Jukka Aho
2d1ba0a0a1
Major cleanup of quadrature module: simplify docstrings to minimal
code-focused style, remove all legacy symbol-based API, and fix Vec
constructor syntax throughout.
Documentation simplification:
- Remove all examples from docstrings
- Simplify file-level docstrings to one-line descriptions
- Remove verbose explanations, accuracy details, references, and
"See also" sections
- Keep only essential information about types and functions
Legacy code removal:
- Remove all legacy symbol-based API (Val{:GLTRI*}, Val{:GLTET*},
Val{:GLPYR*}, Val{:GLWED*}, Val{:GLSEG*}, Val{:GLQUAD*},
Val{:GLHEX*})
- Remove get_order() functions for legacy symbols
- Remove _legacy_tensor_product helper function
- Remove legacy symbol generation code from gl_tensor_product.jl
gauss.jl refactoring:
- Remove old Gauss{N} type and AbstractIntegration hierarchy
- Remove get_rule_name() function and all rule name mappings
(hundreds of lines for segments, triangles, quads, tets, hexes,
wedges, pyramids)
- Remove IntegrationPointNEW alias
- Replace with simple integration_points() function using new API
- Change npoints() signature to take only topology parameter
api.jl improvements:
- Uncomment and fix _infer_basis_order implementations
- Add proper type constraints (<:) for all topology types
- Add Triangle{10} case for cubic triangles
- Add _quadrature_topology_type mapping functions for all topologies
- Enable topology-only dispatch for default_quadrature
Vec constructor fixes:
- Fix all Vec{D} constructor calls to use tuple syntax
- Change Vec{2}(x, y) to Vec{2}((x, y))
- Change Vec{3}(x, y, z) to Vec{3}((x, y, z))
- Applied consistently across all quadrature rule files
JuliaFEM.jl - an open source solver for both industrial and academia usage
The JuliaFEM project develops open-source software for reliable, scalable, distributed Finite Element Method.
The JuliaFEM software library is a framework that allows for the distributed processing of large Finite Element Models across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. The basic design principle is: everything is nonlinear. All physics models are nonlinear from which the linearization are made as a special cases.
At the moment, users can perform the following analyses with JuliaFEM: elasticity, thermal, eigenvalue, contact mechanics, and quasi-static solutions. Typical examples in industrial applications include non-linear solid mechanics, contact mechanics, finite strains, and fluid structure interaction problems. For visualization, JuliaFEM uses ParaView which prefers XDMF file format using XML to store light data and HDF to store large data-sets, which is more or less the open-source standard.
Vision
On one hand, the vision of the JuliaFEM includes the opportunity for massive parallelization using multiple computers with MPI and threading as well as cloud computing resources in Amazon, Azure and Google Cloud services together with a company internal server. And on the other hand, the real application complexity including the simulation model complexity as well as geometric complexity. Not to forget that the reuse of the existing material models as well as the whole simulation models are considered crucial features of the JuliaFEM package.
Recreating the wheel again is definitely not anybody's goal, and thus we try to use and embrace good practices and formats as much as possible. We have implemented Abaqus / CalculiX input-file format support and maybe will in the future extend to other FEM solver formats. Using modern development environments encourages the user towards fast development time and high productivity. For developing and creating new ideas and tutorials, we have used Jupyter notebooks to make easy-to-use handouts.
The user interface for JuliaFEM is Jupyter Notebook, and Julia language itself is a real programming language. This makes it possible to use JuliaFEM as a part of a bigger solution cycle, including for example data mining, automatic geometry modifications, mesh generation, solution, and post-processing and enabling efficient optimization loops.
Installing JuliaFEM
Inside Julia REPL, type:
Pkg.add("JuliaFEM")
Initial road map
JuliaFEM current status: project planning
| Version | Number of degree of freedom | Number of cores |
|---|---|---|
| 0.1.0 | 1 000 000 | 10 |
| 0.2.0 | 10 000 000 | 100 |
| 1.0.0 | 100 000 000 | 1 000 |
| 2.0.0 | 1 000 000 000 | 10 000 |
| 3.0.0 | 10 000 000 000 | 100 000 |
We strongly believe in the test driven development as well as building on top of previous work. Thus all the new code in this project should be 100% tested. Also other people have wisdom in style as well:
Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Errors should never pass silently.
Citing
If you like using our package, please consider citing our article
@article{frondelius2017juliafem,
title={Julia{FEM} - open source solver for both industrial and academia usage},
volume={50},
url={https://rakenteidenmekaniikka.journal.fi/article/view/64224},
DOI={10.23998/rm.64224},
number={3},
journal={Rakenteiden Mekaniikka},
author={Frondelius, Tero and Aho, Jukka},
year={2017},
pages={229-233}
}
Contributing
We welcome contributions! JuliaFEM encourages good practices, starting from unit testing and continuing to full integration testing across platforms.
Interested in contributing? Please read:
- Contributing Guide - Quick start for contributors
- Coding Standards - Required reading (includes important rules like "no Greek letters in code")
- Contributor Manual - Technical details and architecture
Key requirements:
- ✅ Type-stable code (performance critical)
- ✅ Tests included with all changes
- ✅ Follow coding standards (use
u, v, wnot ξ, η, ζ) - ✅ Clean commit messages
Questions? Open a GitHub Discussion or issue - we're happy to help!