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 Di erential 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",
}