An Arnoldi-frontal approach for the stability analysis of flows in a collapsible channel

In this paper, we present a new approach based on a combination of the Arnoldi and frontal methods for solving large sparse asymmetric and generalized complex eigenvalue problems. The new eigensolver seeks the most unstable eigensolution in the Krylov subspace and makes use of the efficiency of the frontal solver developed for the finite element methods. The approach is used for a stability analysis of flows in a collapsible channel and is found to significantly improve the computational efficiency compared to the traditionally used QZ solver or a standard Arnoldi method. With the new approach, we are able to validate the previous results obtained either on a much coarser mesh or estimated from unsteady simulations. New neutral stability solutions of the system have been obtained which are beyond the limits of previously used methods

A Hessenberg-type algorithm for computing PageRank Problems

PageRank is a widespread model for analysing the relative relevance of nodes within large graphs arising in several applications. In the current paper, we present a cost-effective Hessenberg-type method built upon the Hessenberg process for the solution of difficult PageRank problems. The new method is very competitive with other popular algorithms in this field, such as Arnoldi-type methods, especially when the damping factor is close to 1 and the dimension of the search subspace is large. The convergence and the complexity of the proposed algorithm are investigated. Numerical experiments are reported to show the efficiency of the new solver for practical PageRank computations

Stability Analysis in Spanwise-Periodic Double-Sided Lid-Driven Cavity Flows With Complex Cross-Sectional Profiles

Three-dimensional linear instability analyses are presented of steady two-dimensional laminar flows in the lid-driven cavity defined by [15] and further analyzed in the present volume [1], as well as in a derivative of the same geometry. It is shown that in both of the geometries considered three-dimensional BiGlobal instability leads to deviation of the flow from the two-dimensional solution; the analysis results are used to define low- and high-Reynolds number solutions by reference to the flow physics. Critical conditions for linear global instability and neutral loops are presented in both geometries

On the Generation of Large Passive Macromodels for Complex Interconnect Structures

This paper addresses some issues related to the passivity of interconnect macromodels computed from measured or simulated port responses. The generation of such macromodels is usually performed via suitable least squares fitting algorithms. When the number of ports and the dynamic order of the macromodel is large, the inclusion of passivity constraints in the fitting process is cumbersome and results in excessive computational and storage requirements. Therefore, we consider in this work a post-processing approach for passivity enforcement, aimed at the detection and compensation of passivity violations without compromising the model accuracy. Two complementary issues are addressed. First, we consider the enforcement of asymptotic passivity at high frequencies based on the perturbation of the direct coupling term in the transfer matrix. We show how potential problems may arise when off-band poles are present in the model. Second, the enforcement of uniform passivity throughout the entire frequency axis is performed via an iterative perturbation scheme on the purely imaginary eigenvalues of associated Hamiltonian matrices. A special formulation of this spectral perturbation using possibly large but sparse matrices allows the passivity compensation to be performed at a cost which scales only linearly with the order of the system. This formulation involves a restarted Arnoldi iteration combined with a complex frequency hopping algorithm for the selective computation of the imaginary eigenvalues to be perturbed. Some examples of interconnect models are used to illustrate the performance of the proposed technique

Solving Eigenproblems with application in collapsible channel flows

Collapsible channel flows have been attracting the interest of many researchers, because of the physiological applications in the cardiovascular system, the respiratory system and urinary system. The linear stability analysis of the collapsible channel flows in the Fluid-Beam Model can be finalized as a large sparse asymmetric generalized eigenvalue problem, where the stiffness matrix is sparse, asymmetric and nonsingular, and the mass matrix is sparse, asymmetric and singular. The dimensions of the both matrices can reach about ten thousand or more, and the traditional QZ Algorithm is so expensive for this size of eigenvalue problem, due to its large requirement of computational resources and the quite long elapsed time. Unlike the traditional direct methods, the projection methods are much more efficient for solving some specified eigenpairs of the large scale eigenvalue problems, because normally a small subspace is made use of, and the original eigenvalue problem is projected to this small subspace. With this projection, the size of the eigenvalue problem is reduced significantly, and then the small dimensional eigenvalue problem can be easily and rapidly worked out by employing a traditional solver. Combined with a restarting strategy, this can be used to solve large dimensional eigenvalue problem much more rapidly and precisely. So far as we know, the Implicitly Restarted Arnoldi iteration(IRA) is considered as one of the most effective asymmetric eigenvalue solvers. In order to improve the efficiency of linear stability analysis in collapsible channel flows, an IRA method is employed to the linear stability analysis of collapsible channel flows in FBM. A Frontal Solver, which is an efficient solver of large sparse linear system, is also used to replace the process of shift-and-invert transformation. After applying these two efficient solvers, the new eigenvalue solver of collapsible channel flows---Arnoldi method with a Frontal Solver(AR-F), not only gets rid of the restriction of memory storage, but also reduces the computational time observably. Some validating and testing work have been done to variety of meshes. The AR-F can solve the eigenvalues with largest real parts very quickly, and can also solve the large scale eigenvalue problems, which cannot be solved by the QZ Algorithm, whose results have been proved to be correct with the unsteady simulations. Compared with the traditional QZ Algorithm, not only a great deal of elapsed time is saved, but also the increasing rate of the operation numbers is dropped to $O(n)$ from $O(n^3)$ of QZ Algorithm. With the powerful AR-F, the stability problems of refined meshes in collapsible channel flows are no long a barrier to the study. So AR-F is used to solve the eigenvalue problems from two refined meshes of the two different boundary conditions(pressure-driven system and flow-driven system), and the two neutral curves obtained are both revised and extended. This is the first time that IRA is made use of in the problem of fluid-structure interaction, and this is also a critical footstone to adopt a three dimensional model over FBM. Recently, the energy analysis and the energetics are the centre of research in collapsible channel flow. Because the linear stability analysis is much more accurate and faster than the unsteady simulation, the energy solutions from eigenpairs are also achieved in this thesis. The energy analysis with eigenpairs has its own advantages: the accuracy, the timing, the division, any mode and any point. In order to analyze the energy from eigenpairs much more clearly, the energy results with different initial solutions are presented first, then the energy solutions with eigenpairs are validated with those presented by Liu et al. in the pressure-driven system. By using the energy analysis with eigenpairs, much more energy results in flow-dirven system are obtained and analyzed

A short guide to exponential Krylov subspace time integration for Maxwell's equations

The exponential time integration, i.e., time integration which involves the matrix exponential, is an attractive tool for solving Maxwell’s equations in time. However, its application in practice often requires a substantial knowl-edge of numerical linear algebra algorithms, in particular, of the Krylov subspace methods. This note provides a brief guide on how to apply ex-ponential Krylov subspace time integration in practice. Although we con-sider Maxwell’s equations, the guide can readily be used for other similar time-dependent problems. In particular, we discuss in detail the Arnoldi shift-and-invert method combined with recently introduced residual-based stopping criterion. Two of the algorithms described here are available as MATLAB codes and can be downloaded from the websit