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Journal of Thermal Science 2024年第2期33卷 675-695页

作者： ZHANG Hao ZHAO Hongxia ZHANG Xiuao zeng Hongxuan deNG Jianqiang School of Energy and Power Engineering Shandong UniversityJi’nan250061China School of Chemical Engineering and Technology Xi’an Jiaotong UniversityXi’an710049China

The steam ejector is a crucial component in the waste heat recovery *** performance determines the amount of recovered heat and system ***,poor ejector performance has always been the main bottleneck for system ***,this study proposes an optimization methodology to improve the steam ejector's performance by utilizing computational fluid dynamics(CFD) techniques,response surface methodology(RSM),and genetic algorithm(GA).Firstly,a homogeneous equilibrium model(HEM) was established to simulate the two-phase flow in the steam ***,the orthogonal test was presented to the screening of the key decision variables that have a significant impact on the entrainment ratio(ER).Next,the RSM was used to fit a response surface regression model(RSRM).Meanwhile,the effect of the interaction of geometric parameters on the performance of the steam ejector was ***,GA was employed to solve the RSRM's global optimal ER *** results show that the RSRM exhibits a good fit for ER(R^(2)=0.997).After RSM and GA optimization,the maximum ejector efficiency is 27.94%,which is 48.38% higher than the initial ejector of 18.83%.Furthermore,the optimized ejector efficiency is increased by 46.4% on average under off-design ***,the results reveal that the combination of CFD,RSM,and GA presents excellent reliability and feasibility in the optimization design of a two-phase steam ejector.

关键词： two-phase steam ejector optimization methodology CFD techniques response surface methodology genetic algorithm homogeneous equilibrium model

A Novel Tensor decomposition-Based Efficient detector for Low-Altitude Aerial Objects With Knowledge Distillation Scheme

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 487-501页

作者： Nianyin zeng Xinyu Li Peishu Wu Han Li Xin Luo department of Instrumental and Electrical Engineering Xiamen UniversityXiamen 361005China IEEE College of Computer and Information Science Southwest UniversityChongqing 400715China

Unmanned aerial vehicles(UAVs) have gained significant attention in practical applications, especially the low-altitude aerial(LAA) object detection imposes stringent requirements on recognition accuracy and computational resources. In this paper, the LAA images-oriented tensor decomposition and knowledge distillation-based network(TDKD-Net) is proposed,where the TT-format TD(tensor decomposition) and equalweighted response-based KD(knowledge distillation) methods are designed to minimize redundant parameters while ensuring comparable performance. Moreover, some robust network structures are developed, including the small object detection head and the dual-domain attention mechanism, which enable the model to leverage the learned knowledge from small-scale targets and selectively focus on salient features. Considering the imbalance of bounding box regression samples and the inaccuracy of regression geometric factors, the focal and efficient IoU(intersection of union) loss with optimal transport assignment(F-EIoU-OTA)mechanism is proposed to improve the detection accuracy. The proposed TDKD-Net is comprehensively evaluated through extensive experiments, and the results have demonstrated the effectiveness and superiority of the developed methods in comparison to other advanced detection algorithms, which also present high generalization and strong robustness. As a resource-efficient precise network, the complex detection of small and occluded LAA objects is also well addressed by TDKD-Net, which provides useful insights on handling imbalanced issues and realizing domain adaptation.

关键词： Attention mechanism knowledge distillation(KD) object detection tensor decomposition(TD) unmanned aerial vehicles(UAVs)

Study on theoretical model for electrical explosion resistivity of Al/Ni reactive multilayer foil

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defence Technology（防务技术） 2024年第2期32卷 348-356页

作者： zehao Wang Tao Wang Pengfei Xue Mingyu Li Qingxuan zeng State Key Laboratory of Explosion Science and Technology Beijing Institute of TechnologyBeijing 100081China China Ship development and design Center Wuhan 430064China

Al/Ni reactive multilayer foil(RMF)possesses excellent comprehensive properties as a promising substitute for traditional Cu bridge.A theoretical resistivity model of Al/Ni RMF was developed to guide the optimization of ***/Ni RMF with different bilayer thicknesses and bridge dimensions were prepared by MEMS technology and electrical explosion tests were carried *** to physical and chemical reactions in bridge,the electrical explosion process was divided into 5 stages:heating of condensed bridge,vaporization and diffusion of Al layers,intermetallic combination reaction,intrinsic explosion,ionization of metal gases,which are obviously shown in measured voltage *** of interface and grain boundary scattering on the resistivity of film metal were *** on variations of substance and state,the resistivity was developed as a function of temperature at each *** explosion curves were calculated by this model at different bilayer thicknesses,bridge dimensions and capacitor voltages,which showed an excellent agreement with experimental ones.

关键词： Al/Ni reactive multilayer foil Electrical explosion Resistivity model Phase transition Calculation

Unsupervised Multi-Expert Learning Model for Underwater Image Enhancement

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 708-722页

作者： Hongmin Liu Qi Zhang Yufan Hu Hui zeng Bin Fan the School of Intelligence Science and Technology and the Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China the School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China IEEE

Underwater image enhancement aims to restore a clean appearance and thus improves the quality of underwater degraded *** methods feed the whole image directly into the model for ***,they ignored that the R,G and B channels of underwater degraded images present varied degrees of degradation,due to the selective absorption for the *** address this issue,we propose an unsupervised multi-expert learning model by considering the enhancement of each color ***,an unsupervised architecture based on generative adversarial network is employed to alleviate the need for paired underwater *** on this,we design a generator,including a multi-expert encoder,a feature fusion module and a feature fusion-guided decoder,to generate the clear underwater ***,a multi-expert discriminator is proposed to verify the authenticity of the R,G and B channels,*** addition,content perceptual loss and edge loss are introduced into the loss function to further improve the content and details of the enhanced *** experiments on public datasets demonstrate that our method achieves more pleasing results in vision *** metrics(PSNR,SSIM,UIQM and UCIQE) evaluated on our enhanced images have been improved obviously.

关键词： Multi-expert learning underwater image enhancement unsupervised learning

Data-driven Anomaly detection Method Based on Similarities of Multiple Wind Turbines

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 803-818页

作者： Xiangjun zeng Ming Yang Chen Feng Mingqiang Wang Lingqin Xia the College of Electrical Engineering&New Energy China Three Gorges UniversityYichang 443002China the Key Laboratory of Power System Intelligent Dispatch and Control Shandong UniversityJinan 250061China

The operating conditions of wind turbines(WTs)in the same wind farm(WF)may share similarities due to their shared manufacturing process,control strategy,and operating ***,the similarities of WTs are seldom considered in WT anomaly detection,resulting in the disregard of useful *** paper proposes a method to improve the reliability and accuracy of WT anomaly detection using the supervisory control and data acquisition(SCADA)data of multiple WTs in the same ***,a similarity assessment method based on a comparison of different observation time series is proposed,which objectively quantifies the similarities of WT operating ***,the SCADA data of the target WT and selected WTs that are similar are used to establish several estimation models through a long short-term memory(LSTM)*** models that exhibit good estimation performance are used to construct a combined estimation model that estimates the variations in the monitored variables of the target ***,an anomaly detection method that jointly compares the effective value and information entropy of the residuals is proposed to identify *** effectiveness and accuracy of the proposed method are verified using the data of two actual WFs.

关键词： Anomaly detection information entropy long short-term memory similarity assessment wind farm wind turbines

Monte Carlo Simulation-Based Robust Workflow Scheduling for Spot Instances in Cloud Environments

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Tsinghua Science and Technology 2024年第1期29卷 112-126页

作者： Quanwang Wu Jianzhao Fang Jie zeng Junhao Wen Fengji Luo College of Computer Science Chongqing UniversityChongqing 400044China National Experimental Teaching demonstration Center Chongqing UniversityChongqing 400044China College of Big Data and Software Engineering Chongqing UniversityChongqing 400044China School of Civil Engineering The University of SydneySydney 2006Australia

When deploying workflows in cloud environments,the use of Spot Instances(SIs)is intriguing as they are much cheaper than on-demand ***,Sls are volatile and may be revoked at any time,which results in a more challenging scheduling problem involving execution interruption and hence hinders the successful handling of conventional cloud workflow scheduling *** some scheduling methods for Sls have been proposed,most of them are no more applicable to the latest Sls,as they have evolved by eliminating bidding and simplifying the pricing *** study focuses on how to minimize the execution cost with a deadline constraint when deploying a workflow on volatile Sls in cloud *** on Monte Carlo simulation and list scheduling,a stochastic scheduling method called MCLS is devised to optimize a utility function introduced for this *** the Monte Carlo simulation framework,MCLS employs sampled task execution time to build solutions via deadline distribution and list scheduling,and then returns the most robust solution from all the candidates with a specific evaluation mechanism and selection *** results show that the performance of MCLS is more competitive comparedwithtraditionalalgorithms.

关键词： constrained optimization Monte Carlo simulation robustness Spot Instances(Sls) workflow scheduling

Strongyloides stercoralis-induced sepsis and acute respiratory distress syndrome in a patient with Guillain-Barré syndrome

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World Journal of Emergency Medicine 2024年第5期15卷 413-415页

作者： Juhao zeng Yin Wen Hongguang Ding Dongxin Li Hongke zeng department of Critical Care Medicine Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhou 510080China Emergency department Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhou 510080China

Strongyloidiasis stercoralis can cause disease when larvae invade the human body through the skin or mucosa and can also infect a host when the host ingests its eggs.[1]Strongyloidiasis lacks characteristic manifestations,and its clinical symptoms are related to the immune response of the host and the degree of *** cient patients with underlying disease or who are receiving long-term corticosteroid treatment are more prone to developing severe disease.[2]The present study reports a case of Strongyloides stercoralis-induced sepsis and acute respiratory distress syndrome(ARDS)in a patient with Guillain-Barrésyndrome.

关键词： distress Barr sepsis

ANovel Non-Isolated Cubic DC-DC Converter with High Voltage Gain for Renewable Energy Power Generation System

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Energy Engineering 2024年第1期121卷 221-241页

作者： Qin Yao Yida zeng Qingui Jia School of Electrical Engineering Southwest Jiaotong UniversityChengdu610036China

In recent years,switched inductor(SL)technology,switched capacitor(SC)technology,and switched inductor-capacitor(SL-SC)technology have been widely applied to optimize and improve DC-DC boost converters,which can effectively enhance voltage gain and reduce device *** address the issue of low output voltage in current renewable energy power generation systems,this study proposes a novel non-isolated cubic high-gain DC-DC converter based on the traditional quadratic DC-DC boost converter by incorporating a SC and a SL-SC ***,the proposed converter’s details are elaborated,including its topology structure,operating mode,voltage gain,device stress,and power ***,a comparative analysis is conducted on the voltage gain and device stress between the proposed converter and other high-gain ***,a closed-loop simulation system is constructed to obtain simulation waveforms of various devices and explore the dynamic ***,an experimental prototype is built,experimental waveforms are obtained,and the experimental dynamic performance and conversion efficiency are *** theoretical analysis’s correctness is verified through simulation and experimental *** proposed converter has advantages such as high voltage gain,low device stress,high conversion efficiency,simple control,and wide input voltage range,achieving a good balance between voltage gain,device stress,and power *** proposed converter is well-suited for renewable energy systems and holds theoretical significance and practical value in renewable energy *** provides an effective solution to the issue of low output voltage in renewable energy power generation systems.

关键词： Cubic DC-DC converter high voltage gain low device stress high efficiency renewable energy

Study of Flow and Heat Transfer in an Ejector-Driven Swirl Anti-Icing Chamber

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Fluid Dynamics & Materials Processing 2024年第5期20卷 989-1014页

作者： Yi Tu Yuan Wu Yu zeng Hunan University of Arts and Sciences Hunan Key Laboratory of Distributed Electric Propulsion Vehicle Control TechnologyChangde415000China Liaoning Provincial Key Laboratory of Aircraft Ice Protection AVIC Aerodynamics Research InstituteShenyang110034China School of Aeronautic Science and Engineering Beihang UniversityBeijing100191China

The formation of ice on the leading edge of aircraft engines is a serious issue,as it can have catastrophic *** Swirl Anti-Icing(SAI)system,driven by ejection,circulates hot fluid within a 360°annular chamber to heat the engine inlet lip surface and prevent *** study employs a validated Computational Fluid Dynamics(CFD)approach to study the impact of key geometric parameters of this system on flow and heat transfer characteristics within the anti-icing ***,the entropy generation rate and exergy efficiency are analyzed to assess the energy utilization in the *** research findings indicate that,within the considered flow range,reducing the nozzle specific areaφfrom 0.03061 to 0.01083 can enhance the ejection coefficient by over 60.7%.This enhancement increases the air circulating rate,thereby intensifying convective heat transfer within the SAI ***,the reduction inφalso leads to a significant increase in the required bleed air pressure and a higher entropy generation rate,indicating lower exergy *** nozzle angleθnotably affects the distribution of hot and cold spots on the lip surface of the SAI ***θfrom 0°to 20°reduces the maximum temperature difference on the anti-icing chamber surface by 60 K.

关键词： Swirl anti-icing heat transfer exergy efficiency hot and cold spot aircraft engine

Heterogeneous Task Allocation Model and Algorithm for Intelligent Connected Vehicles

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Computers, Materials & Continua 2024年第9期80卷 4281-4302页

作者： Neng Wan Guangping zeng Xianwei Zhou School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China School of Mechanical and Transportation Southwest Forestry UniversityKunming650224China

With the development of vehicles towards intelligence and connectivity,vehicular data is diversifying and growing dramatically.A task allocation model and algorithm for heterogeneous Intelligent Connected Vehicle(ICV)applications are proposed for the dispersed computing network composed of heterogeneous task vehicles and Network Computing Points(NCPs).Considering the amount of task data and the idle resources of NCPs,a computing resource scheduling model for NCPs is *** the heterogeneous task execution delay threshold as a constraint,the optimization problem is described as the problem of maximizing the utilization of computing resources by *** proposed problem is proven to be NP-hard by using the method of reduction to a 0-1 knapsack problem.A many-to-many matching algorithm based on resource preferences is *** algorithm first establishes the mutual preference lists based on the adaptability of the task requirements and the resources provided by *** enables the filtering out of un-schedulable NCPs in the initial stage of matching,reducing the solution space *** solve the matching problem between ICVs and NCPs,a new manyto-many matching algorithm is proposed to obtain a unique and stable optimal matching *** simulation results demonstrate that the proposed scheme can improve the resource utilization of NCPs by an average of 9.6%compared to the reference scheme,and the total performance can be improved by up to 15.9%.

关键词： Task allocation intelligent connected vehicles dispersed computing matching algorithm