Numerical Simulation of Oil-Water Two-Phase Flow in Low Permeability Tight Reservoirs Based on Weighted Least Squares Meshless Method

In response to the complex characteristics of actual low-permeability tight reservoirs,this study develops a meshless-based numerical simulation method for oil-water two-phase flow in these reservoirs,considering complex boundary shapes.Utilizing radial basis function point interpolation,the method approximates shape functions for unknown functions within the nodal influence domain.The shape functions constructed by the aforementioned meshless interpolation method haveδ-function properties,which facilitate the handling of essential aspects like the controlled bottom-hole flow pressure in horizontal wells.Moreover,the meshless method offers greater flexibility and freedom compared to grid cell discretization,making it simpler to discretize complex geometries.A variational principle for the flow control equation group is introduced using a weighted least squares meshless method,and the pressure distribution is solved implicitly.Example results demonstrate that the computational outcomes of the meshless point cloud model,which has a relatively small degree of freedom,are in close agreement with those of the Discrete Fracture Model(DFM)employing refined grid partitioning,with pressure calculation accuracy exceeding 98.2%.Compared to high-resolution grid-based computational methods,the meshless method can achieve a better balance between computational efficiency and accuracy.Additionally,the impact of fracture half-length on the productivity of horizontal wells is discussed.The results indicate that increasing the fracture half-length is an effective strategy for enhancing production from the perspective of cumulative oil production.

Least-squares finite-element method for shallow-water equations with source terms

Numerical solution of shallow-water equations （SWE） has been a challenging task because of its nonlinear hyperbolic nature, admitting discontinuous solution, and the need to satisfy the C-property. The presence of source terms in momentum equations, such as the bottom slope and friction of bed, compounds the difficulties further. In this paper, a least-squares finite-element method for the space discretization and θ-method for the time integration is developed for the 2D non-conservative SWE including the source terms. Advantages of the method include： the source terms can be approximated easily with interpolation functions, no upwind scheme is needed, as well as the resulting system equations is symmetric and positive-definite, therefore, can be solved efficiently with the conjugate gradient method. The method is applied to steady and unsteady flows, subcritical and transcritical flow over a bump, 1D and 2D circular dam-break, wave past a circular cylinder, as well as wave past a hump. Computed results show good C-property, conservation property and compare well with exact solutions and other numerical results for flows with weak and mild gradient changes, but lead to inaccurate predictions for flows with strong gradient changes and discontinuities.

NOVEL WEIGHTED LEAST SQUARES SUPPORT VECTOR REGRESSION FOR THRUST ESTIMATION ON PERFORMANCE DETERIORATION OF AERO-ENGINE

A thrust estimator with high precision and excellent real-time performance is needed to mitigate perfor- mance deterioration for future aero-engines. A weight least squares support vector regression is proposed using a novel weighting strategy. Then a thrust estimator based on the proposed regression is designed for the perfor- mance deterioration. Compared with the existing weighting strategy, the novel one not only satisfies the require- ment of precision but also enhances the real-time performance. Finally, numerical experiments demonstrate the effectiveness and feasibility of the proposed weighted least squares support vector regression for thrust estimator. Key words ： intelligent engine control; least squares ; support vector machine ; performance deterioration

Analysis of Current Situation and Countermeasures of Plant Landscapes on Tianjin Urban Squares of China

Through the survey of plant landscapes on eight representative squares in Tianjin City,the paper had pointed out that plant landscapes on Tianjin squares were improper in terms of plants richness,cultivation layer and color change.It had suggested selecting regional characteristic tree species,applying salt-tolerant plants,emphasizing the diversity of plants species,highlighting the application of towering arbors,stressing the use of color-leaved plants,and creating abundant plant communities,so as to provide citizens with a more practical and ornamental square landscape environment through improving plant landscapes on squares in Tianjin City.

Hydrothermal Synthesis and Crystal Structure of a Square Grid Coordination Copper(II) Polymer from 1,4-Bis(imidazole-1-ylmethyl)benzene

The title compound [Cu（bix）2（NO3）z·H2P]n 1 （bix = 1,4-bis（imidazole-1-ylme-thyl） benzene） has been synthesized by hydrothermal method. Its crystal structure is of monoclinic, space group P1^- with a = 8.3075（13）, b = 9.4725（13）, c = 10.0192（13） A, α = 91.088（4）, β = 104.063（6）, γ = 101.88（1）, V = 746.5（3） A^3, Z = 1, C28H30N10O7Cu1, Mr = 682.16, Dc = 1.518 g/cm^3, μ = 0.796 mm^-1, F（000） = 353, the final R = 0.0535 and wR = 0.0996 for 2921 observed reflections with I 〉 2σ（I）. Each bix ligand binds two Cu（Ⅱ） ions to form a 2-D（4,4） square grid layer, which is connected by hydrogen bonds showing large channels occupied by solvated water molecules and nitrate anions.

Least Squares Evaluations for Form and Profile Errors of Ellipse Using Coordinate Data

To improve the measurement and evaluation of form error of an elliptic section, an evaluation method based on least squares fitting is investigated to analyze the form and profile errors of an ellipse using coordinate data. Two error indicators for defining ellipticity are discussed, namely the form error and the profile error, and the difference between both is considered as the main parameter for evaluating machining quality of surface and profile. Because the form error and the profile error rely on different evaluation benchmarks, the major axis and the foci rather than the centre of an ellipse are used as the evaluation benchmarks and can accurately evaluate a tolerance range with the separated form error and profile error of workpiece. Additionally, an evaluation program based on the LS model is developed to extract the form error and the profile error of the elliptic section, which is well suited for separating the two errors by a standard program. Finally, the evaluation method about the form and profile errors of the ellipse is applied to the measurement of skirt line of the piston, and results indicate the effectiveness of the evaluation. This approach provides the new evaluation indicators for the measurement of form and profile errors of ellipse, which is found to have better accuracy and can thus be used to solve the difficult of the measurement and evaluation of the piston in industrial production.

Seismic performance of recycled concrete-filled square steel tube columns

An experimental study on the seismic performance of recycled concrete-filled square steel tube （RCFST） columns is carried out. Six specimens were designed and tested under constant axial compression and cyclic lateral loading. Two parameters, replacement percentage of recycled coarse aggregate （RCA） and axial compression level, were considered in the test. Based on the experimental data, the hysteretic loops, skeleton curves, ductility, energy dissipation capacity and stiffness degradation of RCFST columns were analyzed. The test results indicate that the failure modes of RCFST columns are the local buckling of the steel tube at the bottom of the columns, and the hysteretic loops are full and their shapes are similar to normal CFST columns. Furthermore, the ductility coefficient of all specimens are close to 3.0, and the equivalent viscous damping coefficient corresponding to the ultimate lateral load ranges from 0.323 to 0.360, which demonstrates that RCFST columns exhibit remarkable seismic performance.

Online Detection of Broken Rotor Bar Fault in Induction Motors by Combining Estimation of Signal Parameters via Min-norm Algorithm and Least Square Method

Current research in broken rotor bar （BRB） fault detection in induction motors is primarily focused on a high-frequency resolution analysis of the stator current. Compared with a discrete Fourier transformation, the parametric spectrum estimation technique has a higher frequency accuracy and resolution. However, the existing detection methods based on parametric spectrum estima- tion cannot realize online detection, owing to the large computational cost. To improve the efficiency of BRB fault detection, a new detection method based on the min-norm algorithm and least square estimation is proposed in this paper. First, the stator current is filtered using a band-pass filter and divided into short overlapped data windows. The min-norm algorithm is then applied to determine the fre- quencies of the fundamental and fault characteristic com- ponents with each overlapped data window. Next, based on the frequency values obtained, a model of the fault current signal is constructed. Subsequently, a linear least squares problem solved through singular value decomposition is designed to estimate the amplitudes and phases of the related components. Finally, the proposed method is applied to a simulated current and an actual motor, the results of which indicate that, not only parametric spectrum estimation technique.

Development of a least squares support vector machine model for prediction of natural gas hydrate formation temperature

Hydrates always are considered as a threat to petroleum industry due to the operational problems it can cause.These problems could result in reducing production performance or even production stoppage for a long time.In this paper, we were intended to develop a LSSVM algorithm for prognosticating hydrate formation temperature(HFT) in a wide range of natural gas mixtures. A total number of 279 experimental data points were extracted from open literature to develop the LSSVM. The input parameters were chosen based on the hydrate structure that each gas species form. The modeling resulted in a robust algorithm with the squared correlation coefficients(R^2) of 0.9918. Aside from the excellent statistical parameters of the model, comparing proposed LSSVM with some of conventional correlations showed its supremacy, particularly in the case of sour gases with high H_2S concentrations, where the model surpasses all correlations and existing thermodynamic models. For detection of the probable doubtful experimental data, and applicability of the model, the Leverage statistical approach was performed on the data sets. This algorithm showed that the proposed LSSVM model is statistically valid for HFT prediction and almost all the data points are in the applicability domain of the model.

Square Wave Voltammetry for Analytical Determination of Cadmium in Natural Water Using Ca10(PO4)6(OH)2-Modified Platinum Electrode

This paper reports on the development of a novel electrochemical assay for cadmium (II) in natural water, which involves the use of disposable hydroxyapatite modified platinum electrode (HAP/Pt). Cadmium (II) was preconcentrated on the surface of the modified electrode and adsorbed onto HAP and oxidized at E = –680 mV. The HAP-modified platinum electrode exhibited superior performance in comparison to the plati- num electrode and surprisingly, yielded a higher electrochemical response. The best defined anodic peak was obtained with 0.2 mol L-1 KNO3 pH 5.0 after 25 min of accumulation time. Using these conditions, the cali- bration plot was linear over the range 1 × 10?8 to 5 × 10?6 mol L-1 Cd2+. The precision was examined by car- rying out eight replicate measurements at a concentration of 2.5 ×10?5 mol L-1;the coefficient of variation was 2.9%. The method was applied to the determination of the analyte in river water samples. The interfere- ence of other metal ions on the voltammetric response of Cd(II) was studied. The HAP films was clearly ob- served in the SEM images and characterized by X-ray diffraction, IR spectroscopy and chemical analysis.

Application of Least Square Support Vector Machine (LSSVM) for Determination of Evaporation Losses in Reservoirs

This article adopts Least Square Support Vector Machine (LSSVM) for prediction of Evaporation Losses (EL) in reservoirs. LSSVM is firmly based on the theory of statistical learning, uses regression technique. The input of LSSVM model is Mean air temperature (T) (?C), Average wind speed (WS)(m/sec), Sunshine hours (SH)(hrs/day), and Mean relative humidity(RH)(%). LSSVM has been used to compute error barn of predicted data. An equation has been developed for the determination of EL. Sensitivity analysis has been also performed to investigate the importance of each of the input parameters. A comparative study has been presented between LSSVM and artificial neural network (ANN) models. This study shows that LSSVM is a powerful tool for determination EL in reservoirs.

Single Image Enhancement in Sandstorm Weather via Tensor Least Square

In this paper,we present a tensor least square based model for sand/sandstorm removal in images.The main contributions of this paper are as follows.First,an important intrinsic natural feature of outdoor scenes free of sand/sandstorm is found that the outlines in RGB channels are somewise similar,which discloses the physical validation using the tensor instead of the matrix.Second,a tensor least square optimization model is presented for the decomposition of edge-preserving base layers and details.This model not only decomposes the color image(taken as an inseparable indivisibility)in X,Y directions,but also in Z direction,which meets the statistical feature of natural scenes and can physically disclose the intrinsic color information.The model’s advantages are twofold:one is the decomposition of edgepreserving base layers and details that can be employed for contrast enhancement without artificial halos,and the other one is the color driving ability that makes the enhanced images as close to natural images as possible via the inherent color structure.Thirdly,the tensor least square optimization model based image enhancement scheme is discussed for the sandstorm weather images.Finally,the experiments and comparisons with the stateof-the-art methods on real degraded images under sandstorm weather are shown to verify our method’s efficiency.

Simultaneous Spectrophotometric Determination of Three Components Including Deoxyschizandrin by Partial Least Squares Regression

The computer auxiliary partial least squares is introduced to simultaneously determine the contents of Deoxyschizandin, Schisandrin, r-Schisandrin in the extracted solution of wuweizi. Regression analysis of the experimental results shows that the average recovery of each component is all in the range from 98.9% to 110.3% , which means the partial least squares regression spectrophotometry can circumvent the overlappirtg of absorption spectrums of mlulti-components, so that sctisfactory results can be obtained without any scrapple pre-separation.

A Study on Natural Convection of Air in a Square Cavity with Partially Thermally Active Side Walls

In this present work, we study heat transfer in a confined environment. We have to determine the thermal and dynamics fields of the cavity while observing the effect of the Rayleigh number which depends on the characteristics of the fluid and the temperatures imposed. The behavior of boundary layers in natural convection is analyzed along this square cavity. The central halves of its vertical walls are heated at different temperatures. The left active part is at a higher temperature than the one on the right wall. The remaining inactive parts and the horizontal walls (upper and lower) are adiabatic. The thermal and dynamic modeling of two-dimensional problem was done using a calculation code Fortran 90 and a visualization software ParaView based on the finite volume method. The equations governing this phenomenon of unsteady flow have thus been solved. This allows the modeling of both air flow and heat transfer with a numerical stabilization of the solution. So, we have presented our results of numerical simulations using a visualization tool. The results show the different velocity and temperature curves, velocity vectors and isotherms in laminar flow regime.

Algorithms and statistical analysis for linear structured weighted total least squares problem

Weighted total least squares(WTLS)have been regarded as the standard tool for the errors-in-variables(EIV)model in which all the elements in the observation vector and the coefficient matrix are contaminated with random errors.However,in many geodetic applications,some elements are error-free and some random observations appear repeatedly in different positions in the augmented coefficient matrix.It is called the linear structured EIV(LSEIV)model.Two kinds of methods are proposed for the LSEIV model from functional and stochastic modifications.On the one hand,the functional part of the LSEIV model is modified into the errors-in-observations(EIO)model.On the other hand,the stochastic model is modified by applying the Moore-Penrose inverse of the cofactor matrix.The algorithms are derived through the Lagrange multipliers method and linear approximation.The estimation principles and iterative formula of the parameters are proven to be consistent.The first-order approximate variance-covariance matrix(VCM)of the parameters is also derived.A numerical example is given to compare the performances of our proposed three algorithms with the STLS approach.Afterwards,the least squares(LS),total least squares(TLS)and linear structured weighted total least squares(LSWTLS)solutions are compared and the accuracy evaluation formula is proven to be feasible and effective.Finally,the LSWTLS is applied to the field of deformation analysis,which yields a better result than the traditional LS and TLS estimations.

Numerical simulation of inlet placement on sewage characteristics in the rounded square aquaculture tank with single inlet

To improve the self-cleaning ability of aquaculture tank and the efficiency of circulating water,physical and numerical experiments were conducted on the influence of inlet structure on sewage discharge in a rounded square aquaculture tank with a single inlet.Based on the physical model of the tank,analysis of how inlet structure adjustment affects sewage discharge efficiency and flow field characteristics was conducted to provide suitable flow field conditions for sinkable solid particle discharge.In addition,an internal flow field simulation was conducted using the RNG k-εturbulence model in hydraulic drive mode.Then a solid-fluid multiphase model was created to investigate how the inlet structure affects sewage collection in the rounded square aquaculture tank with single inlet and outlet.The finding revealed that the impact of inlet structure is considerably affecting sewage collection.The conditions of C/B=0.07-0.11(the ratio of horizontal distance between the center of the inlet pipe and the tank wall(C)to length of the tank(B))andα=25°(αis the angle between the direction of the jet and the tangential direction of the arc angle)resulted in optimal sewage collection,which is similar to the flow field experiment in the rounded square aquaculture tank with single inlet and outlet.An excellent correlation was revealed between sewage collection and fluid circulation stability in the aquaculture tank.The present study provided a reference for design and optimization of circulating aquaculture tanks in aquaculture industry.

THE WEIGHTED KATO SQUARE ROOT PROBLEMOF ELLIPTIC OPERATORS HAVING A BMOANTI-SYMMETRICPART

Let n≥2 and let L be a second-order elliptic operator of divergence form with coefficients consisting of both an elliptic symmetric part and a BMO anti-symmetric part in ℝ^(n).In this article,we consider the weighted Kato square root problem for L.More precisely,we prove that the square root L^(1/2)satisfies the weighted L^(p)estimates||L^(1/2)(f)||L_(ω)^p(R^(n))≤C||■f||L_(ω)^p(R^(n);R^(n))for any p∈(1,∞)andω∈Ap(ℝ^(n))(the class of Muckenhoupt weights),and that||■f||L_(ω)^p(R^(n);R^(n))≤C||L^(1/2)(f)||L_(ω)^p(R^(n))for any p∈(1,2+ε)andω∈Ap(ℝ^(n))∩RH_(2+ε/p),(R^(n))(the class of reverse Hölder weights),whereε∈(0,∞)is a constant depending only on n and the operator L,and where(2+ε/p)'denotes the Hölder conjugate exponent of 2+ε/p.Moreover,for any given q∈(2,∞),we give a sufficient condition to obtain that||■f||L_(ω)^p(R^(n);R^(n))≤C||L^(1/2)(f)||L_(ω)^p(R^(n))for any p∈(1,q)andω∈A_(p)(R^(n))∩pRH_(q/p),(R^(n)).As an application,we prove that when the coefficient matrix A that appears in L satisfies the small BMO condition,the Riesz transform∇L^(−1/2)is bounded on L_(ω)^(p)(ℝ^(n))for any given p∈(1,∞)andω∈Ap(ℝ^(n)).Furthermore,applications to the weighted L^(2)-regularity problem with the Dirichlet or the Neumann boundary condition are also given.

Simultaneous colorimetric determination of morphine and ibuprofen based on the aggregation of gold nanoparticles using partial least square

In this work a new method is presented for simultaneous colorimetric determination of morphine （MOR） and ibuprofen （IBU） based on the aggregation of citrate-capped gold nanoparticles （AuNPs）. Citrate-capped AuNPs were aggregated in the presence of MOR and IBU. The difference in kinetics of AuNPs aggregation in the presence of MOR/IBU was used for simultaneous analysis of MOR and IBU. The formation and size of synthesized AuNPs and the aggregated forms were monitored by infra-red （IR） spectroscopy and transmission electron microscopy （TEM）, respectively. By adding MOR or IBU the absorbance was decreased at 520 nm and increased at 620 nm. The difference in kinetic profiles of aggregation was applied for simultaneous analysis of MOR and IBU using partial least square （PLS） regression as an efficient multivariate calibration method. The number of PLS latent variables was optimized by leave-one-out cross-validation method using predicted residual error sum of square. The proposed model exhibited a high capability in simultaneous prediction of MOR and IBU concentrations in real samples. The results showed linear ranges of 1.33-33.29 μg/mL （R2=0.9904） and 0.28-6.9 μg/mL （R2=0.9902） for MOR and IBU respectively with low detection limits of 0.15 and 0.03 μg/mL（S/N=5）.

A Method for Assessing Customer Harmonic Emission Level Based on the Iterative Algorithm for Least Square Estimation

With the power system harmonic pollution problems becoming more and more serious, how to distinguish the harmonic responsibility accurately and solve the grid harmonics simply and effectively has become the main development direction in harmonic control subjects. This paper, based on linear regression analysis of basic equation and improvement equation, deduced the least squares estimation (LSE) iterative algorithm and obtained the real-time estimates of regression coefficients, and then calculated the level of the harmonic impedance and emission estimates in real time. This paper used power system simulation software Matlab/Simulink as analysis tool and analyzed the user side of the harmonic amplitude and phase fluctuations PCC (point of common coupling) at the harmonic emission level, thus the research has a certain theoretical significance. The development of this algorithm combined with the instrument can be used in practical engineering.

Converting circular tubes into square cross-sectional parts using incremental forming process

Incremental forming process is recently developed to form tubular parts.The fabrication cost and accuracy could be optimized if the effects of process parameters and the optimum values are specified.The aim of this research is using incremental forming of copper tubes to convert a circular tube into a square cross-sectional part.An experimental setup,consisting of a spherical forming punch and a fixture for clamping the tube is designed.The forming punch movement is controlled by a CNC machine.Full factorial design of experiments is carried out in order to determine the effects of process parameters including linear velocity,radial feed,and axial feed of the tool on the thinning ratio and the maximum outer diameter of the square cross-sectional parts.Results show that the radial feed has the major influence on the thinning ratio,while the axial feed plays the major role for the final profile.Increase of radial feed results in higher thinning ratio,and decrease of axial feed results in better shape conformity.Linear velocity does not have a significant effect on thinning ratio.Regression models are also given for predicting the determined responses.