KRAKEN

Fundamentals of the KRAKEN code. KRAKEN is an Eulerian hydrodynamics code capable of treating compressible nonviscous flow of several fluids in a two-dimensional (axially symmetric) region. In many respects it is reminiscent of the FLIC/PIC methods, although it is considerably different in detail. Both Lagrangian and advection (transport) phases of the problem are considered. The code has a straight-forward approach to differencing. The presently used version of the code is discussed; it is hoped that a more efficient version will soon be completed. (RWR)


References in zbMATH (referenced in 72 articles )

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  1. Gorges, Christian; Evrard, Fabien; van Wachem, Berend; Denner, Fabian: Reducing volume and shape errors in front tracking by divergence-preserving velocity interpolation and parabolic fit vertex positioning (2022)
  2. Kenamond, Mack; Kuzmin, Dmitri; Shashkov, Mikhail: A positivity-preserving and conservative intersection-distribution-based remapping algorithm for staggered ALE hydrodynamics on arbitrary meshes (2021)
  3. Larios-Cárdenas, Luis Ángel; Gibou, Frederic: A deep learning approach for the computation of curvature in the level-set method (2021)
  4. Liu, Shengping; Yong, Heng; Guo, Shaodong; Shen, Yiqing; Ni, Guoxi: An improved continuity-preserving interface reconstruction method for multi-material flow (2021)
  5. Després, Bruno; Jourdren, Hervé: Machine learning design of volume of fluid schemes for compressible flows (2020)
  6. Fagbemi, Samuel; Tahmasebi, Pejman; Piri, Mohammad: Elastocapillarity modeling of multiphase flow-induced solid deformation using volume of fluid method (2020)
  7. Lespagnol, Fabien; Dakin, Gautier: High order accurate schemes for Euler and Navier-Stokes equations on staggered Cartesian grids (2020)
  8. Marić, Tomislav; Kothe, Douglas B.; Bothe, Dieter: Unstructured un-split geometrical volume-of-fluid methods - a review (2020)
  9. Dakin, Gautier; Després, Bruno; Jaouen, Stéphane: High-order staggered schemes for compressible hydrodynamics. Weak consistency and numerical validation (2019)
  10. Gibou, Frederic; Hyde, David; Fedkiw, Ron: Sharp interface approaches and deep learning techniques for multiphase flows (2019)
  11. Malan, L. C.; Ling, Y.; Scardovelli, R.; Llor, A.; Zaleski, S.: Detailed numerical simulations of pore competition in idealized micro-spall using the VOF method (2019)
  12. Marboeuf, Alexis; Claisse, Alexandra; Le Tallec, Patrick: Conservative and entropy controlled remap for multi-material ALE simulations with space-staggered schemes (2019)
  13. Barlow, Andrew; Klima, Matej; Shashkov, Mikhail: Constrained optimization framework for interface-aware sub-scale dynamics models for voids closure in Lagrangian hydrodynamics (2018)
  14. Braeunig, Jean-Philippe; Loubère, Raphaël; Motte, Renaud; Peybernes, Mathieu; Poncet, Raphaël: A posteriori limiting for 2D Lagrange plus remap schemes solving the hydrodynamics system of equations (2018)
  15. Gibou, Frederic; Fedkiw, Ronald; Osher, Stanley: A review of level-set methods and some recent applications (2018)
  16. Marić, Tomislav; Marschall, Holger; Bothe, Dieter: An enhanced un-split face-vertex flux-based VoF method (2018)
  17. Mostafaiyan, Mehdi; Wießner, Sven; Heinrich, Gert; Hosseini, Mahdi Salami; Domurath, Jan; Khonakdar, Hossein Ali: Application of local least squares finite element method (LLSFEM) in the interface capturing of two-phase flow systems (2018)
  18. Owkes, Mark; Cauble, Eric; Senecal, Jacob; Currie, Robert A.: Importance of curvature evaluation scale for predictive simulations of dynamic gas-liquid interfaces (2018)
  19. Williams, R. J. R.: Sub-grid properties and artificial viscous stresses in staggered-mesh schemes (2018)
  20. Evrard, Fabien; Denner, Fabian; van Wachem, Berend: Estimation of curvature from volume fractions using parabolic reconstruction on two-dimensional unstructured meshes (2017)

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