Introduction

Sometimes it is useful to interact with third-party meshing software. This may be case, for example, when using meshes based on CAD models. Salvus supports the use of such meshes, and has automated readers for a collection of open-source mesh formats. In this tutorial we'll give an overview of the currently supported formats along with an example of their use. The first thing to do of course is to import the required Python packages.

Copy
%matplotlib inline

from pathlib import Path

import h5py
import matplotlib.pyplot as plt
import numpy as np
import salvus_mesh.unstructured_mesh as um
from salvus_flow import api
from salvus_flow import simple_config as sc
from typing import List

Also, to make our lives a bit easier, we'll write a few short functions that will help us quickly generate Salvus inputs as we proceed

def get_basic_source(
    *, frequency: float, physics: str, location: List
) -> sc.source:
    """Gets a simple physics- and dimension-dependent source.

    Args:
        frequency: Center frequency of the (Ricker) wavelet.
        physics: Physics of the source.
        location: Location of the source.

    Returns:
        SalvusFlow source object appropriate for the specified physics.
    """

    l = location
    src = sc.source.cartesian
    s = sc.stf.Ricker(center_frequency=frequency)
    if physics == "acoustic":
        return src.ScalarPoint3D(
            x=l[0], y=l[1], z=l[2], f=1, source_time_function=s
        )

    return src.VectorPoint3D(
        x=l[0], y=l[1], z=l[2], fx=1.0, fy=1.0, fz=0.0, source_time_function=s
    )


Exodus is one of the more common third-party mesh formats, and salvus_mesh can read Exodus files natively. In the following example we'll read some Exodus meshes into Salvus and run some simulations. We'll focus on two use cases: a purely elastic simulation, and a coupled fluid-solid simulation.


Elastic

Mesh

# Read mesh from Exodus file.
mesh = um.UnstructuredMesh.from_exodus("./data/exodus/glass.e")

# Find the surface of mesh.
mesh.find_surface(side_set_name="surface")

# Mark simulation as elastic.
mesh.attach_field("fluid", np.zeros(mesh.nelem))

# Attach parameters.
pars = {"VP": 5800, "VS": 4000, "RHO": 2600}
template = np.ones_like(mesh.get_element_nodes()[:, :, 0])
for key, value in pars.items():
    mesh.attach_field(key, template * value)

# Visualize.
mesh
When run interactively in a Jupyter Notebook, this output cell contains a widget. Click the button below to load a preview of it. Please note that most interactive functionality does not work without a running Python kernel.
<salvus_mesh.unstructured_mesh.UnstructuredMesh at 0x7faa0d5ccb70>
# Set up simulation.
w = sc.simulation.Waveform(
    mesh=mesh,
    sources=get_basic_source(
        frequency=100.0, physics="elastic", location=[0, 0, 70]
    ),
)

# Generate a movie.
w.output.volume_data.format = "hdf5"
w.output.volume_data.filename = "movie.h5"
w.output.volume_data.fields = ["displacement"]
w.output.volume_data.sampling_interval_in_time_steps = 100

# Validate simulation parameters.
w.validate()
api.run(
    ranks=2,
    get_all=True,
    input_file=w,
    site_name="local",
    output_folder="output",
)
Job `job_1910221507772797_77d439e3e4` running on `local` with 2 rank(s).
Site information:
  * Salvus version: 0.10.5
  * Floating point size: 32
* Downloaded 42.1 MB of results to `output`.
* Total run time: 10.08 seconds.
* Pure simulation time: 9.65 seconds.
<salvus_flow.sites.salvus_job.SalvusJob at 0x7faa0d609a58>

Snapshot of the magnitude of dynamic elastic displacement, visualized using Paraview and the output .xdmf file.


# Read mesh from Exodus file.
mesh_solid = um.UnstructuredMesh.from_exodus("./data/exodus/solid.e")
mesh_fluid = um.UnstructuredMesh.from_exodus("./data/exodus/fluid.e")

# Mark fluid and solid elements.
mesh_solid.attach_field("fluid", np.zeros(mesh_solid.nelem))
mesh_fluid.attach_field("fluid", np.ones(mesh_fluid.nelem))

# Attach parameters (elastic).
pars = {"VP": 5800, "VS": 4000, "RHO": 2600}
template = np.ones_like(mesh_solid.get_element_nodes()[:, :, 0])
for key, value in pars.items():
    mesh_solid.attach_field(key, template * value)

# Attach parameters (acoustic).
pars = {"VP": 1500, "VS": 0, "RHO": 1000}
template = np.ones_like(mesh_fluid.get_element_nodes()[:, :, 0])
for key, value in pars.items():
    mesh_fluid.attach_field(key, template * value)

# Combine both element blocks.
mesh = mesh_solid + mesh_fluid

# Find the surface of mesh.
mesh.find_surface(side_set_name="surface")

# Visualize.
mesh
When run interactively in a Jupyter Notebook, this output cell contains a widget. Click the button below to load a preview of it. Please note that most interactive functionality does not work without a running Python kernel.
<salvus_mesh.unstructured_mesh.UnstructuredMesh at 0x7faa088ecd68>
# Set up simulation.
w = sc.simulation.Waveform(
    mesh=mesh,
    sources=get_basic_source(
        frequency=100.0, physics="acoustic", location=[0, -30, 70]
    ),
)

# Set your simulation length here.
# w.physics.wave_equation.end_time_in_seconds = ?

# Generate a movie.
w.output.volume_data.format = "hdf5"
w.output.volume_data.filename = "movie.h5"
w.output.volume_data.fields = ["displacement", "phi_tt"]
w.output.volume_data.sampling_interval_in_time_steps = 100

# Validate simulation parameters.
w.validate()
api.run(
    ranks=2,
    get_all=True,
    input_file=w,
    site_name="local",
    output_folder="output_coupled",
)
Job `job_1910221507550946_a3a7669dd9` running on `local` with 2 rank(s).
Site information:
  * Salvus version: 0.10.5
  * Floating point size: 32
                                                     
* Downloaded 31.0 MB of results to `output_coupled`.
* Total run time: 10.55 seconds.
* Pure simulation time: 9.93 seconds.
<salvus_flow.sites.salvus_job.SalvusJob at 0x7faa08a4be80>

Snapshot of the magnitude of dynamic elastic displacement and the acoustic pressure, visualized using Paraview and the output .xdmf file.


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