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J. Cortial, C. Farhat, L. Guibas, and M. Rajashekhar, Compressed Sensing and Time-Parallel Reduced-Order Modeling for Structural Health Monitoring using a DDDAS. Int. Conf. Computational Science (ICCS), pp. 1171-1179, 2007.
Abstract:
This paper discusses recent progress achieved in two areas
related to the development of a Dynamic Data Driven Applications System
(DDDAS) for structural and material health monitoring and critical
event prediction. The first area concerns the development and demonstration of a sensor data compression algorithm and its application to the detection of structural damage. The second area concerns the prediction in near real-time of the transient dynamics of a structural system using a nonlinear reduced-order model and a time-parallel ODE (Ordinary Dierential Equation) solver.
Bibtex:
@inproceedings{cfgr-cstpromshmdddas-iccs07,
author="J. Cortial and C. Farhat and L. Guibas and M. Rajashekhar",
title="Compressed Sensing and Time-Parallel Reduced-Order Modeling for Structural Health Monitoring using a DDDAS",
booktitle="IEEE Int. Conf. Computational Science (ICCS))",
pages="1171--1179"
year="2007",
}
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