Diagram GPT's for Seeing Connections in a SWMM5 in Input File

The SWMM5 input file is well-organized into data sections, but sometimes it's challenging to see the relationships between ancillary data such as DWF, inflow, aquifers, groundwater, RDII, and LID coverage within the native SWMM5 UX. This post is in response to a question on OpenSWMM.org about displaying link-node data outside of SWMM5. By using some of the diagram tools accessible through OpenAI, we hope to show how to make a clearer visualization of these interconnections.

This approach can be particularly useful for students, users of API-based SWMM tools like PySWMM, and users of SWMM5, ICM SWMM, or InfoWorks ICM exported to SWMM5. It will help them better understand and visualize the interconnections within their models.

1: Example of a GPT and to Use a SWMM5 file

To visualize the relationships in a SWMM5 file, start by copying a section of the SWMM5 file into a text editor. Then, use a diagram generation tool, such as one of the many available GPT models, for creating diagrams. Search for a diagram GPT model to help organize the data into a visual form, and perform several iterations to refine the diagram. Often, you can edit the diagram using a graphical user interface (GUI).

Here is a simple SWMM5 example (in case you have not seen it many times before)

[JUNCTIONS]
;;Name           Elevation  MaxDepth  InitDepth  SurDepth  Aponded
;;-------------- ---------- ---------- ---------- ---------- ----------
J1               10         5         0          0         0
J2               15         5         0          0         0

[OUTFALLS]
;;Name           Elevation  Type       Stage Data       Gated
;;-------------- ---------- ---------- ---------------- ----------
O1               5          FREE                        NO

[CONDUITS]
;;Name           From Node  To Node    Length     Roughness  InOffset   OutOffset  InitFlow  MaxFlow
;;-------------- ---------- ---------- ---------- ---------- ---------- ---------- ---------- ----------
C1               J1         J2         400        0.01       0          0          0         0
C2               J2         O1         600        0.01       0          0          0         0        

2: Example of a GPT and to Use a SWMM5 file

To visualize the relationships in a SWMM5 file, start by copying a section of the SWMM5 file into a text editor. Here is a sample for LID Data or SUDS data.

Closing Note: Thank you so much for journeying with me through this content. This space is reserved for future updates and insights. Your engagement and time are truly appreciated. Until next time! You can also see my past articles on LinkedIn (91 in 2023). The next goal is 133 or 17*19, in FY2025 (which is the calendar year 2024 and the start of 2025 in Autodesk terms).

Why 1729: The factors of 1729 are 1, 7, 13, 19, 91, 133, 247, and 1729 itself. A bit of history about 1729: It's famously known as the Hardy-Ramanujan number after a story involving two great mathematicians, G.H. Hardy and Srinivasa Ramanujan. According to the anecdote, Hardy visited Ramanujan in the hospital and mentioned that he arrived in a taxi numbered 1729, which he found to be a rather uninteresting number. Ramanujan immediately responded that 1729 is actually very interesting because it is the smallest number expressible as the sum of two cubes in two different ways: 1729=1^3+12^3=9^3+10^3. This property makes 1729 a significant figure in the world of mathematics, showcasing Ramanujan's extraordinary intuitive grasp of numbers.