Finding Regions of Interest on Toroidal Meshes
Fusion promises to provide clean and safe energy, and a considerable amount of research effort is underway to turn this aspiration intoreality. This work focuses on a building block for analyzing data produced from the simulation of microturbulence in magnetic confinementfusion devices: the task of efficiently extracting regions of interest. Like many other simulations where a large amount of data are produced,the careful study of ``interesting'' parts of the data is critical to gain understanding. In this paper, we present an efficient approach forfinding these regions of interest. Our approach takes full advantage of the underlying mesh structure in magnetic coordinates to produce acompact representation of the mesh points inside the regions and an efficient connected component labeling algorithm for constructingregions from points. This approach scales linearly with the surface area of the regions of interest instead of the volume as shown with bothcomputational complexity analysis and experimental measurements. Furthermore, this new approach is 100s of times faster than a recentlypublished method based on Cartesian coordinates.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- Computational Research Division
- DOE Contract Number:
- DE-AC02-05CH11231
- OSTI ID:
- 1011042
- Report Number(s):
- LBNL-4364E; TRN: US1102109
- Journal Information:
- Computational Science&Discovery, Vol. 4, Issue 1; ISSN 1749--4699
- Country of Publication:
- United States
- Language:
- English
Similar Records
A conservative implicit-PIC scheme for the hybrid kinetic-ion fluid-electron plasma model on curvilinear meshes
An electrostatic Particle-In-Cell code on multi-block structured meshes