Results 191 to 200 of about 32,638,059 (250)
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1995
In den vorherigen Kapiteln wurde beschrieben, wie die FEM fur die Losung von Minimierungsproblemen und damit zusammenhangenden DG benutzt wird. Fur eine grose Anzahl von DG existiert jedoch kein aquivalentes Mini-mierungsproblem, so das auf sie die Ritzsche Methode nicht anwendbar ist.
J. J. I. M. van Kan, A. Segal
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In den vorherigen Kapiteln wurde beschrieben, wie die FEM fur die Losung von Minimierungsproblemen und damit zusammenhangenden DG benutzt wird. Fur eine grose Anzahl von DG existiert jedoch kein aquivalentes Mini-mierungsproblem, so das auf sie die Ritzsche Methode nicht anwendbar ist.
J. J. I. M. van Kan, A. Segal
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1977
Consider a separable Hilbert space H and a set M of its elements which is dense in H. According to Theorem 6.18, p. 79, if for some element u ∈ H $$\left( {u,v} \right) = 0\,\,\,holds\,for\,every\,\,\,v \in M,$$ (14.1) then it follows that u = 0 in H. Let now $${\varphi _1},{\varphi _2},\,...$$ (14.2) be a base in H. The assertion is
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Consider a separable Hilbert space H and a set M of its elements which is dense in H. According to Theorem 6.18, p. 79, if for some element u ∈ H $$\left( {u,v} \right) = 0\,\,\,holds\,for\,every\,\,\,v \in M,$$ (14.1) then it follows that u = 0 in H. Let now $${\varphi _1},{\varphi _2},\,...$$ (14.2) be a base in H. The assertion is
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2008
Die Formulierung des Randwert problems aus Kapitel 2 als Variationsproblem war muhsam, das Prinzip der Diskretisierung des Variationsproblems ist nun aber kurz darstellbar und lasst sich sehr allgemein formulieren.
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Die Formulierung des Randwert problems aus Kapitel 2 als Variationsproblem war muhsam, das Prinzip der Diskretisierung des Variationsproblems ist nun aber kurz darstellbar und lasst sich sehr allgemein formulieren.
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2002
In this chapter we consider an FK2 of the form (1.2.2): ϕ(x) — λ ∫ a b k(x,s)ϕ(s)ds = f (s), where a ≤ x,s ≤ b, and the kernel k(x,s) has a weak singularity at an endpoint. In numerical approximations, whether in quadrature, finite differences,finite elements, and the like, the computational methods generally use polynomials as basis functions to ...
Prem K. Kythe, Pratap Puri
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In this chapter we consider an FK2 of the form (1.2.2): ϕ(x) — λ ∫ a b k(x,s)ϕ(s)ds = f (s), where a ≤ x,s ≤ b, and the kernel k(x,s) has a weak singularity at an endpoint. In numerical approximations, whether in quadrature, finite differences,finite elements, and the like, the computational methods generally use polynomials as basis functions to ...
Prem K. Kythe, Pratap Puri
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1984
When evaluated on a uniform grid, the Galerkin method produces symmetric formulae. Thus odd-order derivatives lead to zero coefficients associated with the node at which the function is centered. The steady, two-dimensional convection-diffusion equation is $$ u\frac{\partial T}{\partial x}~+~v\frac{\partial T}{\partial y}~-~D\left( \frac{{{\partial
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When evaluated on a uniform grid, the Galerkin method produces symmetric formulae. Thus odd-order derivatives lead to zero coefficients associated with the node at which the function is centered. The steady, two-dimensional convection-diffusion equation is $$ u\frac{\partial T}{\partial x}~+~v\frac{\partial T}{\partial y}~-~D\left( \frac{{{\partial
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A-to-Z Guide to Thermodynamics, Heat and Mass Transfer, and Fluids Engineering, 2006
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1984
Galerkin methods have been used to solve problems in structural mechanics, dynamics, fluid flow, hydrodynamic stability, magnetohydrodynamics, heat and mass transfer, acoustics, microwave theory, neutron transport, etc. Problems governed by ordinary differential equations, partial differential equations, and integral equations have been investigated ...
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Galerkin methods have been used to solve problems in structural mechanics, dynamics, fluid flow, hydrodynamic stability, magnetohydrodynamics, heat and mass transfer, acoustics, microwave theory, neutron transport, etc. Problems governed by ordinary differential equations, partial differential equations, and integral equations have been investigated ...
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Journal of Computational Physics, 2016
V. Lisitsa, V. Tcheverda, C. Botter
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V. Lisitsa, V. Tcheverda, C. Botter
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2018
As we noted earlier, spectral bases are infinitely differentiable, but have global support. On the other hand, basis functions used in finite difference or finite element methods have small compact support, but have poor differentiability properties. Wavelet bases seem to combine the advantages of both spectral (discussed in Sect.
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As we noted earlier, spectral bases are infinitely differentiable, but have global support. On the other hand, basis functions used in finite difference or finite element methods have small compact support, but have poor differentiability properties. Wavelet bases seem to combine the advantages of both spectral (discussed in Sect.
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