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Stability Analysis of Large-Scale Incompressible Flow Calculations on Massively Parallel Computers

Description: A set of linear and nonlinear stability analysis tools have been developed to analyze steady state incompressible flows in 3D geometries. The algorithms have been implemented to be scalable to hundreds of parallel processors. The linear stability of steady state flows are determined by calculating the rightmost eigenvalues of the associated generalize eigenvalue problem. Nonlinear stability is studied by bifurcation analysis techniques. The boundaries between desirable and undesirable operating conditions are determined for buoyant flow in the rotating disk CVD reactor.
Date: October 25, 1999
Partner: UNT Libraries Government Documents Department

On the Convergence of an Implicitly Restarted Arnoldi Method

Description: We show that Sorensen's [35] implicitly restarted Arnoldi method (including its block extension) is simultaneous iteration with an implicit projection step to accelerate convergence to the invariant subspace of interest. By using the geometric convergence theory for simultaneous iteration due to Watkins and Elsner [43], we prove that an implicitly restarted Arnoldi method can achieve a super-linear rate of convergence to the dominant invariant subspace of a matrix. Moreover, we show how an IRAM computes a nested sequence of approximations for the partial Schur decomposition associated with the dominant invariant subspace of a matrix.
Date: July 12, 1999
Creator: Lehoucq, Richard B.
Partner: UNT Libraries Government Documents Department

Large-Scale Eigenvalue Calculations for Stability Analysis of Steady Flows on Massively Parallel Computers

Description: We present an approach for determining the linear stability of steady states of PDEs on massively parallel computers. Linearizing the transient behavior around a steady state leads to a generalized eigenvalue problem. The eigenvalues with largest real part are calculated using Arnoldi's iteration driven by a novel implementation of the Cayley transformation to recast the problem as an ordinary eigenvalue problem. The Cayley transformation requires the solution of a linear system at each Arnoldi iteration, which must be done iteratively for the algorithm to scale with problem size. A representative model problem of 3D incompressible flow and heat transfer in a rotating disk reactor is used to analyze the effect of algorithmic parameters on the performance of the eigenvalue algorithm. Successful calculations of leading eigenvalues for matrix systems of order up to 4 million were performed, identifying the critical Grashof number for a Hopf bifurcation.
Date: August 1, 1999
Creator: Lehoucq, Richard B. & Salinger, Andrew G.
Partner: UNT Libraries Government Documents Department