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Title of Journal: J Sci Comput

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Abbravation: Journal of Scientific Computing

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Springer US

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DOI

10.1007/978-3-540-39966-7_21

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1573-7691

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SemiLagrangian RungeKutta Exponential Integrator

Authors: Elena Celledoni Bawfeh Kingsley Kometa
Publish Date: 2009/04/04
Volume: 41, Issue: 1, Pages: 139-164
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Abstract

In this paper we consider the case of nonlinear convectiondiffusion problems with a dominating convection term and we propose exponential integrators based on the composition of exact pure convection flows These methods can be applied to the numerical integration of the considered PDEs in a semiLagrangian fashion SemiLagrangian methods perform well on convection dominated problems Pironneau in Numer Math 38309–332 1982 Hockney and Eastwood in Computer simulations using particles McGrawHill New York 1981 Rees and Morton in SIAM J Sci Stat Comput 123547–572 1991 Baines in Moving finite elements Monographs on numerical analysis Clarendon Press Oxford 1994

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  2. Exact Low-Rank Matrix Completion from Sparsely Corrupted Entries Via Adaptive Outlier Pursuit
  3. Efficient Rearrangement Algorithms for Shape Optimization on Elliptic Eigenvalue Problems
  4. Sparsity Enforcing Edge Detection Method for Blurred and Noisy Fourier data
  5. The Finite Volume-Complete Flux Scheme for Advection-Diffusion-Reaction Equations
  6. Simulation of an $$n^{+}\hbox {-}n\hbox {-}n^{+}$$ Diode by Using Globally-Hyperbolically-Closed High-Order Moment Models
  7. Optimal Spectral-Galerkin Methods Using Generalized Jacobi Polynomials
  8. Theoretical and Numerical Investigation of the Finite Cell Method
  9. The Effect of the Consistent Mass Matrix on the Maximum-Principle for Scalar Conservation Equations
  10. Analysis of Nonlinear Spectral Eddy-Viscosity Models of Turbulence
  11. Transformation Methods for the Numerical Integration of Three-Dimensional Singular Functions
  12. A Posteriori Estimates for a Natural Neumann–Neumann Domain Decomposition Algorithm on a Unilateral Contact Problem
  13. Solving 1D Conservation Laws Using Pontryagin’s Minimum Principle
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