Information Model Research Articles

Supporting sustainability assessment of building element materials using a BIM-plug-in for multi-criteria decision-making

The environmental crisis requires the immediate implementation of accurate and robust sustainable solutions throughout the building life cycle. Life Cycle Sustainability Assessment (LCSA) is a scientifically recognised method that integrates the triple dimensions of the life cycle approach, and thereby enabling the evaluation of the performance of mitigation strategies implemented in building projects. However, implementing the LCSA in buildings is limited by the weighting of environmental, economic, and social dimensions to select the best option regarding the numerous materials available. In order to fill this knowledge gap, the paper aims to present the developed Smart BIM3LCA tool, which supports multi-dimensional assessment during the project´s early design steps. Automatic integration of the LCSA, a multi-criteria decision-making tool such as TOPSIS, and building information modelling (BIM), was developed to support the selection of building materials. The BIM plug-in was then validated through its application to a multi-family residential building to select the most sustainable materials during the project´s early design stage.

Pipe production cost management model based on graph theory

The pipe production process is a complex dynamical system with a significant number of production operations and interconnected cost localization centres. Purpose. To develop a mathematical model of the process of handling analytical information of a pipe enterprise using graph theory for the needs of cost management at each production stage. Methodology. Technological flow charts of the production job, where the list of mandatory activities and routing of the operating process are indicated, were used to organize cost accounting by operational centres of their localization with the help of computer modelling elements, namely the graph theory. The work used a complex of research methods, including analysis and scientific synthesis of scientific and technical information; theoretical studies; methods of mathematical and computer modelling, engineering developments. Findings. The cost accounting process is represented by a directed hypergraph. Each production operation is associated with a graph vertex. Each vertex is assigned to a series of interrelated marks: type of technological operation; weight factor; the value of direct costs for the operation; the value of indirect costs for the operation; the expense factor. The initial state of the hypergraph is specified by means of its initial marking, which corresponds to the set cipher of the batch of pipes and its weight. Further execution of the marked hypergraph is performed by running the allowed vertices. Marking of the graph ends if all the information from the technological flow charts of pipe products has been used. Originality. A model of cost management by operational centres is proposed which will allow dividing the prime cost of pipes which differ according to the production technology. It is recommended to rank pipe products within each technologically similar group for an economically feasible allocation of costs between batches of pipes. The proposed process model of processing analytical information of the pipe enterprise using graph theory will allow providing data governance as for the prime cost of each individual batch of pipe products, will contribute to the improvement in the order generation procedure taking into account the acquired information, and will allow making the appropriate adjustments when making management decisions. Practical value. Calculation of expenses for production operations allows one to identify the most cost-intensive of them. Relying on the results of the calculation, the enterprise management has the opportunity to manage costs at any stage of the production process. Moreover, the model allows determining the amount of consumed metal for each production operation, which is relevant for pipe enterprises. It is appropriate to focus further scientific developments in this direction on the possibility of managing non-manufacturing cost with the help of mathematical models in economics to optimize the supply and sales activities of the enterprise.

Advanced Building Information Modeling (BIM) for affordable housing projects: Enhancing design efficiency and cost management

Advanced Building Information Modeling (BIM) for affordable housing projects: Enhancing design efficiency and cost management

7.L. Practice session: Is there an investment case for health at older ages?

Abstract The global demographic landscape is undergoing significant transformation due to increases in longevity and declining birth rates. According to the United Nations, the world’s population aged 65 and over is projected to more than double, reaching over 1.5 billion by 2050, while global fertility rates are expected to decline to 2.4 births per woman by 2030 and continue decreasing to 2.2 births per woman by 2050. Ageing populations have frequently concerned decision-makers due to the potential implications of changes in population age-mix for labour markets and the economy, as well as for the sustainability of public programs and spending, particularly the health sector. For example, as the share of the population at older age increases, there are concerns over how to cope with the possible economic implications of having a smaller share of people at traditional working age (with potentially more people obtaining income security through both public and private pensions) and how to respond to greater health and long-term care needs. Without appropriate policy responses, there are worries that demographic changes will have inevitable consequences for households, public finances and possibly for economic growth and development. To support policy decisions related to population ageing it is important to have informative evidence and modelling tools that allow policymakers to better understand both the implications of population ageing as well as the consequences of policy action or inaction. To this end, this session presents three recently developed modelling tools that aim to address a number of policy relevant questions related to ageing: 1) How does ageing affect health financing and are health systems unsustainable? 2) How does ageing affect economic objectives and does health at older ages matter? 3) Can we develop economically relevant measures of health at older ages if older people do not have formal ties to the labour force? Using data and analyses from a range of European countries, we will demonstrate empirically that the way ageing affects health financing systems, economies, and societies more broadly reflects policy choices and is not an inevitable consequence of demographic changes. Key messages • Policymakers must prioritize informed policies to comprehensively understand the impact of aging on health financing and economies, facilitating the development of sustainable solutions. • Immediate action is imperative to address the implications of aging on labor markets and public spending, ensuring future economic stability and safeguarding societal well-being.

Exploring Architectural Tools for Oculus Quest 2

Virtual Reality (VR) has emerged as a pivotal technology in architectural design and education, offering immersive and interactive experiences that surpass traditional methods. This article delves into the diverse applications of VR in architecture, with a particular emphasis on the various software tools utilized in architectural modeling, visualization, and education. The study conducts a thorough examination of both professional and entry-level VR tools and platforms like Blender, Rhino, Unity, and Enscape, which are increasingly integrated into architectural workflows. By providing real-time rendering, interactive design environments, and enhanced spatial understanding, these tools are transforming the way architects and designers conceive and develop their projects. The article also explores the educational implications of VR software such as Tilt Brush, SketchUp Viewer, and Arkio, which offer accessible platforms for students and educators to engage with complex spatial concepts in an intuitive manner. Through comparative analysis, the study highlights the strengths and limitations of these tools, focusing on their usability, accessibility, and relevance to architectural practice and pedagogy. Furthermore, the integration of VR with Building Information Modeling (BIM) is identified as a significant innovation that enhances collaboration and information synchronization throughout the design and construction process. This article provides a comprehensive overview of the current state of VR software in architecture, offering insights into future trends and potential advancements that could further revolutionize the field. The findings underscore VR’s critical role in fostering creativity, improving design accuracy, and enhancing educational experiences, positioning it as a cornerstone technology in the future of architecture.

VEIDEA: A Comprehensive Framework for Implementing Building Information Modeling-Based Value Engineering Within a Common Data Environment in Construction Projects

The Architecture, Engineering, and Construction (AEC) industry faces significant global challenges, including frequent project delays, budget overruns, and inadequate stakeholder collaboration. To address these issues, Value Engineering (VE) and Building Information Modeling (BIM) have been increasingly used in large-scale, complex construction projects. Although many studies highlight the benefits of integrating VE with BIM, its full practical potential has not yet been realized. This study aims to investigate the integration of VE and BIM within a Common Data Environment (CDE) to improve decision making and project outcomes. A comprehensive framework was developed, consisting of four interconnected modules: (1) Creating the CDE, (2) Developing the BIM Model, (3) Implementing Value Engineering, and (4) Conducting a Value Engineering Study. Central to this framework is the introduction of the VEIDEA” data bank, a structured system based on the OmniClass classification, which stores and organizes VE ideas. Additionally, the framework incorporates the Analytical Hierarchy Process (AHP) to automate the evaluation phase, assisting designers and VE teams in making data-driven decisions on design alternatives. Empirical results from a case study of an office building show significant cost savings, with a 20% reduction in reinforced concrete (RC) slab costs and a 39% reduction in flooring material costs. These findings demonstrate the potential for integrating VE and BIM to enhance cost-effectiveness and overall project performance. This study offers a novel approach to optimizing project collaboration, decision making, and efficiency in the AEC industry.

Generation Method for HVAC Systems Design Schemes in Office Buildings Based on Deep Graph Generative Models

The design process of heating, ventilation, and air conditioning (HVAC) systems is complex and time consuming due to the need to follow design codes. Since the design standards are not fixed, the final outcome often depends on the designer’s experience. The development of building information modeling (BIM) technology has made information throughout the building lifecycle more integrated. BIM-based forward design is now widely used, providing a data foundation for combining HVAC system design with machine learning. This paper proposes an unsupervised learning method based on deep graph generative models to uncover hidden design patterns and optimization strategies from the design results. We trained and validated four deep graph generative models—GAE, GNF, GAN, and diffusion—using HVAC system terminal pipeline layout data. Accuracy and precision metrics were used to compare the generated designs with automated forward design solutions, assessing the models’ ability to capture both local variations and broader changes in design logic. A graph-neural-network-based evaluation method was employed to measure the models’ capacity to detect changes. The results indicate that all four models achieved prediction accuracies exceeding 90% and precision rates above 75%. The models effectively captured both local modifications made by designers and global design changes, showing greater sensitivity to global layout adjustments than to local updates. When comparing the results generated by deep graph generative models and the actual design, it is obvious that the accuracy of the predictions varies significantly due to the complexity of the test buildings.

Research on Collaborative Management of BIM (Building Information Modeling) in Engineering Projects

Abstract: The research on collaborative management of Building Information Modeling (BIM) in engineering projects aims to explore the application of BIM technology in construction engineering and its impact on collaborative management. BIM technology creates digital 3D models, centrally manages project information, promotes information sharing and collaboration, and improves project management efficiency. In construction projects, BIM technology can effectively solve the problems of difficult information sharing and poor information transmission, thereby making collaborative management more efficient. In addition, the application of BIM technology in the design, bidding, and construction stages can ensure the smooth transmission of information and improve the efficiency of collaborative management. Research has shown that the application of BIM technology in structural design significantly improves design quality and demonstrates its wide applicability. However, despite the significant advantages of BIM technology in collaborative management, there are still some challenges, such as trust issues and technical operational difficulties. Through in-depth research and application of BIM technology, more efficient collaborative management models can be provided for future engineering projects, promoting the development of the construction industry.

GLE-net: global-local information enhancement for semantic segmentation of remote sensing images

Remote sensing (RS) images contain a wealth of information with expansive potential for applications in image segmentation. However, Convolutional Neural Networks (CNN) face challenges in fully harnessing the global contextual information. Leveraging the formidable capabilities of global information modeling with Swin-Transformer, a novel RS images segmentation model with CNN (GLE-Net) was introduced. This integration gives rise to a revamped encoder structure. The subbranch initiates the process by extracting features at varying scales within the RS images using the Multiscale Feature Fusion Module (MFM), acquiring rich semantic information, discerning localized finer features, and adeptly handling occlusions. Subsequently, Feature Compression Module (FCM) is introduced in main branch to downsize the feature map, effectively reducing information loss while preserving finer details, enhancing segmentation accuracy for smaller targets. Finally, we integrate local features and global features through Spatial Information Enhancement Module (SIEM) for comprehensive feature modeling, augmenting the segmentation capabilities of model. We performed experiments on public datasets provided by ISPRS, yielding notably remarkable experimental outcomes. This underscores the substantial potential of our model in the realm of RS image segmentation within the context of scientific research.

METODOLOGIA BIM NA GRADUAÇÃO DE ARQUITETURA E URBANISMO: UMA ANÁLISE DAS MATRIZES CURRICULARES DAS INSTITUIÇÕES PRESENCIAIS DE VITÓRIA DA CONQUISTA – BA

This study addresses the importance of introducing the BIM (Building Information Modeling) methodology into the Architecture and Urbanism undergraduate curriculum, considering the continuous transformations in the construction sector. Given the growing need for adaptation to new market demands, it is essential that future architects are qualified to integrate practices that promote greater agility and efficiency in project development. The research adopts a qualitative approach, using bibliographic, to demonstrate the relevance of teaching BIM from the academic stage. The study highlights how this innovative methodology not only prepares students for professional challenges but also significantly enhances their performance in the job market. The inclusion of BIM in the educational environment is identified as a competitive advantage, allowing for a deeper understanding of the design and execution phases, as well as fostering more efficient integration between the various actors involved in the construction process. Thus, this study reinforces the need for curricular reform that incorporates BIM as an essential component of the training of architects and urban planners.

A BIM-integrated Thailand building energy code framework for building envelope thermal requirements in a conceptual design stage

This work presents the development of a building energy code (BEC) of Thailand compliance framework during conceptual design stages (CDS) using building information modeling (BIM) through visual programming language (VPL). The proposed method included five steps: (i) establish a commercial building reference; (ii) develop a BIM base model; (iii) create a BIM overall thermal transfer value (OTTV) and roof thermal transfer value (RTTV) calculation model with VPL scripts; (iv) test the BIM framework with various scenarios; and (v) verify the results with Thailand BEC software. The findings revealed an insignificant difference between the results from the BIM calculation model and those estimated by the Thailand BEC software. This study demonstrated that using BIM with VPL for OTTV and RTTV calculations during the CDS may be implemented automatically, which could help designers make timely decisions to comply with Thailand’s BEC, considering building design, materials, and fenestration ratios.

Implementation Challenges of Building Information Modelling (BIM) in Small to Medium-Sized Enterprises (SMEs) Participating in Public Projects in Qatar

This research investigates the implementation challenges of Building Information Modelling (BIM) in Small to Medium-Sized Enterprises (SMEs) participating in public projects, with a focus on the construction industry in Qatar. Through a combination of literature review, surveys, and interviews, the study identifies key obstacles such as interoperability issues, financial constraints, organisational and cultural resistance, and the lack of comprehensive training programs. The literature highlights the fragmented nature of construction projects and the potential of BIM to improve efficiency through enhanced data handling and collaboration. However, SMEs often struggle with the high initial costs of software and hardware, as well as the need for extensive training to bridge the skill gap. Interviews with industry professionals reveal that while mandatory BIM integration in public projects drives adoption, it also exacerbates these challenges for SMEs, which may lack the necessary resources and expertise. Survey findings indicate that contractors frequently encounter issues with understanding and implementing BIM and meeting the government body standards, suggesting a need for better training and support. The study also emphasises the importance of strategic incremental adoption, where SMEs gradually integrate BIM into their processes, starting with low-level implementation in privately funded projects. The research concludes that while BIM offers significant benefits for the construction industry, its successful adoption requires targeted support for SMEs. This includes financial incentives, improved interoperability standards, comprehensive training programs, and strategic change management approaches. Addressing these challenges will enable SMEs to fully leverage BIM's potential, enhancing project efficiency and competitiveness in the construction sector.

Gestational organophosphate esters (OPEs) and executive function in adolescence: The HOME Study

BackgroundEvidence from toxicological studies indicate organophosphate esters (OPEs) are neurotoxic, but few epidemiological studies investigated associations between gestational OPEs and executive function. ObjectiveTo examine the associations between gestational concentrations of OPE urinary metabolites and executive function at 12 years MethodsWe used data from 223 mother-adolescent dyads from the Health Outcomes of Measures of the Environment (HOME) Study. Women provided spot urine samples at 16 weeks gestation, 26 weeks gestation, and at delivery for quantification of bis(1,3-dichloro-2-propyl) phosphate, bis-2-chloroethyl phosphate (BCEP), diphenyl phosphate (DPHP), and di-n-butyl phosphate (DNBP). Executive function was assessed at age 12 years using the parent- and self-report Behavior Rating Inventory of Executive Function (BRIEF2). Covariate-adjusted associations between specific gravity-corrected OPEs and BRIEF2 scores were estimated using multiple informant models. Bayesian Kernel Machine Regression (BKMR) was used to assess the impact of all OPEs simultaneously. ResultsParent- and self-report BRIEF2 indices and composite scores were weakly to moderately correlated (rs=0.32-0.41). A natural-log unit increase in BCEP at 26 weeks was associated with approximately a 1-point increase on the self-report Cognitive Regulation Index [CRI] (95% CI 0.4, 2.3), the Emotion Regulation Index [ERI] (95% CI 0.3, 2.2), and the Global Executive Composite [GEC] (95% CI 0.4, 2.2), indicating poorer performance. Higher DPHP at 16 weeks was associated with lower parent-report GEC score (β=-1.1, 95% CI -2.3, -0.003). BKMR identified BCEP and DNBP at 26 weeks as important contributors to CRI and ERI, respectively. ConclusionOPE metabolites during gestational development, particularly BCEP, may influence adolescent executive function. However, since the FDR p-values failed to reach statistical significance, additional studies would benefit from using larger cohorts.

Quality Evaluation of Sizeable Surveying-Industry-Produced Terrestrial Laser Scanning Point Clouds That Facilitate Building Information Modeling—A Case Study of Seven Point Clouds

Quality Evaluation of Sizeable Surveying-Industry-Produced Terrestrial Laser Scanning Point Clouds That Facilitate Building Information Modeling—A Case Study of Seven Point Clouds

Ensino do Building Information Modeling (BIM) em Instituições de Ensino Superior no Brasil

Building Information Modeling (BIM) has emerged as a necessary tool in the architecture, engineering, construction and operations scenario, offering an innovative and integrated approach not only for project development, but also contributing to the construction management and maintenance of buildings. . In the Brazilian context, academia has dedicated special attention to BIM, reflected in the production of theses and dissertations carried out over the last few years. This research aimed to identify the main trends and pedagogical approaches used in the productions found, presenting their strengths and advances verified in the use of this methodology, as well as the weaknesses or limiting points, based on Brazilian academic production on teaching BIM in the period from 2013 to 2020, resulting from the analysis of theses and dissertations published in the CAPES Catalog of Theses and Dissertations, which address the topic of Construction Information Modeling or Building Information Modeling in the dimension of its teaching. classifies as applied, exploratory, with a qualitative approach, using the bibliographic research method and application of the content analysis technique. It is hoped that, through the results obtained, the adoption of the BIM methodology in undergraduate courses in architecture and urbanism and related areas can be encouraged in the country.

Analysis of the Spatial Constraints of Urban Underpass Channels Based on BIM

The construction of urban underpasses faces various spatial constraints, which will lead to deformation or failure of the structures if not satisfied. The introduction of BIM (Building Information Modeling) and other modern information technology to achieve rapid and accurate spatial constraint analysis of the design scheme is of great significance to ensure the quality and safety of the underpass and adjacent structures. Firstly, through extensive literature collection and survey, the key spatial constraint indicators of underpasses in dense urban spaces and the evaluation rules of each indicator are determined. Then, an SQL (Structured Query Language)-based database of spatial constraint rules for underpasses in dense urban space areas is constructed, and the spatial constraint analysis process for underpasses in dense urban space areas is proposed. Finally, based on Building Information Modeling, programming support, and a development environment provided by C# and Visual Studio, a spatial constraint analysis system for underpasses in dense urban space areas is developed to realize complex spatial constraint analysis functions. The application practice of the system is carried out by taking a city underpass project as an example. The results show that in the design of urban underpass engineering, the spatial constraint analysis system designed in this paper and the calculation method adopted can simplify the model transmission process, save on labor costs, and reduce the error of the calculation results.

Implementation of the Telemetric Integration of the BIM-RFID in Context of Access Control

Building Information Modelling (BIM) integration with the Internet of Things (IoT) is progressing. The high level of BIM maturity involves using sensor data to manage processes or objects. The article presents the process of creating a telemetry connection between the BIM model and a Radio-Frequency Identification (RFID) sensor in the context of gaining access to various parts of a building. The process of creating a connection using an experimental set based on a microcontroller board for RFID reader support is described. The set was programmed using multiple programming languages and artificial intelligence. The article presents a unique process of connecting an RFID reader with BIM using a simple model that can be replicated in other contexts (e.g., gaining access to different parts of a construction site). Previous research shows that the unidirectional connection of IoT sensors with BIM models is not difficult. Instead, real-time bidirectional and stable connection (telemetry) is problematic. The authors undertook to fill this research gap using a proprietary IoT kit, programming sequence, and lightweight communication protocol. The paper makes a significant contribution to the discussion and understanding of BIM-IoT technology integration. The article also includes the limitations and possibilities for further development of such a connection.

Automatic Indoor Thermal Comfort Monitoring Based on BIM and IoT Technology

Building Information Modeling (BIM) and Internet of Thing (IoT) integration technologies can improve operational efficiency in the operational phase of construction projects. Currently, research on the integration of BIM and IoT has yet to ensure secure data transmission and lacks real-time data processing capabilities. This study builds a framework to collect and analyze BIM and IoT data in real time. The framework is verified to be effective through a case study in an office building. The monitoring system can automatically calculate the Predicted Mean Vote (PMV) value, upload and update real-time temperature and humidity data, and visualize thermal comfort through heat maps. The proposed integration approach offers building management strategies to enhance thermal comfort in office environments, fostering a more inclusive and accommodating workspace that acknowledges the diverse cultural backgrounds of occupants.

Transforming fire protection: AI's evolving role in proactive and reactive applications

Abstract. This paper comprehensively reviews the applications of artificial intelligence (AI) in the field of fire protection. It traces the historical development of AI, from its origins in the 1930s and 1940s to its current state, focusing on major milestones and algorithms that have shaped the field. The paper discusses the evolution of AI, particularly in terms of machine learning, deep learning, and the emergence of various models such as deep neural networks (DNNs), transformer models, and graph neural networks (GNNs). The application of AI in fire protection is explored in two primary categories: proactive and reactive applications. Proactive applications encompass AI's role in decision-making, construction, and operation, including the use of machine learning for environmental analysis, building information modelling (BIM) for design optimization, 3D printing and intelligent robots in construction, and intelligent fire facility management. Reactive applications focus on early fire detection and monitoring, especially in forests, utilizing terrestrial, aerial, and satellite systems equipped with advanced sensors and deep learning techniques. This paper highlights the significant contributions of AI in mitigating fire risks, improving fire detection and response, and enhancing the safety and efficiency of fire protection systems.

A knowledge graph based remanufacturing equipment resource modeling method.

Background The uncertainty and non-standardization of the remanufacturing process result in multi-source heterogeneity of remanufacturing equipment capabilities and knowledge information, which limits the development of informationization and intelligence in remanufacturing. Methods Therefore, we propose a knowledge graph-based modeling method for Remanufacturing Equipment Resource (RMER) information. By analyzing the categories of remanufacturing equipment resources and integrating resource information such as man, machine, material, method, and environment, a unified remanufacturing equipment information model and service capability information model were constructed. Based on the top-down knowledge graph construction process, the RMER semantic association information of the ontology pattern and data layers was extracted and integrated to construct the RMER knowledge graph. Results In this paper, 18 enterprise texts, 50 experience texts and thesis patent texts were selected as the training set, and 2 enterprise texts, 50 experience texts and thesis patent texts were selected as the test set. After multiple rounds of model training, the accuracy rate of entity information extraction reached 91.4%, which proved the accuracy and effectiveness of the model for entity information document extraction. Conclusions This study provides a unified information foundation for mapping and optimizing the resource capabilities of remanufacturing equipment. It can help remanufacturing enterprises to quickly configure equipment resources, and improve the intelligent and automated management level of RMER.