2009
DOI: 10.1007/s10665-009-9350-7
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An improvement of the double discrete ordinate approximation solution by Laplace technique for radiative-transfer problems without azimuthal symmetry and high degree of anisotropy

Abstract: One-dimensional radiative-transfer problems without azimuthal symmetry and with a high degree of anisotropy are solved using the double discrete ordinate approximation methods LTA N and ALTA N . The discussed methods start with projecting out azimuthal components of the original equation and results in an equation system. Then the collocation method is applied to the polar angle and the integral is approximated by a Gaussian quadrature scheme that yields the S N transport equation system. The subsequent applic… Show more

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Cited by 4 publications
(3 citation statements)
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“…The latter case turns Adomian obsolete, because the non-linear term vanishes, whereas ω = 0 diagonalizes the equation system and thus turns Laplace obsolete, since the solution may be obtained directly by integration. The decomposition method as originally introduced is designed for general non-linear problems, but several ways are possible to construct a solution (Cardona et al, 2009;Segatto et al, 2008). The present study may be considered a guideline on how to distribute the influence of the boundary conditions and the non-linearity in order to solve the given problem.…”
Section: Resultsmentioning
confidence: 99%
“…The latter case turns Adomian obsolete, because the non-linear term vanishes, whereas ω = 0 diagonalizes the equation system and thus turns Laplace obsolete, since the solution may be obtained directly by integration. The decomposition method as originally introduced is designed for general non-linear problems, but several ways are possible to construct a solution (Cardona et al, 2009;Segatto et al, 2008). The present study may be considered a guideline on how to distribute the influence of the boundary conditions and the non-linearity in order to solve the given problem.…”
Section: Resultsmentioning
confidence: 99%
“…There may be a potential problem in formula ( 9): when the number of training samples is small and the number of attributes is large, the training samples are not enough to cover so many attributes, so the number of samples of A j =x j may be 0, and the whole category conditional probability P(C i | X) will be equal to 0 [30,31]. If this happens frequently, it is impossible to achieve accurate classification.…”
Section: Laplace Calibrationmentioning
confidence: 99%
“…i P C X will be equal to 0 [20][21]. If this happens frequently, it is impossible to achieve accurate classification.…”
Section: ) Laplace Calibrationmentioning
confidence: 99%