Welcome to Rockable’s documentation!

Rockable is a code, written in C++, implementing the classical discrete element method.

The specificities of the code are to handle:

  1. Sphero-polyhedral shapes

  2. Breakable interfaces

Note

It is designed and developed for academic use (which means that its source code is not publicly downloadable).

_images/RockableRocks.png

Credits

The code was initially developed by Vincent Richefeu, at Laboratoire 3SR, to model rockfalls and rock avalanches. This has been done through The PhD work of Stiven Cuervo and Bruna Garcia, but it actually started before in a code named DEMbox (no longer maintained).

Then, the breakable interfaces have been implemented during the PhD work of Marta Stasiak. A number of improvements have been added at that time thanks to intensive review with Gael Combe, Laboratoire 3SR.

New functionalities are being studied thanks to new collaborations of people from CEA, IATE and CNRS. For example, Lhassan Amarsid (CEA) is working on the introduction of periodic boundary conditions, and multi-processor computing with domain decomposition. Farhang Radjai and students, may introduce new breakable interfaces with energy-based criteria.

Here is the non-exhaustive list of involved people with their main mission:

Features

  • Particle Shapes: the code uses only one 3D shape: sphero-polyhedra or R-shapes. These shapes can be non-convex (with holes if necessary) and have rounded edges and corners (uniform radius per shape).

    Some other shapes are currently considered for special boundary shapes (sphere, cylinder…) and specifique loadings.

  • Boundary Conditions: any rigid element can be used to apply boundary conditions. It is possible to impose velocity, force, or moment component by component. Some predefined systems with servo-control are also available for complex loading conditions (e.g., loading cycles or controlled pressure).

    The possibility of applying tri-periodic loading to an assembly is implemented and currently in the testing phase.

  • Parallel Computation: currently, an OpenMP optimization using compilation flags has been implemented. However, the computational speedup is relatively low. Typically, 8 cores are needed to halve the simulation time (for a dense system with a large number of elements).

  • Documentation: there is little documentation, although efforts are being made to address this.

Contents: