Coder Social home page Coder Social logo

ngsxfem-jupyter's Introduction

GitHub Workflow Status GitHub release (latest by date) jossstatus

PyPI PyPI - Implementation PyPI - Downloads

Docker Pulls badge

lite-badge

Documentation

A preliminary collection of documentation (demos, tutorials, mini API) can be found here. A simple doxygen collection of NGSolve, ngsxfem and ngstrefftz C++ API can be found here.

About ngsxfem

ngsxfem is an add-on library to the finite element package Netgen/NGSolve which enables the use of unfitted finite element technologies known as XFEM, CutFEM, TraceFEM, Finite Cell, ... . ngsxfem is an academic software. Its primary intention is to facilitate the development and validation of new numerical methods for partial differential equations.

The features of ngsxfem

The main features of ngsxfem are:

  • Tools to work on a subset of the triangulation, the "active mesh" only
  • Numerical integration on geometries that are (implicitly) described through level set functions.
  • Higher order representation of level set geometries
  • Space-Time Finite Elements for the treatment of moving domain problems
  • All these features combined with the usual flexibility and power of NGSolve.

ngsxfem has been used in a variety of applications. In the document doc/feature-details.md (see also compiled pdf ) more details on the features is given and in doc/literature.md (see also literature ) an overview of the scientific literature where ngsxfem is used is provided.

Not all features of ngsxfem and NGSolve can directly be combined. Here is an overview of ngsxfem and NGSolve features and if they can directly be combined:

Features ⇲ CFE XFE DG Iso MLS ST Gh Ag Hex Tet MPI
CFE: CutFEM form. / / y y y y y y y y y
XFE: XFEM formulation / / y y n n y n y y y
DG: Discont. Galerkin y y / y n y y y y y n
Iso: isoparametric map y y y / n y y y y y y
MLS: multiple level set y n n n / n y y n y y
ST: space-time FEM y n y y n / y n y y y
Gh: Ghost penalty y y y y y y / / y y n
Ag: Agg. FEM y n y y y n / / y y n
Hex: quads / hexes y y y y n y y y / / y
Tet: trigs./tets y y y y y y y y / / y
MPI: MPI y y n y y y n n y y /

Some of the nos are work in progress and some have not been considered so far. If you need a certain combination to work, please contact us and we will see what we can do.

Examples and Documentation

We provide two main sources with which to learn how to use ngsxfem:

  • At https://github.com/ngsxfem/ngsxfem-jupyter you can find tutorial-style jupyter notebooks for ngsxfem. These explain the core functionalities and usage of the tools provided by ngsxfem. You can run those tutorials interactively (without the need of a local installation) through binder.
  • In the demos-directory we provide several examples that demonstrate the usage of ngsxfem features. See demos/README.md for details.

Installation

We provide installation instructions for building/installing through pip and building/installing from sources in INSTALLATION.md. Further, a docker image is available which can be used to run ngsxfem through docker.

List of contributing authors

Major contributions:

  • Christoph Lehrenfeld (main author)
  • Fabian Heimann (cut integration, space-time, AggFEM)
  • Henry von Wahl (multiple levelsets, mac support, AggFEM)
  • Janosch Preuss (space-time)
  • Thomas Ludescher (multigrid)
  • Paul Stocker (CI, docu, builds, AggFEM)

Additional contributions:

  • Pedro Costa Klein (CI, docu)
  • Maximilian Zienecker (SIMD, CI)

Community guidelines

If you observe any problems with the software / examples / documentation / installation or want to contribute, you can get in touch with us through either:

Citing

If you use ngsxfem for academic work, please consider citing our publication:

C. Lehrenfeld, F. Heimann, J. Preuß and H. von Wahl
ngsxfem: Add-on to NGSolve for geometrically unfitted finite element discretizations
Journal of Open Source Software, 6(64), 3237,
https://doi.org/10.21105/joss.03237

ngsxfem-jupyter's People

Contributors

fabianheimann avatar hvonwah avatar janoschpreuss avatar schruste avatar timvanbeeck avatar ymlou avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.