The Study on Pipe Sudden Enlargem entLocal Resistant Coefficient

During the design of pipeline,the determination of local resistant coefficient is often come arcoss.The sudden enlargement local resistant coefficient ξ 1=1-A 1A 2 2 is determined through theory.In the paper,the sudden enlargement local resistant coefficient under the conditions of three kinds of A 1A 2 was studied in experiment.In the end ,the result shows that ξ 1 is related not only to two flow cross sections,but also to the velocity.Through experimental research,the relationship between ξ 1,A 1A 2 and V 1 was determined.In a word,the hydraulic calculation of pipeline can be done by taking correspondent ξ 1 ,according to the design velocity V 1 and A 1A 2.

Mc Kean–Vlasov BSDEs with Locally Monotone Coefficient

We consider a McKean Vlasov backward stochastic differential equation(MVBSDE) of the form Y_(t)=-F(t,Y_(t),Z_(t),[Y_(t)]) dt+Z_(t) dB_(t),Y_(T)=ξ,where [Y_(t)] stands for the law of Y,.We show that if F is locally monotone in y,locally Lipschitz with respect to z and law's variable,and the monotonicity and Lipschitz constants κ_(n),L_(n) are such that L_(n)^(2)+κ_(n)^(+)=O(log(N)),then the MVBSDE has a unique stable solution.

A MAP OF LOCAL PATTERN ANALOGUE COEFFICIENT——A TOOL FOR DISPLAYING CIRCULATION ANOMALY

Limitations of difference maps showing circulation anomalies are analyzed, and the definition of the local pattern analogue coefficient (LPAC) is given together with the procedure for constructing such a map, followed by an example illustrating its useful application in circulation anomaly.

Turbulence Model Investigations on the Boundary Layer Flow with Adverse Pressure Gradients

In this paper, a numerical study of flow in the turbulence boundary layer with adverse and pressure gradients （APGs） is conducted by using Reynolds-averaged Navier-Stokes （RANS） equations. This research chooses six typical turbulence models, which are critical to the computing precision, and to evaluating the issue of APGs. Local frictional resistance coefficient is compared between numerical and experimental results. The same comparisons of dimensionless averaged velocity profiles are also performed. It is found that results generated by Wilcox （2006） k-co are most close to the experimental data. Meanwhile, turbulent quantities such as turbulent kinetic energy and Reynolds-stress are also studied.

Two-stage Local Walsh Average Estimation of Generalized Varying Coefficient Models

In this paper we investigate the robust estimation of generalized varying coefficient models in which the unknown regression coefficients may change with different explanatory variables. Based on the B-spline series approximation and Walsh-average technique we develop an initial estimator for the unknown regression coefficient functions. By virtue of the initial estimator, the generalized varying coefficient model is reduced to a univariate nonparametric regression model. Then combining the local linear smooth and Walsh average technique we further propose a two-stage local linear Walsh-average estimator for the unknown regression coefficient functions. Under mild assumptions, we establish the large sample theory of the proposed estimators by utilizing the results of U-statistics and shows that the two-stage local linear Walsh-average estimator own an oracle property, namely the asymptotic normality of the two-stage local linear Walsh-average estimator of each coefficient function is not affected by other unknown coefficient functions. Extensive simulation studies are conducted to assess the finite sample performance, and a real example is analyzed to illustrate the proposed method.

Integrating Local Closure Coefficient into Weighted Networks for Link Prediction

Triadic closure is a simple and fundamental kind of link formulation mechanism in network.Local closure coefficient(LCC),a new network property,is to measure the triadic closure with respect to the fraction of length-2 paths for link prediction.In this paper,a weighted format of LCC(WLCC)is introduced to measure the weighted strength of local triadic structure,and a statistic similari-ty-based link prediction metric is proposed to incorporate the definition of WLCC.To prove the metrics effectiveness and scalability,the WLCC formula-tion was further investigated under weighted local Naive Bayes(WLNB)link prediction framework.Finally,extensive experimental studies was conducted with weighted baseline metrics on various public network datasets.The results demonstrate the merits of the proposed metrics in comparison with the weighted baselines.

Determination of ice jam thickness—A new approach

In winter,rivers in cold regions often experience flood disasters resulted from ice jams or ice dams.Investigations of the variation of ice jam thickness and water level during an ice jammed period are not only a practical need for ice prevention to avoid disaster and plan water resource,but also essential for the development of any mathematical model for predicting the evolution of ice jam.So far,some equations based on the energy equation have been proposed to describe the relationship between ice jam thickness and water level.However,in the derivation of these equations,the local head loss coefficient at the ice jam head and the riverbed slope factor were neglected.Obviously,those reported equations cannot be used to preciously describe the flow energy equation with ice jams and accurately calculate the ice jam thickness and water level.In the present study,a more comprehensive theoretical model for hydraulic calculation of ice jam thickness has been derived by considering important and essential factors including riverbed slope and local head loss coefficient at the ice jam head.Furthermore,based on the data collected from laboratory experiments of ice jam accumulation,the local head loss coefficient at the ice jam head has been calculated,and the empirical equation for calculating the local head loss coefficient has been established by considering flow Froude number and the ratio of ice discharge to flow discharge.The results of this study not only provide a new reference for calculating ice jam thickness and water level,but also present a theoretical basis for accurate CFD simulation of ice jams.

Study on Local Resistance of non-Newtonian Power Law Fluid in Elbow Pipes

This paper focuses on the flow characteristic and local resistance of non-Newtonian power law fluid in a curved 90° bend pipe with circular cross-sections, which are widely used in industrial applications. By employing nu- merical simulation and theoretical analysis the properties of the flow and local resistance of power law fluid under different working conditions are obtained. To explore the change rule the experiment is carried out by changing the Reynolds number, the wall roughness and differcnt diameter ratio of elbow pipe. The variation of the local resistance coefficient with the Reynolds number, the diameter ratio and the wall roughness is presented comprehensively in the paper. The results show that the local resistance force coefficient hardly changes with Reynolds number of the power law fluid; the wall roughness has a significant impact on the local resistance coefficicnt. As the pipe wall roughness increasing, the coefficient of local resistance force will increase. The main reason of the influence of the roughness on the local resistance coefficient is the increase of the eddy current region in the power law fluid flow, which increases the kinetic energy dissipation of the main flow. This paper provides theoretical and numerical methods to understand the local resistance property of non-Newtonian power law fluid in elbow pipes.

Detection of Geochemical Element Assemblage Anomalies Using a Local Correlation Approach

As direct prospecting data,geochemical data play an important role in modelling prospect potential.Geochemical element assemblage anomalies are usually reflected by the correlation between elements.Correlation coefficients are computed from the values of two elements,which reflect only the correlation at a global level.Thus,the spatial details of the correlation structure are ignored.In fact,an element combination anomaly often exists in geological backgrounds,such as on a fault zone or within a lithological unit.This anomaly may cause some combination of anomalies that are submerged inside the overall area and thus cannot be effectively extracted.To address this problem,we propose a local correlation coefficient based on spatial neighbourhoods to reflect the global distribution of elements.In this method,the sampling area is first divided into a set of uniform grid cells.A moving window with a size of 3×3 is defined with an integer of 3 to represent the sampling unit.The local correlation in each unit is expressed by the Pearson correlation coefficient.The whole area is scanned by the moving window,which produces a correlation coefficient matrix,and the result is portrayed with a thermal diagram.The local correlation approach was tested on two selected geochemical soil survey sites in Xiao Mountain,Henan Province.The results show that the areas of high correlation are mainly distributed in the fault zone or the known mineral spots.Therefore,the local correlation method is effective in extracting geochemical element combination anomalies.

Ferroelectric-to-relaxor transition and ultrahigh electrostrictive effect in Sm^(3+)-doped Pb(Mg_(1/3)Nb_(2/3))O_(3)-PbTiO_(3)ferroelectrics ceramics

Rare-earth Sm^(3+)-doped Pb(Mg_(1/3)Nb_(2/3))O_(3)-0.25PbTiO_(3)(PMN-0.25PT)ferroelectric ceramics with doping amounts between 0%-3%were developed via a conventional solid-state method.The doping effect of Sm^(3+)ions on the PMN-0.25PT matrix was systematically investigated on the basis of the phase structure,temperature-dependent dielectric,ferroelectric,and electrotechnical properties.Due to the disruption of long-range ferroelectric order,the addition of Sm^(3+)ions effectively lowers the Tm(temperature corresponding to maximum permittivity)of the samples,leading to enhanced relaxor ferroelectric(RFE)characteristic and superior electric field-induced strain(electrostrain)properties at room temperature.Intriguingly,a considerable large-signal equivalent piezoelectric coefficient d∗_(33)of 2376 pm/V and a very small hysteresis were attained in the PMN-0.25PT component doped with 2.5 mol.%Sm^(3+).The findings of piezoelectric force microscopy indicate that the addition of Sm^(3+)increases the local structural heterogeneity of the PMN-0.25PT matrix and that the enhanced electromechanical performance is due to the dynamic behavior of polar nanoregions.Importantly,strong temperature-dependent electrostrain and electrostrictive coefficient Q33 are observed in the critical region around Tm in all Sm^(3+)-modified PMN-0.25PT ceramic samples studied.This work elucidates the phase transition behavior of Sm^(3+)-doped PMN-0.25PT and reveals a critical region where electrostrictive properties can be greatly improved due to a strong temperature-dependent characteristic.

3redon-Illman cohomology with actions of ;otally disconnected groups

We study the Bredon-IUman cohomology with local coefficients for a G-space X in the case of G being a totally disconnected, locally compact group. We prove that any short exact sequence of equivariant local coefficients systems on X gives a long exact sequence of the associated Bredon-Illman cohomology groups with local coefficients.

A robust object tracking framework based on a reliable point assignment algorithm

Visual tracking, which has been widely used in many vision fields, has been one of the most active research topics in computer vision in recent years. However, there are still challenges in visual tracking, such as illumination change, object occlu- sion, and appearance deformation. To overcome these difficulties, a reliable point assignment （RPA） algorithm based on wavelet transform is proposed. The reliable points are obtained by searching the location that holds local maximal wavelet coefficients. Since the local maximal wavelet coefficients indicate high variation in the image, the reliable points are robust against image noise, illumination change, and appearance deformation. Moreover, a Kalman filter is applied to the detection step to speed up the detection processing and reduce false detection. Finally, the proposed RPA is integrated into the tracking-learning-detection （TLD） framework with the Kalman filter, which not only improves the tracking precision, but also reduces the false detections. Experimental results showed that the new framework outperforms TLD and kernelized correlation filters with respect to precision, f-measure, and average overlap in percent.