An Intelligent Agent Architecture for Concurrent CFD Feature Extraction


CFD simulations are advancing to correctly simulate highly complex fluid flow problems that can require weeks on expensive computing clusters. These simulations can generate terabytes of data and pose a severe challenge to a researcher analyzing the data. Presented here is a solution to drastically reduce researcher post-processing time by extracting fluid flow features concurrent with a running CFD simulation using intelligent software agents. The software agents are designed to work inside the CAF́E1 concept and operate efficiently on high performance computing clusters. Three types of agents are given and their belief tuples defined. A simulation of a blunt-fin is run showing convergence of the horseshoe fin line to its final spatial location at 540 iterations, or 60% of solution convergence. The agent architecture correctly selects between two vortex feature extraction algorithms and correctly identifies the expected probabilities of core lines throughout solution convergence.

Meeting Name

48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition (2010: Jan. 4-7, Orlando, FL)


Electrical and Computer Engineering

Keywords and Phrases

Agent architectures; CFD simulations; Complex fluid flow; Computing clusters; Core lines; Feature extraction algorithms; Fin-lines; Fluid flow; High-performance computing clusters; Intelligent agent architecture; Intelligent software agent; Post processing; Spatial location, Aerospace engineering; Computational fluid dynamics; Computer simulation; Convergence of numerical methods; Feature extraction; Fins (heat exchange); Flow of fluids; Intelligent agents, Software agents

International Standard Book Number (ISBN)


Document Type

Article - Conference proceedings

Document Version


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© 2010 American Institute of Aeronautics and Astronautics (AIAA), All rights reserved.

Publication Date

01 Jan 2010

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