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Application of dynamic image analysis to the optical characterisation of fibrous bulk material

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Particuology 2024年第7期90卷 51-60页

作者： Johannes Lunewski Eberhard schmidt Institute of Particle Technology University of WuppertalGermany

Dynamic image analysis provides an automated evaluation method to determine the size and shape of multiple particles. this method represents a common application for ordinary bulk material. the latest draft of ISO 13322–2:2021 describes the state of the art, but lacks instructions for handling fibrous bulk material. Interlocking fibres complicate the measurement conditions and require a disentanglement of fibrous samples during a pre-dispersion step. A further error source includes the fibre orientation inside the measurement zone of the device. If the thresholding algorithm fails to differentiate between the fibre projection area and the background, a subsequent image optimisation solves the problem. this article addresses the mentioned problems by analysing cotton cellulose and polyacrylonitrile fibres. Besides the execution of a pre-dispersion step, the experiments compare the discrepancies between dry and wet dispersion. Here, the software packages PAQXOS and ImageJ perform the image evaluation. In this case, the wet dispersion setup with a subsequent image evaluation by ImageJ provides comprehensible results.

关键词： Bootstrap method Dynamic image analysis Fibre diameter Fibre length distribution Natural fibres Synthetic fibres

Mechanistic modeling of copper corrosions in data center environments

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Building Simulation 2024年第3期17卷 483-492页

作者： Rui Zhang Jianshun Zhang Roger schmidt Jeremy L.Gilbert Department of Mechanical and Aerospace Engineering College of Engineering and Computer ScienceSyracuse UniversitySyracuseNY13244USA Buildings and Transportation Science Division Oak Ridge National LaboratoryOak RidgeTN37830USA SyracuseCoE-New York Center of Excellence in Environmental and Energy Systems Syracuse University727 E.Washington StreetSyracuseNY13244USA Department of Bioengineering Clemson UniversityClemson-Medical University of South Carolina Bioengineering ProgramCharlestonSC29425USA

Air-side economizers are increasingly used to take advantage of“free-cooling”in data centers with the intent of reducing the carbon footprint of ***,they can introduce outdoor pollutants to indoor environment of data centers and cause corrosion damage to the information technology *** evaluate the reliability of information technology equipment under various thermal and air-pollution conditions,a mechanistic model based on multi-ion transport and chemical reactions was *** model was used to predict Cu corrosion caused by Cl_(2)-containing pollutant *** also accounted for the effects of temperature(25℃and 28℃),relative humidity(50%,75%,and 95%),and *** also identified higher air temperature as a corrosion barrier and higher relative humidity as a corrosion accelerator,which agreed well with the experimental *** average root mean square error of the prediction was 13.7Å.the model can be used to evaluate the thermal guideline for data centers design and operation when Cl_(2)is present based on pre-established acceptable risk of corrosion in data centers’environment.

关键词： chloride pollutant mixture copper corrosion model data center temperature relative humidity synergistic effect

A single micro-LED manipulation system based on micro-gripper

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Nanotechnology and Precision Engineering 2024年第2期7卷 45-52页

作者： Jie Bai Pingjuan Niu Erdan Gu Jianming Li Clarence Augustine th Tee School of Mechanical Engineering Tiangong University School of Electronic and Information Engineering Tiangong University Institute of Photonics University of Strathclyde Tianjin Key Laboratory of Micro Low Gravity Environment Simulation Technology Tianjin Aerospace Electromechanical Equipment Research Institute Department of Electrical and Information Engineering School of Physics and Electrical Information EngineeringZhejiang Normal University

Micro-LEDs(μLEDs) have advantages in terms of brightness, power consumption, and response speed. In addition, they can also be used as micro-sensors implanted in the body via flexible electronic skin. One of the key techniques involved in the fabrication of μLED-based devices is transfer printing. Although numerous methods have been proposed for transfer printing, improving the yield of μLED arrays is still a formidable task. In this paper, we propose a novel method for improving the yield of μLED arrays transferred by the stamping method, using an innovative design of piezoelectrically driven asymmetric micro-gripper. Traditional grippers are too large to manipulate μLEDs, and therefore two micro-sized cantilevers are added at the gripper tips. A μLED manipulation system is constructed based on the micro-gripper together with a three-dimensional positioning system. Experimental results using this system show that it can be used successfully to manipulate μLED arrays.

关键词： Micro-gripper Micro-LED Transfer printing Manipulation

Transfer learning from synthetic data for open-circuit voltage curve reconstruction and state of health estimation of lithium-ion batteries from partial charging segments

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Energy and AI 2024年第3期17卷 80-97页

作者： Tobias Hofmann Jacob Hamar Bastian Mager Simon Erhard Jan Philipp schmidt Chair of Systems Engineering for Electrical Energy Storage University of BayreuthWeiherstraße 26Bayreuth95448BavariaGermany BMW Group Petuelring 130Munich80809BavariaGermany

Data-driven models for battery state estimation require extensive experimental training data,which may not be available or suitable for specific tasks like open-circuit voltage(OCV)reconstruction and subsequent state of health(SOH)*** study addresses this issue by developing a transfer-learning-based OCV reconstruction model using a temporal convolutional long short-term memory(TCN-LSTM)network trained on synthetic data from an automotive nickel cobalt aluminium oxide(NCA)cell generated through a mechanistic model *** data consists of voltage curves at constant temperature,C-rates between C/30 to 1C,and a SOH-range from 70%to 100%.the model is refined via Bayesian optimization and then applied to four use cases with reduced experimental nickel manganese cobalt oxide(NMC)cell training data for higher use *** TL models’performances are compared with models trained solely on experimental data,focusing on different C-rates and voltage *** results demonstrate that the OCV reconstruction mean absolute error(MAE)within the average battery electric vehicle(BEV)home charging window(30%to 85%state of charge(SOC))is less than 22 mV for the first three use cases across all *** SOH estimated from the reconstructed OCV exhibits an mean absolute percentage error(MAPE)below 2.2%for these *** study further investigates the impact of the source domain on TL by incorporating two additional synthetic datasets,a lithium iron phosphate(LFP)cell and an entirely artificial,non-existing,cell,showing that solely the shifting and scaling of gradient changes in the charging curve suffice to transfer knowledge,even between different cell chemistries.A key limitation with respect to extrapolation capability is identified and evidenced in our fourth use case,where the absence of such comprehensive data hindered the TL process.

关键词： Lithium-ion battery State of health estimation Transfer learning OCV curve Partial charging Synthetic data

STATNet:One-stage coal-gangue detector based on deep learning algorithm for real industrial application

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Energy and AI 2024年第3期17卷 113-125页

作者： Kefei Zhang a Teng Wang Xiaolin Yang Liang Xu Jesse thé Zhongchao Tan Hesheng Yu Key Laboratory of Coal Processing and Efficient Utilization of Ministry of Education School of Chemical Engineering and TechnologyChina University of Mining and TechnologyXuzhouJiangsu 221116China Department of Mechanical&Mechatronics Engineering University of Waterloo200 University Avenue WestWaterlooOntario N2L 3G1Canada Lakes Environmental Research Inc. 170 Columbia St.W.Suite 1WaterlooOntarioN2L 3L3 Canada Eastern Institute for Advanced Study Eastern Institute of TechnologyNingboZhejiang 315200China Department of Energy and Power Engineering Tsinghua UniversityBeijing 100084China

Coal-gangue object detection has attracted substantial attention because it is the core of realizing vision-based intelligent and green coal separation. However, most existing studies have been focused on laboratory datasets and prioritized model lightweight. this makes the coal-gangue object detection challenging to adapt to the complex and harsh scenes of real production environments. therefore, our project collected and labeled image datasets of coal and gangue under real production conditions from a coal preparation plant. We then designed a one-stage object model, named STATNet, following the “backbone-neck-head” architecture with the aim of enhancing the detection accuracy under industrial coal preparation scenarios. the proposed model utilizes Swin Transformer as backbone module to extract multi-scale features, improved path augmentation feature pyramid network (iPAFPN) as neck module to enrich feature fusion, and task-aligned head (TAH) as head module to mitigate conflicts and misalignments between classification and localization tasks. Experimental results on a real-world industrial dataset demonstrate that the proposed STATNet model achieves an impressive AP50 of 89.27 %, significantly surpassing several state-of-the-art baseline models by 2.02 % to 5.58 %. Additionally, it exhibits stronger robustness in resisting image corruption and perturbation. these findings demonstrate its promising prospects in practical coal and gangue separation applications.

关键词： Coal-gangue detection Swin transformer Impr oved path augmentation feature pyranid network Task-aligned head Object detection

A complete reference genome for the soybean ***

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Plant Communications 2024年第2期5卷 19-22页

作者： Yicheng Huang Dal-Hoe Koo Yizhou Mao Eliot M.Herman Jianwei Zhang Monica A.schmidt National Key Laboratory of Crop Genetic Improvement Hubei Hongshan LaboratoryHuazhong Agricultural UniversityWuhan 430070China Wheat Genetics Resource Center Department of Plant PathologyKansas State UniversityManhattanKS 66506USA BIO5 Institute School of Plant SciencesUniversity of ArizonaTucsonAZ 85721USA

Dear Editors,Soybeans are a global commodity for their edible protein and vegetable *** global population is predicted to be 9.7 billion by 2050(UN,2022),with a concomitant drastic increase in protein *** already 2.4 billion people suffering from food insecurity(FAO et al.,2023),there is an urgent need to meet future production demands for plant-based proteins.

关键词： commodity soybean urgent

Temporally Preserving Latent Variable Models:Offline and Online Training for Reconstruction and Interpretation of Fault Data for Gearbox Condition Monitoring

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Journal of Dynamics, Monitoring and Diagnostics 2024年第2期3卷 156-177页

作者： Ryan Balshaw P.Stephan Heyns Daniel N.Wilke Stephan schmidt Center for Asset Integrity Management Department of Mechanical and Aeronautical EngineeringUniversity of PretoriaPretoriaSouth Africa

Latent variable models can effectively determine the condition of essential rotating machinery without needing labeled *** models analyze vibration data via an unsupervised learning *** preservation is necessary to obtain an informative latent manifold for the fault diagnosis *** a temporalpreserving context,two approaches exist to develop a condition-monitoring methodology:offline and *** latent variable models,the available training modes are not *** many traditional methods use offline training,online training can dynamically adjust the latent manifold,possibly leading to better fault signature extraction from the vibration *** study explores online training using temporal-preserving latent variable *** online training,there are two main methods:one focuses on reconstructing data and the other on interpreting the data *** are considered to evaluate how they diagnose faults over *** two experimental datasets,the study confirms that models from both training modes can detect changes in machinery health and identify faults even under varying ***,the complementarity of offline and online models is emphasized,reassuring their versatility in fault *** the implications of the training approach and the available model formulations is crucial for further research in latent variable modelbased fault diagnostics.

关键词： Condition monitoring unsupervised learning latent variable models temporal preservation training approaches

Summary of the 11th Conference on Magnetic Confined Fusion theory and Simulation

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Plasma Science and Technology 2024年第10期26卷 1-7页

作者： Guangzhou HAO Jianqiang XU Youwen SUN Zhibin GUO Organizing Committee of the 11th Conference on Magnetic Confined Fusion theory and Simulation Southwestern Institute of Physics Chengdu 610041People’s Republic of China Institute of Plasma Physics Hefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031People’s Republic of China State Key Laboratory of Nuclear Physics and Technology Fusion Simulation CenterSchool of PhysicsPeking UniversityBeijing 100871People’s Republic of China 不详

this conference report summarizes recent progress in plasma theory and simulation that was presented in contributed papers and discussions at the 11th Conference on Magnetic Confined Fusion theory and Simulation(CMCFTS)held in Chengdu,China,27–30 October,*** in various fields has been *** example,results on zonal flow generation by mode coupling,simulations of the key physics of divertor detachment,energetic particle effects on magnetohydrodynamic(MHD)modes in addition to ion-and electron-scale turbulence,physics of edge coherent modes and edge-localized modes,and the optimization of ion heating schemes as well as confinement scenarios using advanced integrated modeling are presented at the *** this conference,the scientific research groups were organized into six categories:(a)edge and divertor physics;(b)impurity,heating,and current drive;(c)energetic particle physics;(d)turbulent transport;(e)MHD instability;and(f)integrated modeling and code development.A summary of the highlighted progress in these working groups is presented.

关键词： magnetic confined fusion(MCF) theory and simulation modeling tokamak

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Some Mean Convergence theorems for the Maximum of Normed Double Sums of Banach Space Valued Random Elements

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Acta Mathematica Sinica,English Series 2024年第7期40卷 1727-1740页

作者： Andrew ROSALSKY Le Van thANH Nguyen thi thUY Department of Statistics University of FloridaGainesvilleFL 32611-8545USA Department of Mathematics Vinh UniversityVinhNghe AnViet Nam High School for Gifted Students Vinh UniversityVinhNghe AnViet Nam

In this correspondence,we establish mean convergence theorems for the maximum of normed double sums of Banach space valued random *** of the results pertain to random elements which are *** expand and improve a number of particular cases in the literature on mean convergence of random elements in Banach *** of the main contributions of the paper is to simplify and improve a recent result of Li,Presnell,and Rosalsky[Journal of Mathematical Inequalities,16,117–126(2022)].A new maximal inequality for double sums of M-dependent random elements is proved which may be of independent *** sharpness of the results is illustrated by four examples.

关键词： Double sum mean convergence Rademacher type p Banach space Banach space valued random element M-dependent random elements

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