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

  • J. Cortial
  • C. Farhat
  • L. J. Guibas
  • M. Rajashekhar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4487)

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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