22 resultados para characteristic matrix method
em CentAUR: Central Archive University of Reading - UK
Resumo:
A numerical algorithm for the biharmonic equation in domains with piecewise smooth boundaries is presented. It is intended for problems describing the Stokes flow in the situations where one has corners or cusps formed by parts of the domain boundary and, due to the nature of the boundary conditions on these parts of the boundary, these regions have a global effect on the shape of the whole domain and hence have to be resolved with sufficient accuracy. The algorithm combines the boundary integral equation method for the main part of the flow domain and the finite-element method which is used to resolve the corner/cusp regions. Two parts of the solution are matched along a numerical ‘internal interface’ or, as a variant, two interfaces, and they are determined simultaneously by inverting a combined matrix in the course of iterations. The algorithm is illustrated by considering the flow configuration of ‘curtain coating’, a flow where a sheet of liquid impinges onto a moving solid substrate, which is particularly sensitive to what happens in the corner region formed, physically, by the free surface and the solid boundary. The ‘moving contact line problem’ is addressed in the framework of an earlier developed interface formation model which treats the dynamic contact angle as part of the solution, as opposed to it being a prescribed function of the contact line speed, as in the so-called ‘slip models’. Keywords: Dynamic contact angle; finite elements; free surface flows; hybrid numerical technique; Stokes equations.
Resumo:
Prediction of the solar wind conditions in near-Earth space, arising from both quasi-steady and transient structures, is essential for space weather forecasting. To achieve forecast lead times of a day or more, such predictions must be made on the basis of remote solar observations. A number of empirical prediction schemes have been proposed to forecast the transit time and speed of coronal mass ejections (CMEs) at 1 AU. However, the current lack of magnetic field measurements in the corona severely limits our ability to forecast the 1 AU magnetic field strengths resulting from interplanetary CMEs (ICMEs). In this study we investigate the relation between the characteristic magnetic field strengths and speeds of both magnetic cloud and noncloud ICMEs at 1 AU. Correlation between field and speed is found to be significant only in the sheath region ahead of magnetic clouds, not within the clouds themselves. The lack of such a relation in the sheaths ahead of noncloud ICMEs is consistent with such ICMEs being skimming encounters of magnetic clouds, though other explanations are also put forward. Linear fits to the radial speed profiles of ejecta reveal that faster-traveling ICMEs are also expanding more at 1 AU. We combine these empirical relations to form a prediction scheme for the magnetic field strength in the sheaths ahead of magnetic clouds and also suggest a method for predicting the radial speed profile through an ICME on the basis of upstream measurements.
Resumo:
The influence matrix is used in ordinary least-squares applications for monitoring statistical multiple-regression analyses. Concepts related to the influence matrix provide diagnostics on the influence of individual data on the analysis - the analysis change that would occur by leaving one observation out, and the effective information content (degrees of freedom for signal) in any sub-set of the analysed data. In this paper, the corresponding concepts have been derived in the context of linear statistical data assimilation in numerical weather prediction. An approximate method to compute the diagonal elements of the influence matrix (the self-sensitivities) has been developed for a large-dimension variational data assimilation system (the four-dimensional variational system of the European Centre for Medium-Range Weather Forecasts). Results show that, in the boreal spring 2003 operational system, 15% of the global influence is due to the assimilated observations in any one analysis, and the complementary 85% is the influence of the prior (background) information, a short-range forecast containing information from earlier assimilated observations. About 25% of the observational information is currently provided by surface-based observing systems, and 75% by satellite systems. Low-influence data points usually occur in data-rich areas, while high-influence data points are in data-sparse areas or in dynamically active regions. Background-error correlations also play an important role: high correlation diminishes the observation influence and amplifies the importance of the surrounding real and pseudo observations (prior information in observation space). Incorrect specifications of background and observation-error covariance matrices can be identified, interpreted and better understood by the use of influence-matrix diagnostics for the variety of observation types and observed variables used in the data assimilation system. Copyright © 2004 Royal Meteorological Society
Resumo:
The molecular structures of NbOBr3, NbSCl3, and NbSBr3 have been determined by gas-phase electron diffraction (GED) at nozzle-tip temperatures of 250 degreesC, taking into account the possible presence of NbOCl3 as a contaminant in the NbSCl3 sample and NbOBr3 in the NbSBr3 sample. The experimental data are consistent with trigonal-pyramidal molecules having C-3v symmetry. Infrared spectra of molecules trapped in argon or nitrogen matrices were recorded and exhibit the characteristic fundamental stretching modes for C-3v species. Well resolved isotopic fine structure (Cl-35 and Cl-37) was observed for NbSCl3, and for NbOCl3 which occurred as an impurity in the NbSCl3 spectra. Quantum mechanical calculations of the structures and vibrational frequencies of the four YNbX3 molecules (Y = O, S; X = Cl, Br) were carried out at several levels of theory, most importantly B3LYP DFT with either the Stuttgart RSC ECP or Hay-Wadt (n + 1) ECP VDZ basis set for Nb and the 6-311 G* basis set for the nonmetal atoms. Theoretical values for the bond lengths are 0.01-0.04 Angstrom longer than the experimental ones of type r(a), in accord with general experience, but the bond angles with theoretical minus experimental differences of only 1.0-1.5degrees are notably accurate. Symmetrized force fields were also calculated. The experimental bond lengths (r(g)/Angstrom) and angles (angle(alpha)/deg) with estimated 2sigma uncertainties from GED are as follows. NbOBr3: r(Nb=O) = 1.694(7), r(Nb-Br) = 2.429(2), angle(O=Nb-Br) = 107.3(5), angle(Br-Nb-Br) = 111.5(5). NbSBr3: r(Nb=S) = 2.134(10), r(Nb-Br) = 2.408(4), angle(S=Nb-Br) = 106.6(7), angle(Br-Nb-Br) = 112.2(6). NbSCl3: Nb=S) = 2.120(10), r(Nb-Cl) = 2.271(6), angle(S=Nb-Cl) = 107.8(12), angle(Cl-Nb-Cl) = 111.1(11).
Resumo:
In this work we describe the synthesis of a variety of MCM-41 type hexagonal and SBA-1 type cubic mesostructures and mesoporous silicious materials employing a novel synthesis concept based on polyacrylic acid (Pac)-C(n)TAB complexes as backbones of the developing structures. The ordered porosity of the solids was established by XRD and TEM techniques. The synthesis concept makes use of Pac-C(n)TAB nanoassemblies as a preformed scaffold, formed by the gradual increase of pH. On this starting matrix the inorganic precursor species SiO2 precipitate via hydrolysis of TEOS under the influence of increasing pH. The molecular weight (MW) of Pac, as well as the length of carbon chain in C,TAB, determine the physical and structural characteristics of the obtained materials. Longer chain surfactants (C(16)TAB) lead to the formation of hexagonal phase, while shorter chain surfactants (C(14)TAB, C(12)TAB) favor the SBA-1 phase. Lower MW of Pac (approximate to2000) leads to better-organized structures compared to higher MW ( 450,000), which leads to worm-like mesostructures. Cell parameters and pore size increase with increasing polyelectrolyte and/or surfactant chain, while at the same time SEM photography reveals that the particle size decreases. Conductivity experiments provide some insight into the proposed self-assembling pathway. (C) 2003 Elsevier Inc. All rights reserved.
Resumo:
In this work, IR thermography is used as a non-destructive tool for impact damage characterisation on thermoplastic E-glass/polypropylene composites for automotive applications. The aim of this experimentation was to compare impact resistance and to characterise damage patterns of different laminates, in order to provide indications for their use in components. Two E-glass/polypropylene composites, commingled ®Twintex (with three different weave structures: directional, balanced and 3-D) and random reinforced GMT, were in particular characterised. Directional and balanced Twintex were also coupled in a number of hybrid configurations with GMT to evaluate the possible use of GMT/Twintex hybrids in high-energy absorption components. The laminates were impacted using a falling weight tower, with impact energies ranging from 15 J to penetration. Using IR thermography during cooling down following a long pulse (3 s), impact damaged areas were characterised and the influence of weave structure on damage patterns was studied. IR thermography offered good accuracy for laminates with thickness not exceeding 3.5 mm: this appears to be a limit for the direct use of this method on components, where more refined signal treatment would probably be needed for impact damage characterisation.
Resumo:
This paper identifies the indicators of energy efficiency assessment in residential building in China through a wide literature review. Indicators are derived from three main sources: 1) The existing building assessment methods; 2)The existing Chinese standards and technology codes in building energy efficiency; 3)Academia research. As a result, we proposed an indicator list by refining the indicators in the above sources. Identified indicators are weighted by the group analytic hierarchy process (AHP) method. Group AHP method is implemented following key steps: Step 1: Experienced experts are selected to form a group; Step 2: A survey is implemented to collect the individual judgments on the importance of indicators in the group; Step 3: Members’ judgments are synthesized to the group judgments; Step 4: Indicators are weighted by AHP on the group judgments; Step 5: Investigation of consistency estimation shows that the consistency of the judgment matrix is accepted. We believe that the weighted indicators in this paper will provide important references to building energy efficiency assessment.
Resumo:
A method is described for the analysis of deuterated and undeuterated alpha-tocopherol in blood components using liquid chromatography coupled to an orthogonal acceleration time-of-flight (TOF) mass spectrometer. Optimal ionisation conditions for undeuterated (d0) and tri- and hexadeuterated (d3 or d6) alpha-tocopherol standards were found with negative ion mode electrospray ionisation. Each species produced an isotopically resolved single ion of exact mass. Calibration curves of pure standards were linear in the range tested (0-1.5 muM, 0-15 pmol injected). For quantification of d0 and d6 in blood components following a standard solvent extraction, a stable-isotope-labelled internal standard (d3-alpha-tocopherol) was employed. To counter matrix ion suppression effects, standard response curves were generated following identical solvent extraction procedures to those of the samples. Within-day and between-day precision were determined for quantification of d0- and d6-labelled alpha-tocopherol in each blood component and both averaged 3-10%. Accuracy was assessed by comparison with a standard high-performance liquid chromatography (HPLC) method, achieving good correlation (r(2) = 0.94), and by spiking with known concentrations of alpha-tocopherol (98% accuracy). Limits of detection and quantification were determined to be 5 and 50 fmol injected, respectively. The assay was used to measure the appearance and disappearance of deuterium-labelled alpha-tocopherol in human blood components following deuterium-labelled (d6) RRR-alpha-tocopheryl acetate ingestion. The new LC/TOFMS method was found to be sensitive, required small sample volumes, was reproducible and robust, and was capable of high throughput when large numbers of samples were generated. Copyright (C) 2003 John Wiley Sons, Ltd.
Resumo:
If soy isoflavones are to be effective in preventing or treating a range of diseases, they must be bioavailable, and thus understanding factors which may alter their bioavailability needs to be elucidated. However, to date there is little information on whether the pharmacokinetic profile following ingestion of a defined dose is influenced by the food matrix in which the isoflavone is given or by the processing method used. Three different foods (cookies, chocolate bars and juice) were prepared, and their isoflavone contents were determined. We compared the urinary and serum concentrations of daidzein, genistein and equol following the consumption of three different foods, each of which contained 50 mg of isoflavones. After the technological processing of the different test foods, differences in aglycone levels were observed. The plasma levels of the isoflavone precursor daidzein were not altered by food matrix. Urinary daidzein recovery was similar for all three foods ingested with total urinary output of 33-34% of ingested dose. Peak genistein concentrations were attained in serum earlier following consumption of a liquid matrix rather than a solid matrix, although there was a lower total urinary recovery of genistein following ingestion of juice than that of the two other foods. (c) 2006 Elsevier Inc. All rights reserved.
Resumo:
Finding the smallest eigenvalue of a given square matrix A of order n is computationally very intensive problem. The most popular method for this problem is the Inverse Power Method which uses LU-decomposition and forward and backward solving of the factored system at every iteration step. An alternative to this method is the Resolvent Monte Carlo method which uses representation of the resolvent matrix [I -qA](-m) as a series and then performs Monte Carlo iterations (random walks) on the elements of the matrix. This leads to great savings in computations, but the method has many restrictions and a very slow convergence. In this paper we propose a method that includes fast Monte Carlo procedure for finding the inverse matrix, refinement procedure to improve approximation of the inverse if necessary, and Monte Carlo power iterations to compute the smallest eigenvalue. We provide not only theoretical estimations about accuracy and convergence but also results from numerical tests performed on a number of test matrices.
Resumo:
Many scientific and engineering applications involve inverting large matrices or solving systems of linear algebraic equations. Solving these problems with proven algorithms for direct methods can take very long to compute, as they depend on the size of the matrix. The computational complexity of the stochastic Monte Carlo methods depends only on the number of chains and the length of those chains. The computing power needed by inherently parallel Monte Carlo methods can be satisfied very efficiently by distributed computing technologies such as Grid computing. In this paper we show how a load balanced Monte Carlo method for computing the inverse of a dense matrix can be constructed, show how the method can be implemented on the Grid, and demonstrate how efficiently the method scales on multiple processors. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
In this paper we introduce a new algorithm, based on the successful work of Fathi and Alexandrov, on hybrid Monte Carlo algorithms for matrix inversion and solving systems of linear algebraic equations. This algorithm consists of two parts, approximate inversion by Monte Carlo and iterative refinement using a deterministic method. Here we present a parallel hybrid Monte Carlo algorithm, which uses Monte Carlo to generate an approximate inverse and that improves the accuracy of the inverse with an iterative refinement. The new algorithm is applied efficiently to sparse non-singular matrices. When we are solving a system of linear algebraic equations, Bx = b, the inverse matrix is used to compute the solution vector x = B(-1)b. We present results that show the efficiency of the parallel hybrid Monte Carlo algorithm in the case of sparse matrices.
Resumo:
In this paper we consider bilinear forms of matrix polynomials and show that these polynomials can be used to construct solutions for the problems of solving systems of linear algebraic equations, matrix inversion and finding extremal eigenvalues. An almost Optimal Monte Carlo (MAO) algorithm for computing bilinear forms of matrix polynomials is presented. Results for the computational costs of a balanced algorithm for computing the bilinear form of a matrix power is presented, i.e., an algorithm for which probability and systematic errors are of the same order, and this is compared with the computational cost for a corresponding deterministic method.
Resumo:
In recent years nonpolynomial finite element methods have received increasing attention for the efficient solution of wave problems. As with their close cousin the method of particular solutions, high efficiency comes from using solutions to the Helmholtz equation as basis functions. We present and analyze such a method for the scattering of two-dimensional scalar waves from a polygonal domain that achieves exponential convergence purely by increasing the number of basis functions in each element. Key ingredients are the use of basis functions that capture the singularities at corners and the representation of the scattered field towards infinity by a combination of fundamental solutions. The solution is obtained by minimizing a least-squares functional, which we discretize in such a way that a matrix least-squares problem is obtained. We give computable exponential bounds on the rate of convergence of the least-squares functional that are in very good agreement with the observed numerical convergence. Challenging numerical examples, including a nonconvex polygon with several corner singularities, and a cavity domain, are solved to around 10 digits of accuracy with a few seconds of CPU time. The examples are implemented concisely with MPSpack, a MATLAB toolbox for wave computations with nonpolynomial basis functions, developed by the authors. A code example is included.
Resumo:
This paper introduces a method for simulating multivariate samples that have exact means, covariances, skewness and kurtosis. We introduce a new class of rectangular orthogonal matrix which is fundamental to the methodology and we call these matrices L matrices. They may be deterministic, parametric or data specific in nature. The target moments determine the L matrix then infinitely many random samples with the same exact moments may be generated by multiplying the L matrix by arbitrary random orthogonal matrices. This methodology is thus termed “ROM simulation”. Considering certain elementary types of random orthogonal matrices we demonstrate that they generate samples with different characteristics. ROM simulation has applications to many problems that are resolved using standard Monte Carlo methods. But no parametric assumptions are required (unless parametric L matrices are used) so there is no sampling error caused by the discrete approximation of a continuous distribution, which is a major source of error in standard Monte Carlo simulations. For illustration, we apply ROM simulation to determine the value-at-risk of a stock portfolio.