Tutorial: Mesh Convergence

Tutorial: Mesh Convergence#

This tutorial is intended to demonstrate several advanced usage features that were glossed over in previous tutorials. Specifically, this tutorial will discuss

Building a parameter study from somewhere in the middle of the SCons workflow using a common source
Utilizing --input-file and --output-file command-line arguments
Using the post_processing.py script to create multiple plots

References#

Mesh Convergence Studies [37]
SCons file objects: SCons Node Package

Environment#

SCons and WAVES 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.

Note

The SALib and numpy versions may not need to be this strict for most tutorials. However, Tutorial: Sensitivity Study uncovered some undocumented SALib version sensitivity to numpy surrounding the numpy v2 rollout.

Create the tutorials environment if it doesn’t exist

$ conda create --name waves-tutorial-env --channel conda-forge waves 'scons>=4.6' matplotlib pandas pyyaml xarray seaborn 'numpy>=2' 'salib>=1.5.1' pytest

Activate the environment
```
$ conda activate waves-tutorial-env
```

Some tutorials require additional third-party software that is not available for the Conda package manager. This software must be installed separately and either made available to SConstruct by modifying your system’s PATH or by modifying the SConstruct search paths provided to the waves.scons_extensions.add_program() method.

Directory Structure#

Create and change to a new project root directory to house the tutorial files if you have not already done so. For example

$ mkdir -p ~/waves-tutorials
$ cd ~/waves-tutorials
$ pwd
/home/roppenheimer/waves-tutorials

Note

If you skipped any of the previous tutorials, run the following commands to create a copy of the necessary tutorial files.

$ pwd
/home/roppenheimer/waves-tutorials
$ waves fetch --overwrite --tutorial 11 && mv tutorial_11_regression_testing_SConstruct SConstruct
WAVES fetch
Destination directory: '/home/roppenheimer/waves-tutorials'

Download and copy the tutorial_11_regression_testing file to a new file named tutorial_mesh_convergence with the WAVES Command-Line Utility fetch subcommand.

$ pwd
/home/roppenheimer/waves-tutorials
$ waves fetch --overwrite tutorials/tutorial_11_regression_testing && cp tutorial_11_regression_testing tutorial_mesh_convergence
WAVES fetch
Destination directory: '/home/roppenheimer/waves-tutorials'

Parameter Study File#

Create a new file modsim_package/python/rectangle_compression_mesh_convergence.py from the content below.

waves-tutorials/modsim_package/python/rectangle_compression_mesh_convergence.py

"""Parameter sets and schemas for the rectangle compression simulation"""


def parameter_schema(
    global_seed=[1.0, 0.5, 0.25, 0.125],
):
    """Return mesh convergence WAVES CartesianProduct parameter schema

    :param float global_seed: The global mesh seed size

    :returns: WAVES CartesianProduct parameter schema
    :rtype: dict
    """
    schema = {
        "global_seed": global_seed,
    }
    return schema

This parameter study will define a mesh convergence study where the global size of the finite elements in the model is decreased several times by a factor of two.

Mesh Convergence Selection Dictionary#

Create a new file modsim_package/python/mesh_convergence_stress.yaml from the content below.

waves-tutorials/modsim_package/python/mesh_convergence_stress.yaml

'E values': 'E22'
'S values': 'S22'
'elements': 1
'step': 'Step-1'
'time': 1.0
'integration point': 0

This file defines a YAML formatted dictionary that will be used to change the default data selection of the post_processing.py script.