20 research outputs found

    Contribution to the study of efficient iterative methods for the numerical solution of partial differential equations

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    Multigrid and domain decomposition methods provide efficient algorithms for the numerical solution of partial differential equations arising in the modelling of many applications in Computational Science and Engineering. This manuscript covers certain aspects of modern iterative solution methods for the solution of large-scale problems issued from the discretization of partial differential equations. More specifically, we focus on geometric multigrid methods, non-overlapping substructuring methods and flexible Krylov subspace methods with a particular emphasis on their combination. Firstly, the combination of multigrid and Krylov subspace methods is investigated on a linear partial differential equation modelling wave propagation in heterogeneous media. Secondly, we focus on non-overlapping domain decomposition methods for a specific finite element discretization known as the hp finite element, where unrefinement/refinement is allowed both by decreasing/increasing the step size h or by decreasing/increasing the polynomial degree p of the approximation on each element. Results on condition number bounds for the domain decomposition preconditioned operators are given and illustrated by numerical results on academic problems in two and three dimensions. Thirdly, we review recent advances related to a class of Krylov subspace methods allowing variable preconditioning. We examine in detail flexible Krylov subspace methods including augmentation and/or spectral deflation, where deflation aims at capturing approximate invariant subspace information. We also present flexible Krylov subspace methods for the solution of linear systems with multiple right-hand sides given simultaneously. The efficiency of the numerical methods is demonstrated on challenging applications in seismics requiring the solution of huge linear systems of equations with multiple right-hand sides on parallel distributed memory computers. Finally, we expose current and future prospectives towards the design of efficient algorithms on extreme scale machines for the solution of problems coming from the discretization of partial differential equations

    Least-squares methods for computational electromagnetics

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    The modeling of electromagnetic phenomena described by the Maxwell's equations is of critical importance in many practical applications. The numerical simulation of these equations is challenging and much more involved than initially believed. Consequently, many discretization techniques, most of them quite complicated, have been proposed. In this dissertation, we present and analyze a new methodology for approximation of the time-harmonic Maxwell's equations. It is an extension of the negative-norm least-squares finite element approach which has been applied successfully to a variety of other problems. The main advantages of our method are that it uses simple, piecewise polynomial, finite element spaces, while giving quasi-optimal approximation, even for solutions with low regularity (such as the ones found in practical applications). The numerical solution can be efficiently computed using standard and well-known tools, such as iterative methods and eigensolvers for symmetric and positive definite systems (e.g. PCG and LOBPCG) and reconditioners for second-order problems (e.g. Multigrid). Additionally, approximation of varying polynomial degrees is allowed and spurious eigenmodes are provably avoided. We consider the following problems related to the Maxwell's equations in the frequency domain: the magnetostatic problem, the electrostatic problem, the eigenvalue problem and the full time-harmonic system. For each of these problems, we present a natural (very) weak variational formulation assuming minimal regularity of the solution. In each case, we prove error estimates for the approximation with two different discrete least-squares methods. We also show how to deal with problems posed on domains that are multiply connected or have multiple boundary components. Besides the theoretical analysis of the methods, the dissertation provides various numerical results in two and three dimensions that illustrate and support the theory

    Spectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018

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    This open access book features a selection of high-quality papers from the presentations at the International Conference on Spectral and High-Order Methods 2018, offering an overview of the depth and breadth of the activities within this important research area. The carefully reviewed papers provide a snapshot of the state of the art, while the extensive bibliography helps initiate new research directions

    Boundary layer instabilities due to surface irregularities: a harmonic Navier-Stokes approach

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    Maintaining laminar flow and delaying transition to turbulence on aircraft wings reduces friction drag and hence fuel consumption for an improved ecological footprint. Nonetheless, widespread models of disturbance growth in boundary layers discard important transition stages and are inadequate to incorporate the effect of surface irregularities causing rapid variations in the underlying steady flow. This thesis applies global or Harmonic Navier-Stokes (HNS) methods to quantify the growth of instabilities in shear flows with two inhomogeneous spatial directions. Such methods deliver greater fidelity than the standard Parabolised Stability Equations (PSE). This work presents an efficient parallel computational framework to solve linear and non-linear HNS problems. We use BiGlobal analysis to investigate the existence of temporally unstable modes on a flat plate with smooth indentations featuring laminar separation bubbles (LSBs). Then, for the first time, it is applied to a swept-wing boundary layer featuring Backward- and Forward-Facing Steps (BFSs and FFSs). Localised unstable modes are identified for step heights exceeding the local boundary-layer displacement thickness of the clean geometry. BFSs are found to be more destabilising than equivalent FFSs, especially in the presence of the LSB formed behind the infinite-swept BFS. Next, we introduce the non-linear HNS method as an improvement over the non-linear PSE, able to model receptivity and non-linear mode interaction at a fraction of the cost of Direct Numerical Simulation. The method can model flow destabilisation scenarios on swept wings exhibiting surface features and holds the potential for accurate transition prediction. Its performance is assessed in the case of a Tollmien-Schlichting wave interacting with a cylindrical roughness located on a nearly flat aerofoil section. Finally, we consider crossflow disturbances generated by placing Discrete Roughness Elements (DRE) at the leading edge of a swept wing and follow their non-linear development up to a strongly saturated state. Non-linear receptivity effects are found to arise with increasing DRE heights.Open Acces

    Generalized averaged Gaussian quadrature and applications

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    A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

    MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

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    Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described
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