MICROCOMPUTER APPLICATIONS OF WEIGHTED RESIDUAL METHODS IN THE NUMERICAL SOLUTION OF NONLINEAR PROBLEMS.

G D Baker

MICROCOMPUTER APPLICATIONS OF WEIGHTED RESIDUAL METHODS IN THE NUMERICAL SOLUTION OF NONLINEAR PROBLEMS.

G D Baker

Research output: Contribution to conference › Paper

Abstract

The microcomputer implementation of the numerical solution of nonlinear differential equations using collocation and Galerkin methods, with a Newton search, is considered. One example of large deflections of a tapered cantilever is solved in detail to provide a parametric study of the numerical variables. The results indicate that the Gauss point collocation scheme is the most efficient, the least affected by precision, and so well suited to small office computers. (Author abstract. ) Refs.

Original language	English
Publication status	Published - 1985

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title = "MICROCOMPUTER APPLICATIONS OF WEIGHTED RESIDUAL METHODS IN THE NUMERICAL SOLUTION OF NONLINEAR PROBLEMS.",

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N2 - The microcomputer implementation of the numerical solution of nonlinear differential equations using collocation and Galerkin methods, with a Newton search, is considered. One example of large deflections of a tapered cantilever is solved in detail to provide a parametric study of the numerical variables. The results indicate that the Gauss point collocation scheme is the most efficient, the least affected by precision, and so well suited to small office computers. (Author abstract. ) Refs.

AB - The microcomputer implementation of the numerical solution of nonlinear differential equations using collocation and Galerkin methods, with a Newton search, is considered. One example of large deflections of a tapered cantilever is solved in detail to provide a parametric study of the numerical variables. The results indicate that the Gauss point collocation scheme is the most efficient, the least affected by precision, and so well suited to small office computers. (Author abstract. ) Refs.

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M3 - Paper

ER -

MICROCOMPUTER APPLICATIONS OF WEIGHTED RESIDUAL METHODS IN THE NUMERICAL SOLUTION OF NONLINEAR PROBLEMS.

Abstract

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