In Situ Visualization of Discontinuous Galerkin Based High-Order Methods

Abstract

Develop the theory and framework for a scalable in situ visualization system for any PDE-based solver (independent of whether it is high-order or not), that performs in situ visualization of higher-order results in a pixel-exact manner. (1) Generate Òhigh-order FEMÓ appropriate dimensionality reduction feature extraction methods, such as vortex cores, which can be accomplished as part of an in situ data processing pipeline in order to reduce the amount of data that must be transmitted and stored to accomplish the scientific task of interest. (2) Specify regions of interest in an in situ fashion within a simulation field based upon the visualization objective, extract and transmit relevant high-order FEM modal information to the visualization system, and then reconstruct the visualization features of interest.

Document Details

Document Type
DoD Grant Award
Publication Date
Jan 12, 2017
Source ID
W911NF1510222

Entities

People

  • Robert Kirby

Organizations

  • Army Contracting Command
  • United States Army
  • University of Utah

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms