Summary
In this lecture, we'll cover the following:
- Adding predefined column (nodal) points into the mesh generation process.
- Extending the meshing function to handle additional geometric constraints.
- Embedding point entities into a surface using Gmsh.
- Mapping geometric points to mesh node tags using a proximity tolerance.
- Enhancing visualisation to highlight specific nodes (e.g. column locations).
In this lecture, we extend our meshing workflow by incorporating predefined column points into the mesh. We modify our existing function to accept additional point inputs, insert these into the geometry, and explicitly embed them into the surface so that Gmsh respects them during mesh generation. We also implement a method to track these points by mapping them to the nearest mesh nodes using a tolerance-based search, ensuring we can later reference them for boundary conditions or restraints.
We then enhance our data extraction by recording node tags not only for column locations but also along the outer boundary of the slab. Finally, we update the visualisation function to clearly distinguish column nodes from the rest of the mesh. Together, these improvements give us a more flexible and analysis-ready meshing tool, enabling precise control over key nodal locations.
Next up
Next, we will consolidate all of these meshing functions into a reusable utility file, streamlining the workflow for future analyses.
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Finite Element Analysis of Plate and Shell Structures: Part 1 - Plates
An analysis pipeline for thick and thin plate structures, a roadmap from theory to toolbox
After completing this course...
- You will understand how Reissner-Mindlin theory enables us to accurately capture both thin and thick plate behaviour.
- You will understand how to turn the fundamental mechanics of plate behaviour into a custom finite element solver written in Python.
- You will have developed meshing workflows that utilise the powerful open-source meshing engine, GMSH.
- In addition to using your own custom finite element code, you will be comfortable validating your results using OpenSeesPy and Pynite.