Past Numerical Analysis Group Internal Seminar

Today
14:30
Niall Bootland
Abstract

We explore the use of applying multiple preconditioners for solving linear systems arising in simulations of incompressible two-phase flow. In particular, we use a selective MPGMRES algorithm, for which the search space grows linearly throughout the iterative solver, and block preconditioners based on Schur complement approximations

  • Numerical Analysis Group Internal Seminar
Today
14:00
Ellya Kawecki
Abstract

We introduce a discontinuous Galerkin finite element method (DGFEM) for Hamilton–Jacobi–Bellman equations on piecewise curved domains, and prove that the method is consistent, stable, and produces optimal convergence rates. Upon utilising a long standing result due to N. Krylov, we may characterise the Monge–Ampère equation as a HJB equation; in two dimensions, this HJB equation can be characterised further as uniformly elliptic HJB equation, allowing for the application of the DGFEM

  • Numerical Analysis Group Internal Seminar
16 January 2018
14:30
Ozzy Nilsen
Abstract

We propose a new parameter estimation technique for SDEs, based on the inverse problem of finding a forward operator describing the evolution of temporal data. Nonlinear dynamical systems on a state-space can be lifted to linear dynamical systems on spaces of higher, often infinite, dimension. Recently, much work has gone into approximating these higher-dimensional systems with linear operators calculated from data, using what is called Dynamic Mode Decomposition (DMD). For SDEs, this linear system is given by a second-order differential operator, which we can quickly calculate and compare to the DMD operator.

  • Numerical Analysis Group Internal Seminar
16 January 2018
14:00
Miles Caddick
Abstract

In 2016-17, Fjordholm, Kappeli, Mishra and Tadmor developed a numerical method by which one could compute measure-valued solutions to systems of hyperbolic conservation laws with either measure-valued or deterministic initial data. In this talk I will discuss the ideas behind this method, and discuss how it can be adapted to systems of quasi-linear parabolic PDEs whose nonlinearity fails to satisfy a monotonicity condition.

  • Numerical Analysis Group Internal Seminar
28 November 2017
14:30
Charles Dapogny
Abstract

The purpose of this work is to introduce a new constraint functional for shape optimization problems, which enforces the constructibility by means of additive manufacturing processes, and helps in preventing the appearance of overhang features - large regions hanging over void which are notoriously difficult to assemble using such technologies. The proposed constraint relies on a simplified model for the construction process: it involves a continuum of shapes, namely the intermediate shapes corresponding to the stages of the construction process where the total, final shape is erected only up to a certain level. The shape differentiability of this constraint functional is analyzed - which is not a standard issue because of its peculiar structure. Several numerical strategies and examples are then presented. This is a joint work with G. Allaire, R. Estevez, A. Faure and G. Michailidis.

  • Numerical Analysis Group Internal Seminar
21 November 2017
14:30
Andrew Thompson
Abstract

I will describe a novel algorithm for computing the Walsh Hadamard Transform (WHT) which consists entirely of Haar wavelet transforms. The algorithm shares precisely the same serial complexity as the popular divide-and-conquer algorithm for the WHT. There is also a natural way to parallelize the algorithm which appears to have a number of attractive features.

  • Numerical Analysis Group Internal Seminar
21 November 2017
14:00
Joseph Field
Abstract

Medical imaging is a key diagnostic tool, and is paramount for disease detection and for patient monitoring during ongoing care. Often, to reduce the amount of radiation that a patient is subjected to, there is a strong incentive to consider image reconstruction from incomplete sets of measurements, and so the imaging process is formulated as a compressed sensing problem.

In this talk, we will focus on compressed sensing for digital tomosynthesis (DTS), in which three-dimensional images are reconstructed from a set of two-dimensional X-ray projections. We first discuss a reconstruction approach for static bodies, with a particular interest in the choice of basis for the image representation. We will then focus on the need for accurate image reconstructions when the body of interest is not stationary, but is undergoing simple motion, discussing two different approaches for tackling this dynamic problem.

  • Numerical Analysis Group Internal Seminar
14 November 2017
14:30
Florian Wechsung
Abstract

The design of shapes that are in some sense optimal is a task faced by engineers in a wide range of disciplines. In shape optimisation one aims to improve a given initial shape by iteratively deforming it - if the shape is represented by a mesh, then this means that the mesh has to deformed. This is a delicate problem as overlapping or highly stretched meshes lead to poor accuracy of numerical methods.

In the presented work we consider a novel mesh deformation method motivated by the Riemannian mapping theorem and based on conformal mappings.

  • Numerical Analysis Group Internal Seminar
14 November 2017
14:00
Federico Danieli
Abstract

Time parallelisation techniques provide an additional direction for the parallelisation of the solution of time-dependent PDEs or of systems of ODEs. In particular, the Parareal algorithm has imposed itself as the canonical choice to achieve parallelisation in time, also because of its simplicity and flexibility. The algorithm works by splitting the time domain in chunks, and iteratively alternating a prediction step (parallel), in which a "fine" solver is employed to achieve a high-accuracy solution within each chunk, to a correction step (serial) where a "coarse" solver is used to quickly propagate the update between the chunks. However, the stability of the method has proven to be highly sensitive to the choice of fine and coarse solver, even more so when applied to chaotic systems or advection-dominated problems.


In this presentation, an alternative formulation of Parareal is discussed. This aims to conduct the update by estimating directly the sensitivity of the solution of the integration with respect to the initial conditions, thus eliminating altogether the necessity of choosing the most apt coarse solver, and potentially boosting its convergence properties.

 

  • Numerical Analysis Group Internal Seminar

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