene were *** study found that graphene has higher thermal conductivity and is easier to form SACs than BN,but the SACs formed on BN surface have higher thermodynamic stability.

关键词： First-principles calculation Thermal conductivity Single atom catalysts Graphene BN

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Prediction of vertical displacement for a buried pipeline subjected to normal fault using a hybrid FEM-ANN approach

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Frontiers of Structural and Civil engineering 2024年第3期18卷 428-443页

作者： Hedye JALALI Reza YEGANEH KHAKSAR Danial MOHAMMADZADEH S. Nader KARBALLAEEZADEH Amir H.GANDOMI department of Civil engineering Architecture and UrbanismSadjad University of TechnologyPO Box ***MashhadIran department of Civil engineering Faculty of EngineeringEqbal Lahoori Institute of Higher EducationPO Box ***MashhadIran Faculty of Civil engineering Architectureand ArtScience and Research Branch of Islamic Azad UniversityPO Box ***TehranIran Faculty of engineering&Information Technology University of Technology SydneyUltimoNSW 2007Australia University Research and Innovation Center(EKIK) Óbuda UniversityBudapest 1034Hungary

Fault movement during earthquakes is a geotechnical phenomenon threatening buried pipelines and with the potential to cause severe damage to critical ***,effective prediction of pipe displacement is crucial for preventive management *** study aims to develop a fast,hybrid model for predicting vertical displacement of pipe networks when they experience *** this study,the complex behavior of soil and a buried pipeline system subjected to a normal fault is analyzed by using an artificial neural network(ANN)to generate predictions the behavior of the soil when different parameters of it are *** this purpose,a finite element model is developed for a pipeline subjected to normal fault *** data bank used for training the ANN includes all the critical soil parameters(cohesion,internal friction angle,Young’s modulus,and faulting).Furthermore,a mathematical formula is presented,based on biases and weights of the ANN *** results show that the maximum error of the presented formula is 2.03%,which makes the proposed technique efficiently predict the vertical displacement of buried pipelines and hence,helps to optimize the upcoming pipeline projects.

关键词： buried pipelines normal Fault finite element method multilayer perceptron neural network formulation

Significant annealing-induced hardening effect in nanolaminate d-nanotwinne d(CrCoNi)_(97.4)Al_(0.8)Ti_(1.8)me dium-entropy alloy by severe cold rolling

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Journal of Materials Science & Technology 2024年第3期170卷 156-166页

作者： Shuqing Yuan Hui Fu Lei Qian Chi Fai Cheung Xu-Sheng Yang State Key Laboratory of Ultra-precision Machining Technology Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina Hong Kong polytechnic University Shenzhen Research Institute Shenzhen 518060China

Due to the easy coarsening caused by poor thermal stability,the verified annealing-induced hardening in nanograined metals can only maintain at a relatively low-temperature *** this study,a nanolam-inated(CrCoNi)_(97.4)Al_(0.8)Ti_(1.8)medium-entropy alloy with an average lamellae thickness of∼20 nm embedded by thinner nanotwins was fabricated by severe cold rolling to achieve superior thermal *** with the conventional nanotwinned CrCoNi with nanotwins inside ultra-fined grains,the hier-archical nanolaminated-nanotwinned(CrCoNi)_(97.4)Al_(0.8)Ti_(1.8) exhibits a significant annealing-induced hard-ening effect,i.e.,hardness increasing from∼250 HV in the original specimen to∼500 HV in the cold-rolled status and finally∼630 HV after annealing at 600℃for 1 *** microstructure characterizations reveal that the reduced dislocation density and formation of L1_(2)ordered domain are mainly responsible for such hardening effect,which is facilitated by the effectively suppressed coarsening with annealing temperature,i.e.,slow detwinning process and well-retained low-angle nanolamellar *** coarsening mechanisms from the cold-rolled nanolamellae to the fully recrystallized micro-equiaxed structures under the annealing temperatures ranging from 400 to 800℃ were also elucidated by atomic observations.

关键词： Annealing-induced hardening Thermal stability Nanolaminated-nanotwinned structure CrCoNi Detwinning Grain boundary migration

Research on Modeling and Parameter Identification of Comprehensive Load Model of Distribution Network in Industrial Park

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Chinese Journal of Electronics 2024年第1期33卷 264-273页

作者： Tingling WANG Xiaohe YAN School of Electric engineering North China University of Water Resources and Electric Power Wenzhou polytechnic

With the rapid development of industrial parks, its load model research has become a hot spot. In order to study the load of power system in industrial park, based on the characteristics of the industrial park load, a comprehensive load admittance static model with full voltage range adaptability is considered, and a comprehensive load model of distribution network of the industrial park is established. A complete parameter identification of the model is carried out through chaos particle swarm optimization. The simulation results show that the model can effectively describe the load characteristics of the distribution network in industrial parks.

关键词： Chaos Adaptation models Analytical models Parameter estimation Induction motors Simulation Distribution networks

A Study on Enhancing Chip Detection Efficiency Using the Lightweight Van-YOLOv8 Network

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Computers, Materials & Continua 2024年第4期79卷 531-547页

作者： Meng Huang Honglei Wei Xianyi Zhai School of Mechanical engineering and Automation Dalian Polytechnic UniversityDalian116034China

In pursuit of cost-effective manufacturing,enterprises are increasingly adopting the practice of utilizing recycled semiconductor *** ensure consistent chip orientation during packaging,a circular marker on the front side is employed for pin alignment following successful functional ***,recycled chips often exhibit substantial surface wear,and the identification of the relatively small marker proves ***,the complexity of generic target detection algorithms hampers seamless *** these issues,this paper introduces a lightweight YOLOv8s-based network tailored for detecting markings on recycled chips,termed ***,to alleviate the influence of diminutive,low-resolution markings on the precision of deep learning models,we utilize an upscaling approach for enhanced *** technique relies on the Super-Resolution Generative Adversarial Network with Extended Training(SRGANext)network,facilitating the reconstruction of high-fidelity images that align with input ***,we replace the original YOLOv8smodel’s backbone feature extraction network with the lightweight VanillaNetwork(VanillaNet),simplifying the branch structure to reduce network ***,a Hybrid Attention Mechanism(HAM)is implemented to capture essential details from input images,improving feature representation while concurrently expediting model inference *** results demonstrate that the Van-YOLOv8 network outperforms the original YOLOv8s on a recycled chip dataset in various ***,it demonstrates superiority in parameter count,computational intricacy,precision in identifying targets,and speed when compared to certain prevalent algorithms in the current *** proposed approach proves promising for real-time detection of recycled chips in practical factory settings.

关键词： Lightweight neural networks attention mechanisms image super-resolution enhancement feature extraction small object detection

Recycling arsenic-containing bio-leaching residue after thermal treatment in cemented paste backfill:Structure modification,binder properties and environmental assessment

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International Journal of Minerals,Metallurgy and Materials 2024年第10期31卷 2136-2147页

作者： Dengfeng Zhao Shiyu Zhang Yingliang Zhao department of Mining engineering Lyuliang UniversityLvliang 033000China School of Civil and Environmental engineering University of Science and Technology BeijingBeijing 100083China School of Mining engineering Taiyuan University of TechnologyTaiyuan 030024China department of Civil and Environmental engineering The Hong Kong Polytechnic UniversityHong Kong 00852China

The substantial arsenic(As)content present in arsenic-containing bio-leaching residue(ABR)presents noteworthy environ-mental challenges attributable to its inherent instability and susceptibility to *** its elevated calcium sulfate content,ABR exhibits considerable promise for industrial *** study delved into the feasibility of utilizing ABR as a source of sulfates for producing super sulfated cement(SSC),offering an innovative binder for cemented paste backfill(CPB).Thermal treatment at varying temperatures of 150,350,600,and 800℃ was employed to modify ABR’s *** investigation encompassed the examination of phase transformations and alterations in the chemical composition of As within ***,the hydration characteristics of SSC utilizing ABR,with or without thermal treatment,were studied,encompassing reaction kinetics,setting time,strength development,and *** findings revealed that thermal treatment changed the calcium sulfate structure in ABR,consequently impacting the resultant sample ***,calcination at 600℃ demonstrated optimal modification effects on both early and long-term strength *** enhanced performance can be attributed to the augmented formation of reaction products and a densified ***,the thermal treatment elicited modifications in the chemical As fractions within ABR,with limited impact on the As immobilization capacity of the prepared binders.

关键词： cemented paste backfill bio-leaching residue arsenic immobilization binder hydration calcination

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An Underwater Target Detection Algorithm Based on Attention Mechanism and Improved YOLOv7

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Computers, Materials & Continua 2024年第2期78卷 2829-2845页

作者： Liqiu Ren Zhanying Li Xueyu He Lingyan Kong Yinghao Zhang College of Information Science and engineering Dalian Polytechnic UniversityDalian116034China

For underwater robots in the process of performing target detection tasks,the color distortion and the uneven quality of underwater images lead to great difficulties in the feature extraction process of the model,which is prone to issues like error detection,omission detection,and poor ***,this paper proposed the CER-YOLOv7(CBAM-EIOU-RepVGG-YOLOv7)underwater target detection *** improve the algorithm’s capability to retain valid features from both spatial and channel perspectives during the feature extraction phase,we have added a Convolutional Block Attention Module(CBAM)to the backbone *** Reparameterization Visual Geometry Group(RepVGG)module is inserted into the backbone to improve the training and inference *** Efficient Intersection over Union(EIoU)loss is also used as the localization loss function,which reduces the error detection rate and missed detection rate of the *** experimental results of the CER-YOLOv7 algorithm on the UPRC(Underwater Robot Prototype Competition)dataset show that the mAP(mean Average Precision)score of the algorithm is 86.1%,which is a 2.2%improvement compared to the *** feasibility and validity of the CER-YOLOv7 are proved through ablation and comparison experiments,and it is more suitable for underwater target detection.

关键词： Deep learning underwater object detection improved YOLOv7 attention mechanism

Fault detection of new and aged lithium-ion battery cells in electric vehicles

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Green Energy and Intelligent Transportation 2024年第3期3卷 42-53页

作者： Sara Sepasiahooyi Farzaneh Abdollahi department of Electrical engineering Amirkabir University of Technology(Tehran Polytechnic)424 Hafez AveTehranIran department of Mechanical engineering Texas Tech UniversityLubbockTXUSA department of Mechanical and Aerospace engineering Carleton UniversityOttawaONCanada

In this paper,a novel model-based fault detection in the battery management system of an electric vehicle is *** adaptive observers are designed to detect state-of-charge faults and voltage sensor faults,considering the impact of battery *** aging primarily affects capacity and resistance,becoming more pronounced in the later stages of a battery *** incorporating aging effects into our fault diagnosis scheme,our proposed approach prevents false or missed alarms for the aged battery *** aging effect of battery,capacity fading and resistance growth,are considered unknown *** adaptive observer is employed to design a fault detector,considering unknown parameters in the battery *** adaptive observers are designed for two different scenarios:In the first scenario,it is presumed that aging effects remain constant over time due to their slow rate of ***,it is assumed that aging effects are ***,the fault detection scheme can detect faults of new battery cells as well as aged *** simulations have been conducted on a Lithium-ion battery cell and extended to battery pack,to demonstrate the performance of the proposed approach in more real-world *** results showed that the designed observers can detect faults correctly in a seven years old battery as well as a new one.

关键词： Adaptive observer Aging Electric vehicle Fault detection Lithium-ion battery State of charge

A Privacy-preserving Energy Management System Based on Homomorphic Cryptosystem for IoT-enabled Active Distribution Network

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 167-178页

作者： Qian Hu Siqi Bu Wencong Su Vladimir Terzija the department of Physics Hong Kong Baptist UniversityHong KongChina the department of Electrical and Electronic engineering Shenzhen Research InstituteThe Hong Kong Polytechnic UniversityHong KongChina the department of Electrical and Computer engineering University of Michigan-DearbornDearbornMI 48128USA the School of engineering Newcastle UniversityNewcastleUK

Active distribution network(ADN),as a typically cyber-physical system,develops with the evolution of Internet of Things(IoTs),which makes the network vulnerable to cybersecurity *** this paper,the eavesdropping attacks that lead to privacy breaches are addressed for the IoT-enabled ADN.A privacy-preserving energy management system(EMS)is proposed and empowered by secure data exchange protocols based on the homomorphic *** the information transmission among distributed generators and load customers in the EMS,private information including power usage and electricity bidding price can be effectively protected against eavesdropping *** correctness of the final solutions,e.g.,optimal market clearing price and unified power utilization ratio,can be deterministically *** simulation results demonstrate the effectiveness and the computational efficiency of the proposed homomorphically encrypted EMS.

关键词： Eavesdropping attack energy management system homomorphic cryptosystem Internet of Things(IOTs) active distribution network(ADN) privacy-preserving

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Distributed fiber optic sensors for tunnel monitoring:A state-of-the-art review

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Journal of Rock Mechanics and Geotechnical engineering 2024年第9期16卷 3841-3863页

作者： Xuehui Zhang Honghu Zhu Xi Jiang Wout Broere Geo-engineering Section Department of Geoscience and EngineeringDelft University of TechnologyDelft2628CNthe Netherlands School of Earth Sciences and engineering Nanjing UniversityNanjing210023China department of Civil and Environmental engineering The Hong Kong Polytechnic UniversityKowloonHong KongChina

Distributed fiber optic sensors(DFOSs)possess the capability to measure strain and temperature variations over long distances,demonstrating outstanding potential for monitoring underground *** study presents a state-of-the-art review of the DFOS applications for monitoring and assessing the deformation behavior of typical tunnel infrastructure,including bored tunnels,conventional tunnels,as well as immersed and cut-and-cover *** systems based on Brillouin and Rayleigh scattering principles are both *** implementing DFOS monitoring,the fiber optic cable can be primarily installed along transverse and longitudinal directions to(1)measure distributed strains by continuously adhering the fiber to the structure’s surface or embedding it in the lining,or(2)measure point displacements by spot-anchoring it on the lining *** are four critical aspects of DFOS monitoring,including proper selection of the sensing fiber,selection of the measuring principle for the specific application,design of an effective sensor layout,and establishment of robust field sensor *** four issues are comprehensively discussed,and practical suggestions are provided for the implementation of DFOS in tunnel infrastructure monitoring.

关键词： Distributed fiber optic sensor(DFOS) Tunnel infrastructure Distributed strain sensing Point displacement monitoring Field instrumentation