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| <li class="toctree-l1"><a class="reference internal" href="theory.html">Background theory</a></li> | ||
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| <section id="setup"> | ||
| <h1>Setup<a class="headerlink" href="#setup" title="Link to this heading"></a></h1> | ||
| <p>We use <a class="reference external" href="https://github.com/FEniCS/dolfinx">dolfinx</a> for full 3D heat transfer model. Compiling and installing dolfinx can be challenging. We suggests using a Docker images.</p> | ||
| <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>docker<span class="w"> </span>run<span class="w"> </span>-ti<span class="w"> </span>-v<span class="w"> </span><YOUR_WORK_DIR>:/<span class="w"> </span>dolfinx:dolfinx:v0.7.0 | ||
| <span class="c1"># Then inside the interactive shell</span> | ||
| pip<span class="w"> </span>install<span class="w"> </span>warmth | ||
| </pre></div> | ||
| </div> | ||
| <p>3D part of the library has only been tested with Python 3.10.x and Dolfinx v0.7.x</p> | ||
| </section> | ||
| <section id="workflow"> | ||
| <h1>Workflow<a class="headerlink" href="#workflow" title="Link to this heading"></a></h1> | ||
| <p><a class="reference external" href="https://github.com/equinor/warmth/tree/main/docs/notebooks/3D_simulation.ipynb">Notebook example</a></p> | ||
| <p>Step 1 - Extract 1D models from maps</p> | ||
| <p>Step 2 - Find beta factor and curstal thickness through time using 1D simulation</p> | ||
| <p>Step 3 - Build 3D mesh and run simulation</p> | ||
| <section id="d-heat-equation-simulation-using-dolfinx"> | ||
| <h2>3D heat equation simulation using dolfinx<a class="headerlink" href="#d-heat-equation-simulation-using-dolfinx" title="Link to this heading"></a></h2> | ||
| <p>The 3D simulation performs a series of heat equation solves, regularly updating the mesh positions from the 1D nodes. The equations are solved using the PETSc solver from the dolfinx package (part of the FeNiCs project). The compute mesh is built by defining hexahedra for every rectangle of 1D nodes and for every layer (i.e. each sediment, the crust, the lithosphere, and the aesthenosphere), which are then subdivided into tetrahedra.</p> | ||
| <p>The dolfinx model building and solving is managed by the class <a class="reference internal" href="#warmth3D/fixed_mesh_model.py"><span class="xref myst">UniformNodeGridFixedSizeMeshModel</span></a>. The use of this class is demonstrated in <a class="reference internal" href="#tests/warmth3D_mapA_example.py"><span class="xref myst">warmth3D_mapA_example.py</span></a>. Note that the NodeGrid class definition in this script should match the definition used in <a class="reference internal" href="#warmth3D/parallel-1Dsed.py"><span class="xref myst">parallel-1Dsed.py</span></a> to compute the 1D solutions. This script writes the results (mesh positions and function values) at every 1M years in xdmf format for visualization in ParaView.</p> | ||
| </section> | ||
| <section id="resqml-output"> | ||
| <h2>RESQML output<a class="headerlink" href="#resqml-output" title="Link to this heading"></a></h2> | ||
| <p>The test script <a class="reference internal" href="#tests/warmth3D_mapA_example.py"><span class="xref myst">warmth3D_mapA_example.py</span></a> further demonstrates writing the unstructured grid (with properties) in RESQML format, as a pair of .epc and .h5 files. The RESQML I/O functions are in a separate file, <a class="reference internal" href="#warmth3D/resqpy_helpers.py"><span class="xref myst">resqpy_helpers.py</span></a>, and require a modified version of the resqpy library. To visualise RESQML data in ParaView, a 3rd-party plug-in can be installed, see <a class="reference external" href="https://github.com/F2I-Consulting/fespp">fespp</a>.</p> | ||
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| # Setup | ||
| We use [dolfinx](https://github.com/FEniCS/dolfinx) for full 3D heat transfer model. Compiling and installing dolfinx can be challenging. We suggests using a Docker images. | ||
| ```bash | ||
| docker run -ti -v <YOUR_WORK_DIR>:/ dolfinx:dolfinx:v0.7.0 | ||
| # Then inside the interactive shell | ||
| pip install warmth | ||
| ``` | ||
| 3D part of the library has only been tested with Python 3.10.x and Dolfinx v0.7.x | ||
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| # Workflow | ||
| [Notebook example](https://github.com/equinor/warmth/tree/main/docs/notebooks/3D_simulation.ipynb) | ||
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| Step 1 - Extract 1D models from maps | ||
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| Step 2 - Find beta factor and curstal thickness through time using 1D simulation | ||
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| Step 3 - Build 3D mesh and run simulation | ||
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| ### 3D heat equation simulation using dolfinx | ||
| The 3D simulation performs a series of heat equation solves, regularly updating the mesh positions from the 1D nodes. The equations are solved using the PETSc solver from the dolfinx package (part of the FeNiCs project). The compute mesh is built by defining hexahedra for every rectangle of 1D nodes and for every layer (i.e. each sediment, the crust, the lithosphere, and the aesthenosphere), which are then subdivided into tetrahedra. | ||
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| The dolfinx model building and solving is managed by the class [UniformNodeGridFixedSizeMeshModel](warmth3D/fixed_mesh_model.py). The use of this class is demonstrated in [warmth3D_mapA_example.py](tests/warmth3D_mapA_example.py). Note that the NodeGrid class definition in this script should match the definition used in [parallel-1Dsed.py](warmth3D/parallel-1Dsed.py) to compute the 1D solutions. This script writes the results (mesh positions and function values) at every 1M years in xdmf format for visualization in ParaView. | ||
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| ### RESQML output | ||
| The test script [warmth3D_mapA_example.py](tests/warmth3D_mapA_example.py) further demonstrates writing the unstructured grid (with properties) in RESQML format, as a pair of .epc and .h5 files. The RESQML I/O functions are in a separate file, [resqpy_helpers.py](warmth3D/resqpy_helpers.py), and require a modified version of the resqpy library. To visualise RESQML data in ParaView, a 3rd-party plug-in can be installed, see [fespp](https://github.com/F2I-Consulting/fespp). | ||
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@@ -9,6 +9,7 @@ Welcome to warmth's documentation! | |
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| theory | ||
| example | ||
| 3D | ||
| apireference | ||
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| # Background theory | ||
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| 3D simulations in warmth are under active development. Currently, yhey are based on a uniform reactangular grid of 1D nodes (defined in a NodeGrid data structure). The sediment inputs, horizons are present day, are provided as .gri files, which are read into a SedimentStack class. | ||
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| ### Pre-requisite: grid of 1D node simulation | ||
| The complete 1D warmth simulation is run for some of the 1D nodes. For other 1D nodes the subsidence, beta factor, and crustal thickness are interpolated. The 1D simulations can be run using the script [parallel-1Dsed.py](warmth3D/parallel-1Dsed.py). Results for each node are pickled to a separate file (this is to be improved!). | ||
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| ### 3D heat equation simulation using dolfinx | ||
| The 3D simulation performs a series of heat equation solves, regularly updating the mesh positions from the 1D nodes. The equations are solved using the PETSc solver from the dolfinx package (part of the FeNiCs project). The compute mesh is built by defining hexahedra for every rectangle of 1D nodes and for every layer (i.e. each sediment, the crust, the lithosphere, and the aesthenosphere), which are then subdivided into tetrahedra. | ||
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| The dolfinx model building and solving is managed by the class [UniformNodeGridFixedSizeMeshModel](warmth3D/fixed_mesh_model.py). The use of this class is demonstrated in [warmth3D_mapA_example.py](tests/warmth3D_mapA_example.py). Note that the NodeGrid class definition in this script should match the definition used in [parallel-1Dsed.py](warmth3D/parallel-1Dsed.py) to compute the 1D solutions. This script writes the results (mesh positions and function values) at every 1M years in xdmf format for visualization in ParaView. | ||
|
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| ### RESQML output | ||
| The test script [warmth3D_mapA_example.py](tests/warmth3D_mapA_example.py) further demonstrates writing the unstructured grid (with properties) in RESQML format, as a pair of .epc and .h5 files. The RESQML I/O functions are in a separate file, [resqpy_helpers.py](warmth3D/resqpy_helpers.py), and require a modified version of the resqpy library. To visualise RESQML data in ParaView, a 3rd-party plug-in can be installed, see [fespp](https://github.com/F2I-Consulting/fespp). | ||
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| ### 3D dependencies | ||
| The dolfinx package is Linux-only(?) and has to be compiled from source or installed using apt-get. The resqpy dependency can be installed with pip, but, for now, some writing of properties on unstructured grids requires a change in resqpy that is not yet merged. The other dependencies xtgeo and meshio can be installed using pip (requirements file is to be added). | ||
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