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Applying approximate LU-factorizations as preconditioners in eight iterative methods for solving systems of linear algebraic equations

100%
Zlatev Z., Georgiev K.
Open Mathematics
|
2013
|
tom 11
|
nr 8
1510-1530
EN
Many problems arising in different fields of science and engineering can be reduced, by applying some appropriate discretization, either to a system of linear algebraic equations or to a sequence of such systems. The solution of a system of linear algebraic equations is very often the most time-consuming part of the computational process during the treatment of the original problem, because these systems can be very large (containing up to many millions of equations). It is, therefore, important to select fast, robust and reliable methods for their solution, also in the case where fast modern computers are available. Since the coefficient matrices of the systems are normally sparse (i.e. most of their elements are zeros), the first requirement is to efficiently exploit the sparsity. However, this is normally not sufficient when the systems are very large. The computation of preconditioners based on approximate LU-factorizations and their use in the efforts to increase further the efficiency of the calculations will be discussed in this paper. Computational experiments based on comprehensive comparisons of many numerical results that are obtained by using ten well-known methods for solving systems of linear algebraic equations (the direct Gaussian elimination and nine iterative methods) will be reported. Most of the considered methods are preconditioned Krylov subspace algorithms.
2
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Sensitivity studies of pollutant concentrations calculated by the UNI-DEM with respect to the input emissions

81%
Dimov I., Georgieva R., Ostromsky T., Zlatev Z.
Open Mathematics
|
2013
|
tom 11
|
nr 8
1531-1545
EN
The influence of emission levels on the concentrations of four important air pollutants (ammonia, ozone, ammonium sulphate and ammonium nitrate) over three European cities (Milan, Manchester, and Edinburgh) with different geographical locations is considered. Sensitivity analysis of the output of the Unified Danish Eulerian Model according to emission levels is provided. The Sobol’ variance-based approach for global sensitivity analysis has been applied to compute the corresponding sensitivity measures. To measure the influence of the variation of emission levels over the pollutants concentrations the Sobol’ global sensitivity indices are estimated using efficient techniques for small sensitivity indices to avoid the effect of loss of accuracy. Theoretical studies, as well as, practical computations are performed in order to analyze efficiency of various variance reduction techniques for computing small indices. The importance of accurate estimation of small sensitivity indices is analyzed. It is shown that the correlated sampling technique for small sensitivity indices gives reliable results for the full set of indices. Its superior efficiency is studied in details.
3
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Richardson Extrapolation combined with the sequential splitting procedure and the θ-method

81%
Zlatev Z., Faragó I., Havasi Á.
Open Mathematics
|
2012
|
tom 10
|
nr 1
159-172
EN
Initial value problems for systems of ordinary differential equations (ODEs) are solved numerically by using a combination of (a) the θ-method, (b) the sequential splitting procedure and (c) Richardson Extrapolation. Stability results for the combined numerical method are proved. It is shown, by using numerical experiments, that if the combined numerical method is stable, then it behaves as a second-order method.
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