2008
DOI: 10.1007/s12190-008-0110-z
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Approximation of derivative in a system of singularly perturbed convection-diffusion equations

Abstract: In this paper, a numerical method for a weakly coupled system of two singularly perturbed convection-diffusion second order ordinary differential equations with a small parameter multiplying the highest derivative is presented. Parameteruniform error bounds for the numerical solution and also to numerical derivative are established. Numerical results are provided to illustrate the theoretical results.

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Cited by 8 publications
(9 citation statements)
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“…We split the argument into two cases depending on the localization of the mesh point. In the first case x i ∈ Ω N ∩ [σ, 1], using the arguments in [1] and [14,Lemma 6], for…”
Section: Error Analysismentioning
confidence: 99%
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“…We split the argument into two cases depending on the localization of the mesh point. In the first case x i ∈ Ω N ∩ [σ, 1], using the arguments in [1] and [14,Lemma 6], for…”
Section: Error Analysismentioning
confidence: 99%
“…Most of this work has concentrated on problems involving a single differential equation. Only a few authors have developed robust parameteruniform numerical methods for system of singularly perturbed ordinary differential equations (see [2,4,8,9,10,11,15,16,19] and references therein). While many finite difference methods have been proposed to approximate such solutions, there has been much less research into the finite difference approximations of their derivatives, even though such approximations are desirable in certain applications (flux or drag).…”
Section: Introductionmentioning
confidence: 99%
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“…Recently, the uniform first-order convergence of normalized flux by the upwind finite difference scheme using grid equidistribution was proved in [18]. As well known, the attainment of high accuracy in a numerical solutions does not automatically lead to good approximation of derivatives of exact solutions for convection-diffusion problems, and approximations of derivatives are desirable in many fields [22,18,14,19].…”
Section: Introductionmentioning
confidence: 99%