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Adaptive space-meshing strategies for the numerical solution of parabolic partial differential equations in one space dimension

Neary, Paul P (1990) Adaptive space-meshing strategies for the numerical solution of parabolic partial differential equations in one space dimension. Master of Science thesis, Dublin City University.

Abstract
The effectiveness of adaptive space-meshing in the solution of one-dimensional parabolic partial differential equations (PDEs) is assessed. Present day PDE software typically involves discretisation in space (using Finite Differences or Finite Elements) to produce a system of ordinary differential equations (ODEs) which is then solved routinely using currently available high quality ODE integrators. Such approaches do not attempt to control the errors in the spatial discretisation and th e task of ensuring an effective spatial approxim ation and num erical grid are left entirely to the user. Numerical experiments with Burgers’ equation demonstrate the inadequacies of this approach and suggest the need foradaptive spatial m eshing as the problem evolves. The currently used adaptive m eshing techniques for parabolic problems are reviewed and two effective strategies are selected for study. Numerical experim ents dem onstrate their effectiveness in term s of reduced com putational overhead and increased accuracy. From these experiences possible future trends in adaptive meshing can be identified.
Metadata
Item Type:Thesis (Master of Science)
Date of Award:1990
Refereed:No
Supervisor(s):Carroll, John
Uncontrolled Keywords:One-dimensional Parabolic Partial Differential Equations (PDE); Partial Numerical solutions
Subjects:Mathematics > Differential equations
Mathematics
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Science and Health > School of Mathematical Sciences
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 License. View License
ID Code:19137
Deposited On:04 Sep 2013 10:56 by Celine Campbell . Last Modified 19 Jul 2018 15:01
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