Dynamic Grid Adaptation Research Articles

Simulation techniques for multiphase and multicomponent flows

AbstractThe simulation of multiphase and multicomponent fluid flows often requires large coupled systems of nonlinear partial differential equations. These equations are convection‐dominated, with important local diffusive effects. An operator splitting technique is used to address these different phenomena. Adaptive local grid refinement methods are then presented to resolve the moving internal boundary layers which arise and often govern the mass transfer between the phases. Owing to the large size of many application, efficiency in computation is critical. Concepts of domain decomposition for dynamic adaptive grid refinement are presented. Techniques for dividing the problems into pieces for parallel computation on separate processors are also discussed.

Use of a Dynamic Grid Adaptation in the Asymmetric Weighted Residual Method

A dynamic grid adaptive method has been developed for use with the asymmetric weighted residual method. The method automatically adapts the number and position of the spatial mesh points as the sol...

A survey of dynamically-adaptive grids in the numerical solution of partial differential equations

The construction of dynamically-adaptive curvilinear coordinate systems based on numerical grid generation and the use thereof in the numerical solution of partial differential equations is surveyed, and correlations are made among the various approaches. These adaptive grids are coupled with the physical solution being done on the grid so that the grid points continually move in the course of the solution in order to resolve developing gradients, or higher variations, in the solution. Particular attention is given to systems using elliptic grid generation based on variational principles. It is noted that dynamic grid adaption can remove the oscillations common when strong gradients occur on fixed grids, and that it appears that when the grid adapts to the solution most numerical solution algorithms work well. Particular applications in computational fluid dynamics and heat transfer are noted.