An Algorithmic and Software Framework for Applied PDEs ISIC
PI: Phil Colella (LBNL), TSTT Point of Contact: David Brown (LLNL)

The goal of this project is to develop a high-performance algorithmic and software framework for solving partial differential equations arising from problems in three important mission areas for the DOE Office of Science: magnetic fusion, accelerator design and combustion. This framework will provide investigators in these areas with a new set of simulation capabilities based on locally structured grid methods, including adaptive meshes for problems with multiple length scales; embedded boundary and overset grid methods for complex geometries; efficient and accurate methods for particle and hybrid particle/mesh simulations; and high-performance implementations on distributed-memory multiprocessors. This project will be undertaken as an end-to-end process, with close interactions with stakeholders from the applications disciplines. TSTT standards for embedded boundary and overset meshes, including local refinement meshes, will be developed collaboratively with APDEC researchers in order to conform with APDEC needs for this technology.

The core meshing technology being used by APDEC is adaptive mesh refinement (AMR) on embedded boundary (EB) meshes. EB meshes are Cartesian meshes in which boundaries are described by arbitrary cutting surfaces, resulting in partial cells near the boundary. The Overture project at LLNL contributes research and development activities to both TSTT and APDEC. In particular, the Overture project is responsible over the next few years for delivering a stand-alone capability for building geometry and EB meshes either from scratch, or starting with CAD geometry data. The EB mesh representations will be compatible with the meshing interfaces under development by TSTT, thus allowing interoperability with the other meshing technologies within TSTT. The EB mesh generator will also be available as part of the TSTT meshing technology distribution. LLNL staff meet regularly with members of the APDEC project at Lawrence Berkeley National Laboratory.