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Numerical methods elimination method

Disadvantages software system is determined deficiencies of the diffusion model of formation grown-in microdefects. These include (i) one-dimensional model (ii) failure to accoxmt for the width of the V-shaped distribution of precipitates (iii) uncertainty in determining of thermal conditions of growth (iv) the error of approximate numerical methods. Elimination of these deficiencies will increase the accuracy of the calculations. [Pg.628]

A set of n first-degree equations in n unknowns is solved in a similar fashion by multiplication and addition to eliminate n - 1 unknowns and then back substitution. Second-degree equations in 2 unknowns may be solved in the same way when two of the following are given the product of the unknowns, their sum or difference, the sum of their squares. For further solutions, see Numerical Methods. ... [Pg.26]

We present and discuss results for MD modeling of fluid systems. We restrict our discussion to systems which are in a macroscopically steady state, thus eliminating the added complexity of any temporal behavior. We start with a simple fluid system where the hydrodynamic equations are exactly solvable. We conclude with fluid systems for which the hydrodynamic equations are nonlinear. Solutions for these equations can be obtained only through numerical methods. [Pg.249]

The method using GC/MS with selected ion monitoring (SIM) in the electron ionization (El) mode can determine concentrations of alachlor, acetochlor, and metolachlor and other major corn herbicides in raw and finished surface water and groundwater samples. This GC/MS method eliminates interferences and provides similar sensitivity and superior specificity compared with conventional methods such as GC/ECD or GC/NPD, eliminating the need for a confirmatory method by collection of data on numerous ions simultaneously. If there are interferences with the quantitation ion, a confirmation ion is substituted for quantitation purposes. Deuterated analogs of each analyte may be used as internal standards, which compensate for matrix effects and allow for the correction of losses that occur during the analytical procedure. A known amount of the deuterium-labeled compound, which is an ideal internal standard because its chemical and physical properties are essentially identical with those of the unlabeled compound, is carried through the analytical procedure. SPE is required to concentrate the water samples before analysis to determine concentrations reliably at or below 0.05 qg (ppb) and to recover/extract the various analytes from the water samples into a suitable solvent for GC analysis. [Pg.349]

A set of linear equations can be solved by a variety of procedures. In principle the method of determinants is applicable to any number of equations but for large systems other methods require much less numerical effort. The method of Gauss illustrated here eliminates one variable at a time, ends up with a single variable and finds all the roots by a reverse procedure. [Pg.30]

As it will be discussed, while three maxima of the first derivative are observed, the second one is a consequence of the applied numerical method. Using the second derivative values in the last column, local inverse linear interpolation gives V = 3.74 ml and V = 7.13 ml for the two equivalence points. We will see later on how the false end point can be eliminated. [Pg.234]

Numeric dispersion can be eliminated largely by a high-resolution discretisation. The Grid-Peclet number helps for the definition of the cell size. Pinder and Gray (1977) recommend the Pe to be < 2. The high resolution discretisation, however, leads to extremely long computing times. Additionally the stability of the numeric finite-differences method is influenced by the discretisation of time. The Courant number (Eq. 104) is a criterion, so that the transport of a particle is calculated within at least one time interval per cell. [Pg.64]

Here, cp is a random number for the calculation step i . It is given by a standard procedure for the normal distribution values with a mean value of zero where Dj-Aj and F) are the corresponding Dj-a and F values for the j bin and the particle position i . The only limitation of the numerical method is concentrated in the fact that Ax must have very small values in order to eliminate all the problems of non-convergence caused by the second term on the right half of the equation (4.119). [Pg.233]

The problem table is a numerical method for determining the pinch temperatures and the minimum utility requirements, introduced by Linnhoff and Flower (1978). It eliminates the sketching of composite curves, which can be useful if the problem is being solved manually. It is not widely used in industrial practice any more, due to the wide availability of computer tools for pinch analysis (see Section 3.17.7). [Pg.130]

These functions of p are special to the molecule in question. They may be expressed either analytically, as in the example in Sect. 5, or as a set of specific values derived numerically for appropriate values of p. Since numerical methods are most likely for larger molecules, we shall aim particularly at expressions where most partial derivates other than those of aa and have been eliminated. Numerically derived partial derivatives may introduce uncontrollable errors. [Pg.136]

Use the first equation to eliminate Na and obtain a governing equation for Ca. The values of parameters are D = 1x10 cmVs, Ct = 4x10 mol/cm L = 0.2 cm, k = 8x10" cmVs/mol and K = 6x10 cmVmol. Solve this problem numerically (choose any appropriate numerical method) to obtain the concentration profile. [Pg.291]

This is a system of equations of the form Ax = B. There are several numeral algorithms to solve this equation including Gauss elimination, Gauss-Jacobi method, Cholesky method, and the LU decomposition method, which are direct methods to solve equations of this type. For a general matrix A, with no special properties such as symmetric, band diagonal, and the like, the LU decomposition is a well-established and frequently used algorithm. [Pg.1953]

Olteanu and Pavel (1995) presented theoretical premises of the dissociation model for electrical conductivity in molten salt mixtures. The authors gave a versatile numerical method together with its corresponding computing procedure and provided an easier and more precise way of calculation. Eliminating the sum (x a + X2 2) from Eqs. (8.25) and (8.26), one obtains a relation between a and o 2 independent of molar fractions... [Pg.341]

In the final step DHPCG calculates the NSIM derivatives for the reactants that are being simulated. Since the derivative forms of T37pe (1), (2) and (3) equations are all linear with respect to the CP (i) s, they are solved simultaneously for the CP(iys by the Gaussian elimination method. The partial derivatives used in the evaluation of the derivative form of the Type (1) equation are calculated with the same numerical differentiation formula that is used in the NONLIN module. [Pg.61]


See other pages where Numerical methods elimination method is mentioned: [Pg.34]    [Pg.592]    [Pg.80]    [Pg.197]    [Pg.49]    [Pg.82]    [Pg.208]    [Pg.26]    [Pg.92]    [Pg.270]    [Pg.188]    [Pg.34]    [Pg.592]    [Pg.270]    [Pg.846]    [Pg.311]    [Pg.174]    [Pg.328]    [Pg.151]    [Pg.652]    [Pg.169]    [Pg.178]    [Pg.685]    [Pg.269]    [Pg.1951]    [Pg.2075]    [Pg.792]    [Pg.168]    [Pg.64]    [Pg.263]    [Pg.165]    [Pg.222]    [Pg.865]    [Pg.623]    [Pg.865]    [Pg.255]   
See also in sourсe #XX -- [ Pg.301 ]




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