Parallelisation, and complex number support, as well as a large number Including support for a wide range of cell types and elements, memory In 2018, work started on FEniCSx: the new version of the FEniCS library.įEniCSx has a number of major improvements over the legacy library, Latest version of FEniCSx. FEniCSx comes withĮxtensive documentation and numerous examples. Installation and documentationįEniCSx is available for a range of platforms (Linux, Mac, Windows).Ĭhoose between Docker containers, binary packages, Spack packages and The solver was initially developed on aĭesktop computer for a small scale problem, and the same code was thenĭeployed on a supercomputer using over 24,000 parallel processes. The finiteĮlement system of linear equations comprises more than \(3.3 \timesġ0^9\) degrees of freedom. Thermomechanical FEniCSx simulation of a turbocharger. The figure shows the von Mises stresses computed from a nonlinear On laptops and workstations, and the same code may then be deployed on This frameworkĪllows for rapid prototyping of finite element formulations and solvers Simple as calling mpirun -np 64 python script.py. Executing a FEniCSx script in parallel is as Mesh are also easily created with gmsh, hereĭefined by three spheres immersed in a 3D channel.Įach component of the FEniCSx platform has been fundamentally designedįor parallel processing. Vector-valued functions for the velocity and continuous piecewise linearįunctions for the pressure (Taylor-Hood). The above code snippet also shows how to define a suitable finiteĮlement function space, using continuous piecewise quadratic LinearProblem ( a, L, bcs, petsc_options = ) solver. TestFunctions ( W ) a = inner ( grad ( u ), grad ( v )) * dx - p * div ( v ) * dx + div ( u ) * q * dx L = inner ( f, v ) * dx # Compute solution FunctionSpace ( mesh, TH ) # Define variational problem
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