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TrixiShallowWater

Shallow water simulations with Trixi.jl

https://github.com/trixi-framework/trixishallowwater.jl

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
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    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
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    DOI references
    Found 4 DOI reference(s) in README
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    Academic publication links
    Links to: zenodo.org
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    Scientific vocabulary similarity
    Low similarity (16.5%) to scientific vocabulary

Keywords from Contributors

geometry mesh high-order-methods finite-elements pde interactive projections polygons pinns ode
Last synced: 7 months ago · JSON representation

Repository

Shallow water simulations with Trixi.jl

Basic Info
Statistics
  • Stars: 21
  • Watchers: 11
  • Forks: 9
  • Open Issues: 7
  • Releases: 2
Created almost 3 years ago · Last pushed 8 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Security Authors Zenodo

README.md

TrixiShallowWater.jl

Stable Dev Slack Build Status Coverage Coverage License: MIT DOI

TrixiShallowWater.jl is a numerical simulation package focused on solving shallow water equations with the discontinuous Galerkin method and written in Julia. The package builds on the numerical simulation framework for conservation laws Trixi.jl and provides several specialized models and features specific for shallow water applications. Below is a short summary of the available features:

  • 1D and 2D simulations on line/quad meshes
    • Cartesian and curvilinear meshes
    • Conforming and non-conforming meshes
    • Hierarchical quadtree meshes with adaptive mesh refinement
  • High-order accuracy in space and time
  • Shallow water capabilities
    • Wetting and drying
    • Multi-layer flows
    • Sediment transport via an Exner model

Installation

If you have not yet installed Julia, please follow the instructions for your operating system. TrixiShallowWater.jl works with Julia v1.10 and newer. We recommend using the latest stable release of Julia.

For users

TrixiShallowWater.jl and its related tools are registered Julia packages. Hence, you can install TrixiShallowWater.jl, the numerical solver framework Trixi.jl, visualization tools Trixi2Vtk.jl, and Plots.jl as well as relevant time integration sub-packages of OrdinaryDiffEq.jl, by executing the following commands in the Julia REPL: ```julia julia> using Pkg

julia> Pkg.add(["TrixiShallowWater", "Trixi", "Trixi2Vtk", "Plots", "OrdinaryDiffEqLowStorageRK", "OrdinaryDiffEqSSPRK"]) `` You can copy and paste all commands to the REPL *including* the leading julia>` prompts - they will automatically be stripped away by Julia. The package OrdinaryDiffEq.jl and its sub-packages provide time integration schemes used by TrixiShallowWater.jl, while Plots.jl can be used to directly visualize TrixiShallowWater.jl's results from the REPL.

For developers

If you plan on editing TrixiShallowWater.jl itself, you can download TrixiShallowWater.jl locally and use the code from the cloned directory: bash git clone git@github.com:trixi-framework/TrixiShallowWater.jl.git cd TrixiShallowWater.jl mkdir run cd run julia --project=. -e 'using Pkg; Pkg.develop(PackageSpec(path=".."))' # Install local TrixiShallowWater.jl clone julia --project=. -e 'using Pkg; Pkg.add(["Trixi", "OrdinaryDiffEqLowStorageRK", "OrdinaryDiffEqSSPRK", "Trixi2Vtk", "Plots"])' # Install additional packages Note that the postprocessing tools Trixi2Vtk.jl and Plots.jl are optional and can be omitted.

If you installed TrixiShallowWater.jl this way, you always have to start Julia with the --project flag set to your run directory, e.g., bash julia --project=. if already inside the run directory. Further details, of how to develop TrixiShallowWater.jl together with a local clone Trixi.jl, can be found in the Development section of the documentation.

Referencing

You can directly refer to TrixiShallowWater.jl as

bibtex @misc{winters2025trixi, title={{TrixiShallowWater.jl}: {S}hallow water simulations with {T}rixi.jl}, author={Winters, Andrew R and Ersing, Patrick and Ranocha, Hendrik and Schlottke-Lakemper, Michael}, year={2025}, howpublished={\url{https://github.com/trixi-framework/TrixiShallowWater.jl}}, doi={10.5281/zenodo.15206520} }

Authors

TrixiShallowWater.jl is maintained by the Trixi authors. Its principal developers are Andrew Winters (Linköping University, Sweden) and Patrick Ersing (Linköping University, Sweden). The full list of contributors can be found in AUTHORS.md.

License and contributing

TrixiShallowWater.jl is licensed under the MIT license (see LICENSE.md). Since TrixiShallowWater.jl is an open-source project, we are very happy to accept contributions from the community. To get in touch with the developers, join us on Slack or create an issue.

Acknowledgments

This project has benefited from funding from Vetenskapsrådet (VR, Swedish Research Council), Sweden through the VR Starting Grant "Shallow water flows including sediment transport and morphodynamics", VR grant agreement 2020-03642 VR.

Owner

  • Name: Trixi.jl
  • Login: trixi-framework
  • Kind: organization

Adaptive high-order numerical simulations of hyperbolic PDEs in Julia

GitHub Events

Total
  • Create event: 25
  • Commit comment event: 6
  • Release event: 2
  • Issues event: 13
  • Watch event: 7
  • Delete event: 19
  • Issue comment event: 93
  • Push event: 132
  • Pull request review comment event: 199
  • Pull request review event: 240
  • Pull request event: 74
  • Fork event: 4
Last Year
  • Create event: 25
  • Commit comment event: 6
  • Release event: 2
  • Issues event: 13
  • Watch event: 7
  • Delete event: 19
  • Issue comment event: 93
  • Push event: 132
  • Pull request review comment event: 199
  • Pull request review event: 240
  • Pull request event: 74
  • Fork event: 4

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 52
  • Total Committers: 6
  • Avg Commits per committer: 8.667
  • Development Distribution Score (DDS): 0.596
Past Year
  • Commits: 37
  • Committers: 4
  • Avg Commits per committer: 9.25
  • Development Distribution Score (DDS): 0.486
Top Committers
Name Email Commits
Patrick Ersing 1****g 21
dependabot[bot] 4****] 16
Michael Schlottke-Lakemper m****l@s****m 7
Hendrik Ranocha r****a 6
Andrew Winters a****s@l****e 1
CompatHelper Julia c****y@j****g 1
Committer Domains (Top 20 + Academic)
julialang.org: 1 liu.se: 1 sloede.com: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 16
  • Total pull requests: 122
  • Average time to close issues: 5 months
  • Average time to close pull requests: 14 days
  • Total issue authors: 5
  • Total pull request authors: 9
  • Average comments per issue: 2.0
  • Average comments per pull request: 2.12
  • Merged pull requests: 112
  • Bot issues: 0
  • Bot pull requests: 29
Past Year
  • Issues: 8
  • Pull requests: 75
  • Average time to close issues: 24 days
  • Average time to close pull requests: 7 days
  • Issue authors: 4
  • Pull request authors: 7
  • Average comments per issue: 1.13
  • Average comments per pull request: 1.97
  • Merged pull requests: 68
  • Bot issues: 0
  • Bot pull requests: 18
View more stats
Top Authors
Issue Authors
  • patrickersing (7)
  • andrewwinters5000 (4)
  • sloede (2)
  • mongibellili (1)
  • JuliaTagBot (1)
Pull Request Authors
  • patrickersing (72)
  • dependabot[bot] (41)
  • ranocha (17)
  • andrewwinters5000 (15)
  • JoshuaLampert (6)
  • sloede (4)
  • MarcoArtiano (2)
  • DanielDoehring (2)
  • github-actions[bot] (1)
Top Labels
Issue Labels
bug (1) help wanted (1) breaking (1) enhancement (1)
Pull Request Labels
dependencies (41) enhancement (22) bug (11) github_actions (10) documentation (6) breaking (4)

Packages

  • Total packages: 1
  • Total downloads:
    • julia 1 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
juliahub.com: TrixiShallowWater

Shallow water simulations with Trixi.jl

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 1 Total
Rankings
Dependent repos count: 8.4%
Forks count: 18.6%
Average: 22.5%
Stargazers count: 26.3%
Dependent packages count: 36.4%
Last synced: 8 months ago

Dependencies

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.github/workflows/TagBot.yml actions
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.github/workflows/ci.yml actions
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