LIGGGHTS

LIGGGHTS open source discrete element method particle simulation code. LIGGGHTS stands for LAMMPS improved for general granular and granular heat transfer simulations. LAMMPS is a classical molecular dynamics simulator. It is widely used in the field of Molecular Dynamics. Thanks to physical and algorithmic analogies, LAMMPS is a very good platform for DEM simulations. LAMMPS offers a GRANULAR package to perform these kind of simulations. LIGGGHTS aims to improve those capability with the goal to apply it to industrial applications. See http://www.liggghts.com/ for documentation.


References in zbMATH (referenced in 20 articles )

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  1. Davydzenka, Tsimur; Tahmasebi, Pejman: High-resolution fluid-particle interactions: a machine learning approach (2022)
  2. Shen, Zhihao; Wang, Gang; Huang, Duruo; Jin, Feng: A resolved CFD-dem coupling model for modeling two-phase fluids interaction with irregularly shaped particles (2022)
  3. Xu, Wenxiang; Zhang, Bin; Jia, Mingkun; Wang, Wei; Gong, Zheng; Jiang, Jinyang: Discrete element modeling of 3D irregular concave particles: transport properties of particle-reinforced composites considering particles and soft interphase effects (2022)
  4. Feng, Y. T.: An energy-conserving contact theory for discrete element modelling of arbitrarily shaped particles: contact volume based model and computational issues (2021)
  5. Tronci, Giovanni; Buffo, Antonio; Vanni, Marco; Marchisio, Daniele: Validation of the diffusion mixture model for the simulation of bubbly flows and implementation in OpenFOAM (2021)
  6. Xiong, Shuchun; Chen, Shunhua; Zang, Mengyan; Makoto, Tsubokura: Development of an unresolved CFD-DEM method for interaction simulations between large particles and fluids (2021)
  7. Yu, Tao; Zhao, Jidong: Semi-coupled resolved CFD-DEM simulation of powder-based selective laser melting for additive manufacturing (2021)
  8. Zhang, Pei; Dong, Yueshi; Galindo-Torres, S. A.; Scheuermann, A.; Li, Ling: Metaball based discrete element method for general shaped particles with round features (2021)
  9. Kildashti, Kamyar; Dong, Kejun; Samali, Bijan: An accurate geometric contact force model for super-quadric particles (2020)
  10. Andrew Abi-Mansour: PyGran: An object-oriented library for DEM simulation and analysis (2019) not zbMATH
  11. Wachs, Anthony: Particle-scale computational approaches to model dry and saturated granular flows of non-Brownian, non-cohesive, and non-spherical rigid bodies (2019)
  12. Chang, Xiaolin; Wang, Y. T.; Zhou, W.; Ma, Gang; Liu, J. Y.: The influence of rotational resistance on critical state of granular materials (2017)
  13. Kabanda, Patrick; Wang, Mingbo: Numerical simulation of barite sag in pipe and annular flow (2017)
  14. Seil, Philippe; Pirker, Stefan: LBDEMcoupling: open-source power for fluid-particle systems (2017)
  15. Blais, Bruno; Lassaigne, Manon; Goniva, Christoph; Fradette, Louis; Bertrand, François: Development of an unresolved CFD-DEM model for the flow of viscous suspensions and its application to solid-liquid mixing (2016)
  16. Wang, Kun; Sun, WaiChing: A semi-implicit discrete-continuum coupling method for porous media based on the effective stress principle at finite strain (2016)
  17. Blais, Bruno; Bertrand, François: On the use of the method of manufactured solutions for the verification of CFD codes for the volume-averaged Navier-Stokes equations (2015)
  18. Blais, Bruno; Tucny, Jean-Michel; Vidal, David; Bertrand, François: A conservative lattice Boltzmann model for the volume-averaged Navier-Stokes equations based on a novel collision operator (2015)
  19. Servin, M.; Wang, D.; Lacoursière, C.; Bodin, K.: Examining the smooth and nonsmooth discrete element approaches to granular matter (2014)
  20. Shan, Tong; Zhao, Jidong: A coupled CFD-DEM analysis of granular flow impacting on a water reservoir (2014)