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 Differential Equation) solver. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Cortial, J., Farhat, C., Guibas, L. J., & Rajashekhar, M. (2007). Compressed sensing and time-parallel reduced-order modeling for structural health monitoring using a DDDAS. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4487 LNCS, pp. 1171–1179). Springer Verlag. https://doi.org/10.1007/978-3-540-72584-8_153
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