ENZO

Enzo is a community-developed adaptive mesh refinement simulation code, designed for rich, multi-physics hydrodynamic astrophysical calculations. Enzo is freely available, developed in the open, with a strong support structure for assistance. Simulations conducted with Enzo have been featured in numerous refereed journal articles, and it is capable of running on computers from laptop to Top500.


References in zbMATH (referenced in 14 articles )

Showing results 1 to 14 of 14.
Sorted by year (citations)

  1. Lopes, Müller Moreira; Domingues, Margarete Oliveira; Deiterding, Ralf; Mendes, Odim: Magnetohydrodynamics adaptive solvers in the AMROC framework for space plasma applications (2021)
  2. A. Brandenburg, A. Johansen, P. A. Bourdin, W. Dobler, W. Lyra, M. Rheinhardt, S. Bingert, N. E. L. Haugen, A. Mee, F. Gent, N. Babkovskaia, C.-C. Yang, T. Heinemann, B. Dintrans, D. Mitra, S. Candelaresi, J. Warnecke, P. J. Käpylä, A. Schreiber, P. Chatterjee, M. J. Käpylä, X.-Y. Li, J. Krüger, J. R. Aarnes, G. R. Sarson, J. S. Oishi, J. Schober, R. Plasson, C. Sandin, E. Karchniwy, L. F. S. Rodrigues, A. Hubbard, G. Guerrero, A. Snodin, I. R. Losada, J. Pekkilä, C. Qian (The Pencil Code Collaboration): The Pencil Code, a modular MPI code for partial differential equations and particles: multipurpose and multiuser-maintained (2020) arXiv
  3. Dey, Tamal K.; Wang, Jiayuan; Wang, Yusu: Graph reconstruction by discrete Morse theory (2018)
  4. Schornbaum, Florian; Rüde, Ulrich: Extreme-scale block-structured adaptive mesh refinement (2018)
  5. Kidder, Lawrence E.; Field, Scott E.; Foucart, Francois; Schnetter, Erik; Teukolsky, Saul A.; Bohn, Andy; Deppe, Nils; Diener, Peter; Hébert, François; Lippuner, Jonas; Miller, Jonah; Ott, Christian D.; Scheel, Mark A.; Vincent, Trevor: SpECTRE: A task-based discontinuous Galerkin code for relativistic astrophysics (2017)
  6. Lee, Dongwook; Faller, Hugues; Reyes, Adam: The piecewise cubic method (PCM) for computational fluid dynamics (2017)
  7. Hatori, Tomoharu; Ito, Atsushi M.; Nunami, Masanori; Usui, Hideyuki; Miura, Hideaki: Level-by-level artificial viscosity and visualization for MHD simulation with adaptive mesh refinement (2016)
  8. Kulikov, Igor; Vorobyov, Eduard: Using the PPML approach for constructing a low-dissipation, operator-splitting scheme for numerical simulations of hydrodynamic flows (2016)
  9. Razi, Mani; Attar, Peter; Vedula, Prakash: Numerical solution of multidimensional hyperbolic PDEs using defect correction on adaptive grids (2016)
  10. Sousbie, Thierry; Colombi, Stéphane: \textttColDICE: A parallel Vlasov-Poisson solver using moving adaptive simplicial tessellation (2016)
  11. Powell, Devon; Abel, Tom: An exact general remeshing scheme applied to physically conservative voxelization (2015)
  12. Sætra, Martin L.; Brodtkorb, André R.; Lie, Knut-Andreas: Efficient GPU-implementation of adaptive mesh refinement for the shallow-water equations (2015)
  13. Schmidt, Wolfram: Numerical modelling of astrophysical turbulence (2014)
  14. Reynolds, Daniel R.; Hayes, John C.; Paschos, Pascal; Norman, Michael L.: Self-consistent solution of cosmological radiation-hydrodynamics and chemical ionization (2009)