SCD seminar: Parallel implementation of adaptive mesh refinement in a nonlinear solver

SCD will offer a seminar on Wednesday, 5 May 2004 at 10:30 in the Walter Orr Roberts Room of the Fleischman Building. Please plan to join us!

Andrzej Wyszogrodzki, a postdoc at Alamos National Laboratory (LANL), will give a presentation:

"Parallel implementation of the
adaptive mesh refinement (AMR) technique
in the framework of the fully-implicit
Jacobian-Free Newton-Krylov (JFNK) solver"

Abstract

HIgh GRADient (HIGRAD), a compressible hydrodynamic numerical model developed at LANL, is utilized to study extreme atmospheric phenomena such as hurricanes or wildfires. To be useful for the meteorological and fire-fighting communities, this model requires considerable speedup of the real-time computations and increased accuracy.

We solve for all model variables in a fully implicit and nonlinearly consistent manner to achieve second-order, in-time accuracy by using the nonlinear JFNK method. The efficiency of this system is increased by developing a physics-based preconditioner that uses the semi-implicit method to solve an approximate form of the governing equations.

One of the crucial aspects of many atmospheric phenomena is the accurate tracking of weather parameters (such as winds, temperature, or moisture content) over the region where they directly affect or control the weather system. We have implemented an efficient parallel AMR package (PARAMESH) in the JFNK framework.

This technique allows us to zoom in the model resolution on the interesting area and to move this high-resolution region from one location to another, thus allowing the accurate tracking of the atmospheric parameters using high resolution only where required. The details of AMR implementation, the model algorithm's performance and parallelization aspects, and finally the accuracy of the solution will be discussed in the case of a simple test problem.

For more information, contact Jennifer DeLaurant at 303-497-1263, delauran@ucar.edu.