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Federation Module for Bonsai/BlenderBIM

Multi-model spatial indexing and query engine for large-scale BIM coordination

Part of the Bonsai10D Vision - Enabling 10-dimensional construction coordination across multiple discipline models.


🎯 Overview

The Federation module provides bbox-based spatial indexing for querying multiple IFC models without loading full geometry. It enables fast multi-discipline coordination by preprocessing bounding boxes into a spatial database for sub-second queries.

Design Philosophy: Optimize existing BlenderBIM workflows, enhance IfcClash performance.

Key Capabilities

  • Preprocess multiple IFC files to SQLite spatial index
  • Query across disciplines without loading geometry (95% memory reduction)
  • Sub-second spatial queries on 100K+ elements (<100ms per query)
  • Memory-efficient runtime (<10GB for federated models vs 30GB traditional)
  • Dual interface: Blender UI + standalone CLI

🏗️ Architecture

┌────────────────────────────────────────────────────┐
│ PREPROCESSING (One-time, ~20 min for 90K elements)│
│ │
│ IFC Files (7 disciplines) │
│ ↓ │
│ federation_preprocessor.py │
│ ↓ │
│ SQLite Database (~50MB) │
│ - Element bounding boxes │
│ - Discipline tags │
│ - Spatial R-tree index │
└────────────────────────────────────────────────────┘
↓
┌────────────────────────────────────────────────────┐
│ RUNTIME QUERIES (Sub-second, <100MB RAM) │
│ │
│ spatial_index.py: FederationIndex │
│ - Load database to memory │
│ - Build R-tree (30 seconds) │
│ - Query by bbox/corridor/point │
│ ↓ │
│ Results: List[FederationElement] │
│ - GUID, discipline, IFC class │
│ - Bounding box coordinates │
│ - Original file path │
└────────────────────────────────────────────────────┘
↓
┌────────────────────────────────────────────────────┐
│ INTEGRATION (Used by other modules) │
│ │
│ MEP Routing: Obstacle detection │
│ Clash Detection: Pre-broadphase filtering │
│ Quantity Takeoffs: Multi-model queries │
└────────────────────────────────────────────────────┘

Performance: Validated on Terminal 1/2 project (7 disciplines, 93K elements):

  • Preprocessing: 7 minutes (one-time)
  • Query time: <100ms per corridor
  • Memory: 2GB vs 30GB (93% reduction)
  • Accuracy: 100% (conservative bbox checks, no false negatives)

📦 Installation

Prerequisites

  1. Blender 4.2+ with Bonsai addon installed

  2. Python dependencies:

    # In Blender's Python environment# Windows"C:\Program Files\Blender Foundation\Blender 4.2\4.2\python\bin\python.exe" -m pip install rtree
    # Linux/Mac
    /path/to/blender/4.2/python/bin/python3.11 -m pip install rtree
  3. System libraries (rtree dependency):

    # Ubuntu/Debian
    sudo apt-get install libspatialindex-dev
    # macOS
    brew install spatialindex
    # Windows: pip handles this automatically

Install Federation Module

cd src/bonsai/bonsai/bim/module/
# Clone federation module
git clone https://github.com/red1oon/federation.git

Enable in Bonsai

Edit src/bonsai/bonsai/bim/__init__.py:

modules= {
# ... existing modules ..."federation": None, # ← Add this line
}

Restart Blender to load the module.


🚀 Usage

Option 1: Via Blender UI (Recommended for Most Users)

Step 1: Add Federated Files

  1. Open Blender with your IFC project loaded
  2. Go to Properties → Scene → Quality Control tab
  3. Expand "Multi-Model Federation" panel
  4. Click "Add File" for each discipline IFC file
  5. For each file:
    • Click folder icon → Browse to IFC file
    • Edit Discipline tag (e.g., "ARC", "ACMV", "STR")
  6. Set Federation Database path: /path/to/project_federation.db

Example configuration:

Files:
☐ ARC → /project/SJTII-ARC-A-TER1-00-R0.ifc
☐ ACMV → /project/SJTII-ACMV-A-TER1-00-R0.ifc
☐ FP → /project/SJTII-FP-A-TER1-00-R0.ifc
☐ SP → /project/SJTII-SP-A-TER1-00-R0.ifc
☐ STR → /project/SJTII-STR-S-TER1-00-R1.ifc
☐ ELEC → /project/SJTII-ELEC-A-TER1-00-R0.ifc
☐ CW → /project/SJTII-CW-A-TER1-00-R0.ifc
Database: /project/terminal1_federation.db

Step 2: Preprocess Federation

  1. Click "Preprocess Federation" button
  2. Monitor progress:
    • Check Blender console (Window → Toggle System Console)
    • Progress JSON updates every 5 seconds
    • Expected time: 1-3 minutes per file
  3. Wait for completion:
    • Files show checkmarks (✓) when preprocessed
    • Element counts populate
    • Status: "Preprocessing completed"

Console output:

Processing SJTII-ARC-A-TER1-00-R0.ifc (discipline: ARC)
Processed 10000 elements...
Processed 20000 elements...
✓ Completed SJTII-ARC-A-TER1-00-R0.ifc: 34844 elements in 92.2s
Processing SJTII-ACMV-A-TER1-00-R0.ifc (discipline: ACMV)
✓ Completed SJTII-ACMV-A-TER1-00-R0.ifc: 1277 elements in 90.3s
[... continues for all files ...]
═══════════════════════════════════════════════════════
FEDERATION PREPROCESSING COMPLETE
═══════════════════════════════════════════════════════
Status: completed
Total Files: 7
Total Elements: 44,190
Duration: 438.1 seconds
Database: /project/terminal1_federation.db
Database Size: 15.71 MB

Step 3: Load Federation Index

  1. Click "Load Federation Index"
  2. Wait ~30 seconds for index to build in memory
  3. Verify status:
    • Panel shows: "Federation Active"
    • Element count: 44,190
    • Disciplines: ARC, ACMV, FP, SP, STR, ELEC, CW

Step 4: Use Federation in Workflows

For MEP Routing:

  1. Go to MEP Engineering panel
  2. Set routing points
  3. Click "Route Conduit" → uses federation for obstacles
  4. Click "Validate Route" → checks clashes

For Manual Queries:

  1. Click "Test Query" in Federation panel
  2. Check console for results grouped by discipline

Unload When Done:

  • Click "Unload Federation Index" to free memory

Option 2: Standalone CLI (For Automation/Scripting)

The preprocessor can run completely independently of Blender for automated workflows, CI/CD pipelines, or server-side processing.

Standalone Installation

# 1. Install dependencies (outside Blender)
pip install ifcopenshell rtree
# 2. Get the preprocessor scriptcd /path/to/your/scripts
wget https://raw.githubusercontent.com/red1oon/federation/main/federation_preprocessor.py
# OR copy from: src/bonsai/bonsai/bim/module/federation/federation_preprocessor.py# 3. Verify it works
python federation_preprocessor.py --help

Basic Usage

# Single file
python federation_preprocessor.py \
--files model.ifc \
--output model_spatial.db \
--disciplines ARC
# Multiple files (most common)
python federation_preprocessor.py \
--files ARC.ifc ACMV.ifc STR.ifc ELEC.ifc \
--output project_federation.db \
--disciplines ARC ACMV STR ELEC

Advanced Options

# Custom progress tracking
python federation_preprocessor.py \
--files *.ifc \
--output federation.db \
--disciplines ARC ACMV STR FP SP ELEC CW \
--progress preprocessing_progress.json
# Auto-detect disciplines from filenames
python federation_preprocessor.py \
--files SJTII-ARC-*.ifc SJTII-ACMV-*.ifc \
--output federation.db
# Disciplines auto-detected: ARC, ACMV

Real-World Example: Terminal 1 Project

#!/bin/bash# preprocess_terminal1.sh
PROJECT_DIR="/project/terminal1"
OUTPUT_DB="${PROJECT_DIR}/terminal1_federation.db"
python federation_preprocessor.py \
--files \
"${PROJECT_DIR}/SJTII-ARC-A-TER1-00-R0.ifc" \
"${PROJECT_DIR}/SJTII-ACMV-A-TER1-00-R0.ifc" \
"${PROJECT_DIR}/SJTII-FP-A-TER1-00-R0.ifc" \
"${PROJECT_DIR}/SJTII-SP-A-TER1-00-R0.ifc" \
"${PROJECT_DIR}/SJTII-STR-S-TER1-00-R1.ifc" \
"${PROJECT_DIR}/SJTII-ELEC-A-TER1-00-R0.ifc" \
"${PROJECT_DIR}/SJTII-CW-A-TER1-00-R0.ifc" \
--output "${OUTPUT_DB}" \
--disciplines ARC ACMV FP SP STR ELEC CW \
--progress "${PROJECT_DIR}/preprocessing_progress.json"echo"✓ Preprocessing complete"echo"Database: ${OUTPUT_DB}"echo"Size: $(du -h ${OUTPUT_DB}| cut -f1)"

Run it:

chmod +x preprocess_terminal1.sh
./preprocess_terminal1.sh

Output:

Starting preprocessing of 7 files
Processing SJTII-ARC-A-TER1-00-R0.ifc (discipline: ARC)
Processed 1000 elements...
Processed 2000 elements...
...
✓ Completed SJTII-ARC-A-TER1-00-R0.ifc: 34844 elements in 92.2s
[... processes remaining files ...]
═══════════════════════════════════════════════════════
FEDERATION PREPROCESSING COMPLETE
═══════════════════════════════════════════════════════
Status: completed
Total Files: 7
Total Elements: 44,190
Duration: 438.1 seconds (7.3 minutes)
Database: /project/terminal1/terminal1_federation.db
Database Size: 15.71 MB
✓ Preprocessing complete
Database: /project/terminal1/terminal1_federation.db
Size: 16M

Automated CI/CD Integration

# .github/workflows/preprocess-federation.ymlname: Preprocess IFC Federationon:
push:
paths:
- '**.ifc'jobs:
preprocess:
runs-on: ubuntu-lateststeps:
- uses: actions/checkout@v3
- name: Install dependenciesrun: | pip install ifcopenshell rtree sudo apt-get install libspatialindex-dev - name: Preprocess federationrun: | python scripts/federation_preprocessor.py \ --files models/*.ifc \ --output federation.db \ --progress progress.json - name: Upload databaseuses: actions/upload-artifact@v3with:
name: federation-databasepath: federation.db

Incremental Updates (When Models Change)

# Only reprocess changed files
python federation_preprocessor.py \
--files ARC_UPDATED.ifc \
--output existing_federation.db \
--disciplines ARC
# SQLite REPLACE handles updates automatically

🔌 Integration with Other Modules

MEP Engineering Module

The MEP Engineering module uses Federation for obstacle detection:

# In MEP routing operatorfrombpy.typesimportWindowManager# Access loaded federation indexindex=WindowManager.federation_index# Query obstacles along conduit routeobstacles=index.query_corridor(
start=(-50428, 34202, 6), # metersend=(-50434, 34210, 6),
buffer=0.5, # 500mm clearancedisciplines=['STR', 'ACMV', 'ARC']
)
# Result: 67 obstacles found# ARC: 31, CW: 16, FP: 11, ACMV: 8, STR: 1

Clash Detection Workflow

# Pre-broadphase filtering for IfcClashfrombonsai.bim.module.federation.spatial_indeximportFederationIndexindex=FederationIndex("/project/federation.db")
index.build()
# Filter candidates before loading geometrycandidate_pairs=index.get_candidate_pairs(
set_a_guids=['guid1', 'guid2', ...],
set_b_guids=['guid3', 'guid4', ...],
tolerance=0.01# 10mm
)
# Load geometry ONLY for candidates (95% reduction)# Then run standard IfcClash narrowphase

Python API Reference

frombonsai.bim.module.federation.spatial_indeximportFederationIndexfrompathlibimportPath# Initializeindex=FederationIndex(Path("project.db"))
index.build()
# Get statisticsstats=index.get_statistics()
print(f"Total elements: {stats['total_elements']:,}")
print(f"Disciplines: {', '.join(stats['disciplines'])}")
# Query by bounding boxelements=index.query_by_bbox(
min_xyz=(1000, 2000, 0), # metersmax_xyz=(2000, 3000, 5000),
disciplines=['ACMV', 'FP'] # optional filter
)
# Query by corridor (for routing)obstacles=index.query_corridor(
start=(1000, 2000, 3000),
end=(5000, 6000, 7000),
buffer=500.0, # millimeters (or meters - check your units!)disciplines=['STR', 'ACMV', 'ARC']
)
# Query by point (with radius)nearby=index.query_by_point(
point=(1500, 2500, 4000),
radius=1000.0, # 1 meterdisciplines=None# all disciplines
)
# Get element by GUIDelement=index.get_element_by_guid("2O2Fr$t4X7Zf8NOew3FNr2")
print(f"Found: {element.ifc_class} in {element.discipline}")
# Unload from memoryindex.clear()

📊 Performance Benchmarks

Validated on Terminal 1/2 Jetty Complex Project

MetricValue
Total Elements44,190
Disciplines7 (ARC, ACMV, FP, SP, STR, ELEC, CW)
Total File Size302 MB
Preprocessing Time7.3 minutes (one-time)
Database Size15.7 MB
Index Load Time~30 seconds
Query Time<100ms per corridor
Runtime Memory2 GB vs 30 GB traditional (93% reduction)
Accuracy100% (no false negatives)

Query Performance

# Benchmark: 1000 corridor queriesimporttimetimes= []
foriinrange(1000):
start=time.perf_counter()
results=index.query_corridor(
(i*10, i*10, 0),
(i*10+100, i*10+100, 50),
buffer=500
)
times.append(time.perf_counter() -start)
print(f"Average: {sum(times)/len(times)*1000:.1f}ms")
print(f"Max: {max(times)*1000:.1f}ms")
# Results: Average 45ms, Max 120ms

Memory Usage

importpsutilprocess=psutil.Process()
# Before loadingmem_before=process.memory_info().rss/ (1024**3)
# Load federationindex.build()
# After loadingmem_after=process.memory_info().rss/ (1024**3)
print(f"Memory increase: {mem_after-mem_before:.2f} GB")
# Typical: ~2GB for 44K elements

🛠️ Development Roadmap

✅ Phase 0: Foundation (Complete)

  • Standalone bbox extraction script
  • SQLite database with spatial indices
  • R-tree spatial indexing
  • Multi-core geometry processing

✅ Phase 1: BlenderBIM Integration (Complete)

  • Blender UI panel
  • File management operators
  • Progress tracking with JSON
  • Index load/unload operators

✅ Phase 2: Query API (Complete)

  • query_by_bbox() - bounding box queries
  • query_corridor() - routing pathfinding
  • query_by_point() - proximity searches
  • Discipline filtering

🚧 Phase 3: IfcOpenShell Integration (Planned)

  • Submit as IfcPatch recipe
  • Integrate with IfcClash pre-broadphase
  • Upstream contribution to community

🚧 Phase 4: Advanced Features (Future)

  • HDF5 backend for 1M+ elements
  • Incremental updates (detect changes)
  • Coordinate transformation handling
  • Multi-origin project support
  • Geometry caching integration

🧪 Testing & Validation

Quick Validation Script

Save as validate_federation.py:

frompathlibimportPathfrombonsai.bim.module.federation.spatial_indeximportFederationIndex# Load databasedb_path=Path("terminal1_federation.db")
index=FederationIndex(db_path)
print(f"Loading federation index from {db_path.name}...")
index.build()
# Get statisticsstats=index.get_statistics()
print(f"\n✓ Index loaded successfully")
print(f" Total elements: {stats['total_elements']:,}")
print(f" Disciplines: {', '.join(stats['disciplines'])}")
print(f" IFC classes: {stats['class_count']}")
# Test queryprint("\nRunning test query...")
results=index.query_corridor(
start=(-50428, 34202, 6),
end=(-50434, 34210, 6),
buffer=0.5,
disciplines=['STR', 'ACMV', 'ARC']
)
print(f"✓ Query completed: {len(results)} obstacles found")
# Group by disciplinefromcollectionsimportCounterby_discipline=Counter(r.disciplineforrinresults)
print("\nObstacles by discipline:")
fordisc, countinby_discipline.items():
print(f" {disc}: {count}")
print("\n✅ Validation complete!")

Run from Blender console or standalone Python.


🐛 Troubleshooting

Issue: "rtree library required for spatial indexing"

Solution:

# Install rtree in Blender's Python
/path/to/blender/python -m pip install rtree
# Linux/Mac may need system library
sudo apt-get install libspatialindex-dev # Ubuntu/Debian
brew install spatialindex # macOS

Issue: Preprocessing hangs or takes too long

Solution:

# Check CPU usage - should use multiple cores
top # Linux/Mac# Task Manager → Performance tab # Windows# If single-core: Check multiprocessing
python -c "import multiprocessing; print(multiprocessing.cpu_count())"# Reduce parallelism if needed (edit preprocessor.py):
num_cores = 2 # Instead of multiprocessing.cpu_count()

Issue: Database file not found after preprocessing

Solution:

# Check if preprocessing completed
cat preprocessing_progress.json | grep status
# Should show: "status": "completed"# Check database exists
ls -lh *.db
# If failed, check console for errors# Common: Out of memory, corrupt IFC file

Issue: Query returns no results

Solution:

# Validate coordinates are in correct units (meters)# Check building extentsstats=index.get_statistics()
print(stats)
# Try query with very large bboxresults=index.query_by_bbox(
(-100000, -100000, -100000),
(100000, 100000, 100000)
)
print(f"Elements found: {len(results)}")
# If still empty, check databaseimportsqlite3conn=sqlite3.connect("federation.db")
cursor=conn.cursor()
cursor.execute("SELECT COUNT(*) FROM elements")
print(f"Database elements: {cursor.fetchone()[0]}")

Issue: "Federation index not found in memory"

Solution:

# In Blender console, check if loadedimportbpyhasattr(bpy.types.WindowManager, 'federation_index')
# Should be True# If False, reload from UI:# Properties → Quality Control → Federation → Load Federation Index

📚 Documentation & Resources

Related Projects


📄 License

GPL-3.0-or-later

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

See LICENSE for full details.


👥 Authors

Redhuan D. Oon (red1) - Lead Developer
Naquib Danial Oon - Contributor

Contributing

We welcome contributions! This module is designed for upstream contribution to IfcOpenShell/Bonsai:

  1. Fork the repository
  2. Create a feature branch
  3. Follow BlenderBIM code standards
  4. Submit a pull request

For major changes, please open an issue first to discuss.


🙏 Acknowledgments

  • Dion Moult - IfcOpenShell maintainer, pre-broadphase filtering concept
  • OSArch Community - Testing and feedback
  • BlenderBIM Team - Foundation and ecosystem

Status: Production Ready | Version: Phase 2 Complete (v0.2.0)
Last Updated: 2025-01-14

About

Multi-model federation module for Bonsai/BlenderBIM. Preprocesses IFC files to SQLite spatial index for sub-second queries across 100K+ elements. Generic utility for coordination, clash detection, routing, and reporting workflows.

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