Dynamic Data Driven Methodologies for Multiphysics System Modeling and Simulation

J. Michopoulos1, C. Farhat2, E. Houstis3,4, P. Tsompanopoulou4, H. Zhang3, and T. Gullaud2

1Code 6390, Special Projects Group, U.S. Naval Research Laboratory, U.S.A
john.michopoulos@nrl.navy.mil

2Dept. of Mechanical Engineering, Stanford University, U.S.A
cfarhat@stanford.edu
tgullaud@stanford.edu

3Computer Sciences Dept. & Electrical and Computer Engineering Dept., Purdue University, U.S.A
enh@purdue.edu
hzhang@purdue.edu

4Dept. of Comp. Eng. and Telecommunications, University of Thessaly, Greece
enh@uth.gr
yota@uth.gr

Abstract. We are presenting a progress overview associated with our work on a data-driven environment for multiphysics applications (DDEMA). In this paper, we emphasize the dynamic-data-driven adaptive modeling and simulation aspects. Adaptive simulation examples of sensor-originating data-driven precomputed solution synthesis are given for two applications. Finally, some of the computational implementation details are presented.

LNCS 3515, pp. 616-623.

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