Efficient Iterative Algorithms for Linear Stability Analysis of Incompressible Flows

dc.contributor.authorElman, Howard C.
dc.contributor.authorRostami, Minghao W.
dc.date.accessioned2013-11-10T20:38:30Z
dc.date.available2013-11-10T20:38:30Z
dc.date.issued2013-11-07
dc.description.abstractLinear stability analysis of a dynamical system entails finding the rightmost eigenvalue for a series of eigenvalue problems. For large-scale systems, it is known that conventional iterative eigenvalue solvers are not reliable for computing this eigenvalue. A more robust method recently developed in Elman & Wu (2012) and Meerbergen & Spence (2010), Lyapunov inverse iteration, involves solving large-scale Lyapunov equations, which in turn requires the solution of large, sparse linear systems analogous to those arising from solving the underlying partial differential equations. This study explores the efficient implementation of Lyapunov inverse iteration when it is used for linear stability analysis of incompressible flows. Efficiencies are obtained from effective solution strategies for the Lyapunov equations and for the underlying partial differential equations. Existing solution strategies are tested and compared, and a modified version of a Lyapunov solver is proposed that achieves significant savings in computational cost.en_US
dc.identifier.urihttp://hdl.handle.net/1903/14715
dc.language.isoen_USen_US
dc.relation.ispartofseriesUM Computer Science Department;CS-TR-5028
dc.relation.ispartofseriesUMIACS;UMIACS-TR-2013-05
dc.titleEfficient Iterative Algorithms for Linear Stability Analysis of Incompressible Flowsen_US
dc.typeTechnical Reporten_US

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