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Visualization of Shear Force and Bending Moment Diagrams

Using Xarray and Plotly (MIDAS-style Post-Processing)

📌 Submission Details

  • Project Title: Visualization of Shear Force and Bending Moment Diagrams using Xarray and Plotly
  • Organization: Osdag (FOSSEE, IIT Bombay)
  • Task Type: Technical Screening Assignment
  • Domain: Structural Engineering / Software Development

  • Submitted by: Divit Singhania
  • Program: B.Tech Computer Science (AI & ML)
  • Institution: VIT Bhopal University

🎥 Video Demonstration

A short screen-recorded demonstration of the code execution and generated plots is available below:

🔗 YouTube (Unlisted) Video Link: Click here

🧠 Project Overview

This repository contains Python scripts to generate 2D and 3D Shear Force Diagrams (SFD) and Bending Moment Diagrams (BMD) from an Xarray dataset, closely replicating MIDAS Civil post-processing visualizations.

The project demonstrates:

  • Correct use of FEM element connectivity
  • Accurate node-based geometric reconstruction
  • Preservation of sign conventions from the dataset
  • Professional-quality 2D and 3D structural plots

📁 Repository Structure

xarray-visualization/
│
├── data/
│   ├── screening_task.nc
│   ├── node.py
│   └── element.py
│
├── scripts/
│   ├── xarray_usage.py
│   ├── task1_2d.py
│   └── task2_3d.py
│
├── figures/
│   ├── dataset_visualization.png
│   ├── node_element_connectivity.png
│   ├── SDF_2D.png
│   ├── BMD_2D.png
│   ├── SDF_3D.png
│   └── BMD_3D.png
│
├── report/
│   └── Report.pdf
│
├── requirements.txt
├── README.md
└── .gitignore

📊 Dataset Description

screening_task.nc (Xarray Dataset)

  • Dimensions

  • Element → Beam element IDs

  • Component → Internal force components

  • Force Components Used

  • Vy_i, Vy_j → Shear force at start/end node

  • Mz_i, Mz_j → Bending moment at start/end node

Suffix meaning:

  • _i → Start node of element
  • _j → End node of element

dataset_visualization

Figure 1: Xarray dataset structure and force components

🧩 Node Coordinates & Element Connectivity

node.py defines node geometry:

node_id → (x, y, z)

element.py defines FEM connectivity:

element_id → (start_node, end_node)

node_element_conectivity

Figure 2: Node coordinates and element connectivity. All plots use actual geometry — no assumed or artificial coordinates.

🧪 Scripts Overview

1️⃣ xarray_usage.py

Inspects dataset structure

  • Identifies force components.
  • Extracts tabular force data for verification.

2️⃣ task1_2d.py — Task-1 (2D Plots)

Generates 2D Shear Force (SFD) and Bending Moment (BMD) diagrams for the Central Longitudinal Girder elements: [15, 24, 33, 42, 51, 60, 69, 78, 83].

Plotting Logic:

  • SFD: Step-wise (constant per element).
  • BMD: Linear interpolation between nodes.
  • Sign Convention: Preserved exactly from the dataset.

SFD_2D

Figure 3: 2D Shear Force Diagram

BMD_2D

Figure 4: 2D Bending Moment Diagram

3️⃣ task2_3d.py — Task-2 (3D MIDAS-Style Plots)

Generates 3D SFD & BMD for all five longitudinal girders.

Visualization Features:

  • X: Bridge length | Z: Bridge width | Y: Force magnitude (vertical extrusion).
  • Vertical Hatching: "Fence" style plotting for transparency.
  • Heat-map Coloring: Jet colormap (Blue → Red) based on magnitude.
  • Global Scaling: Auto-scaled to maintain visual proportions.

SFD_3D

Figure 5: 3D Shear Force Diagram (SFD) — All Girders

BMD_3D

Figure 6: 3D Bending Moment Diagram (BMD) — All Girders

▶️ How to Run the Code

# 1. Install dependencies
pip install -r requirements.txt

# 2. Navigate to scripts folder
cd scripts

# 3. Run verification script
python xarray_usage.py

# 4. Run Task 1 (2D Plots)
python task1_2d.py

# 5. Run Task 2 (3D Plots)
python task2_3d.py

🧾 Report Documentation

A detailed PDF report is available, covering dataset inspection, code logic, plot construction, and verification against marking criteria.

📄 Read the Report

🛠️ Tech Stack

  • Python 3.11
  • Xarray – Dataset handling
  • NumPy – Numerical operations
  • Plotly – 2D & 3D visualization
  • netCDF4 – Dataset backend
  • Pandas - Dataset visualization

✅ Alignment with Marking Criteria

Criterion Status Implementation
Correct node coordinates ✅ Imported directly from node.py
Correct element connectivity ✅ Imported directly from element.py
Sign convention preserved ✅ No manual flipping; visualization matches raw data
Visual clarity & scaling ✅ Proper axes labels, 1.5x Z-expansion, auto-scaling
MIDAS-style 3D plots ✅ Vertical extrusion + vertical hatching + heat-map colors

📦 Files Included

  • xarray_usage.py – Dataset inspection
  • task1_2d.py – 2D SFD & BMD
  • task2_3d.py – 3D MIDAS-style SFD & BMD
  • node.py, element.py – Structural data
  • screening_task.nc – Force dataset
  • SFD_BMD_Report.pdf – Documentation

🏁 Conclusion

This project demonstrates how professional structural post-processing—commonly available in commercial tools like MIDAS Civil—can be reproduced using open-source Python libraries, while maintaining engineering correctness, geometric fidelity, and visual clarity.

📜 License

This project is licensed under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license, as required by FOSSEE for screening task submissions.