Science Score: 36.0%

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

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    7 of 8 committers (87.5%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (6.8%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: chrisknewman
  • License: other
  • Language: C++
  • Default Branch: master
  • Size: 113 MB
Statistics
  • Stars: 20
  • Watchers: 4
  • Forks: 9
  • Open Issues: 81
  • Releases: 0
Created over 9 years ago · Last pushed 11 months ago
Metadata Files
Readme License Citation

README.md

Tusas is a general / flexible code for solving coupled systems of nonlinear partial differential equations. Tusas was originally developed for phasefield simulation of solidification. In order for Tusas to be effective, the PDEs must be compatible with structured or unstructured Lagrange (nodal) finite element discretizations and explicit (Euler) or implicit (Euler, Trapezoid, BDF2) temporal discretizations.

The Tusas approach consists of a finite element spatial discretization of the fully-coupled nonlinear system, which is treated explicitly or implicitly in time with a preconditioned Jacobian-free Newton-Krylov (JFNK) method. As the JFNK method only requires a residual, from an implementation standpoint, Tusas allows a flexible framework as it only requires the user to implement code for a the residual equation. The key to efficient implementation of JFNK is effective preconditioning. As the dominant cost of JFNK is the linear solver, effective preconditioning reduces the number of linear solver iterations per Newton iteration. The preconditioning strategy in Tusas is based on block factorization and algebraic multigrid that allows an efficient, implicit time integration. As such, Tusas allows flexible precondtioning as it only requires the user to implement code for a row of the preconditioning matrix. In addition, configuration of the nonlinear system and preconditioner can be performed at runtime.

For questions and inquiries a mailing list is available for discussion: tusas-users@googlegroups.com

Google / gmail users can sign in and click the "Join group" button. Otherwise send an email to: tusas-users+subscribe@googlegroups.com

Owner

  • Name: Chris Newman
  • Login: chrisknewman
  • Kind: user
  • Company: Los Alamos National Laboratory

GitHub Events

Total
  • Issues event: 10
  • Watch event: 1
  • Issue comment event: 8
  • Push event: 54
  • Pull request event: 13
  • Fork event: 2
  • Create event: 1
Last Year
  • Issues event: 10
  • Watch event: 1
  • Issue comment event: 8
  • Push event: 54
  • Pull request event: 13
  • Fork event: 2
  • Create event: 1

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 581
  • Total Committers: 8
  • Avg Commits per committer: 72.625
  • Development Distribution Score (DDS): 0.048
Past Year
  • Commits: 48
  • Committers: 3
  • Avg Commits per committer: 16.0
  • Development Distribution Score (DDS): 0.042
Top Committers
Name Email Commits
chris newman c****n@l****v 553
DeWitt, Stephen d****j@o****v 14
Amelia Trainer a****o@l****v 9
Christopher Kyle Newman c****n@p****v 1
Christopher Kyle Newman c****n@r****v 1
Neil Carlson n****c@l****v 1
Supriyo Ghosh g****4@g****m 1
cnewman c****n@p****v 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 152
  • Total pull requests: 15
  • Average time to close issues: 4 months
  • Average time to close pull requests: 3 months
  • Total issue authors: 2
  • Total pull request authors: 5
  • Average comments per issue: 0.79
  • Average comments per pull request: 0.87
  • Merged pull requests: 10
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 7
  • Pull requests: 4
  • Average time to close issues: 11 minutes
  • Average time to close pull requests: 6 days
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 1.25
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • chrisknewman (154)
  • stvdwtt (2)
Pull Request Authors
  • stvdwtt (6)
  • jeremy-lilly (4)
  • gsupriyo2004 (3)
  • chrisknewman (2)
  • pbarc (1)
  • jeanlucf22 (1)
  • golowimmer (1)
  • brian-oneill (1)
Top Labels
Issue Labels
enhancement (98) bug (53)
Pull Request Labels