Running Gmsh once

In this example we will run a gmsh script to generate a mesh file using the GmshRunner class.

Installing gmsh: For this example you will need to have a gmsh executable which can be downloaded and installed from here: https://gmsh.info/#Download

We start by importing what we need for this example.

import time
from pathlib import Path

#pyvale imports
import pyvale.dataset as dataset
from pyvale.mooseherder import GmshRunner

First we need to create a ‘runner’ for gmsh which needs to know the path to the gmsh executable. You will need to replace this path with the path to where you have install gmsh on your system.

gmsh_path = Path.home() / 'gmsh/bin/gmsh'
gmsh_runner = GmshRunner(gmsh_path)

Next we grab a gmsh file from pyvale simulation library and we set this as the input file for our runner.

gmsh_input = dataset.sim_case_gmsh_file_path(case_num=17)
gmsh_runner.set_input_file(gmsh_input)

Now we can run gmsh to generate our mesh using the run method, the parse only flag means we will run gmsh head less and not open the gmsh GUI but terminal output will still be written to stdout.

We also use our performance timer to time how long our mesh generation takes and then we print this to the console. Note that parallelisation options for gmsh can be controlled in the gmsh .geo script file.

start_time = time.perf_counter()
gmsh_runner.run(gmsh_input,parse_only=True)
run_time = time.perf_counter() - start_time

print()
print("-"*80)
print(f'Gmsh run time = {run_time :.3f} seconds')
print("-"*80)
print()

The GmshRunner and the MooseRunner implement the SimRunner abstract base class. Later on when we will see that we can use this to run a list of different sim runners in order using MooseHerd workflow manager. This allows us to first build our mesh with gmsh and then run a moose simulation using that mesh. We can also implement our own SimRunner’s to add additional pre or post processing steps to our simulation chain.