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Benchmark evaluation of tomographic algorithms for simultaneous reconstruction of temperature and volume fraction fields of soot and metal-oxide nanoparticles in non-uniform flames

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Science China(Technological Sciences) 2021年第2期64卷 237-250页

作者： SHUI ChongYuan LIU HeCong cai weiwei Key Laboratory for Power Machinery and Engineering of Ministry of Education School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

With the growing applications of nanofluid flame, the monitoring and controlling of its combustion process is of paramount importance. Thus, it is necessary to develop diagnosing methods which can simultaneously image important parameters such as temperature and volume fractions of soot, metal-oxide nanoparticles. Tomographic emission spectroscopy is an effective method which has been proposed for this purpose. However, the inversion process was only reported with least-squares QR decomposition(LSQR) so far and there are numerous well-established reconstruction algorithms which have not been utilized ***, this work aims to perform systematic comparative studies on several representative algorithms for the inversion process. In the simulative studies, algorithms including Tikhonov regularization, algebraic reconstruction technique(ART), LSQR,Landweber algorithm, maximum likelihood expectation maximization(MLEM), and ordered subset expectation maximization(OSEM) were discussed. The effects of the number of iterations, the signal-to-noise ratio, and the number of projections and the calibration error in projection angles on the performance of the algorithms were investigated. Advice on selecting the suitable algorithms under different application conditions is then provided according to the extensive numerical studies.

关键词： inverse analysis algorithms temperature field soot and metal-oxide volume fraction non-uniform nanofluid flame

Volumetric imaging of flame refractive index, density, and temperature using background-oriented Schlieren tomography

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Science China(Technological Sciences) 2021年第1期64卷 98-110页

作者： LIU HeCong HUANG JianQing LI Lei cai weiwei School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Volumetric imaging represents one of the major development trends of flow diagnostics due to both the advancement in hardware and the requirement for more information to further understand complicated turbulent and/or reactive flows. Backgroundoriented Schlieren tomography(BOST) has become increasingly popular due to its experimental simplicity. It has been demonstrated to be capable of simultaneously recovering the distributions of refractive index, density, and temperature of ***, its capability in thermometry has only been demonstrated under the axisymmetric assumption, which greatly limits its applicability. In this work, we dedicated to developing a cost-effective BOST system for the simultaneous retrieval of refractive index, density, and temperature distributions for the asymmetric flame. A few representative tomographic inversion algorithms were assessed as well. Both numerical and experimental demonstrations were conducted and the results show that our implemented BOST can successfully reconstruct the three-dimensional temperature distribution with a satisfactory accuracy.

关键词： Schlieren tomography combustion diagnostics temperature

Mission scheduling of multi-sensor collaborative observation for space surveillance network

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Journal of Systems Engineering and Electronics 2023年第4期34卷 906-923页

作者： LONG Xi cai weiwei YANG Leping WANG Tianyu College of Aerospace Science and Engineering National University of Defense TechnologyChangsha 410073China School of Traffic and Transportation Engineering Central South UniversityChangsha 410073China

With increased dependence on space assets,scheduling and tasking of the space surveillance network(SSN)are vitally *** multi-sensor collaborative observation scheduling(MCOS)problem is a multi-constraint and high-conflict complex combinatorial optimization problem that is nondeterministic polynomial(NP)-*** research establishes a sub-time window constraint satisfaction problem(STWCSP)model with the objective of maximizing observation *** the significant effect of genetic algorithms(GA)on solving the problem of resource allocation,an evolution heuristic(EH)algorithm containing three strategies that focus on the MCOS problem is *** each case,a task scheduling sequence is first obtained via an improved GA with penalty(GAPE)algorithm,and then a mission planning algorithm(heuristic rule)is used to determine the specific observation *** to the model without sub-time windows and some other algorithms,a series of experiments illustrate the STWCSP model has better performance in terms of total *** about strategy and parameter sensitivity validate its excellent performance in terms of EH algorithms.

关键词： multi-sensor observation resource scheduling subtime window evolution heuristic algorithm

A semi-transparent selective undo algorithm for multi-user collaborative editors

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Frontiers of Computer Science 2021年第5期15卷 53-69页

作者： weiwei cai Fazhi HE Xiao LV Yuan CHENG School of Computer Science Wuhan UniversityWuhan 430072China Department of Computer Engineering Naval University of EngineeringWuhan 430072China School of Information Management Wuhan UniversityWuhan 430072China

Multi-user collaborative editors are useful computer-aided tools to support human-to-human *** multi-user collaborative editors,selective undo is an essential utility enabling users to undo any editing operations at any *** editors usually adopt operational transformation(OT)to address concurrency and consistency ***,it is still a great challenge to design an efficient and correct OT algorithm capable of handling both normal do operations and user-initiated undo operations because these two kinds of operations can interfere with each other in various *** this paper,we propose a semi-transparent selective undo algorithm that handles both do and undo in a unified framework,which separates the processing part of do operations from the processing part of undo *** proofs are provided to prove the proposed algorithm under the well-established *** analysis and experimental evaluation are conducted to show that the proposed algorithm outperforms the prior OT-based selective undo algorithms.

关键词： human-centric collaboration collaborative editing systems selective undo concurrency control replication consistency

Development of a single-camera volumetric thermometry for gas flows based on space division multiplexing

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Science China(Technological Sciences) 2022年第7期65卷 1646-1650页

作者： WANG Qian LIU HeCong cai weiwei Key Laboratory of Education Ministry for Power Machinery and Engineering School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Optical imaging methods have been widely applied in combustion diagnostics due to their high sensitivity, versatility, non-intrusiveness, and amenability for implementation in harsh environment [1,2]. Compared with traditional intrusive diagnostics, such as thermometry with thermocouples and manometry with pressure transducers, planar imaging methods provide richer insights into fluid dynamics and complex combustion phenomena.

关键词： planar insight flows

同方期刊数据库

Li-ion battery temperature estimation based on recurrent neural networks

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Science China(Technological Sciences) 2021年第6期64卷 1335-1344页

作者： JIANG YuHeng YU YiFei HUANG JianQing cai weiwei MARCO James Key Laboratory of Education Ministry for Power Machinery and Engineering School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China University of Warwick-Warwick Manufacturing Group(WMG) Coventry CV47ALUK

The monitoring of Li-ion battery temperatures is essential to ensure high efficiency and *** this work,two types of recurrent neural networks (RNNs),which are long short-term memory-RNN (LSTM-RNN) and gated recurrent unit-RNN(GRU-RNN),are proposed to estimate the surface temperature of 18650 Li-ion batteries during the discharging processes under different ambient *** datasets acquired from the Prognostics Center of Excellence (PCo E) of NASA are used to train,validate and test the *** previous work,temperature has been set as the output of the networks;however,here the temperature difference along the time axis is adopted as the *** net heat generated results in net temperature change,which is more closely aligned with electrochemical and thermodynamic *** simulation results show that the two RNNs can achieve accurate real-time battery temperature *** maximum absolute error in temperature estimation is approximately 0.75°C and the correlation coefficient between the estimated and measured temperature curves is greater than *** influences of three crucial parameters,which are the number of hidden neurons,initial learning rate and maximum number of iterations,are also assessed in terms of training time,root mean square error and mean absolute error.

关键词： battery temperature estimation model recurrent neural network long short-term memory gated recurrent unit

Formation keeping control through inter-satellite electromagnetic force

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Science China(Technological Sciences) 2013年第5期56卷 1102-1111页

作者： cai weiwei YANG LePing ZHU YanWei ZHANG YuanWen College of Aerospace Science and Engineering National University of Defense Technology

Satellite formation keeping through inter-satellite electromagnetic force provides an attractive alternative for future space missions due to its distinct advantages of no propellant consumption or plume contamination as compared to conventional ***,the internal force nature as well as the high nonlinearity and coupling of electromagnetic force brings new control challenges for this novel *** this paper,analysis on the dynamics characteristics and special control issues in the presence of electromagnetic force is carried out on the basis of the derived relatively translational *** the model uncertainties,external disturbances and sensor noise,a combined nonlinear control scheme involving feed-forward and feedback control components is proposed for electromagnetic-force-based formation *** feed-forward component is directly obtained through desired configuration and dynamics under nominal conditions while the feedback component is realized utilizing active disturbance rejection control methodology with some reasonable *** simulation is presented to verify the feasibility and validity of the combined control scheme.

关键词： inter-satellite electromagnetic force formation keeping dynamics analysis active disturbance rejection nonlinear control

Stable NiPt-Mo_(2)C active site pairs enable boosted water splitting and direct methanol fuel cell

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Green Energy & Environment 2023年第2期8卷 559-566页

作者： Jing Li Zhu Guo Wenjie Zhang Jing Guo Konggang Qu weiwei cai Sustainable Energy Laboratory Faculty of Materials Science and ChemistryChina University of GeosciencesWuhan430074China Shandong Provincial Key Laboratory/Collaborative Innovation Center of Chemical Energy Storage&Novel Cell Technology Liaocheng UniversityLiaocheng252059China

Sluggish kinetics of methanol oxidation reaction(MOR)and alkaline hydrogen evolution reaction(HER)even on precious Pt catalyst impede the large-scale commercialization of direct methanol fuel cell(DMFC)and water electrolysis *** both of MOR and alkaline HER are related to water dissociation reaction(WDR),it is reasonable to invite secondary active sites toward WDR to pair with Pt for boosted MOR and alkaline HER activity on ***_(2)C and Ni species are therefore employed to engineer NiPt-Mo_(2)C active site pairs,which can be encapsulated in carbon cages,via an in-situ self-confinement *** activity of Pt in NiPt-Mo_(2)C@C toward HER is boosted to11.3 A mg_(pt)^(-1),33 times higher than that of Pt/***,MOR catalytic activity of Pt in NiPt-Mo_(2)C@C is also improved by 10.5 times and the DMFC maximum power density is hence improved by *** considering the great stability,NiPt-Mo_(2)C@C exhibits great practical application potential in DMFCs and water electrolysers.

关键词： Hydrogen evolution reaction Methanol oxidation reaction Direct methanol fuel cell Active site pair Self-confinement

Multi-Feature Fusion-Guided Multiscale Bidirectional Attention Networks for Logistics Pallet Segmentation

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Computer Modeling in Engineering & Sciences 2022年第6期131卷 1539-1555页

作者： weiwei cai Yaping Song Huan Duan Zhenwei Xia Zhanguo Wei School of Logistics and Transportation Central South University of Forestry and TechnologyChangsha410004China Graduate School Northern Arizona UniversityFlagstaffAZ 86011USA

In the smart logistics industry,unmanned forklifts that intelligently identify logistics pallets can improve work efficiency in warehousing and transportation and are better than traditional manual forklifts driven by ***,they play a critical role in smart warehousing,and semantics segmentation is an effective method to realize the intelligent identification of logistics ***,most current recognition algorithms are ineffective due to the diverse types of pallets,their complex shapes,frequent blockades in production environments,and changing lighting *** paper proposes a novel multi-feature fusion-guided multiscale bidirectional attention(MFMBA)neural network for logistics pallet *** better predict the foreground category(the pallet)and the background category(the cargo)of a pallet image,our approach extracts three types of features(grayscale,texture,and Hue,Saturation,Value features)and fuses *** multiscale architecture deals with the problem that the size and shape of the pallet may appear different in the image in the actual,complex environment,which usually makes feature extraction *** study proposes a multiscale architecture that can extract additional semantic ***,since a traditional attention mechanism only assigns attention rights from a single direction,we designed a bidirectional attention mechanism that assigns cross-attention weights to each feature from two directions,horizontally and vertically,significantly improving ***,comparative experimental results show that the precision of the proposed algorithm is 0.53%–8.77%better than that of other methods we compared.

关键词： Logistics pallet segmentation image segmentation multi-feature fusion multiscale network bidirectional attention mechanism HSV neural networks deep learning