Chapter

Computational Science – ICCS 2007

Volume 4487 of the series Lecture Notes in Computer Science pp 1171-1179

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

  • J. CortialAffiliated withInstitute for Computational and Mathematical Engineering
  • , C. FarhatAffiliated withInstitute for Computational and Mathematical EngineeringDepartment of Mechanical Engineering
  • , L. J. GuibasAffiliated withDepartment of Computer Science, Stanford University, Stanford, CA 94305
  • , M. RajashekharAffiliated withDepartment of Computer Science, Stanford University, Stanford, CA 94305

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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.