Reduced-Order Wave-Propagation Modeling Using the Eigensystem Realization Algorithm

Stephen A. Ketcham (), Minh Q. Phan () and Harley H. Cudney ()
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Stephen A. Ketcham: Engineer Research and Development Center
Minh Q. Phan: Dartmouth College, Thayer School of Engineering
Harley H. Cudney: Engineer Research and Development Center

A chapter in Modeling, Simulation and Optimization of Complex Processes, 2012, pp 183-193 from Springer

Abstract: Abstract This paper presents a computationally efficient version of the Eigensystem Realization Algorithm (ERA) to model the dynamics of large-domain acoustic propagation from High Performance Computing (HPC) data. This adaptation of the ERA permits hundreds of thousands of output signals to be handled at a time. Once the ERA-derived reduced-order models are obtained, they can be used for future simulation of the propagation accurately without having to go back to the HPC model. Computations that take hours on a massively parallel high performance computer can now be carried out in minutes on a laptop computer.

Keywords: Singular Value Decomposition; High Performance Computing; Random Access Memory; Hankel Matrice; Markov Parameter (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-25707-0_15

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DOI: 10.1007/978-3-642-25707-0_15

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