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[21] Enhancing Engineering and Architectural Design Through Virtual Reality and Machine Learning Integration

EBSCO – Screened Emerging Applications (2024–2026) 2025

Paper Description extracted from PDF · abstract · 98 words

The present study introduces a framework for integrating building information modelling (BIM) to building energy modelling (BEM) using labelled property graphs (LPG) and the Modelica simulation environment. The proposed methodology leverages graphs to effectively represent space boundarytopologyinformation.Graphsexcelatmodellingrelationships,enablingefficientqueries, intuitivevisualizationsandeasiererrordetectioninBIMmodels.Graph-basedoperationsareapplied to adapt the model for energy modelling. Additional steps including IFC validation, active systems and building operation parameters parsing, zoning process, and Modelica dynamic energy model generationarethoroughlydiscussed,providingvaluableinsights.Performance-wise,theframework showed promising results, achieving acceptable parsing times of only a few seconds. A case study of a multistory building in France demonstrated the framework’s effectiveness and functionality. ThemethodologystreamlinesthetraditionallycomplexBIM-to-BEMworkflow,ensuringrobustdata mappingandaccurateenergysimulations,andofferingpracticalguidelinesforfutureapplications. ARTICLE HISTORY Received12March2024 Accepted30December2024

AuthorsShehadeh, Ali and Alshboul, Odey
Year2025
VenueBuildings (2075-5309)
DOI10.3390/buildings15030328
Source DatabaseEBSCO (Applied Science & Technology)
Bridge-to-GNNCategory Borderline
GNN ArchitectureGNN (heuristic — verify)
Graph EncodingNot yet extracted from PDF
AEC TaskNot yet extracted from PDF
CohortMature Applications (2024–2026)

Extracted Methodology heuristic — verify before citing

Dataset Size45 nodes (heuristic — verify)
Implementation FrameworkRevit / Dynamo, Neo4j (heuristic — verify)
Primary MetricAccuracy (heuristic — verify)
Quality Assessment2/6 · rigor: Low ·
Code/Data: ✓Baseline: ✓ (heuristic — verify)

Detected Technical Stack auto-detected from PDF · regex catalogue match

GNN architectures detectedKnowledge Graph Embedding (TransE/RotatE/DistMult)
Frameworks / librariesRevit / Dynamo · IFC OpenShell / IfcOpenShell · EnergyPlus · OpenStudio · Neo4j / Cypher · RDF / OWL / SPARQL
Benchmark datasets referencedReplica
Code repositories found in texthttps://github.com/ibpsa/modelica-ibpsa
Dataset stats found45 nodes
Quality (heuristic, 6-flag)3/6 · rigor: Medium
Code/Data: ✓Benchmark: ✓Baseline: ✓CV/Split: —Ablation: —Reproducible: —

Lineage Families

None assigned

Enabled By / Precursors

None tracked

Extended By

None in corpus

Infrastructure Dependencies

Revit / Dynamo (detected from PDF) IFC OpenShell / IfcOpenShell (detected from PDF) EnergyPlus (detected from PDF) OpenStudio (detected from PDF) Neo4j / Cypher (detected from PDF) RDF / OWL / SPARQL (detected from PDF)

Research Frontier Tags

frontier-2025+

Part of the GML/GNN in AEC Systematic Review (PRISMA 2020) — 112 papers, 2020–2026