Study of flow instability in turbine engine compressors is crucial to understand the inception
and evolution of engine stall. Aerodynamics experts have been working on detecting the …

The size of large-scale scientific datasets created from simulations and computed on
modern supercomputers continues to grow at a fast pace. A daunting challenge is to analyze …

Multivariate spatial data play an important role in computational science and engineering
simulations. The potential features and hidden relationships in multivariate data can assist …

High-resolution simulation data sets provide plethora of information, which needs to be
explored by application scientists to gain enhanced understanding about various …

Array DBMSs strive to be the best systems for managing, processing, and even visualizing
big Nd arrays. The last decade blossomed with R&D in array DBMS, making it a young and …

Creating a data representation is a common approach for efficient and effective data
management and exploration. The compressed bitmap indexing is one of the emerging data …

The study of multiphase flow is essential for designing chemical reactors such as fluidized
bed reactors (FBR), as a detailed understanding of hydrodynamics is critical for optimizing …

We propose a deep learning approach to collectively compare two or multiple ensembles,
each of which is a collection of simulation outputs. The purpose of collective comparison is …

The analysis and visualization of data created from simulations on modern supercomputers
is a daunting challenge because the incredible compute power of modern supercomputers …

Local distribution search is used in query-driven visualization for identifying salient features.
Due to the high computational and storage costs, local distribution search in multi-field …