Compressed Sensing and Time-Parallel Reduced-Order Modeling for Structural Health Monitoring Using a DDDAS

  • J. Cortial
  • C. Farhat
  • L. J. Guibas
  • M. Rajashekhar
Conference paper

DOI: 10.1007/978-3-540-72584-8_153

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4487)
Cite this paper as:
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: Shi Y., van Albada G.D., Dongarra J., Sloot P.M.A. (eds) Computational Science – ICCS 2007. ICCS 2007. Lecture Notes in Computer Science, vol 4487. Springer, Berlin, Heidelberg

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.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • J. Cortial
    • 1
  • C. Farhat
    • 1
    • 2
  • L. J. Guibas
    • 3
  • M. Rajashekhar
    • 3
  1. 1.Institute for Computational and Mathematical Engineering 
  2. 2.Department of Mechanical Engineering 
  3. 3.Department of Computer Science, Stanford University, Stanford, CA 94305U.S.A

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