Building Information Modeling Model Research Articles

Implementation of Building Information Modeling (BIM) Utilizing Tekla Structures for Work Volume Calculation (Institute of Technology Keling Kumang Project in Sekadau District)

In the construction industry, planners use contract drawings and the Work Plan and Conditions (RKS) to determine the work to complete. The conventional approach in calculating the volume and quantity of work usually relies on Microsoft Excel as a calculation tool based on AutoCAD drawings. However, this method is considered inefficient and time-consuming, which can affect the quality of the resulting infrastructure. Building Information Modeling (BIM) is a solution to improve efficiency in planning and managing construction projects. In this research, Tekla Structures was chosen for its ability to generate project drawings, manage and monitor projects, amplify details with high accuracy, and automatically calculate the volume of work after modelling. This research aims to encourage wider application of digital technology in the construction industry in Indonesia. The results showed that comparing the total volume of concrete work between the calculation using Tekla Structures and secondary data had an accuracy rate of 87.61%, with a deviation of 12.39%. Meanwhile, the total volume of reinforcement works showed an accuracy of 95.66% with a deviation of 4.34%. This insignificant volume difference indicates that Tekla Structures can be relied upon to calculate the volume of work, especially in detailing and reinforcement. Although the accuracy of volume calculation is already high, improvement of the BIM model is still needed to make it closer to the actual conditions in the field. One of the efforts that can be made is to integrate real-time data from the field into the BIM model so that the accuracy of calculations increases and can support planning and project management more effectively.

Design and Analysis of Green Building Solar Energy Utilization System Based on BIM

In order to intuitively present the layout and design of the solar energy utilization system, improve the integrity, and consistency of the design. Design and analyze the solar energy utilization system of green buildings based on Building Information Model (BIM). The data acquisition layer collects relevant data of green buildings and solar energy utilization system in RFID and WSN mode and transmits them to the data processing layer; the data processing layer filters the data related to green buildings and solar energy utilization system according to IPC construction standards, and transmits them to the model layer through the Internet of Things; the model layer uses the REVIT software combined with the filtered data to build and update the BIM model of green buildings and solar energy utilization system, intuitively present the layout and design of the solar energy utilization system, and improve the integrity and consistency of the design; the application layer uses the fuzzy comprehensive evaluation model, combined with the green building and solar energy utilization system BIM model, to simulate and analyze the solar energy utilization system environment of green buildings; the user layer provides users with human–computer interaction functions to view the design and analysis process of the solar energy utilization system of green buildings. Experiments show that this method can effectively collect relevant data of green buildings and establish a BIM model of solar energy utilization system; this method can effectively design the solar energy utilization system of green buildings; the solar energy utilization system designed by this method can effectively reduce the electric heating capacity of green buildings, and has an excellent energy-saving effect.

BIM-Based Model Checking: A Scientometric Analysis and Critical Review

Building information modeling (BIM) has been widely applied throughout the entire lifecycle of projects in the architecture, engineering, and construction (AEC) industry. The errors in BIM models can lead to significant losses in engineering projects, thus leading to BIM-based model checking (BMC) technology garnering an increasing amount of attention. Despite numerous documents detailing the BMC process, there is a lack of systematic analysis and visualization of existing research. This study employs a combined approach of scientometric analysis and a critical review to survey articles on BMC published from 2008 to 2024 in the Web of Science (WOS) and Scopus databases. The scientific analysis objectively presents the status and evolution of this research field through quantitative data, including publications, authors, and references. Furthermore, the critical review is employed to analyze the content of the articles, summarizing the topics and challenges of current research. Finally, potential promising directions for future development are proposed.

Application of Parametric Modeling Techniques for Automated Detailing of Exterior Finishes in Architectural BIM Models: A South Korean Case Study

The South Korean government has mandated the use of Building Information Modeling (BIM) as the main medium for design deliverables in public projects. Such stipulations require detailed BIM models to be submitted in the detailed design phases, which places a burden especially on small- to medium-sized design firms. The requirement means that both the interior and exterior finishes of a building need to be explicitly modeled, which when performed manually is labor intensive and error prone. The goal of this study was to apply parametric modeling techniques to automatically model such details, focusing on the exterior finishes. Through interviews with design experts, four elements were selected: parapets, external wall finishes, downspouts, and inspection ladders. Parametric processes and rules for each finish were developed and subsequently programmed as add-ins in Autodesk Revit. Validation through case studies conducted using three different BIM models resulted in the average scores of 92.28% and 92.44% in terms of accuracy and efficiency, respectively. In particular, downspouts achieved a perfect accuracy score, while external wall finishes achieved a 94.42% reduction in modeling time. Modeling errors, which occurred due to inconsistencies in the test models, also demonstrate the need for specifying uniform modeling conventions of BIM model submissions in the detailed design phases.

BIM-Based Automatic Extraction of Daily Concrete and Formwork Requirements for Site Work Planning

Material planning is important in construction, for it affects procurement, cost, and schedule. Proper planning of material supply and logistics helps streamline the performance of all tasks through the avoidance of excessive or insufficient material supply. Material planning relies on quantity takeoff (QTO) and project schedules. Conventionally, quantity takeoff was a manual process based on 2D drawings and human interpretation and was error-prone. Presently, with the popularity of Building Information Modelling (BIM), in BIM-based projects, using inbuilt quantity takeoff functions, quantities of work can be generated automatically from BIM models to aid the quantity takeoff. However, if those inbuilt QTO solutions are object-based, then the quantities of works extracted may not meet the requirements of the users in selected cases, e.g., in zone-based construction projects. Also, for estimating daily material requirements, the accuracy of the quantities of work becomes more important, not only for the purpose of efficient planning but also for reducing construction waste. Since works using the same type of material can go overlapping, in addition to estimating the amount of material for each work, the total amount of material for a day must also be calculated. Thus, this research aims to develop a framework for automatic extraction of zone-based concrete volumes and formwork positions for cast-in-place concrete structures using the data in BIM models, followed by linking them with project schedules for estimating daily concrete and formwork requirements. This framework extends the body of knowledge by introducing an innovative algorithm for automatically calculating overlapped areas between concrete members and a rule for naming tasks in the schedule, followed by evaluating the formwork requirements without drawing formwork in a 3D model. A software tool will be developed to achieve the aim, and a case study will be used to validate the proposed framework.

Systematization of BIM data management to improve centralization, interoperability and traceability of building asset information in digital environments

This article connects Building Information Modeling (BIM) methodology with relational databases, presenting a large-scale framework that enhances work processes and knowledge for digital building asset management. It emphasizes the significance of data connections, aligning digital technologies with valuable information extraction and advocating for strategic digital continuity. Current digital procedures in construction often lack standardized protocols, hindering efficient information creation, monitoring, and reuse. The integration of BIM with other data sources facilitates better control in coordination and management, leading to time and cost savings throughout the asset lifecycle. The research is organized into four blocks: database construction, BIM data integration, quality control, and data consolidation, leading to a new systematization proposal for building management. Key contributions include insights into the global structuring of asset management information and the potential for synchronous use of BIM models with relational databases, enabling data sharing and access for various specialists across different environments.

BIM-based Rebar Modeling for Variable Section L-shaped Columns

Building Information Modeling (BIM), as a kind of digital means applied in the process of building design, construction and management, has been widely used in all aspects of construction engineering. However, the application of BIM in the field of steel reinforcement engineering, due to the wide variety of rebar and complex shapes in the plan construction drawings, the rebar modeling is inefficient and prone to errors, and the traditional plug-in for standard column models is usually difficult to cope with the demand for modeling rebar of complex components such as variable cross-section shaped columns. Therefore, with the help of the program and algorithms to create a BIM model of rebar can reduce the occurrence of the above problems. This paper mainly uses Revit secondary development technology, with the help of C# programming language to develop a program for automatic generation of reinforcing steel BIM model for variable section L-shaped columns. The program combines the structural requirements of reinforcement in the building code and standard drawings, identifies the key nodes of the shaped column model, calculates the coordinate points of the reinforcement, and carries out targeted algorithmic processing for the arrangement of reinforcement in the complex variable cross-section area of the upper and lower columns to complete the creation of the BIM model of reinforcement in the shaped column. The development of this program provides a variety of efficient ideas for the creation of complex structural reinforcement for other shaped columns, which helps to save the time of designers to create BIM models, ensures the geometric accuracy of the reinforcement model, and helps to promote the informatization and intelligentization of the construction of reinforced concrete structures.

Soil Sharing and Equipment Operations Through Digitalization of Large-Scale Earthworks

The modern construction industry is undergoing considerable changes driven by increased specialization, technological advancements, and growing complexity. The integration of smart construction technology is rapidly advancing as a solution to address the aging workforce in the sector. However, the uncertainty and risks associated with soil construction on job sites remain, leading to increased costs during project execution. Recently, construction sites have sought to enhance productivity by leveraging building information modeling (BIM) and smart construction devices. The adoption of smart equipment, such as machine control and machine guidance, is on the rise in both structural and earthwork projects, with ongoing efforts to mitigate uncertainties. This study proposes a practical approach to reduce the uncertainty in earthworks by optimizing soil sharing strategies and equipment allocation from the initial design phase. A BIM model was developed as a solid structure and then segmented using Dynamo. This model was utilized to create a construction plan using Primavera P6, while AnyLogic (8.9.2) was employed to assess the suitability of equipment combinations, ultimately demonstrating the cost-saving benefits of the proposed approach. Through repeated simulations, work efficiency was enhanced by approximately 6.2% compared to the original 2D planning approach.

Digital Twins in Structural Health Assessment and Monitoring: Applications in Historical Timber Buildings

ABSTRACT This paper explores the application of Digital Twins (DTs) for supporting the structural health monitoring (SHM) of timber buildings, with a particular emphasis on historical timber structures. It reviews technologies and methods for DT creation, examining how geospatial data and Building Information Modeling (BIM) serves as foundational elements in developing digital twins. The paper discusses integrating these elements with various data and models to enhance SHM tasks, detailing actionable DT approaches for documenting, analyzing, simulating and predicting structural behavior. The study highlights that while high-fidelity geometric models are well developed, their application for advanced SHM tasks remains limited. Integration of sensor data into BIM frameworks is promising but still faces challenges such as limited automation and difficulties in handling real-time and long-term data. Additionally, the paper notes that the implementation of DTs for the simulation of the effects of hygrothermal phenomena on the long-term behavior and durability of timber structures is underexplored. Multi-dimensional BIM models and machine and deep learning techniques in data-driven, physics-based models are promising approaches for timber cultural heritage management and beyond.

AI-based automation for structural design of buildings

With the recent advancement of technology and computational empowerment, processes that were executed manually have the potential to be automated. In Civil Engineering, this is being seen through the implementation of technologies such as Building Information Modeling (BIM), Generative Design, Machine Learning and Artificial Intelligence. The objective of this work is to develop a computational system aiming to optimize the development of architectural and structural projects, implementing technologies such as artificial intelligence and generative design to automate and systematize processes inherent to the project pre-dimensioning phase when designing a building. Initially, the user interacts with an AI-based chatbot interface which allows the definition of a building’s main characteristics, such as number of stories, apartments per story and minimum areas. The system has access to a database that contains different architectural BIM models and will filter them in order to provide the best option according to the user specifications. The selected model is processed by a Dynamo script in Autodesk Revit that automatically creates and allocates structural elements, e.g. beams, columns, slabs, and foundation. The script considers the intersection between walls and building corners, also positioning columns in wider spans avoiding doors and windows. This structure is converted into an analytical model, so it can be exported to Autodesk Robot Structural Analysis where another Dynamo script is executed, which contains loads determined by technical standards as the Brazilian ABNT NBR 6118:2023 for concrete design. This script analyzes bending moments, shear effects and axial forces of the structural elements and, through limiting parameters, sends messages to Autodesk Revit, stating if a structural element needs to be modified to attend applied loads. This process runs continuously until all elements are adequate. Using this technology, enterprises specialized in architectural and structural projects will save time, since allocating and pre-dimensioning structural elements are processes that are executed manually. Therefore, engineers are then able to focus on greater challenges involved in structural analysis and architects can simulate the dimensions of elements more accurately. There are still many processes in Autodesk Revit and Robot Structural Analysis that can be automated, and these will be further developed as a sequence of this study.

BIM-based optimization approach to reduce life cycle costs by focusing on the integration of construction and operation phases in office-commercial buildings

This study investigates the application of Building Information Modeling (BIM) to reduce life cycle costs (LCC) by addressing critical nonconformances encountered during the construction and operational phases of buildings. The primary aim is to identify nonconformances that escalate operational costs and to evaluate how BIM can effectively reduce these costs. The research begins with a comprehensive review of existing literature and utilizes the Delphi method to identify four key nonconformances that most significantly impact operational expenses. To further analyze these issues, semi-structured interviews and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are employed to determine the cost ranges of components associated with these nonconformances in both the construction and operational phases. The study finds that BIM-based optimization can lead to substantial cost reductions, although there are limitations due to the lack of precise data on the operational phase of low-cost equipment. The key contribution of this research is the development of a framework that helps designers create more effective BIM models, enhancing facilities management (FM) and reducing LCC. The originality of this study lies in its integrated approach, combining BIM and optimization techniques to directly address operational cost issues, which provides a novel perspective on improving life cycle cost management in buildings. Future research should expand the dataset and explore a broader range of nonconformances to refine and extend the framework's applicability.

BIM tunneling documentation in Rohbaustollen Angath

AbstractSince 2023, Austrian Federal Railways (ÖBB), with BEMO‐ÖSTU STETTIN, has been constructing the 2.6 km raw construction tunnel Angath (Rohbaustollen Angath) along the Angerberg. It will support geological investigations, logistics for the future main railway tunnel Angerberg, and act as a rescue tunnel, ensuring safety. The project includes a pre‐cut, tunnel excavation, and a 110‐meter section of the main railway tunnel, with turning niches and cross adits. Building information modeling (BIM) is used for design, tendering, control, and documentation. The integrated project delivery (IPD) model ensures shared responsibility for risks and costs. BIM optimizes data flow and transparency, with tunneling documentation collected on‐site, verified in ÖBB's Common Data Environment (MSP), and used for parametric modeling. Cost and progress monitoring occur via software RIB iTWO (Version 2023, 2023). Project documentation and the linking of the documentation into a 3D BIM model of a tunnel enables early detection of deviations and appropriate action to be taken, with transparency and traceability being critical to the success of the IPD project.

Enabling circularity in Turkish construction: a case of BIM-based material management utilizing material passports

PurposeThe Turkish construction sector, facing mounting environmental pressures, needs to rapidly adopt circular economy (CE) principles. However, a critical barrier is the lack of accessible and comprehensive material information. This paper investigates how building information modeling (BIM) can facilitate the adoption of material passports (MPs) to overcome this challenge and helps enabling circularity in Turkish construction.Design/methodology/approachA case study approach is adopted, focusing on the New Istanbul Esenler Arena, a major sports facility designed with BIM. An in-depth analysis of the project's BIM model and material data was conducted to develop a practical framework for integrating MPs into BIM workflows. The framework outlines a comprehensive MP data structure, addresses technical integration strategies and highlights the importance of stakeholder collaboration.FindingsThe research demonstrates that integrating MPs with BIM has the potential to significantly enhance material tracking throughout the building lifecycle, leading to more informed decision-making regarding material selection, reuse and recycling. This approach can improve material recovery rates, reduce construction waste and minimize the environmental impact of construction projects. The study also identifies key challenges to MP implementation, such as ensuring data accuracy and interoperability, and proposes strategies to overcome these hurdles.Originality/valueThis paper contributes to the limited but growing body of knowledge on the practical implementation of BIM and MPs for circular construction, particularly in the Turkish context. The proposed framework, informed by a real-world case study, provides valuable guidance for construction professionals, policymakers and researchers seeking to accelerate the transition to a circular economy in the built environment.

Integrating BIM and GIS for an Existing Infrastructure

Data-driven digital transformation is becoming increasingly relevant. Building information modelling (BIM) and geographic information systems (GIS) are two technologies specific to the construction industry. The two approaches are different, but complementary. In this article, BIM–GIS integration is approached from some of the most relevant aspects, such as standardization or level of detail, and a comparison between both approaches is presented with the aim of improving the operation and maintenance of urban infrastructure. By means of the Madrid Calle 30 ring road as a case study, the integration of the BIM model of the road in a GIS scenario using the IFC and SLPK formats is shown. The information is stored in an external database, which allows updates without modifying the 3D model and facilitates the inclusion of real-time data. The study highlights the challenges of interoperability between BIM and GIS, as well as the need for open standards and software tools that enable a wider implementation in the FM of this type of infrastructure.

Dokładność modelu BIM z chmury punktów dla obiektu wykonanego w technologii szklanej

Mapping glass objects in 3D space has long raised doubts as to the possibility of obtaining data, and as to the accuracy of that data. The basics of terrestrial laser scanning technology and the principles of the physics of light propagation in the environment of transparent and reflective surfaces, as a rule, contradict the technological possibility of a faithful mapping thereof. Although Building Information Modelling (BIM) of existing objects based on data from terrestrial laser scanning is an increasingly common practice, it is recognized, nevertheless, that the accuracy of the model is primarily reflected in the accuracy of the point cloud obtained as a result of scanning. The article discusses the possibilities of developing a BIM model of an object made in glass technology, based on data obtained with the method of terrestrial laser scanning. The subject of the study was the glazed façade of the complex of buildings belonging to the University of Agriculture in Krakow. The study on the fidelity of mapping glazed surfaces included the acquisition and processing of the point cloud, 3D modelling of the object using the Revit software, and the analysis of the accuracy of mapping the existing status in comparison with architectural design and construction documentation. Based on the research, the possibility of using the BIM process was assessed using TLS data in the process of recreating the geometry of an object made in glass technology. The results of the study showed a significant convergence of the façade model geometry with the actual course of the structure, which, however, can be attributed to the development methodology, i.e. the accuracy of 3D data acquisition, the registration process, the filtration procedure, the method of parametric modelling of the façade structure itself, and ultimately fitting three-layer glazing into the model of that structure.

Transforming point cloud data into 3D BIM models: a case study on slabs

We explore the automatized transition of point cloud data into a Building Information Model (BIM), an essential task for reconstructions, demolition plans, or auditing. In this study, we use point cloud data generated by 3D laser scanning. The research elaborates on the process of segregating and segmenting floor slabs from point clouds and the developed algorithms categorize point cloud subsets based on different height parameters (z-coordinates). Once slabs are identified, a function is applied to create envelopes for each slab level, accommodating any convex or concave shape. The resulting geometry, along with relevant auxiliary data, is exported in the Industry Foundation Classes (IFC) format, a standard for BIM data exchange. The exported entities can then be further processed using prevalent software such as Revit or ArchiCAD.

Blockchain-Based Responsibility Management Framework for Smart City Building Information Modeling Projects Using Non-Fungible Tokens

In the context of digital construction, responsibility management in smart city building information modeling (BIM) projects spans the entire building lifecycle. The involvement of numerous BIM designers in project management and frequent data exchanges pose significant challenges for the traceability, immutability, and responsibility attribution of BIM models. To address these issues, this study proposes a blockchain-based responsibility management and collaboration framework for BIM projects using non-fungible tokens (NFTs), aiming to enhance the management of responsibilities and accountability in BIM projects. This research adopts a design science methodology, strictly adhering to scientific research procedures to ensure rigor. First, NFTs based on blockchain technology were developed to generate corresponding digital signatures for BIM model files. This approach ensures that each BIM model file has a unique digital identity, enhancing transparency and traceability in responsibility management. Next, the interplanetary file system (IPFS) was used to generate digital fingerprints, with the content identifier generated by IPFS uploaded to the blockchain to ensure the immutability of BIM model files. This method guarantees the integrity and security of BIM model files throughout their lifecycle. Finally, the proposed methods were validated through a blockchain network. The experimental results indicate that the proposed framework is theoretically highly feasible and demonstrates good applicability and efficiency in practical production. The constructed blockchain network meets the actual needs of responsibility management in smart city BIM projects, enhancing the transparency and reliability of project management.

A knowledge graph-based framework to automate the generation of building energy models using geometric relation checking and HVAC topology establishment

Building Energy Models (BEM) are widely utilized throughout all stages of a building's lifecycle to understand and enhance energy usage. However, creating these models demands significant effort, particularly for larger buildings or those with complex HVAC systems. While a substantial amount of information can be extracted from Building Information Models (BIM) — which are increasingly accessible and provide necessary data for geometric and HVAC contexts — this information is not readily usable in setting up BEM and typically requires manual translation. To address this challenge, this paper introduces a BIM-to-BEM (BIM2BEM) framework that focuses on automating the generation of HVAC parts of BEM models from BIM data. Core to the methodology is the extraction of HVAC system topologies from the BIM model and the creation of a knowledge graph with the HVAC topology. The topology transformation unfolds in three key stages: first, a geometry-induced knowledge graph is established by examining the geometric relationships among HVAC elements; second, this graph is converted into an informative HVAC topology with enhanced properties from additional data sources; and finally, the informative topology is simplified into a BEM-oriented HVAC topology compliant with BEM platforms such as EnergyPlus. A case study of a large university building with a complex HVAC system showcases that the proposed framework achieves automatic and precise generation of building performance simulation models. The model's predictions are then validated against actual measurements from the building.

Bim-based Digital Twin development for university Campus management. Case study ETSICCP

Innovation and digitalization are outstanding topics acquiring each day more importance for local governments, especially in Facility Management sector. Moreover, during the COVID-19 situation, new management needs emerged, especially in large public buildings. Building Information Modeling (BIM) is considered as one of the emerging technologies used to reach a total digitalization of the infrastructure. Nevertheless, BIM implementation carries important barriers with itself like, high software and hardware investments, initial BIM skills training or low data interoperability. The objective of this project is to overpass those implementation barriers. For this purpose, the paper shows the creation of a BIM-based intelligent platform for infrastructure management that leads to the development of a Digital Twin (DT). To show the potential of the software developed, a real implementation in the Civil Engineering School at Universidad Politécnica de Madrid was carried out, obtaining significant results thanks to the actual feedback of infrastructure users and managers. The novelty of this project relies on the final results achieved, obtaining a complete DT for management functionalities like space reservation, live sensors data or assets management. All of it, linking BIM models with own software and hardware development using Internet of Things and cloud computing. A multidisciplinary work is compiled in this paper, providing the reader with the most relevant challenges detected in a real digitalization process.

The Role of Building Information Modeling (BIM) in Enhancing Efficiency, Sustainability, and Integration with Emerging Technologies

BIM integrates collaboration, efficiency, and sustainable features throughout the life of the building. This paper deals with the application of BIM in various phases of the project, more so with the intervention of emergent technologies like IoT, AI, and AR. Indeed, in the BIM approach to the post-construction phase, facility management and predictive maintenance can be assured, thanks to real-time monitoring and performance optimisation of the building systems. Integration with IoT and sensors means continuous data exchange and upgrading towards energy efficiency, which is beneficial in saving money for operational costs. It points out that some significant challenges in adopting BIM are mainly related to data privacy, security issues, and interoperability. As the BIM model will contain sensitive information, robust security must be developed, including data encryption, user authentication, and secure data protocols. Due to the absence of standard data formats on various BIM platforms, smooth data exchange is hardly possible. Standardisation efforts, using Industry Foundation Classes-IFC, are discussed as vital in overcoming these challenges. The paper finally discusses the future of BIM, pointing out how AI and machine learning will be integrated into the process to optimise design, improve decision-making, and enhance overall building performance, making BIM a core tool in the future of construction and facility management.