shorten paper

Author: DaJansenGit

paper.md

@@ -47,54 +47,52 @@ bibliography: paper.bib
 
 # Summary
 
-Building Information Modeling (BIM) offers comprehensive data about buildings, but transforming this information into domain-specific simulation models remains challenging. **bim2sim** addresses this gap by providing a Python framework that transforms Industry Foundation Classes (IFC) models into simulation models for multiple domains. This open-source framework implements a two-stage approach with a uniform meta-structure for IFC data extraction and domain-specific plugins for simulation model generation. The framework currently focuses on Building Energy Performance Simulation (BEPS) and Heating, Ventilation, and Air Conditioning (HVAC) simulations, with additional support for Computational Fluid Dynamics (CFD) and Life Cycle Assessment (LCA). The framework significantly reduces manual effort in simulation model creation while providing extensibility for future domain-specific applications.
+Building Information Modeling (BIM) offers comprehensive data about buildings, but transforming this information into domain-specific simulation models remains challenging. **bim2sim** addresses this gap by providing a Python framework that transforms Industry Foundation Classes (IFC) models into simulation models for multiple domains. This open-source framework implements a two-stage approach with a uniform meta-structure for IFC data extraction and domain-specific plugins for simulation model generation. The framework focuses on Building Energy Performance Simulation (BEPS) and Heating, Ventilation, and Air Conditioning (HVAC) simulations, with support for Computational Fluid Dynamics (CFD) and Life Cycle Assessment (LCA).
 
 # Statement of Need
-Energy-efficient building design and operation heavily rely on BEPS, but creating these simulation models manually is notoriously time-consuming, error-prone, and requires specialized expertise. While BIM provides a rich source of building data, the direct use of this information for simulation faces several challenges:
+Energy-efficient building design and operation heavily rely on BEPS, but creating these simulation models manually is time-consuming, error-prone, and requires specialized expertise. While BIM provides rich building data, direct use for simulation faces several challenges:
 
-1. **Geometric Discrepancies**: Architectural BIM models employ geometric representations that differ from those required by simulation tools, necessitating complex transformations (e.g., second-level Space Boundary (SB))
-2. **Semantic Gaps**: Critical simulation parameters (material properties, usage profiles, HVAC specifications) are often missing or incompletely defined in BIM models
-3. **Topological Gaps**: HVAC simulation requires accurate component connection information, but topological relationships are frequently incorrect or missing in existing BIM files
-4. **Data Format Incompatibilities**: Various simulation domains and tools demand specific input formats and data schemas that differ from standard BIM exports
+1. **Geometric Discrepancies**: Architectural BIM models employ geometric representations that differ from simulation requirements
+2. **Semantic Gaps**: Critical simulation parameters are often missing in BIM models
+3. **Topological Gaps**: HVAC simulation requires accurate component connections often missing in BIM files
+4. **Data Format Incompatibilities**: Simulation domains demand specific input formats different from BIM exports
 
-According to case studies cited in the literature, creating simulation models manually can take days to weeks for complex buildings, with significant risk of errors and inconsistencies. This creates a major bottleneck in the design process and limits the application of building performance simulation in practice.
+Creating simulation models manually can take days to weeks for complex buildings, creating a major bottleneck in the design process.
 
-**bim2sim** addresses these critical needs by:
+**bim2sim** addresses these needs by:
 
-1. Automating the transformation from IFC data to simulation models, reducing model creation time from days to under an hour for high-quality BIM inputs
-2. Providing a flexible Python framework that can be easily extended to support new simulation tools and domains
-3. Supporting multiple simulation domains and tools through specialized plugins (TEASER [@Remmen.2016], EnergyPlus [@EnergyPlus.2001], AixLib [@Maier.2023], Comfort, HKESim, LCA, and OpenFOAM)
-4. Handling imperfect IFC data through repair algorithms and user decision management
-5. Maintaining OpenBIM compatibility while minimizing external tool dependencies
+1. Automating transformation from IFC to simulation models, reducing creation time from days to under an hour
+2. Providing a flexible Python framework extensible to new simulation tools
+3. Supporting multiple domains through specialized plugins
+4. Handling imperfect IFC data through repair algorithms
+5. Maintaining OpenBIM compatibility with minimal dependencies
 
-The framework aims to enable engineers, architects, researchers, and practitioners to efficiently incorporate building performance simulation into their workflows, supporting better-informed decisions. By reducing the time and expertise barriers to simulation model creation, **bim2sim** helps bridge the gap between building design and performance analysis.
+The framework enables efficient incorporation of building performance simulation into workflows, supporting better-informed decisions.
 
 # Architecture and Implementation
 
-**bim2sim** is implemented in Python, making it accessible and interoperable with other tools in the building analysis ecosystem. The general structure and the existing plugins are illustrated in \autoref{fig:bim2sim_framework}.
+**bim2sim** is implemented in Python with a two-stage architecture illustrated in \autoref{fig:bim2sim_framework}.
 
 ![bim2sim framework structure and plugins. Dashed plugins are still under heavy active development.\label{fig:bim2sim_framework}](docs/source/img/static/bim2sim_framework_overview.png)
 
-The tool employs a two-stage architecture:
-
-1. **Base Framework**: Transforms IFC data into a uniform meta-structure that preserves essential building information while resolving inconsistencies
-2. **Domain-Specific Plugins**: Convert the meta-structure into simulation-ready models for specific applications
+1. **Base Framework**: Transforms IFC data into a uniform meta-structure
+2. **Domain-Specific Plugins**: Convert the meta-structure into simulation-ready models
 
 ## Core Components of Base Framework
 
 - **Elements**: Domain-specific meta-structure for building component classes 
-- **Tasks**: Modular processing steps that can be sequenced into workflows
-- **Playground**: Task execution environment that manages the transformation process
-- **Simulation Settings**: Configuration system for customizing simulation parameters
+- **Tasks**: Modular processing steps sequenced into workflows
+- **Playground**: Task execution environment managing transformations
+- **Simulation Settings**: Configuration system for customizing parameters
 - **Plugins**: Domain-specific extensions for different simulation targets
 
 ## Key Features
 
-- IFC parser that extracts geometric and semantic data utilizing the existing Python implementation of IfcOpenShell [@IfcOpenShell]
-- Decision management for handling ambiguities in IFC data
-- Enrichment processes for adding missing information (materials, usage profiles) 
-- Algorithms to correct missing or incorrect SB information
-- Algorithms for simplifying HVAC systems to make them suitable for Modelica simulations
+- IFC parser utilizing IfcOpenShell [@IfcOpenShell]
+- Decision management for handling ambiguities
+- Enrichment processes for adding missing information
+- Algorithms to correct Space Boundary (SB) information
+- HVAC system simplification for Modelica simulations
 - Exporters for different simulation platforms
 
 ## Available Plugins
@@ -116,12 +114,11 @@ The following plugins are currently in development and exist only in feature bra
 
 # Existing Publications on Methodology
 
-* The methodology and use case demonstration for the BEPS-focused plugins **TEASER** and **EnergyPlus** will be published in a forthcoming paper by Jansen et al. [@Jansen2025bim2sim]
-* The methodology and detailed implementation of the HVAC-focused plugins **AixLib** and **HKESim** are comprehensively documented in Jansen et al. [@jansen2023bim2sim]
-* The algorithms for handling geometric and semantic inconsistencies within the SBs are presented in Richter et al. [@Richter.2021]
-* The framework for the BEPS-focused plugin **Comfort** has been presented in Richter et al. [@richterFrameworkAutomatedIFCbased2023]. 
-  The implementation of this Comfort plugin is further described and evaluated on a use case on future climate scenarios in Richter et al. [@richterExtendingIFCBasedBim2sim2023]
-* The fundamentals of the methodology of the CFD-focused plugin **OpenFOAM** has been presented by Richter et al. [@richterExtendingIFCbasedFramework2024] and extended to improve mesh quality by Hochberger et al. [@hochbergerAutomatedIFCbasedMesh2024].
+* The methodology for **TEASER** and **EnergyPlus** plugins will be published in Jansen et al. [@Jansen2025bim2sim]
+* Implementation of **AixLib** and **HKESim** plugins are documented in Jansen et al. [@jansen2023bim2sim]
+* Algorithms for handling SBs are presented in Richter et al. [@Richter.2021]
+* The **Comfort** plugin framework is presented in Richter et al. [@richterFrameworkAutomatedIFCbased2023] and evaluated in Richter et al. [@richterExtendingIFCBasedBim2sim2023]
+* The methodology of **OpenFOAM** plugin has been presented by Richter et al. [@richterExtendingIFCbasedFramework2024] and extended by Hochberger et al. [@hochbergerAutomatedIFCbasedMesh2024]
 
 # Comparison with Similar Tools
 **bim2sim** addresses the challenge of leveraging BIM data for building energy simulations, a field with several existing approaches. In our paper [@Jansen2025bim2sim] (currently under review), we conducted a comprehensive analysis of these BIM-to-simulation tools. \autoref{tab:bim2bemApproaches} presents an abbreviated comparative overview of these tools. The complete analysis in the to-be-published paper considers additional dimensions such as IFC version support, space and surface boundary handling, and data enrichment methods. In the abbreviated version shown here, we focus on the most important aspects: simulation domains (BEPS, HVAC), modular architecture, open-source availability, and implementation technologies.
@@ -147,8 +144,8 @@ The following plugins are currently in development and exist only in feature bra
 | bim2sim | bim2sim | EP, Mod | Mod | Y | Y | Py, IFC |
 
 # Acknowledgments
-**bim2sim** was developed through collaboration between academic institutions (RWTH Aachen University's EBC - Institute for Energy Efficient Buildings and Indoor Climate, E3D - Institute of Energy Efficiency and Sustainable Building) and industry partners (ROM Technik GmbH). The framework was initially created under the "BIM2SIM" project with continued enhancement through the follow-up "BIM2Praxis" project, both funded by the German Federal Ministry for Economic Affairs and Energy (BMWi/BMWK).
+**bim2sim** was developed through collaboration between academic institutions (RWTH Aachen University's EBC - Institute for Energy Efficient Buildings and Indoor Climate, E3D - Institute of Energy Efficiency and Sustainable Building) and industry partners (ROM Technik GmbH). The framework was initially created under the "BIM2SIM" project with continued enhancement through the "BIM2Praxis" project, both funded by the German Federal Ministry for Economic Affairs and Energy (BMWi/BMWK).
 
-We acknowledge the funding support from the German Federal Ministry for Economic Affairs and Energy (grant number 03ET1562A/B) and the Federal Ministry for Economic Affairs and Climate Action (grant number 3EN1050A/B).
+We acknowledge funding support from the German Federal Ministry for Economic Affairs and Energy (grant number 03ET1562A/B) and the Federal Ministry for Economic Affairs and Climate Action (grant number 3EN1050A/B).
 
-# References
+# References