![]() ![]() Some of the data was compiled by others: e.g., the Rwandan government, the International Criminal Tribunal on Rwanda (ICTR), Human Rights Watch, African Rights and Ibuka. Some of the data collection was conducted by ourselves (e.g., focus groups of civilians, interviews with civilians as well as genocidaires and a survey in Butare). ![]() Still other sources interviewed perpetrators, asking them what they did and why. Other sources interviewed/surveyed bystanders, asking them what they saw as well as who was lost and how. Some sources directly interviewed/surveyed victims and survivors in Rwanda or refugee camps outside of it, asking them exactly what they lived through. To shed some light on these issues, our research consulted numerous sources both inside as well as outside Rwanda. What we do not know as well is exactly who was engaged in what activity at what time and at what place. What we know is that there was a significant amount of violence. This approach allows users to specify exactly their modelling requirements and provides transparency.For approximately 14 years, GenoDynamics has been attempting to understand exactly who did what to whom in Rwanda during 1994 with an emphasis on evidenced-based research. Simulation chronology is also fully exposed and the user is expected to explicitly specify when events should occur. For example, the user may describe a viscosity which is piecewise constant, temperature dependent, or visco-elasto-plastic in behaviour. At the centre of this design is the Function class, which aims to provide a natural interface from which users can describe their problem mathematics. Underworld2 provides a minimal set of highly flexible core functionality, with user domain concerns left to the users themselves to construct. The Jupyter Notebook front end provisioned across cloud facilities has also proven to be an appropriate environment for the use of Underworld as a teaching tool for solid Earth geoscience. This hybrid approach allows Underworld to obtain accurate velocity solutions (on the mesh) for a given material configuration, while simultaneously ensuring the accurate time advection of material interfaces and history information (using particle swarms).Ī primary aim of Underworld2 is to enable rapid prototyping of models, and to this end embedded visualisation (LavaVu) and modern development environments such as Jupyter Notebooks have been embraced, with the latter also providing a path to cloud computing amenability. In Underworld, the finite element mesh can be static or dynamic, but it is not constrained to move in lock-step with the evolving geometry of the fluid. Underworld2 provides capacity for modelling 2- and 3-dimensional geodynamics processes, utilising a particle-in-cell finite element approach for solution to Stokes flow type configurations. For scalability across multiprocessor platforms, MPI (Message Passing Interface) is leveraged, and for performant operation all heavy computations are executed within a statically typed layer. ![]() The API also provides the tools required for inline analysis and data management. Primarily the API consists of a set of Python classes from which numerical geodynamics models may be constructed. Underworld2 is a Python API (Application Programming Interface) which provides functionality for the modelling of geodynamics processes, and is designed to work (almost) seamlessly across PC, cloud and HPC infrastructure.
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