An analytical framework for particle and volume data of large-scale combustion simulations

Abstract

This paper presents a framework to enable parallel data analyses and visualizations that combine both Lagrangian particle data and Eulerian field data of large-scale combustion simulations. Our framework is characterized by a new range query based design that facilitates mutual queries between particles and volumetric segments. Scientists can extract complex features, such as vortical structures based on vector field classifications, and obtain detailed statistical information from the corresponding particle data. This framework also works in reverse as it can extract vector field information based on particle range queries. The effectiveness of our approach has been demonstrated by an experimental study on vector field data and particle data from a large-scale direct numerical simulation of a turbulent lifted ethylene jet flame. Our approach provides a foundation for scalable heterogeneous data analytics of large scientific applications.