Architecture , Engineering And Construction Research Articles

Methodology for the generation of 3D city models and integration of HBIM models in GIS: Case studies

The Architecture, Engineering and Construction (AEC) industry increasingly demands the availability of semantic and interactive digital models with the environment, capable of simulating decision-making during its life cycle and representing the results achieved. This motivates the need to develop models that integrate spatial information (GIS) and construction information (HBIM), favouring the achievement of the Smart City and Digital Twin concepts. GIS & HBIM platform is a useful tool, with potential applications in the world of built heritage; but it still has certain inefficiencies related to interoperability, the semantics of the formats and the geometry of the models. The objective of this contribution is to suggest a procedure for the generation of 3D visualization models of existing cities by integrating HBIM models in GIS environments. For this, three software and two types of data sources (existing plans and point cloud) are used. The methodology is tested in four locations of different dimensions, managing to identify the advantages/disadvantages of each application.

Methodology for the generation of 3D city models and integration of HBIM models in GIS: Case studies

The Architecture, Engineering and Construction (AEC) industry increasingly demands the availability of semantic and interactive digital models with the environment, capable of simulating decision-making during its life cycle and representing the results achieved. This motivates the need to develop models that integrate spatial information (GIS) and construction information (HBIM), favouring the achievement of the Smart City and Digital Twin concepts. GIS & HBIM platform is a useful tool, with potential applications in the world of built heritage; but it still has certain inefficiencies related to interoperability, the semantics of the formats and the geometry of the models. The objective of this contribution is to suggest a procedure for the generation of 3D visualization models of existing cities by integrating HBIM models in GIS environments. For this, three software and two types of data sources (existing plans and point cloud) are used. The methodology is tested in four locations of different dimensions, managing to identify the advantages/disadvantages of each application.

Design of Economic Sustainability Supported by Enterprise Resource Planning Systems in Architecture, Engineering, and Construction

The implementation of information systems is a current topic, especially in the digital age and the digital economy. Enterprise resource planning (ERP) systems (such as some information systems) are a tool that can be used for information systems to enable the sustainable design of the management processes in architecture, engineering and construction (AEC). The focus of design for economic sustainability is defining selected key performance indicators and targeting good values for these indicators in AEC. The subject of this research was the idea that implementing ERP systems in construction management could positively affect the financial results; i.e., provide economic sustainability. This research analyzed the ways that these systems can reduce the costs and increase the revenues of construction companies. The aim of the research was to analyze the impact of the implementation of ERP systems on selected key performance indicators (costs and revenues) in AEC. A questionnaire was used as a tool to collect research data. It was distributed to construction companies operating in Slovakia. The research sample consisted of 125 respondents, of which 55 could be used for the research questions. Data processing was undertaken, with Cronbach’s alpha used to verify the suitability of the research questions and Fisher’s test and Pearson’s correlation coefficient used to confirm the dependence. The research confirmed the impact of ERP systems on cost reduction and revenue growth in the context of designing the economic sustainability of businesses in AEC.

Assessing Performance Dimensions in Architecture, Engineer-ing and Construction Organizations

The collaborative nature of the project environment of the Architecture, Engineering and Construction (AEC) industry necessitates close and prolonged collaboration of diverse organizations in order to execute a project. For the duration of the project, a certain degree of strategic alignment amongst the participating organizations often becomes necessary for the successful execution of the project. The impact of such strategic alignments on the organization’s own performance, is often inevitable. While the performance criteria for the project may be clearly defined along with the project’s program and specifications, the performance criteria that each participating organization has set for itself are not always as evident or articulated to others. In this paper, the results of an exploratory field research are presented. The data analysis revealed that both shared and unique dimensions of performance apply to Architecture, Engineering and Construction organizations. The research findings are significant in that they provide a framework for assessing the degree of compatibility, in terms of shared strategic goals, for firms engaging in projects networks and alliances.

An interactive assessment framework for residential space layouts using pix2pix predictive model at the early-stage building design

PurposeIn this study, a novel framework based on deep learning models is presented to assess energy and environmental performance of a given building space layout, facilitating the decision-making process at the early-stage design.Design/methodology/approachA methodology using an image-based deep learning model called pix2pix is proposed to predict the overall daylight, energy and ventilation performance of a given residential building space layout. The proposed methodology is then evaluated by being applied to 300 sample apartment units in Tehran, Iran. Four pix2pix models were trained to predict illuminance, spatial daylight autonomy (sDA), primary energy intensity and ventilation maps. The simulation results were considered ground truth.FindingsThe results showed an average structural similarity index measure (SSIM) of 0.86 and 0.81 for the predicted illuminance and sDA maps, respectively, and an average score of 88% for the predicted primary energy intensity and ventilation representative maps, each of which is outputted within three seconds.Originality/valueThe proposed framework in this study helps upskilling the design professionals involved with the architecture, engineering and construction (AEC) industry through engaging artificial intelligence in human–computer interactions. The specific novelties of this research are: first, evaluating indoor environmental metrics (daylight and ventilation) alongside the energy performance of space layouts using pix2pix model, second, widening the assessment scope to a group of spaces forming an apartment layout at five different floors and third, incorporating the impact of building context on the intended objectives.

BIM and real estate valuation: challenges, potentials and lessons for future directions

PurposeBuilding information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.Design/methodology/approachThis paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.FindingsFour domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.Originality/valueThis paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.

Beyond googly eyes: stakeholder perceptions of robots in construction

The interest in advanced robotic equipment in construction has increased in recent years. However, actual industry adoption lags behind—and fundamental considerations might be at fault. To date, little scholarship in Architecture, Engineering and Construction (AEC) addresses the stakeholder perception of construction robot design. Therefore, we ask, “How do visual attributes of a construction robot influence the perception of AEC stakeholders?” To conduct our study, we performed a bibliometric analysis on a corpus of 59 scholarly research articles, 5 expert interviews and created and pre-validated a robot database of 50 robot pictures classified on their visual attributes of morphology, color and material. As a result, we present a study with 161 construction professionals who judged these robots based on three visual main criteria: ease of use, work task adaptability and risk of job loss. In total, more than 6500 data points are collected and analyzed using binary logistic regression. The five key findings are that construction professionals perceive that: (1) Zoomorphic (animal-like) robots are easier to use than anthropomorphic (human-like) or mechanomorphic (machine-like) robots, (2) Bright robots are easier to use than dark robots, (3) Zoomorphic and anthropomorphic robots are more multifunctional than mechanomorphic robots, (4) Anthropomorphic and mechanomorphic robots are more of a risk to job loss than zoomorphic robots, and (5) Dark robots are more of a risk to job loss than bright ones. These results are important for academics and practitioners that aim to increase the likelihood of positive stakeholder perception of robots in construction. The findings can further help to develop specific user-centered design principles. Such implementation can reduce the risk of construction professionals rejecting future robots when they are introduced at the AEC job site.

An approach for semi-automated data quality assurance within BIM models

Abstract Successful Building Information Modelling (BIM) enabled projects that require large volumes of project data to be embedded within BIM models. However, with this wealth of data, relevance and accuracy have been identified as important issues affecting the BIM performance of the project. Currently, Quality Assurance (QA) in the industry has focused on geometric data, including scrutinising physical and spatial clashes. However, as BIM practices progress in the industry, the requirements for nongeometric model data and their quality have become more necessary. This study aimed to ascertain the feasibility of using visual programming for semi-automating the BIM QA process in a practical case study on using BIM in infrastructure projects. This paper outlines a generic semi-automated QA methodology and its application in a construction project case study. The validity of this method was tested and evaluated in practice through (n=2) workshops. The methodology was implemented within an integrated engineering consultancy, employing visual programming methodology to generate QA summaries and additionally highlight model elements with data quality issues based on a defined set of parameters. Based on the evaluation findings, the proposed process was feasible and provided a pathway for low-cost and low-skill QA of BIM model data within the architecture, engineering and construction (AEC) industry. The paper’s main scientific contribution is a conceptual framework for using visual programming to achieve automatic quality assurance.

The co-movement effect of managers' psychological factors on the BIM adoption decision in SMEs: a study based on fsQCA

PurposeGiven the complexity of building information modeling (BIM) adoption decisions in small- and medium-sized enterprises (SMEs) in the Architecture, Engineering and Construction (AEC) industry, understanding BIM adoption decision-making through the net effect of a single factor on BIM adoption decisions alone is limited. Therefore, this paper analyzed the co-movement effect of managers' psychological factors on the BIM adoption decisions from the perspective of managers' perceptions. The purpose is to let managers have a deep understanding of their BIM adoption decisions, and put forward targeted suggestions for the AEC industry to promote the adoption of BIM by SMEs.Design/methodology/approachData from 192 managers in SMEs collected by the questionnaire were used in a fuzzy set qualitative comparative analysis (fsQCA). Due to the limitations of fsQCA in making the best use of the data used, as a complement to fsQCA, necessary conditions analysis (NCA) was used to analyze the extent to which necessary conditions influenced the outcome.Findings(1) NCA analysis shows that high perceived resource availability (PRA) and high performance expectancy (PE) are necessary conditions for high BIM adoption intention (AI). (2) fsQCA analysis shows that high PE is the single core condition for high AI. fsQCA analysis identifies three configurations of managers' psychological factors, reflecting three types of managers' decision preferences, namely benefit preference, loss aversion and risk avoidance, respectively. Different decision preferences may lead to different BIM adoption strategies, such as full in-house use, partial in-house/outsourcing and full outsourcing of BIM processes. (3) High perceived risk (PR) and low perceived business value of BIM (PBV) are the core conditions for low AI.Originality/valueThis paper expands on the application of fsQCA to context of BIM adoption decisions. Based on the results of fsQCA analysis, this paper also establishes the relationship between managers' decision-making psychology and BIM adoption strategy choice and analyzes the impact of different decision biases on BIM adoption strategy choice. It concludes with suggestions for encouraging managers to adopt BIM and for avoiding decision-making bias.

Offsite Construction: Reflection is Simply Not Good Enough – We Need a New Prism!

This paper reflects on the recurrent challenges facing Architecture Engineering and Construction (AEC), noting that slow incremental changes have only just stated to address efficiency and product delivery systems underpinning its value proposition. Whilst these challenges embrace many areas, from quality through to waste and concomitant carbon footprint initiatives; the challenge here is “why have other sectors out-performed AEC in many of these areas?”. Acknowledging this, the work presented here challenges the industry to re-think its position, advocating the use of a new ‘prism’ - one which highlights new opportunities for exploitation, rather than re-examining parochial ‘traditional’ approaches. The rationalisation underpinning this treatise rests on the need for AEC to transition towards Industry 4.0. This work presents findings from three case study construction organisations based in Turkey. The foci concentrated on the use and application Offsite Construction (OSC) concepts, addressing the specific technology-related needs to transition to Industry 4.0. This is particularly important given the need for organisations to not only unlock their digital potential to improve performance and capability, but also leverage better value throughout the whole process. Emphasis was therefore placed on this transformative ‘journey’ using agility as the main prism. Research findings highlight the need to step back from adopting conventional thinking and linear approaches, to ones which help actuate evidenced-based levers for change: from conceptualising, embedding, implementing and diffusing new technology per se (into existing business systems and processes); but also embrace the macro, meso and micro drivers associated with the skills and people involved in the delivery of these products and services. In doing so, the paper presents a number of agility-driven innovation and exploitation opportunities, from Additive Manufacturing through to Distributed Ledgers and new data-centric logistic platforms.

Analysis of factors influencing the creation and stimulation of the Australian market for recycled construction and demolition waste products

Growing population and urbanisation have led to a significant increase in construction and demolition (C&D) waste generation. There are urgent calls for government and industry to develop better methods for C&D waste management. The creation and stimulation of a market for recycled construction and demolition waste have emerged as a targeted intervention to divert waste from landfill sites and create a second life for waste material. This study evaluates key factors affecting the creation and stimulation of the market for C&D recycled waste products in Australia. Through an extensive review of the literature and several semi-structured interviews involving 27 stakeholders from across the architecture, engineering and construction (AEC) industry, this study establishes four groups of enablers (i.e., encouragement factors, education, enforcement and engagement) and barriers (i.e., operations, market, governance and logistics) to creating and stimulating a market for C&D waste. Furthermore, the institutional theory was applied to findings to demonstrate how normative, coercive and mimetic drivers influence AEC's stakeholders' decisions and justify their C&D waste management practices. The study proposes a Framework for Waste Market Development (FfWMD) to provide practical solutions to overcome the current barriers identified in this study. The study findings guide government decision-makers and AEC industry practitioners to facilitate end markets for C&D waste and contribute to achieving a circular economy (CE). Further empirical studies on the elements of the FfWMD can be developed to test the complex interactions between stakeholders and processes.

Teaching of emerging technology in construction education

As technology becomes ubiquitous in the architecture, engineering and construction (AEC) industry, there is a need to evaluate how construction education is incorporating technology in the undergraduate curriculum. Given recent trends, we are especially interested in emerging technologies that facilitate AEC integration. In the first phase of the study, a scoping review of literature was used to identify publications related to eight emerging construction-related technology types. Following, the second phase focused on how these emerging technologies were taught in construction education. Of the 58 papers identified in the second phase, the overwhelming majoring discussed technology as pedagogical aid to improve visualization, while only 10 focused on instruction about the technology itself. Some technology types did not have any education specific publications identified by the researchers. Emerging themes from the data also suggest alignments between drones and surveying, and robotics and programming and computational thinking. A majority of the papers mention several technology types and Building Information Modelling (BIM), suggesting an integrated view of emerging construction technology. We conclude the review by suggesting the need for more publications related to teaching of new technology, so that instructors can share best practices in integrating them into the construction curriculum.

AN INTEGRATED BIM-POWER BI APPROACH FOR DATA EXTRACTION AND VISUALIZATION

Abstract. Building Information Modeling (BIM) is one of the most promising advances in the Architecture, Engineering and Construction (AEC) industry. Even though BIM models are rich and very structured, they are not suitable for extracting information quickly and efficiently to respond to some specific queries required for making decisions. Hence, extracting information from BIM models is a very important and challenging issue. This motivated us to propose an integrated solution based on Dynamo and Power BI to allow extraction and visualization of BIM data according four relevant use cases in the AEC domain: cost extraction, clash detection, change detection and plan extraction. The research presented in this paper is based on programming algorithms on Dynamo for information extraction and creating dashboards on Power BI for the visualization of the extracted results. Additionally, we used a Revit plug-in which automates the execution of Dynamo scripts through customized buttons that correspond to each of the analyses treated in this research.

Examining the effect of interoperability factors on building information modelling (BIM) adoption in Malaysia

PurposeBuilding information modelling (BIM) has transformed the traditional practices of the Architecture, Engineering and Construction (AEC) industry. BIM creates a collaborative digital representation of built environment data. Competitive advantage can be achieved with collaborative project delivery and rich information modelling. Despite the abundant benefits, BIM’s adoption in the AEC is susceptible to confrontation. A substantial impediment to BIM adoption often cited is data interoperability. Other facets of interoperability got limited attention. Other academic areas, including information systems, discuss the interoperability construct ahead of data interoperability. These interoperability factors have yet to be surveyed in the AEC industry. This study aims to investigate the effect of interoperability factors on BIM adoption and develop a comprehensive BIM adoption model.Design/methodology/approachThe theoretical foundations of the proposed model are based on the European interoperability framework (EIF) and technology, organization, environment framework (TOE). Quantitative data collection from construction firms is gathered. The model has been thoroughly examined and validated using partial least squares structural equation modelling in SmartPLS software.FindingsThe study’s findings indicate that relative advantage, top management support, government support, organizational readiness and regulation support are determinants of BIM adoption. Financial constraints, complexity, lack of technical interoperability, semantic interoperability, organizational interoperability and uncertainty are barriers to BIM adoption. However, compatibility, competitive pressure and legal interoperability do not affect BIM adoption.Practical implicationsFinally, this study provides recommendations containing the essential technological, organizational, environmental and interoperability factors that AEC stakeholders can address to enhance BIM adoption.Originality/valueTo the best of the authors’ knowledge, this paper is one of the first studies to combine TOE and EIF in a single research model. This research provides empirical evidence for using the proposed model as a guide to promoting BIM adoption. As a result, the highlighted determinants can assist organizations in developing and executing successful policies that support BIM adoption in the AEC industry.

Knowledge Graphs’ Ontologies and Applications for Energy Efficiency in Buildings: A Review

The Architecture, Engineering and Construction (AEC) industry has been utilizing Decision Support Systems (DSSs) for a long time to support energy efficiency improvements in the different phases of a building’s life cycle. In this context, there has been a need for a proper means of exchanging and managing of different kinds of data (e.g., geospatial data, sensor data, 2D/3D models data, material data, schedules, regulatory, financial data) by different kinds of stakeholders and end users, i.e., planners, architects, engineers, property owners and managers. DSSs are used to support various processes inherent in the various building life cycle phases including planning, design, construction, operation and maintenance, retrofitting and demolishing. Such tools are in some cases based on established technologies such Building Information Models, Big Data analysis and other more advanced approaches, including Internet of Things applications and semantic web technologies. In this framework, semantic web technologies form the basis of a new technological paradigm, known as the knowledge graphs (KG), which is a powerful technique concerning the structured semantic representation of the elements of a building and their relationships, offering significant benefits for data exploitation in creating new knowledge. In this paper, a review of the main ontologies and applications that support the development of DSSs and decision making in the different phases of a building’s life cycle is conducted. Our aim is to present a thorough analysis of the state of the art and advancements in the field, to explore key constituents and methodologies, to highlight critical aspects and characteristics, to elaborate on critical thinking and considerations, and to evaluate potential impact of KG applications towards the decision-making processes associated with the energy transition in the built environment.

A Systematic Review of Architectural Design Collaboration in Immersive Virtual Environments

Emerging applications of immersive virtual technologies are providing architects and designers with powerful interactive environments for virtual design collaboration, which has been particularly beneficial since 2020 while the architecture, engineering and construction (AEC) industry has experienced an acceleration of remote working. However, there is currently a lack of critical understanding about both the theoretical and technical development of immersive virtual environments (ImVE) for supporting architectural design collaboration. This paper reviewed recent research (since 2010) relating to the topic in a systematic literature review (SLR). Through the four steps of identification, screening, eligibility check, and inclusion of the eligible articles, in total, 29 journal articles were reviewed and discussed from 3 aspects: ImVE in the AEC industry, ImVE for supporting virtual collaboration, and applications of ImVE to support design collaboration. The results of this review suggest that future research and technology development are needed in the following areas: (1) ImVE support for design collaboration, particularly at the early design stage; (2) cognitive research about design collaboration in ImVE, toward the adoption of more innovative and comprehensive methodologies; (3) further enhancements to ImVE technologies to incorporate more needed advanced design features.

Investigating the future of model-based construction in the UK

PurposeAlthough data rich building information models have been widely adopted in the Architecture Engineering and Construction (AEC) industry in the United Kingdom (UK), use of 2D drawings on site for construction is still the norm. The ability of 2-dimensional (2D) drawings to convey complex 3-dimensional information is limited and requires interpretation from operatives, and 2D drawings can be quickly superseded by model updates. Although constructing directly from a model has been adopted in the aerospace and automotive industries, its use in construction is in its infancy. This research therefore aims to investigate the potential for, and barriers to, model-based construction in the UK.Design/methodology/approachThis research uses a qualitative approach, thematically analysing 13 semi-structured interviews with UK-based construction professionals who have experience of paperless or model-based construction.FindingsAlthough model -based construction has been implemented to a limited extent on some civil engineering projects; research and investment in software, network capacity, legal and contractual issues, and cultural and human factors will need to be considered before model-based construction can be implemented more widely.Originality/valueThe research contributes to an understudied, emergent area of construction practice and outlines hurdles that need to be understood and overcome before more widespread adoption of model-based construction can take place.

Operations management concepts applied to offsite construction

The Architecture Engineering and Construction (AEC) industry has been criticized for low productivity, lack of innovations, damage to the environment, lack of improvement. Several innovations have emerged to address these problems and, in this paper, the relationship between operations management (OM) and offsite construction will be discussed. The purpose of this paper is to present a proposal for the application of OM concepts in offsite construction. A research method based on the assumption that construction processes can be analyzed as production systems will be used. The resulting proposal consists of the exploration of potential applications, benefits, and barriers of OM in offsite construction based on the current experience of OM in manufacturing processes. A thorough discussion about the implications of this proposal in a project and supply chain levels are presented. The most important conclusions were related to the need for applying OM concepts in offsite construction projects and the need for more research in this direction to prove the proposed proposal.

Effect of project organization elements on the mental health of project management practitioner in AEC projects

PurposeDue to the frenetic and dynamic working conditions ascribed to architecture, engineering and construction (AEC) project organizations, enormous research has addressed the poor mental health propensity of project management practitioners (PMPs). However, research has not considered the distant factors related to organizational design causing poor mental health. Therefore, this study addresses the problem by integrating institutional theory, agency theory and resource-based theory (RBT) to explore the relationship between organizational design elements: project governance, knowledge management, integrated project delivery, project management skills and mental health management indicators. Examples of mental health management indicators include social relationships, work-life balance and project leadership.Design/methodology/approachPurposive sampling method was adopted to collect survey data from 90 PMPs in 60 AEC firms in Australia. Structural equation modelling (SEM) was utilized to test the relationship between the variables.FindingsThe research found that project governance, knowledge management and integrated project delivery are positively correlated to mental health management indicators. However, the research finding suggests that project management skills have a negative impact on mental health management indicators.Originality/valueThe findings offer guidelines to AEC firms on achieving positive mental health management outcomes through concentration on project governance, knowledge management and integrated project delivery. It further calls for a reconsideration of existing project management skills causing poor mental health management outcomes.

Numerical and Experimental Validation of Active Vibration Control Logic Performance of a Hybrid Noise Control-Based Brick

The limitations of active noise control (ANC) in coping with low frequencies and of passive noise control (PNC) in coping with middle-high frequencies are objects of research that present the potentialities of hybrid noise control (HBC). It aims at combining both of the behaviours by broadening the range of absorbed frequencies. Among the several application fields, the AEC (architecture, engineering, and construction) market can take advantage for those applications in which the noise conditions are caused by sound sources that tune in a broad frequencies range. In this frame, the paper describes the numerical and experimental validation of the active behaviour of an under-development project of a hybrid noise control-based acoustic bricks. The latter intends to embed the potentialities of active vibrational noise control (AVC) and passive destructive interference (PDI) in a unique design of an easy-to-mount, 3D-printed, customisable smart acoustic blocks. Active vibration control, the object of this paper, is provided by a 5-mm thick aluminium circular plate with an attached piezoelectric patch. The vibration of the latter, depending on a specific control law, defines the vibration of the plate itself achieving an abatement of the reflection coefficient. Through mathematical modelling and tests in an impedance tube, the results show that the control logic can reach an average abatement of the reflection coefficient of 82% in the frequency range 144–1007 Hz.