Enhancing Open BIM Interoperability: Automated Generation of a Structural Model from an Architectural Model

Abstract

Building information modelling (BIM) is an appreciated technology in the field of architecture and construction management. Collaboration of information in BIM has not been fully utilized in the structural engineering stream as many engineers keep on working with previous prevailing design approaches. Failure to adequately facilitate automation in design could lead to structural defects, construction rework, or even structural clashes, with major financial implications. Given the inherent complexity of large-scale construction projects, the ‘manual design and detailing’ of structure is a challenging task and prone to human errors. Against this backdrop, this study developed a 4D building information management approach to facilitate automated structural models for professionals designing all the elements required in reinforced concrete (RC) structures like slabs, beams, and columns. The main contribution of this study is to obtain structural models directly from architecture models automatically, which reduces effort and possible errors in the previous prevailing approaches. The framework enables execution of all the model design works automatically through coding. This is achieved by executing a script which is beneficial for integrated project delivery (IPD). The 3D structural model in BIM software presented in this study extracts and transfers the geometrical data and links these data in Industry Foundation Classes (IFC) files using integration facilitated by Python 3.6 and IFCopenshell. The developed automated programme framework offers a cost-effective and accurate methodology to address the limitations and inefficiencies of traditional methods of structural modelling, which had been carried out manually. The authors have developed a novel tool to extract structural models from architectural models without proprietary software, greatly benefiting BIM managers by enhancing 3D BIM models. This advancement toward Open BIM, crucial for the architecture, engineering, and construction (AEC) industry’s future, is accessible to educators and beginners and highlights BIM’s effectiveness in improving structural analysis and productivity. The core finding of this study is to generate a structural model from an architecture model by automating the script with Python integration of IFC and IFCopenshell. The merits of the developed framework are reduced clashes, more economical structural modelling, and fully automated smart work as functions of the IPD.

1. Introduction

The use of BIM in the AEC industry has been increasing significantly over the decades. BIM alters how the AEC sector functions in designing, documenting, visualising, reporting on buildings and other facilities in accordance with rules, standards, regulations, etc. [1]. BIM includes software and information processing techniques throughout the course of a building project, and facilitates the production, management, and application of digital models for efficient communication and decision-making. It assists AEC specialists in the planning, design, and construction processes, virtually visualising a future building, and identifying potential design, construction, or operational difficulties [2]. The practices of all the concerned disciplines, including civil engineering in general and structural engineering in particular, can benefit from such advantages. In addition, over the past decade, design tools in the AEC industry have evolved from 2D modeling to 3D modeling. BIM as a powerful set of design management tools has recently become an emerging research area. BIM has been utilized across various sectors, integrated with sustainable supply chain management (SSCM), to minimize both labor and material downtime, reduce waste, and optimize resource utilization. This approach addresses the escalating challenges of cost reduction and resource efficiency that have emerged [3,4]. One fundamental standpoint of using BIM is its capacity to join functionalities of various software applications, to visualize results, and to share project materials crosswise over various disciplines and stages where its advantages can be accomplished, including detecting and avoiding clashes before the construction phase. BIM has revolutionized the construction industry and has become a hotly debated topic of discussion in every organization in the AEC industry. In addition, improving teamwork is a fundamental benefit of BIM processes [5]. According to Dasović et.al., 30% of the total cost of projects in the traditional construction has been misused in material wastage, management errors, absence of teamwork, inefficient employment, and insufficient optimization. BIM can help to minimise the costs resulting from such misuses in construction projects [6,7].

There are different types of methods used to achieve interoperability. Interoperability refers to the ability of different systems or components to communicate, exchange data, and operate together seamlessly, often facilitated by standardized formats or protocols, enhancing overall compatibility and efficiency. The most commonly used data are API, direct link and indirect link using add-ons, which are proprietary due to their commercial application. Kochanski and Borkowski explored a method in which visual and generative programming techniques were used, and it was a step toward interoperability and automation [8]. There are also several non-proprietary building data formats currently available [9]. One of them is the IFC, an open standard data format developed by the International Alliance for Interoperability (IAI), which was formed in 1995 by an international consortium of organizations in the AEC industry [10]. The technology for exchanging information using IFC has now been established, but further development in many aspects is still needed before comprehensive interoperability solutions are reached [11].

1.1. The Necessity for Automated Structural Model Extraction

The growing global population compels the AEC industry to seek smarter and more efficient approaches to design and construction. By 2050, the global population is projected to reach 9.7 billion according to the UN [12]. BIM not only enables design and construction teams to work more efficiently, but also allows them to capture valuable data throughout the process [12]. BIM directives are increasingly implemented worldwide, because they facilitate precise and accurate coordination, planning, design, and construction, contributing to reduced project costs, enhanced feasibility, and optimized schedules. Moreover, BIM technology boosts productivity, minimizes waste, and optimizes resource utilization. Minimizing construction waste is vital, as it can pose significant harm to the environment. In fact, construction waste can be effectively reduced or even eradicated by implementing BIM technology at an early stage of a project. BIM serves the backbone of advancement and civilization, with its global impact being felt in construction nowadays [7,13]. A report highlighted that 75% of companies that embraced BIM experienced positive returns on their investment, underscoring the value and effectiveness of BIM [14]. Traditionally, engineers and designers may produce precise 2D building models using computer-aided design (CAD) before real prototypes are constructed. These 2D digital models may be readily adjusted, changed, and tested. The approach to AEC projects has changed with the transition from CAD to BIM. Whereas CAD is primarily concerned with producing digital representations of physical items, BIM goes beyond CAD by adding intelligence and more data to the model. Figure 1 explains the changeover from CAD to BIM.

Finite element method (FEM) software, as mentioned in Figure 1, is a computational tool used to simulate and analyze physical systems by dividing them into smaller, simpler finite elements. It aids in optimizing design, performing stress and strain analysis, and conducting thermal and dynamic studies, etc. Popular FEM software packages include ANSYS, Abaqus, FreeCAD, and COMSOL Multiphysics, among which, FreeCAD serves as both FEM and BIM software and is open-source. It is used for analysis and design within the BIM framework. The architecture and engineering sections greatly benefit from automated structural model production. Time and cost management is greatly enhanced by simplifying the modelling process. Automated methods accelerate the job process, enhance productivity and reduce costs, especially for large and complicated projects, whereas manual approaches can be labor- and time-intensive [15]. In addition, automated methods guarantee consistency and accuracy by adhering to predetermined rules and procedures. They eliminate drafting mistakes, leading to more trustworthy models that lower the possibility of structural or design problems [16]. Furthermore, automated methods implementing BIM techniques are excellent at handling complicated geometries, such as elaborate curves and erratic patterns, allowing the creation of models that accurately depict the original design. The capability for iterative design and analysis, which is discussed in the next paragraph, is another benefit of automated structural model production [17].

Figure 2 depicts the conventional data flow between architectural and structural engineers, indicating the drawbacks and errors in the conventional approach. The conventional data flow starts with the conceptual architectural design, which is passed to structural engineers. After the model’s completion, the final architectural design is passed to structural engineers for final analysis and design. The structural design is then passed to construction supervisors to start the construction work. If any discrepancy occurs during site construction, the information is returned to the architectural engineers for re-design of the architectural models, which then are again forwarded to the structural engineers for re-design of the structural models. This process could be repeated multiple times to overcome clashes detected during the construction. Such iterative design and analysis processes, in fact, can be facilitated by using BIM techniques and 3D automation. The possibility of error would be minimized if all data were 3D visual and could be defined clearly in the BIM system. In BIM automation, if any error or clash is detected during construction, it can be raised to BIM engineers. Resolving the error or clash within the BIM model subsequently updates all related designs and dependent data within the model. This is the significant advantage of BIM, and such an open-source BIM technique can be termed Open BIM.

The IFC format for interoperability was designed to transfer a comprehensive model with accurate and full building data from one computer program to another without losing any information. However, studies [17] have shown that end users who use interoperability in their daily jobs still cannot fully trust the mapping process, due to major data loss by using commercial software vendors. In this study, Open BIM was used in a new way where there was no interference relating to commercial vendors in the data sharing process. Open BIM can also be easily connected with analytical and simulation software packages, enabling effective data transmission, structural optimization, static/dynamic analysis, and performance assessment. The Open BIM technique can improve the design workflow, which also facilitates thorough and accurate analysis. Overall, this new way to use Open BIM is a valuable tool for contemporary architectural and engineering practices. It offers significant advantages in handling complex geometries, ensuring consistency and accuracy, facilitating iterative design and analysis, and integrating with analysis tools generated using Octave/MATLAB through Python as well as commercial software tools such as staadpro and Etabs, which also accommodate the import and export of IFC format. In addition, automated structural model generation enables the rapid development and assessment of multiple design alternatives, allowing engineers and designers to investigate various options and hence to achieve structures with improved performance. Consequently, this process contributes to superior project outcomes and more informed design decisions [18].

1.2. Literature Review

One of the critical and trending areas of research in the AEC industry is the generation of structural models from architectural models utilizing BIM and IFC. This review critically evaluates recent studies on this topic, focusing on methodologies, challenges, and developments in BIM technology.

To accurately extract structural models, the potential of semantic web technologies to improve data exchange and model extraction processes has been explored through computational approaches to analyze 3D topological connections within complex building models. Although the developed approaches are versatile, their practical applicability may be constrained by the significant processing resources required [19]. Eastman et.al [20] provided a comprehensive explanation of BIM, emphasizing its applications and advantages throughout project lifecycles. Their approach included several real-world examples unique to structural model extraction [20]. Kocakaya et al. [21] discussed BIM-based techniques for industrialized buildings, emphasizing the significance of accurate structural model extraction from existing architectural models. Although their approaches were demonstrated well through worked examples, there were several technical challenges in the application of their methodologies on real-world implementation [21]. In 2016, Fleming [22] investigated interoperability among various BIM software using seven different data transferring methods. The direct-link method yielded the most accurate result in terms of interoperability. In their model, this approach allowed the successful extraction of interior data without fluctuations and ensured that details of applied loads and boundary circumstances were transferred correctly. However, reinforcements details were not exported to the new .ifc file in the study [22].

Pauwels et al. investigated advancements in data interchange and model extraction procedures within the AEC industry through the use of semantic web technologies. While the findings are promising, the integration of these technologies with BIM and IFC remains in its early stage [23]. Sacks et al. [24] examined the impact of 3D parametric modelling on structural engineering productivity and identified significant practical implementation challenges. Managing complicated models requires specialized skills. Although the book provides a compressive overview of BIM technology, supported by real-world examples and case studies on structural model extraction, its depth might be overwhelming for beginners. The study by Kaseem et al. [25] also investigated the macro-level adoption of BIM and its regulatory implications for techniques in structural model extraction. Although that study provided valuable insights, it did not address all technical difficulties at the project level [24,25,26,27].

Zhu and Kassem (2018) assessed the integration of BIM and robotics for automated construction processes, including structural model extraction. While this integration showed potential for efficiency gains, high costs and technical complexity have hindered its widespread adoption [28]. BuildingSMART International (2020) proposed detailed specifications and standards for IFC, facilitating interoperability in BIM. Despite its importance, the complexity and steep learning curve associated with IFC implementation pose significant challenges [29]. Tang et al. [30] examined the integration of BIM with IoT devices, which could improve real-time data collection and model accuracy. However, despite its promising prospects, this integration requires significant advancements in both hardware and software.

Overall, these studies contribute to a comprehensive understanding of the current state of research on deriving automated structural models from architectural models using BIM and IFC. They highlight the necessity for further study to address practical, collaborative, and technological challenges associated with BIM approaches.

1.3. Research Background and Objectives

Data transmission in BIM occurs through three methods: direct native file, application programming interface (API), and open formats like IFC or CIS/2 for information conversation. Direct native file is a tool that works with programming from the same provider, such as Revit and Robot structure analyses, both developed by Autodesk. This method involves using a proprietary file format designed by Autodesk, such as “.rvt” for internal data transfer. As the result, the model or data file can be accessed directly without the need for a mediator or external source in the database [31,32,33]. This sort of workflow represents data in IFC using a predefined format without any information loss. Such circumstances can be met in Revit, i.e., Revit Architecture and Revit Structure. A second data format is API interference, which is used by the Revit connection (add-on) as is a sort of association between two different programming interfaces. Every software requires its own API and is executed using programming coding such as C++, Java, Python, C, etc. Such a kind of association exists between Tekla Structures and Robot Structural Analysis, which are two structural BIM software packages, and this linkage should work both ways. Thirdly and importantly for OpenBIM implementation, open file format for indirect linking allows sharing models among software packages by different providers. The IFC configuration, as an open format, has progressively become a mainstream and valuable strategy for such kinds of information transfer. Each software type, which needs to utilize an open configuration record, must export and import model using IFC format file without data loss. The literature review indicates that most relevant research work is on the transfer of data by first two methods i.e., direct and API link. Some research work, as discussed earlier above, transferred data using open-format IFC but transferring a model to another BIM software package was not achieved. Nowadays, with a new era of technology, especially with recent updates from commercial software like Revit, AECOsim, SCIA, Tekla, FreeCAD (open source) etc., it is possible to import and export IFC files with fewer errors in the models. It is clear from the literature review that importing and exporting using IFC still needs serious attention in terms of BIM technology. Commercial software providers do not try to use open-source formats such as the IFC format, and a possible reason is financial. They also do not keep up to date with the development of IFCs as per buildingSmart guidelines. Conversely, commercially available software might not be affordable for every engineer or researcher. To overcome the problem of data exchange and allow users and engineers to work openly, developing an open platform where anyone can work seems necessary.

To achieve the overall objective of development of such an open platform, the aim of the pioneer research in this paper is to investigate the entities i.e., data format within IFC, and explore methods for extracting and creating IFC files using tools like Python as programming language, IFCOPENSHEEL to read and write IFC format, csv for reading and writing files line by line, etc. IFC is nowadays widely used in the construction and architecture industry to exchange data between different software applications. By understanding the entities and their relationships within the IFC framework, researchers or professionals can better manipulate and work with IFC files for their specific needs. This research also involves exploring and implementation of BIM using different software applications. BIM is a process that involves creating and managing digital representations of physical and functional characteristics of a building. Different software options available for BIM were investigated and analyzed to determine the best approach for extracting the structural model from an architectural model using the IFC format. This process allows a more efficient and accurate transfer of information between the architectural and structural design phases, facilitating collaboration and reducing errors in construction projects.

2. Conceptual Framework and Definitions

This section conceptually explores how the procedure has been aligned to create a cohesive approach for future use in construction and related industries. This study also included defining BIM as a digital representation of the physical and functional characteristics of structures. IFC serves as an open file format standard for BIM data exchange, while interoperability refers to the ability of different systems and software to communicate and work together seamlessly. The methodology explained in this section suggests that building a unified future with these elements can enhance collaboration, efficiency, and innovation within the construction sector and beyond.

2.1. Interoperability

There are three main components in this research, i.e., BIM, IFC, and the data exchange that interlinks BIM and IFC to become a workflow, which is called interoperability. Interoperability is defined as the capability of two or more programs to exchange data using the same set of exchange formats to read and write files. As an example, in Figure 3, step 1 and step 2 use the same data exchange format (i.e., IFC) to transfer data using interoperability (step 3), to the BIM applications. BIM application here refers to any BIM software that can import and export data using the IFC format, e.g., Revit, FreeCAD, AecoSIM, Navisworks, ArchiCAD, Tekla Structures, etc. BIM is facing challenges in interoperability [8]. Inefficiency or lack of interoperability may cause several problems of incompatibility and clashes that may occasionally become obvious only during the execution stage [34,35].

2.2. Building Information Modelling—BIM

BIM is a process of designing and collaborating on building data using one clear set of computer models rather than separate sets of drawings. A building information model is a representation of the building process that facilitates the exchange of information in digital format. BIM provides the parametric information that facilitates accurate cost estimates, simulations, scheduling, energy analysis, etc. BIM also facilitates coordination among engineering, fabricating, and construction partners. It applies to all construction related sectors including roads, railways, utilities, bridges, tunnels, structures, architecture, topography, etc. BIM models include architectural, structural, and mechanical, electrical, and plumbing (MEP) models that can be created using different software products, such as those from Autodesk (Revit Architecture, Revit MEP, AutoCAD MEP), Graphisoft (ArchiCAD, ArchiCAD MEP), and Bentley (BIM). Open BIM serves as a collaborative platform facilitating interdisciplinary teamwork for collective design and the seamless processing of buildings, all while adhering to standardized protocols and workflows. It has been implemented by many firms, counting GRAPHISOFT and Tekla working collectively to promote the idea of Open BIM in the AEC. This enables a clear and open workflow among project associates, allowing them to join irrespective of the tools used in the projects. It also brings information from the data dictionary to avoid errors and repetitive input of the same data [29]. BIM is based on parametric modelling, and it can serve as a single repository for building data throughout the course of a project [36,37,38].

Information is the heart of BIM. Good information management and exchange improve the entire life cycle of a project, enabling the designers, engineers, builders, manufacturers, and owners to have a clear image of the project prior to the actual construction. BIM is not only a simplified version of how the building is modelled, but also how the process of construction is organized and controlled. Different individuals and organizations have provided varying definitions and examples of applications for the concept of BIM.

Table 1. Various BIM applications available.

Symbol/Icon	Software	Company	Source	Website
	FreeCAD	FreeCAD Team	Opensource	https://www.freecad.org/
	IfcOpenShell	Amazing volunteers	Opensource	https://ifcopenshell.org/
	AecoSim	Bentley	Commercial	http://www.bentley.com/
	ArchiCAD	Graphisoft	Commercial	https://graphisoft.com/
	Revit	Autodesk	Commercial	https://www.autodesk.com
	Tekla Structure	Tekla Corporation	Commercial	https://www.tekla.com/
	Navisworks	Navisworks	Commercial	https://www.autodesk.com
	Trimble Connect	Trimble	Commercial	https://connect.trimble.com/
	Revizto	Revizto	Commercial	https://revizto.com/
	ALLPLAN	Nemetschek Group	Commercial	https://www.allplan.com/
	Rhinocerous/Rhino7	Robert McNeel and Associates,	Commercial/Opensource	https://www.rhino3d.com/
	BlenderBIM	Blender.org and volunteers	Opensource	https://blenderbim.org/
	BimServer	Bimserver	Opensource	https://bimserver.org/
	VectorWorks	A Nemetschek	Commercial	https://www.vectorworks.net
	CYPE Architecture	Cype Ingenieros	Opensource	https://info.cype.com/

shows some commonly used BIM applications, some of which are opensource and others that are commercial BIM software packages. These applications are used to import and export information using IFC format as per building SMART guidelines [18]. Nonetheless, the National Building Information Model Standard Project Committee encapsulates the essence of this concept, defining BIM as the digital portrayal of both the physical and functional attributes of a structure. This digital portrayal serves as a store of interconnected knowledge, containing detailed information about the building. It creates an accurate framework for making well-informed choices over the structure’s entire lifecycle with its inception.

2.3. Industry Foundation Class—IFC & Extensible Markup Language (XML)

Industry Foundation Classes (IFC) and Extensible Markup Language (XML) are two formats used for data exchange, especially in the context of BIM and related sectors. This is an extensive examination of their benefits and drawbacks, along with the arguments for why IFC is frequently preferred to XML in BIM systems. The IFC system serves as a standardized file format for defining architectural and construction-related CAD graphic data, ensuring consistency and compatibility across different software platforms and representing them as 3D objects within a real-world context. Its main advantage is to enable architects and engineers to exchange complex building and construction data, including geometry, spatial relationships, and properties of building components, between BIM applications tools. The use of IFC adds a common language to maintain meaning while transferring information between different BIM applications without significant loss of information. The IFC format essentially comprises a list of templates that can be filled in and saved as .IFC files for anybody to read/write, and it is well-suited to detailed and complex structures, which is crucial for accurate BIM processes. The merit of using IFC is that it is available free of charge and therefore, everyone has access to it. The templates are not owned or controlled by any single company, and the continuous evolution of the IFC format, entities, and data is overseen through the collaboration of diverse stakeholders from the construction and facilities management sectors. The IFC format has a few drawbacks, the main one being its complexity, which can make it challenging to use and implement, particularly for smaller projects or teams without extensive BIM knowledge. IFC files may expand hugely, making them difficult to handle and exchange. Large IFC files may require a lot of resources to process and render, which could cause programme performance to suffer. For effective operation, Open BIM aims to utilize a single open-source file format that meets multiple requirements. Open code file format has many potentials. The IFC scheme structure is very simple. The editing and checking content of the IFC model are also user friendly which can be achieved using a text editor. The IFC code language is in English, but in some countries, the property names are being translated into other languages.

BIM allows multiple file formats that may be used and supports various encodings of the same underlying data. In addition to the most widely used IFC format, there is an XML format, which is suitable for interoperability with XML tools (for example, cost estimation and facility management applications) and exchanging partial building models. Both IFC and XML formats can be compressed into ZIP format for huge project models and databases [38,39,40]. XML is simpler and more generic, making it easy to learn and use. It is widely recognized and utilized in many industries. Its excellent adaptability and flexibility make it useful for a variety of data types and structures for a broad range of applications outside of BIM. The text-based format is easy to understand and debug. XML is great for integrating with web technologies and systems, such as web services and databases. There are certain demerits of this format in implementation with BIM i.e., it lacks the richness and detail required to accurately depict complex BIM connections and data. Although adaptable, XML does not provide the same level of interoperability and standardization as IFC does for the construction industry. Large XML files are slow to analyze and process and require significant time, though this is typically an issue compared with IFC due to the generally simpler structure of XML data.

The IFC system is designed to meet the unique requirements of the AEC sector; IFC offers a standardised way of representing complex building data that XML is unable to match. BIM requires the capacity to express complex geometry, spatial connections, and features, and compared with XML, IFC offers a more reliable framework for this, which is essential for collaboration in large construction projects. IFC has gained acceptance and support from significant BIM software providers and industry stakeholders, solidifying its status as the accepted standard solution for exchanging BIM data. Many industry standards and regulations mandate the use of IFC for BIM projects, to ensure compliance and consistency. The IFC schema is specified using the EXPRESS data definition language, as defined in ISO10303-11:1994 [29]. IFC data files are clear text files following the STEP physical file format, as defined in ISO10303-21:1994 [29]. IFC files following the STEP physical file format are governed by the IFC schema in EXPRESS. These IFC formats were developed by the International Alliance for Interoperability (IAI), now renamed as buildingSMART, which is the international authority for sets of standards that deal with processes, data, terms, and change management for the specification, management, and effective utilization of assets in the built asset industry [29]. The IFC method has been developed by buildingSMART. The IAI team is administered by the International Organization for Standardization (ISO). The method could be trailed by the whole AEC sector. BuildingsSMART had four rings in the logo which describe the four key stages of building, i.e., Design, Procure, Assemble, and Operate [29].

• Design: The first phase represents the development stage, wherein architectural concepts and plans are generated.
• Procure: The second part of the ring logo denotes the procurement stage, which entails acquiring the required tools, supplies, and other necessities for building.
• Assemble: The third ring entails the actual construction of the structure, joining the various parts of the building to create the finished structure.
• Operate: The fourth ring signifies the stage of ongoing development, focusing on the utilization of the building, including its maintenance and overall performance management throughout this period.

3. Methodology

The role and concept of building information modelling (BIM) in building design present a multifaceted challenge. This research endeavours to thoroughly explore all facets to maintain a comprehensive scope. The study was conducted in stages to devise innovative strategies aimed at addressing identified gaps and issues in BIM deployment, management, and collaboration between architectural and structural models. The investigation aimed to gather relevant data to inform the effective design of structural models in subsequent stages. The extraction of a structural model from the architectural model was the key objective to achieve in this research. The different tools and software integration used in this research are defined in Figure 4.

Figure 4 shows the flow chart from initial stage to the final integration with all tools used. These tools’ icons are represented in Table 1, showing their name and scope. The figure also represents some internal factors and variables that may affect BIM model which are also described below.

The 3D model stores a variety of data crucial for structural analysis and design. This includes properties of reinforced concrete (RC) members, which can be modified programmatically if needed, as well as material specifications such as concrete and steel grades. Additionally, the model incorporates information regarding the utilization of different areas within the structure, such as study rooms, bedrooms, kitchens, etc., along with the option to add loading specifications as required during the structural design phase. Moreover, by including the position of columns, beams, and slabs in the model, details such as end conditions, support types, and panel arrangements can be easily extracted, facilitating accurate structural modelling and analysis.

Open-Source Tools Used: IFC Tools Used for Building Data

There are two different methods in BIM: Open BIM and closed BIM, which differ in their capacities for data interchange and cooperation. Open BIM places a strong emphasis on information sharing and interoperability between various software programmes, using open standards and file formats to promote stakeholder engagement. Closed BIM, on the other hand, relies on a single software platform and exclusive file formats, possibly restricting interchange and cooperation with external systems. In contrast to closed BIM, which may limit choice, inhibit cooperation, and raise the danger of being tied to a single vendor, Open BIM offers greater freedom, less vendor lock-in, and the wider option to pick software solutions, including IFC tools like IfcOpenSell, Blender, Solibri, etc., depending on individual needs.

Some open-source libraries and tools used in this research were:

• IFC-SDK: offering a selection of tools, libraries, and APIs for interacting with IFC files and integrating support for the IFC file format in software programmes.
• IfcOpenShell: a command-line tool set and open-source software library that supports dealing with IFC files. IfcOpenShell was created for the purposes of reading, writing, and modifying IFC files. It is a software development platform for 3D modelling and numerical simulation built on top of open CASCADE technology (OCCT). It makes use of OCCT’s capabilities to offer complete access to IFC data and geometry.
• IfcPlusPlus: an open-source software library that supports dealing with IFC files. It reduces the difficulty to read and write IFC files.

Python: adopted by different users such as engineers, accountants, and scientists for their day-to-day activities. In building and construction, Python can be helpful in managing and automating the whole process from architectural design in drawings or software to final construction design on site, which in today’s terminology is known as BIM technology. Python was the main open-source tool used in this research for collaboration and sharing of data from one tool to another.

4. Deployment of the BIM Approach

To initiate the process of generating a structural model from an architectural model using Python and IFCopenshell, we began by installing the required libraries, notably IFCopenshell and csv. Afterwards, we accessed the architectural model stored in the IFC file to identify and remove architectural elements like doors, windows, stairs, walls, etc. We proceeded to convert these elements into their corresponding structural components, creating columns, beams, and slabs, as necessary. A new IFC file was created for the structural model and the transformed components were integrated into it. Optionally, additional processing such as material assignment, grades, etc., may be performed. Finally, to optimize system resources, we ensured the IFC files were closed once the transformation process was completed.

4.1. Preparing Sample Architectural Models

Several architectural models as shown in Figure 5, Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12 and Figure 13 with increasing complexity were prepared using three different software programs: FreeCAD, Revit, and AECOSim, and some additional software as described earlier in Table 1. These architectural models contained sufficient building information. These architectural models were then exported as IFC files, which were then used as the inputs for further conversion to structural models from the architectural models. The structural model data were presented in the IFC format, which can be recognized by structural software programmes. The exchange of information between architectural and structural models is essential to facilitate data interchange for the analysis and design phases of the structure. The converted structural models considered only pertinent data for structural analysis, including global location of elements, geometry, material information, loading and boundary conditions of building components, etc.

Figure 5, Figure 6 and Figure 7 show three basic architectural models created for assessing the compatibility of extraction of structural entities using Python script.

The other six models studied in this research were six buildings located in different seismic zones in India. India is divided into four seismic zones: Zone II experiences low to moderate seismic activity, covering northern and eastern regions; Zone III, moderate activity, includes cities like Mumbai and Punjab; Zone IV, high activity, encompasses areas such as Gujarat and Sikkim; and Zone V, very high activity, includes the northeastern region and parts of Jammu and Kashmir. These zones inform building codes and structural designs to mitigate earthquake risks effectively.

Figure 8 shows a three-story police station in seismic zone III, located in Haryana state, India. Its total area is 650 m².

Figure 9 is a model of a four-story college located in seismic zone II of Uttar Pradesh state, India. The total area of the building is 2658 m². This building consists of lecture halls, laboratories, and machine rooms.

Figure 10 shows a hospital building constructed in seismic zone III, in Punjab state, India. The total area of the structure is 3057 m². There are two lifts, staircase and different wards in this building.

The two buildings in Figure 11 and Figure 12 are a government residential complex located in Punjab, India with a total area of 1623 m². It consists of multiple levels.

Figure 13 shows a building block of a university which consists of two elevators, staircases, multiple lecture halls, and offices. The total area of this structure is 3025 m². This building is located in Punjab state, India.

4.2. Extraction of Structural Model Using IFCopenshell: Fulfilling the Requirements for Integration

Several BIM software packages were tested in this research for this purpose, however, most of them either did not produce results correctly or produced results only at a high cost. So, the authors decided to carry out this extraction process using available open-source tools. It was a time-consuming process to find the right tools to perform this task; IFCopenshell, an open-source tool using Python language, was eventually chosen. It provides a library for all Python versions from 3.1 to 3.8. For this task, Python 3.8 was selected as the latest version compatible with IFCopenshell.

The first step in the process was to ready the software. To achieve this, site packages of IFCopenshell were installed in the Python folder/path on the computer. IFCopenshell can be imported in Python using a command “Import Ifcopenshell”. It should be noted that there are a large number of libraries and modules in IFCopenshell and importing all of them would lead to a longer computer run time, which could delay our output. Therefore, another command “Import Ifcopenshells as Ifc” which only imports IFC relevant libraries and hence requires less computer memory, was used instead.

The second step was to open IFC files of an architectural mode in Python. IFC files are not directly readable by Python. The IFC files were opened in Python using IFCopenshell. This can be done in either of the following two ways:

Import File = ifcopenshell.open(r”path\of\file”)

Import File = ifc.open(r”path\of\file”)

The third step was to extract structural model from the imported model by extracting entities of IFC for structural members. This was carried out using the IFC schema by buildingSMART. A text file (.txt) was used to store the entities (IfcBeam, IfcColumn, IfcSlab, IfcMaterial, etc.). Finally, Python read these entities in the .ifc files employing the “by_type_function”.

Syntax =”InputFile.by_type(IFCSLAB)” command. Looping was used to extract and simultaneously save the extracted data to a new .ifc file with both IFC header and footer.

This is the complete workflow to convert the architectural model to the structural model. Eventually, the new .ifc file represents a structural model.

Table 2. Structural IFC Entities used in this research.

IFCPERSON	IFCPOLYLOOP	IFCCONVERSIONBASEDUNIT	IFCPRESENTATIONSTYLEASSIGNMENT
IFCORGANIZATION	IFCSIUNIT	IFCUNITASSIGNMENT	IFCSTYLEDREPRESENTATION
IFCAPPLICATION	IFCPROJECT	IFCBUILDINGSTOREY	IFCMATERIALDEFINITIONREPRESENTATION
IFCOWNERHISTORY	IFCGROUP	IFCAXIS2PLACEMENT2D	IFCRELASSOCIATESMATERIAL
IFCBUILDING	IFCCOLUMN	IFCRECTANGLEPROFILEDEF	IFCPERSONANDORGANIZATION
IFCDIRECTION	IFCBEAM	IFCEXTRUDEDAREASOLID	IFCFACEOUTERBOUND
IFCCARTESIANPOINT	IFCSLAB	IFCCOLOURRGB	IFCPRODUCT DEFINITIONSHAPE
IFCAXIS2PLACEMENT3D	IFCSITE	IFCSURFACESTYLERENDERING	IFCDIMENSIONALEXPONENTS
IFCRELAGGREGATES	IFCFACE	IFCSURFACESTYLE	IFCGEOMETRIC REPRESENTATIONCONTEXT
IFCCLOSEDSHELL	IFCSTYLEDITM	IFCLOCALPLACEMENT	IFCSHAPEREPRESENTATION
IFCFACETEDBREP	IFCMATERIAL	IFCCONVERSIONBASEDUNIT	IFCPOSTALADDRESS

lists the IFC entities used in this study for structural models with required information for structural analysis and design.

4.3. Mapping of IFC File Using IFCopenshell and Python: Internal Entities

Parsing with IFCopenshell and Python allows the user to extract data/entities as needed from an uploaded .ifc file. In IFCopenshell–Python, the main function used is by_type(<argument>): This allows the user to find what type of data we are searching (i.e., IfcOrganization, IfcProject, IfcMaterial, IfcSlab, etc.) to extract from the .ifc file. The name of the argument is the same as the entity presented; as an example, “IfcSlab” should be used as the argument name to extract information for “IfcSlab”. Figure 14 represents the hierarchy of three main elements of the structure model, i.e., slab, beam, and column. These elements were stored deep in .ifc data file that was used to form the structural BIM 3-dimensional model.

The following example illustrates the extraction of slab data from an .ifc file using IFCopenshell in this study. Through Python code integrated with the IFCopenshell package, the desired information was retrieved from the exported IFC file. The functions provided facilitate the reading and parsing of IFC files, allowing access to BIM objects and their attributes from the IFC model.

# Importing IFCopenshell in Python

>>> import ifcopenshell as ifc

# Opening .ifc file using open () function by giving the path of file where it is present

>>> file = ifc.open ("path of file")

#if want to run using other location then attach file here

#inputFile = ifcopenshell.open(r"flle_path")

 

f = input("Enter a file name without extension: ") \\ include files stored in data_base

inputFile = ifc.open(f+"_FullModel.ifc")

outputFile = open('Structure_Model.ifc','w')

outputFile.write(Header)

 

def capital(string):

     i = string.split('(')

     i[0] = i[0].upper()

     string='('.join(i)

     return string

def repeat(some, outputFile):

     for one in some:

        print(capital(str(one)))

        # listLine.append(capital(str(one)))

        print(capital(str(one)),';', file=outputFile)

test = open("Testall.txt", 'r')

line = test.readline()

while line:

     print(line[:-1])

    one = inputFile.by_type(str(line[:-1]))

    repeat(one, outputFile)

    line = test.readline()

test.close()

outputFile.write(Footer)

outputFile.close()

At the final stage, the target data, i.e., structural IFC entities written in Table 2, were extracted from the IFC file using the above Python programme short script. The programme iteratively extracted the necessary data by using the internal data structure of the IFC-based BIM model and the IFC schema, consisting of a hierarchy of classes, attributes, and relationships that represent various building elements, properties, and their interconnections. This schema provides a framework for organizing and exchanging BIM data across different software platforms and disciplines within the construction industry. An information dictionary, a self-defined data structure, was used to store the extracted data.

5. Results and Discussion

5.1. Execution of Python Script

The following steps were executed in this research using integration of tools in Python coding.

• The Python script was run on start-up as shown in Figure 15. It requests the file name as an initial input for the script. The file refers to the .ifc file of the 3D architecture model as developed in the above Section “Open-Source Tools Used: IFC Tools used for Building Data”, for conversion to the structural model.
• There are architecture models saved in our database. Type the name of an architectural model as required, and press enter to start, as shown in Figure 16. The program will start developing a structural model for the entered architectural model. The user can also add a location in the system from where the program can directly take the model for execution of the task.
• Extracted structural data as per architectural details in the file are entered via internal integration using Python in steps 1 to 2;
• As indicated previously, the last open file, “Structure_Model.ifc,” encompasses the 3D structural representation of the architectural model provided to the script, as described in Section 4.2.
• Export the output file “structuremodel.ifc” to BIM software or IFC viewer, which support the .ifc format.

5.2. Successful Implementation of Automated Structural Model

The structural model generated from architectural models introduced in the Section “Open-Source Tools Used: IFC Tools used for Building Data” after execution of the above Python scripts are shown in Figure 17, Figure 18, Figure 19, Figure 20, Figure 21, Figure 22, Figure 23, Figure 24 and Figure 25, where Figure 17, Figure 18, Figure 19, Figure 20, Figure 21, Figure 22 and Figure 23 show the workflow for complicated architectural models. As indicated in these figures, they are structural models with structural elements only, including columns, beams, slabs, etc. All the non-structural elements, e.g., walls, windows, doors, etc., in the architectural models in Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13 and Figure 14 have been excluded from the structural models.

In construction enterprises, integrating architectural and structural design processes has long been a concern. This study included preparation of a workflow demonstrating a way to automatically extract critical structural components from architectural models using Python and IFCopenshell, with fully functioning examples. This workflow can apparently help to fill the gap in integration among design disciplines. The technique developed in this study facilitates a smooth translation from the architectural design information to a structural representation, allowing improved interoperability and more efficient collaboration between architects and structural engineers. This study presents an efficient and automated procedure to extract important structural data from architectural plans through the integration of various technologies, leading to the optimization of the construction workflow.

5.3. Further Discussion as Future Scope

Ideally, all the programming and integration can be added to the cloud database server, which can be used by any person or organisation to extract structural models from architecture models and can be termed as the BIM server. The BIM server provides a platform to visualize and validate the properties, elements, and information stored within the 3D BIM model. It allows stakeholders to remotely access and review the model, ensuring accuracy and compliance with standards. Additionally, it enables the storage and retrieval of project-related data, facilitating collaboration and quality assurance throughout the project lifecycle. The BIM server is a web-based database where users can share their architectural models and have structure models extracted. Users should be able to download or extract any type of models i.e., architectural model, structure model, or MEP model. Some trial examples of this work have been run as preliminary work. Figure 26 shows the test server and the attempt to run the script for the above research on the BIM server. This is just a test server which is not at a working stage; nevertheless, the figures show how data can be arranged or shown on a server/website.

6. Conclusions

In this study, the BIM tools, IFCopenshell and Python were integrated and used to extract information for structural analysis. The developed tool showed the advantages and difficulties related to using BIM in the field of structural analysis. In this research, the authors developed a novel tool capable of extracting structural models from architectural models without relying on proprietary or commercial software. This tool will greatly benefit BIM managers, enabling them to add diverse information to 3D BIM models. However, achieving these goals within companies and the AEC market requires comprehensive BIM education. This necessity was the key reason for developing an Open BIM platform. The most significant innovation of this research is its advancement toward Open BIM, which is crucial for the future of the AEC industry. This platform will be accessible to educators and beginners who cannot afford expensive software.

The research demonstrated the effectiveness of BIM in gathering appropriate data for structural analysis from structural models, illustrating its potential to streamline processes and boost productivity. The use of BIM has demonstrated promise in automating some data extraction processes, decreasing human error, and improving accuracy. The research pointed to several issues that must be resolved. Obstacles might include the necessity for ongoing updates and maintenance of the BIM models as well as difficulty in effectively extracting information from intricate BIM models and inconsistent data quality and formats. The need for creating reliable algorithms and procedures has been stressed in talks around the study as a mean of enhancing the precision and dependability of BIM information extraction. To maximize the potential benefits of BIM, the necessity for standardized data formats and coordination among the many stakeholders has also been emphasized. Overall, the findings add to the increasing body of knowledge in the fields of BIM and structural analysis by giving academics, practitioners, and decision makers useful information. To overcome the issues mentioned and fully realize the promise of BIM in assisting structural analysis in the building sector, more research and development activities are required.

One minor limitation of this study is that if an architect fails to adequately describe and include all relevant information in the 3D model, the program’s effectiveness is compromised. A BIM model is deemed complete only when it contains all necessary information for its entire lifecycle. This highlights the importance of rigorously utilizing 3D BIM models, which represent the future of construction.