Contents
How is adaptive mesh refinement used in amrclaw?
The basic adaptive refinment strategy used in AMRClaw Description and Detailed Contents is to refine on logically rectangular patches. A single Level 1 grid covers the entire domain (usually — if it is too large it may be split into multiple Level 1 grids).
How is adaptive mesh refinement used in problem solving?
In adaptive methods, one adjusts the computational effort locally to maintain a uniform level of accuracy throughout the problem domain. Adaptive Mesh Refinement (AMR) Modified equation analysis: finite difference solutions to partial differential equations behave like solutions to the original equations with a modified right-hand side.
Who is the founder of adaptive mesh refinement?
(To be described…) This style of AMR is often called Berger-Oliger-Colella adaptive refinement, after the papers of Berger and Oliger [BergerOliger84] and [BergerColella89].
How is clustering done in adaptive mesh refinement?
Creating the new grids and initializing the values of q and also any aux arrays for each new grid. Clustering is done using and algorithm developed by Berger and Rigoutsis [BergerRigoutsis91] that finds a nonoverlapping set of rectangles that cover all flagged points and balances the following conflicting goals:
Which is an example of advanced mesh refinement?
Advanced mesh refinement has been introduced via functionals. Functionals allow the ability to generate grids and provide mesh adaptation.
Who is the author of adaptive mesh refinement?
This style of AMR is often called Berger-Oliger-Colella adaptive refinement, after the papers of Berger and Oliger [BergerOliger84] and [BergerColella89]. The Fortran code in $CLAW/amrclaw is based on code originally written by Marsha Berger for gas dynamics, and merged in Clawpack in the early days of Clawpack development by MJB and RJL.
When to use anisotropic refinement in Amr?
A single Level 1 grid covers the entire domain (usually — if it is too large it may be split into multiple Level 1 grids). Some rectangular portions of this grid are covered by Level 2 grids refined by some refinement factor R in each direction (anisotropic refinement is now allowed too — see Specifying AMRClaw run-time parameters in setrun.py ).