
doi: 10.1108/eb005909
The decomposition model has demon‐strated accurate and physically realistic solutions of systems modelled by non‐linear equations. Linear or determin‐istic 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 non‐linear 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 memory‐saving manner with important implications for computa‐tional analysis and modelling.
Multigrid methods; domain decomposition for boundary value problems involving PDEs, Banach space, Numerical solutions to equations with nonlinear operators, nonlinear operator, Hilbert space, Schrödinger equation, Nonlinear ordinary differential equations and systems, Numerical methods for initial value problems involving ordinary differential equations, nonlinear functional equations, Iterative procedures involving nonlinear operators, Applications to the sciences, Linear higher-order PDEs, decomposition method, Adomian's polynomials
Multigrid methods; domain decomposition for boundary value problems involving PDEs, Banach space, Numerical solutions to equations with nonlinear operators, nonlinear operator, Hilbert space, Schrödinger equation, Nonlinear ordinary differential equations and systems, Numerical methods for initial value problems involving ordinary differential equations, nonlinear functional equations, Iterative procedures involving nonlinear operators, Applications to the sciences, Linear higher-order PDEs, decomposition method, Adomian's polynomials
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