Dynamic-Data-Driven Real-Time Computational Mechanics Environment

John Michopoulos1, Charbel Farhat2, and Elias Houstis3,4

1Special Projects Group, Code 6303, U.S. Naval Research Laboratory, U.S.A.
john.michopoulos@nrl.navy.mil

2Dept. of Aerospace Engineering Sciences, University of Colorado at Boulder, U.S.A.
charbel.farhat@colorado.edu

3Computer Sciences Department, Purdue University, U.S.A.

4Dept. of Comp. Eng. and Telecommunications, University of Thessaly, Greece
enh@cs.purdue.edu

Abstract. The proliferation of sensor networks in various areas of technology has enabled real-time behavioral monitoring of various physical systems in various length and time scales. The opportunity to use these data dynamically for improving speed, accuracy, and general performance of predictive behavior modeling simulation is of paramount importance. The present paper identifies enabling modeling methods and computational strategies that are critical for achieving real-time simulation response of very large and complex systems. It also discusses our choices of these technologies in the context of sample multidisciplinary computational mechanics applications.

LNCS 3038, pp. 693-700.

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