It assumes that the user knows what he is doing and does not verify the validity of the model parameters (`toughio` does verify the functional arguments). ![]() Besides, `toughio` is designed to be just a TOUGH input and output file reader/writer. Abaqus, FLAC3D, Gmsh, LaGriT) to generate the mesh by importing and converting it to a TOUGH mesh, which also conveniently facilitates the coupling of TOUGH with any other simulator that also supports the same mesh formats. On the other hand, although it provides basic meshing features, `toughio` mostly relies on common third-party softwares (e.g. It also checks that the model parameters are valid to ensure that a TOUGH simulation runs smoothly. On the one hand, a PyTOUGH mesh is represented as a MULGRAPH geometry where elements can be unstructured horizontally but only layered vertically. `toughio` and PyTOUGH share the same objectives, yet with different approaches and philosophies. Currently, to the best of our knowledge, only more » PyTOUGH offers an exhaustive number of features to carry out a complete TOUGH simulation using a scripting language. Although its primary target is the latest version TOUGH3, `toughio` can also be used to read/write TOUGH2 input/output files. `toughio` is a lightweight, object-oriented and vectorized Python library that aims to provide user-friendly routines to facilitate pre- and post-processing of a TOUGH simulation. TOUGH is a widely used general purpose numerical simulator designed for fluid and heat flows of multiphase, multicomponent fluid mixtures in porous and fractured media, which has been applied to many real-world problems such as underground geological storage, geothermal reservoir engineering or nuclear waste disposal, to name a few. (5) MeshConv, a mesh file converter that can be used to convert 3D tetrahedron meshes from and to either of the following formats: Gmsh,, Netgen,, ExodusII,, HyperMesh. (4) UnitTest, a unit test harness, running hundreds of tests per second, capable of testing serial, synchronous, and asynchronous functions. (3) RNGTest, a test harness to subject random number generators to stringent statistical tests enabling quantitative ranking with respect to their quality and computational cost. Using the NS-AMR problem we plan to explore how to scale such high-load-imbalance simulations, representative of large production multiphysics codes, to very large problems on very large computers using an asynchronous runtime system. Two planned new features of Inciter, compared to the previous release (LA-CC-16-015), to be implemented in 2017, are (a) a simple Navier-Stokes solver for ideal single-material compressible gases, and (b) solution-adaptive mesh refinement (AMR), which enables dynamically concentrating compute resources to regions with interesting physics. Inciter is used to research asynchronous mesh-based algorithms and to experiment with coupling asynchronous to bulk-synchronous parallel code. (2) Inciter, more » an overdecomposition-aware finite element field solver for partial differential equations using 3D unstructured grids. It allows the estimation of arbitrary coupled statistics and probability density functions and is currently used for the design of statistical moment approximations for multiple mixing materials in variable-density turbulence. It is a mathematical tool to analyze and design the behavior of stochastic differential equations. Currently, Quinoa consists of the following tools: (1) Walker, a numerical integrator for systems of stochastic differential equations in time. At this time it remains a test-bed to experiment with various algorithms using fully asynchronous runtime systems. ![]() Quinoa is a set of computational tools that enables research and numerical analysis in fluid dynamics.
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