2017
DOI: 10.1016/j.jcp.2017.04.076
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Implicit mesh discontinuous Galerkin methods and interfacial gauge methods for high-order accurate interface dynamics, with applications to surface tension dynamics, rigid body fluid–structure interaction, and free surface flow: Part I

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Cited by 69 publications
(99 citation statements)
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“…Numerous numerical approaches also exists, for example using Lagrange multipliers [12], finite cell methods [13,14,15], immersed interface methods [16], the s-version of the finite element method [17,18] and XFEM [19,20,21] to name a few. Discontinuous Galerkin methods have also successfully been used [22,23,24,25], as well as variants using local enrichments [26,27,28]. There are also substantial and important works in domain decomposition methods see for example [29,30] or [31,32] and the references therein.…”
Section: Related Workmentioning
confidence: 99%
“…Numerous numerical approaches also exists, for example using Lagrange multipliers [12], finite cell methods [13,14,15], immersed interface methods [16], the s-version of the finite element method [17,18] and XFEM [19,20,21] to name a few. Discontinuous Galerkin methods have also successfully been used [22,23,24,25], as well as variants using local enrichments [26,27,28]. There are also substantial and important works in domain decomposition methods see for example [29,30] or [31,32] and the references therein.…”
Section: Related Workmentioning
confidence: 99%
“…For the numerical tests in this work we have used a high-order accurate discontinuous Galerkin (DG) spatial discretization. The methodology and algorithms employed are essentially identical to those detailed in [60,61], and as such, only a brief description is provided here.…”
Section: Spatial Discretizationmentioning
confidence: 99%
“…Briefly, the scheme can be stated as formulating a discrete gradient operator G (using a numerical flux which upwinds from the "left" on internal mesh faces) such that the accompanying discrete divergence operator (using numerical fluxes which upwind from the "right") is the adjoint of G. The primary component of the resulting discrete Laplacian operator then has the form of G G where G is the adjoint of G; boundary data enters in the form of source terms, derived from modifications to the numerical fluxes on boundary mesh faces taking into account Dirichlet and Neumann boundary conditions. In addition, following the discussion in [60], penalty stabilization parameters are included to ensure well-posedness of the discrete system. Ultimately, one obtains a symmetric positive definite linear system for the viscous solve, and a symmetric positive semidefinite linear system for the projection operator.…”
Section: Spatial Discretizationmentioning
confidence: 99%
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“…These could include free-volume based models of BMGs [46], plasticity models based on the random first-order transition theory of the glass transition [47], hypo-elastic materials [48,49,50], geophysical models [51,52], and rate-independent plasticity models [53,54,55,56]. We also emphasize that Chorin's projection method represents a first step towards more complex projection-based algorithms such as gauge methods [57,58,59] and pressure-Poisson methods [60,61], and that we have laid the groundwork here to generalize these algorithms to the case of hypo-elastoplasticity.…”
Section: Introductionmentioning
confidence: 99%