In this lecture, we'll cover:

• How to refactor our existing truss analysis code so it can handle any truss
• What input data is required to fully define a truss for analysis
• How to structure user-defined inputs in a Jupyter Notebook
• How to organise nodal coordinates, member connectivity, supports and loading
• How to clearly separate data entry from the analysis code

In this lecture, we focus on generalising the truss analysis code developed previously so that it can analyse any truss, not just a single hard-coded example. We begin by identifying exactly what information must be supplied by a user in order to fully define a truss. This includes material properties such as Young’s modulus and cross-sectional area (assumed constant for now), a displacement scale factor for visualisation, the nodal coordinates defined in ascending node order, the member connectivity specified by the nodes at each end, the restrained degrees of freedom representing supports, and the external load vector.

We structure this information clearly within a dedicated data entry section of the notebook, using NumPy arrays to store nodes and members. Particular emphasis is placed on clarity, ordering, and good annotation so that the notebook can be reused reliably. The key idea is that once this data entry section is complete, nothing else in the code should need to be modified for a different truss. By separating problem definition from analysis logic, we mirror the workflow of commercial structural analysis software, albeit in text form rather than through a graphical interface.

Next up:

In the next lecture, we build a function to automatically calculate member lengths and orientation angles from the nodal coordinate data.