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Encyclopedia > Adaptive mesh refinement

In numerical analysis, central to any Eulerian method is the manner in which it discretizes the continuous domain of interest into a grid of many individual elements. This grid may be static, established once and for all at the beginning of the computation, or it may be dynamic, tracking the features of the result as the computation progresses. If the computation has features which one wants to track which are much smaller than the overall scale of the problem, and which move in time, then one must either include many more static grids to cover the region of interest, or adopt a dynamic scheme. Numerical analysis is the study of algorithms for the problems of continuous mathematics (as distinguished from discrete mathematics). ... The term grid has several meanings in various fields: in mathematics and geometry, a grid is a system of two sets of lines that intersect each other at a fixed angle, usually a right angle (i. ...


The advantages of a dynamic gridding scheme are:

  1. Increased computational savings over a static grid approach.
  2. Increased storage savings over a static grid approach.
  3. Complete control of grid resolution, compared to the fixed resolution of a static grid approach, or the Lagrangian-based adaptivity of smoothed particle hydrodynamics.

Smoothed Particle Hydrodynamics (SPH) is a computational method used for simulating fluid flows. ...

Introduction to adaptive mesh refinement

In a series of papers, Marsha Berger, John Oliger, and Phillip Colella developed an algorithm for dynamic gridding called local adaptive mesh refinement. The algorithm begins with the entire computational domain covered with a coarsely resolved base-level regular Cartesian grid. As the calculation progresses, individual grid cells are tagged for refinement, using a criterion that can either be user-supplied (i.e. mass per cell remains constant, hence higher density regions are more highly resolved) or based on Richardson extrapolation.


All tagged cells are then refined, meaning that a finer grid is overlayed on the coarse one. After refinement, individual grid patches on a single fixed level of refinement are passed off to an integrator which advances those cells in time. Finally, a correction procedure is implemented to correct the transfer along coarse-fine grid interfaces, to insure that the amount of any conserved quantity leaving one cells exactly balances the amount enter the bordering cell. If at some point the level of refinement in a cell is greater than required, the high resolution grid may be removed and replaced with a coarser one.


Image:amrgridimg.jpg


The image above shows the grid structure of an AMR calculation of a shock impacting an inclined slope. Each of the boxes is a grid; the more boxes it is nested within, the higher the level of refinments. As the image shows, the algorithm uses high resolution grids only at the physical locations and times where they are required. This allows the user to solve problems that are completely intractable on a uniform grid; for example, astrophysicists have used AMR to model a collapsing giant molecular cloud core down to an effective resolution of 131,072 cells per initial cloud radius, corresponding to a resolution of 10^15 cells on a uniform grid. A dark nebula is a large cloud which appears as star-poor regions where the dust of interstellar medium seems to be concentrated. ...


  Results from FactBites:
 
Adaptive Mesh Refinement for Singular Current Sheets (3032 words)
Since the singular structures like tubes and sheets are not space filling, adaptive mesh codes seem to be the right choice for studying these problems, as has been done by Pumir and Siggia[4,5].
Finally, we conclude that adaptive mesh refinement is an ideal tool for studying singular structures and should be pursued further to study three dimensional problems as the finite time blow up in the incompressible Euler equations.
Applying adaptive mesh refinement to the evolution of singular structures like current sheets in magnetohydrodynamics is motivated by the expected reduction of memory needed to resolve them.
COMPUTING SCIENCES: Zooming In On Data (976 words)
Using a technique called adaptive mesh refinement, researchers break their data down into cells, covering areas of particular interest with a mesh of thousands of segments, which then can be individually analyzed in detail.
Adaptive mesh refinement allows scientists to focus on the details of the turbulent airflow around the wings without having to spend a large percentage of the available resources describing the relatively smooth flow in the much larger region of space away from the wings.
Using this type of local mesh refinement, scientists are able to focus their existing computer power on a narrower part of the overall problem, so as to get the most information, given a limited amount of computer time and memory.
  More results at FactBites »


 
 

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