Publish in OALib Journal

ISSN: 2333-9721

APC: Only $99


Any time

2019 ( 25 )

2018 ( 210 )

2017 ( 199 )

2016 ( 187 )

Custom range...

Search Results: 1 - 10 of 11425 matches for " Leilei Cao "
All listed articles are free for downloading (OA Articles)
Page 1 /11425
Display every page Item
Numerical Simulation on Effects of Electromagnetic Force on the Centrifugal Casting Process of High Speed Steel Roll  [PDF]
Minghu Yuan, Leilei Cao, Yaozeng Xu, Xuding Song
Modeling and Numerical Simulation of Material Science (MNSMS) , 2014, DOI: 10.4236/mnsms.2014.41004
A three-dimensional mathematical and physical model coupling with the heat transfer and the flow of molten metal in the centrifugal casting of the high speed steel roll was established by using CFD software FLUENT. It can be used to analyze the distribution of the temperature filed and the flow filed in the centrifugal casting under the gravity, the electromagnetic stirring force and the centrifugal force. Some experiments were carried out to verify the above analysis results. The effects of the electromagnetic force on the centrifugal casting process are discussed. The results showed that under the 0.15 T electromagnetic field intensity, both the absolute pressure of metal flow to mold wall and the metal flow velocity on the same location have some differences between the electromagnetic centrifugal casting and the centrifugal casting. Numerical results for understanding the electromagnetic stirring of the centrifugal casting process have a guiding significance.
Bis[μ2-1-(2-carboxybenzoyl)thiosemicarbazide(3−)]hexapyridinetrinickel(II) pyridine monosolvate monohydrate
Fan Cao,Leilei Li,Dacheng Li
Acta Crystallographica Section E , 2011, DOI: 10.1107/s1600536811048367
Abstract: The reaction of Ni(OAc)2·4H2O with 1-(2-carboxybenzoyl)thiosemicarbazide (H3L) produces the title complex, [Ni3(C9H6N3O3S)2(C5H5N)6]·C5H5N·2H2O, which contains an linear array of three NiII atoms. The asymmetric unit contains half of the complex molecule, a water molecule and a half-molecule of pyridine. The central NiII atom, located on a crystallographic inversion centre, has an octahedral N4O2 environment. The other two NiII atoms have a square-pyramidal N3OS environment, each bridged to the central NiII atom via the L3 group. The carboxylate groups coordinate to the metal atoms in a monodentate fashion. The water molecule is linked to the complex molecule via O—H...O hydrogen bonds. The molecules further assemble into a one-dimensional network parallel to [001] via intermolecular N—H...O hydrogen bonds.
Approximate Kepler’s Elliptic Orbits with the Relativistic Effects  [PDF]
Leilei Jia
International Journal of Astronomy and Astrophysics (IJAA) , 2013, DOI: 10.4236/ijaa.2013.31004

Beginning with a Lagrangian, we derived an approximate relativistic orbit equation which describes relativistic corrections to Keplerian orbits. The critical angular moment to guarantee the existence of periodic orbits is determined. An approximate relativistic Kepler’s elliptic orbit is illustrated by numerical simulation via a second-order perturbation method of averaging.

Application of Improved Deep Auto-Encoder Network in Rolling Bearing Fault Diagnosis  [PDF]
Jian Di, Leilei Wang
Journal of Computer and Communications (JCC) , 2018, DOI: 10.4236/jcc.2018.67005
Abstract: Since the effectiveness of extracting fault features is not high under traditional bearing fault diagnosis method, a bearing fault diagnosis method based on Deep Auto-encoder Network (DAEN) optimized by Cloud Adaptive Particle Swarm Optimization (CAPSO) was proposed. On the basis of analyzing CAPSO and DAEN, the CAPSO-DAEN fault diagnosis model is built. The model uses the randomness and stability of CAPSO algorithm to optimize the connection weight of DAEN, to reduce the constraints on the weights and extract fault features adaptively. Finally, efficient and accurate fault diagnosis can be implemented with the Softmax classifier. The results of test show that the proposed method has higher diagnostic accuracy and more stable diagnosis results than those based on the DAEN, Support Vector Machine (SVM) and the Back Propagation algorithm (BP) under appropriate parameters.
Finite difference/local discontinuous Galerkin method for solving the fractional diffusion-wave equation
Leilei Wei
Mathematics , 2015,
Abstract: In this paper a finite difference/local discontinuous Galerkin method for the fractional diffusion-wave equation is presented and analyzed. We first propose a new finite difference method to approximate the time fractional derivatives, and give a semidiscrete scheme in time with the truncation error $O((\Delta t)^2)$, where $\Delta t$ is the time step size. Further we develop a fully discrete scheme for the fractional diffusion-wave equation, and prove that the method is unconditionally stable and convergent with order $O(h^{k+1}+(\Delta t)^{2})$, where $k$ is the degree of piecewise polynomial. Extensive numerical examples are carried out to confirm the theoretical convergence rates.
Does Security Transaction Volume-Price Behavior Resemble a Probability Wave?
Leilei Shi
Quantitative Finance , 2010, DOI: 10.1016/j.physa.2005.10.016
Abstract: Motivated by how transaction amount constrain trading volume and price volatility in stock market, we, in this paper, study the relation between volume and price if amount of transaction is given. We find that accumulative trading volume gradually emerges a kurtosis near the price mean value over a trading price range when it takes a longer trading time, regardless of actual price fluctuation path, time series, or total transaction volume in the time interval. To explain the volume-price behavior, we, in terms of physics, propose a transaction energy hypothesis, derive a time-independent transaction volume-price probability wave equation, and get two sets of analytical volume distribution eigenfunctions over a trading price range. By empiric test, we show the existence of coherence in stock market and demonstrate the model validation at this early stage. The volume-price behaves like a probability wave.
Preparation of Bulk 13C-Enriched Graphene Materials
Leilei Tian,Xin Wang,Li Cao,Mohammed J. Meziani,Chang Yi Kong,Fushen Lu,Ya-Ping Sun
Journal of Nanomaterials , 2010, DOI: 10.1155/2010/742167
Abstract: Arc-discharge has been widely used in the bulk production of various carbon nanomaterials, especially for structurally more robust single-walled carbon nanotubes. In this paper, the same bulk-production technique was applied to the synthesis of significantly 13C-enriched graphitic materials, from which graphene oxides similarly enriched with 13C were prepared and characterized. The results demonstrate that arc-discharge is a convenient method to produce bulk quantities of 13C-enriched graphene materials from relatively less expensive precursors (largely amorphous 13C powders). 1. Introduction Graphene nanosheets (GNs) consisting of a single or few layers of hexagonally arrayed sp2-bonded carbons in a two-dimensional lattice have attracted tremendous amount of recent attention for their interesting and/or unique properties, with a long list of predicted technological applications [1–10]. For example, individual GNs have been found to possess superior electronic properties arising from the confinement of electrons in two dimensions [3], and as a zero-bandgap semiconductor to feature long-range ballistic transport and high carrier mobility at room temperature [8, 11, 12]. GNs also exhibit excellent thermal transport properties [10], with their dispersion into polymeric matrices resulting in record-setting thermal conductive performances [13–15]. The preparation or production in larger quantities of GNs has been actively pursued in the research community [16, 17]. Among widely investigated methods are those based on the micromechanical cleavage of graphite [11], epitaxial growth [18], and chemical exfoliation of graphite [13, 19], especially the exfoliation through the route of graphene oxides (GOs) [20]. For structural characterization and other purposes, 13C-enriched GNs (or GOs as precursors) are particularly valuable. However, the 13C-enrichment in bulk quantities of graphene materials has hardly been a routine task. There are only a few relevant studies in the literature (all based on the same sample source), despite their obviously high impact in the graphene research field [21–23]. The sample of 13C-enriched graphite films in the available studies was synthesized by using cold-wall chemical vapor deposition (CVD) onto nickel substrate, with isotopically enriched methane as the 13C source [22]. Beyond CVD, arc-discharge under inert atmosphere has been widely used in the bulk production of various carbon nanomaterials, including especially carbon nanotubes [24–28]. In fact, single-walled carbon nanotubes from arc-discharge production are generally
Is Order the Defining Feature of Magnitude Representation? An ERP Study on Learning Numerical Magnitude and Spatial Order of Artificial Symbols
Hui Zhao, Chuansheng Chen, Hongchuan Zhang, Xinlin Zhou, Leilei Mei, Chunhui Chen, Lan Chen, Zhongyu Cao, Qi Dong
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0049565
Abstract: Using an artificial-number learning paradigm and the ERP technique, the present study investigated neural mechanisms involved in the learning of magnitude and spatial order. 54 college students were divided into 2 groups matched in age, gender, and school major. One group was asked to learn the associations between magnitude (dot patterns) and the meaningless Gibson symbols, and the other group learned the associations between spatial order (horizontal positions on the screen) and the same set of symbols. Results revealed differentiated neural mechanisms underlying the learning processes of symbolic magnitude and spatial order. Compared to magnitude learning, spatial-order learning showed a later and reversed distance effect. Furthermore, an analysis of the order-priming effect showed that order was not inherent to the learning of magnitude. Results of this study showed a dissociation between magnitude and order, which supports the numerosity code hypothesis of mental representations of magnitude.
Fast CR-SRAM Using New Charge-Recycling Scheme  [PDF]
Leilei Li, Xin Chen, Xu Wang
Engineering (ENG) , 2012, DOI: 10.4236/eng.2012.48064
Abstract: In this paper, a CR-SRAM using new charge recycling scheme is described, novel bit-line pre-charge voltage distribution is proposed. The SRAM pre-charge voltage level is designed by logarithm instead of linear. The new design leads to improvement in speed compared to the original CR-SRAM. Simulation results show that the new CR-SRAM using novel pre-charge voltage distribution scheme reduced the write access time by 34% with 9% power dissipation penalty.
Optimal Control for Time-Delay Bilinear Systems with Sinusoidal Disturbances  [PDF]
Dexin Gao, Min Wang, Leilei Li
Intelligent Control and Automation (ICA) , 2013, DOI: 10.4236/ica.2013.41005

This paper considers the optimal control problem for time-delay bilinear systems affected by sinusoidal disturbances with known frequency and measurable amplitude and phase. Firstly, using the differential homeomorphism, a time-delay bilinear system affected by sinusoidal disturbances is changed to a time-delay pseudo linear system through the coordinate transformation. Then the system with time-delay in control variable is transformed to a linear controllable system without delay using model transformation. At last based on the theory of linear quadratic optimal control, an optimal control law which is used to eliminate the influence of the disturbances is derived from a Riccati equation and Matrix equations. The simulation results show the effectiveness of the method.

Page 1 /11425
Display every page Item

Copyright © 2008-2017 Open Access Library. All rights reserved.