An Efficient Methodology for the Physical Sciences

An Efficient Methodology for the Physical Sciences The decomposition model has demonstrated accurate and physically realistic solutions of systems modelled by nonlinear equations. Linear or deterministic equations become simple special cases and the result is a general method of solution connecting the fields of ordinary and partial differential equations. No linearisation or resort to numerically intensive discretised methods is involved. The avoidance of these limiting and restrictive methods offers physically correct solutions as well as insights into the behaviour of real systems where nonlinear effects play a crucial role. In difficult applications, such as those now approached by computational fluid dynamics, the potential saving in computation will be substantial. The method clearly offers the potential of a significant step forward in the rapid solution of complex applications in a time and memorysaving manner with important implications for computational analysis and modelling. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

An Efficient Methodology for the Physical Sciences

Kybernetes, Volume 20 (7): 11 – Jul 1, 1991

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0368-492X
DOI
10.1108/eb005909
Publisher site
See Article on Publisher Site

Abstract

The decomposition model has demonstrated accurate and physically realistic solutions of systems modelled by nonlinear equations. Linear or deterministic equations become simple special cases and the result is a general method of solution connecting the fields of ordinary and partial differential equations. No linearisation or resort to numerically intensive discretised methods is involved. The avoidance of these limiting and restrictive methods offers physically correct solutions as well as insights into the behaviour of real systems where nonlinear effects play a crucial role. In difficult applications, such as those now approached by computational fluid dynamics, the potential saving in computation will be substantial. The method clearly offers the potential of a significant step forward in the rapid solution of complex applications in a time and memorysaving manner with important implications for computational analysis and modelling.

Journal

KybernetesEmerald Publishing

Published: Jul 1, 1991

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