README#

Description#

Turbo-Turtle (LANL code O4765) is a collection of solid body modeling tools for 2D sketched, 2D axisymmetric, and 3D revolved models. It also contains general purpose meshing and image generation utilities appropriate for any model, not just those created with this package. Implemented for Abaqus and Cubit as backend modeling and meshing software. Orginal implementation targeted Abaqus so most options and descriptions use Abaqus modeling concepts and language.

Turbo-Turtle makes a best effort to maintain common behaviors and features across each third-party software’s modeling concepts. As much as possible, the work for each subcommand is performed in Python 3 to minimize solution approach duplication in third-party tools. The third-party scripting interface is only accessed when creating the final tool specific objects and output. The tools contained in this project can be expanded to drive other meshing utilities in the future, as needed by the user community.

This project derives its name from the origins as a sphere partitioning utility following the turtle shell (or soccer ball) pattern.

Documentation#

Author Info#

Installation#

Turbo-Turtle can be installed in a Conda environment with the Conda package manager. See the Conda installation and Conda environment management documentation for more details about using Conda.

$ conda install --channel conda-forge turbo_turtle

Quick Start#

  1. View the CLI usage

    $ turbo-turtle -h
    $ turbo-turtle docs -h
    $ turbo-turtle geometry -h
    $ turbo-turtle cylinder -h
    $ turbo-turtle sphere -h
    $ turbo-turtle partition -h
    $ turbo-turtle mesh -h
    $ turbo-turtle image -h
    $ turbo-turtle merge -h
    $ turbo-turtle export -h
    

Developer Instructions#

Cloning the Repository#

Cloning the repository is very easy, simply refer to the sample session below. Keep in mind that you get to choose the location of your local Turbo-Turtle repository clone. Here we use /projects/roppenheimer/repos as an example.

[roppenheimer@sstelmo repos]$ git clone ssh://git@re-git.lanl.gov:10022/aea/python-projects/turbo-turtle.git

Compute Environment#

This repository requires Abaqus and Cubit to be installed and on the system PATH. If you use an AEA linux computer, then the project continuous-integration environment is available as a development environment.

On an AEA Linux Machine#

[roppenheimer@sstbigbird turbo-turtle]$ module use /projects/aea_compute/modulefiles
[roppenheimer@sstbigbird turbo-turtle]$ module load turbo-turtle-dev

Local development environment#

You can also create a local environment with the Conda package manager as

[roppenheimer@mymachine turbo-turtle]$ conda env create --file environment.yml --name turbo-turtle-dev
[roppenheimer@mymachine turbo-turtle]$ conda activate turbo-turtle-dev

Testing#

This project now performs CI testing on AEA compute servers. The up-to-date test commands can be found in the .gitlab-ci.yml file. The full regression suite includes the documentation builds, Python 3 unit tests, Abaqus Python unit tests, and the system tests.

$ pwd
/home/roppenheimer/repos/turbo-turtle
$ scons regression

There is also a separate style guide check run as

$ scons flake8 black-check

The full list of available aliases can be found as scons -h.