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#7 adding 3D mesh generation documentation
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‎docs/doc.html‎

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@@ -38,7 +38,7 @@ <h3>Get Started</h3>
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<p>New to <code>svVascularize</code>? Begin with the quickstart tutorial that walks you through generating a vascular tree and running a 0‑D hemodynamic simulation in under five minutes.</p>
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<ul>
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<li><a href="quickstart.html">🟢 Quickstart tutorial</a></li>
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<li><a href="tutorials/pipeline.html">End‑to‑end pipeline (generation → 3‑D CFD)</a></li>
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<li><a href="pipeline.html">End‑to‑end pipeline (generation → 3‑D CFD)</a></li>
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</ul>
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<h3>Concept Guides</h3>

‎docs/pipeline.html‎

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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="utf-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1" />
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<title>svVascularize Quickstart</title>
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<link href="https://fonts.googleapis.com/css?family=Montserrat:400,700" rel="stylesheet" />
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<link rel="stylesheet" href="style.css" />
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</head>
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<body>
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<header class="topnav">
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<div class="container">
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<h1><a href="index.html">svVascularize</a></h1>
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<nav>
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<a href="index.html#about">About</a>
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<a href="install.html">Installation</a>
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<a href="doc.html">Documentation</a>
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<a href="index.html#simulation">Simulation</a>
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<a href="https://pypi.org/project/svv/" target="_blank" rel="noopener">PyPI</a>
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<a href="https://github.com/SimVascular/svVascularize" target="_blank" rel="noopener">GitHub</a>
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</nav>
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</div>
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</header>
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<main class="container content">
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<h2>End-to-End Pipeline for 3D CFD Simulations</h2>
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<p> Generating a watertight, simulation-ready finite element mesh for computational fluid dynamics is a challenging
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multi-step problem. For typical workflows modeling bloodflow from clinical imaging data, this process involves
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pathline generation, segmentation, solid surface creation, volume mesh generation, mesh optimization/smoothing,
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and boundary identification. The pathline and segmentation steps are dependent upon available image data, thus
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these steps are very different for synthetically generated vascular structures which inheriently lack imaging
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data. The remaining steps are somewhat the same except that the workflow employed with
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<code>svVascularize</code> is automated since the number of vessels may quickly exceed practical manual
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efforts for model and mesh creation. These automated steps are all part of the <code>Simulation</code> class
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which can be used to wrap around synthetic vascular objects in order to build simulation files. We will
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demonstrate the basic API below for a simple vascular tree. </p>
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<pre data-copy> <code class="language-python">import pyvista as pv
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from svv.domain.domain import Domain
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from svv.tree.tree import Tree
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from svv.simulation.simulation import Simulation
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cube = Domain(pv.Cube())
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cube.create()
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cube.solve()
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cube.build()
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t = Tree()
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t.set_domain(cube)
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t.set_root()
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t.n_add(2)</code></pre>
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<p> Now that we have a simple tree we can start building simulations from this object. </p>
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<pre data-copy> <code class="language-python"># Create Simulation Container for Synthetic Tree Object
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sim = Simulation(t)
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# Build All Surface/Volume Meshes for 3D CFD Simulation
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sim.build_meshes()</code></pre>
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<p>This method will produce unioned surface <code>.vtp</code> meshes and their cooresponding volume meshes <code>.vtu</code>
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representing the synthetic vascular object. Additionally, the procedure will attempt to append boundary layer meshes
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along the walls vessels, typical in many hemodynamic studies to account for the steep velocity gradients near vessel
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walls. If successful, the surfaces meshes will be stored within the simulation container list
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<code>simulation.fluid_domain_surface_meshes</code>, volume meshes will be stored within the container
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<code>simulation.fluid_domain_volume_meshes</code>, and boundary layers will be stored within the container
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<code>simulation.fluid_domain_boundary_layers</code>. Storing the meshes as python objects allows for more custom
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modification procedures that users may want to implement prior to creating the simulation files.
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</p>
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<div class="callout"><strong>Mesh building: </strong> This step is potentially memory and compute intensive depending
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on the size of the synthetic vascular object being discretized. Under the hood, <code>svVascularize</code> is
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using a combination of <code>tetgen</code> and <code>mmg</code> meshing utilities via python subprocess calls.
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These, as well as surface mesh unioning operations, are non-trivial and may take minutes-hours to complete.
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Users can supply custom meshing parameters for their applications to override default values this may result
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in more efficient meshing, but it is recommended that default parameters are attemped first.</div>
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</main>
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<footer>
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<div class="container">
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<p>&copy; 2025 SimVascular, Stanford University, The Regents of the University of California, and others —
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<a href="https://opensource.org/license/BSD-3-Clause">BSD 3-Clause License</a><br></p>
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</div>
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</footer>
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<script defer src="script.js"></script>
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</body>
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</html>

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