Abstract

In this paper, an efficient, high-order accurate, level set reinitialisation method is proposed, based on the elliptic reinitialisation method (Basting and Kuzmin, 2013 [1]), which is discretised spatially using the discontinuous Galerkin (DG) symmetric interior penalty method (SIPG). In order to achieve this a number of improvements have been made to the elliptic reinitialisation method including; reformulation of the underlying minimisation problem driving the solution; adoption of a Lagrange multiplier approach for enforcing a Dirichlet boundary condition on the implicit level set interface; and adoption of a narrow band approach. Numerical examples confirm the high-order accuracy of the resultant method by demonstrating experimental orders of convergence congruent with optimal convergence rates for the SIPG method, that is hp+1 and hp in the L2 and DG norms respectively. Furthermore, the degree to which the level set function satisfies the Eikonal equation improves proportionally to hp, and the often ignored homogeneous Dirichlet boundary condition on the interface is shown to be satisfied accurately with a rate of convergence of at least h2 for all polynomial orders.

Highlights

  • The level set method is a popular technique used for representing and tracking evolving interfaces in computer simulations which has found use across a wide range of areas interesting to computational physicists and engineers

  • The work presented in this paper provides a solution to the elliptic reinitialisation problem using a discontinuous Galerkin (DG) method for the spatial discretisation

  • A practical method for level set reinitialisation using an SIPG discretisation has been presented, based on the elliptic reinitialisation method originally presented by Basting and Kuzmin, [1]

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Summary

Introduction

The level set method is a popular technique used for representing and tracking evolving interfaces in computer simulations which has found use across a wide range of areas interesting to computational physicists and engineers. Mousavi [19] found that it was 135 possible to create a method which was practically viable by utilising a severe time step restriction, a sufficiently smoothed signum function and including an artificial viscosity term Such a solution to the reinitialisation problem is less than ideal as a large number of iterations are required to return a signed distance function everywhere in the domain, which could be considered prohibitively expensive. A similar solution was presented by Li et al [23] whereby the level set evolution problem was 155 reframed as an optimisation problem including an energy driving the evolution and a penalty term restricting deviation from a signed distance function This lead to a formulation of the evolution equation which could be stated as.

Discontinuous Galerkin elliptic level set reinitialisation
Symmetric interior penalty discontinuous Galerkin method preliminaries
Numerical Examples
Multiple arbitrary interfaces
Conclusions
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