IFC.Circul 🏗️

A Python package for extracting space-level topological relationships from IFC (Industry Foundation Classes) building models.

📋 Overview

This project was developed as part of a master's thesis research at the Technical University of Munich.

Thesis Details

• Title: Reasoning IFC Models for Space-level Circulation Design Rationale using Graph-based Analysis and Community Detection
• Author: Harshal Gunjal
• Supervisor: Jiabin Wu
• Institution: Chair of Computational Modeling and Simulation, Technical University of Munich

⚙️ Installation

Prerequisites

• Git
• Anaconda Navigator
• PyCharm Community Edition
• Gephi

Required Packages

• IfcOpenShell
• Graphviz
• Trimesh
• rtree
• scipy
• pyglet
• NumPy
• NetworkX

Setup Instructions

1. Clone the repository:

   git clone https://github.com/hgunjal/IFC.Circul

2. Create and configure environment:

   • Launch Anaconda Navigator
   • Create a new environment
   • Install all required packages listed above

3. Open the project in PyCharm Community Edition

🚀 Usage

1. Configure Input/Output Settings

   • Open config.py
   • Set the input IFC file path
   • Configure output directories

2. Generate Topological Relationships

   • Run ifc_to_csv_or_json.py
   • This will create space-level topological relationships in JSON format

3. Create Graph Representation

   • Run ifc_to_graph.py
   • Converts the JSON file to a DOT graph file

4. Analyze Results

   • Open the generated DOT file using Gephi
   • Perform graph analysis and visualization
   • Girvan-Newman Clustering to perform community detection and Avg. Path Length to perform centrality analysis

📊 Sample Visualization

1. Building Model Visualization

3D visualization of the IFC building model

Floor plan view of the IFC model

2. Topological Analysis

Space-level topological graph where:

• Different node colors represent different building floors
• Green edges indicate exits
• Red edges represent stair accessibility
• Regular edges show horizontal accessibility between spaces

Centrality analysis performed in Gephi, highlighting nodes with highest betweenness centrality on the right side, indicating key circulation points in the building

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For questions and support, please open an issue in the GitHub repository.