In this section, we'll cover:

• Generalising our Python implementation of the direct stiffness method so it can analyse any truss structure
• Structuring our code to accept input data for geometry, supports and loading
• Automating the full solution process within a Jupyter Notebook
• Building on previous example-specific implementations to create a reusable analysis tool
• Understanding how commercial structural analysis software works behind the scenes

In this lecture, we move beyond writing code for specific example structures and focus on developing a fully general implementation of the direct stiffness method in Python. Our aim is to create a Jupyter Notebook that can analyse any truss structure simply by accepting input data that defines the geometry, support conditions and applied loads. Once this information is provided, our code should carry out the entire solution process automatically, without further manual intervention.

We build on the groundwork laid in previous sections, where we progressively generalised our code. Here, we refine and extend that approach so that it becomes flexible and reusable rather than tailored to a single example. Although we base our development on the structure analysed in the previous section, the ultimate goal is to produce a tool that can handle arbitrary truss configurations. In doing so, we not only replicate the workflow of commercial structural analysis software, but also deepen our understanding of how such software operates behind the scenes.

Next up:

In the next lecture, we define the input data structure for a generalised truss solver, clearly separating the problem definition from the analysis logic.