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Buildings
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Digital Twin in the AEC Industry – Advances and Challenges
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Digital Twin in the AEC Industry – Advances and Challenges

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: closed (20 December 2023) | Viewed by 50284

Special Issue Editors

Dr. Pedro F. Pereira

E-Mail Website
Guest Editor
Faculty of Engineering, University of Porto, 4100 Porto, Portugal
Interests: thermal comfort; building physics; indoor air quality; energy efficiency; building performance simulation; digital building twins
Special Issues, Collections and Topics in MDPI journals
Dr. Nuno M. M. Ramos

E-Mail Website
Guest Editor
Department of Civil Engineering, University of Porto, 4100 Porto, Portugal
Interests: building physics; building technology; energy efficiency; circular economy; indoor environmental quality; occupant behaviour; digital twins; intelligent buildings; durability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, technology developments have created new opportunities in the architecture, engineering, and construction (AEC) industry. Recently, researchers from many fields have increased their interest in the application of a new concept, digital twins (DT). It is believed that the application of this concept in the AEC industry will lead the way to achieving construction 4.0. The main challenge of DT implementation is the ability to guarantee the capacity of the system to continuously update the digital model to ensure that it stays similar to the physical twin. Therefore, monitoring, control, simulation, and optimization will be necessary during its life cycle. This will allow the prediction of the future state of the construction, including pathologies and anomalies, allowing us to simulate and test preventive measures. However, a DT is not always a comprehensive representation of the physical model. The scope of the digital replica depends on the objectives of the developers and on the dimension of the monitoring system and the models used to create the DT. This Special Issue intends to group studies concerning digital twins during the life cycle of construction projects (design, construction, operation, and demolition/circularity) in the following sub-topics, which include but are not limited to:

  • Occupant behaviour;
  • Visual comfort;
  • Thermal comfort;
  • Acoustic comfort;
  • Indoor air quality;
  • Energy efficiency;
  • Facilities maintenance;
  • Structural health monitoring;
  • Water consumption;
  • Worker/user/occupantsafety.

Furthermore, we welcome studies that focus on an initial part of the digital twin that are related to the use and development of advanced methods related to artificial intelligence and data collection, analysis, and processing tools that apply to part or all of the sub-topics described above. We also welcome studies related to the conceptualization and standardization of digital twins and reviews of the current state of the art.

Dr. Pedro F. Pereira
Dr. Nuno M. M. Ramos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • digital building twin
  • intelligent buildings
  • building simulation
  • artificial intelligence
  • structural health monitoring
  • facilities maintenance
  • indoor environmental quality
  • energy efficiency
  • water consumption
  • occupant behaviour

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Published Papers (5 papers)

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Research

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41 pages, 8701 KiB  
Article
Data Fusion for Smart Civil Infrastructure Management: A Conceptual Digital Twin Framework
by Obaidullah Hakimi, Hexu Liu, Osama Abudayyeh, Azim Houshyar, Manea Almatared and Ali Alhawiti
Buildings 2023, 13(11), 2725; https://doi.org/10.3390/buildings13112725 - 29 Oct 2023
Cited by 18 | Viewed by 3790
Abstract
Effective civil infrastructure management necessitates the utilization of timely data across the entire asset lifecycle for condition assessment and predictive maintenance. A notable gap in current predictive maintenance practices is the reliance on single-source data instead of heterogeneous data, decreasing data accuracy, reliability, [...] Read more.
Effective civil infrastructure management necessitates the utilization of timely data across the entire asset lifecycle for condition assessment and predictive maintenance. A notable gap in current predictive maintenance practices is the reliance on single-source data instead of heterogeneous data, decreasing data accuracy, reliability, adaptability, and further effectiveness of engineering decision-making. Data fusion is thus demanded to transform low-dimensional decisions from individual sensors into high-dimensional ones for decision optimization. In this context, digital twin (DT) technology is set to revolutionize the civil infrastructure industry by facilitating real-time data processing and informed decision-making. However, data-driven smart civil infrastructure management using DT is not yet achieved, especially in terms of data fusion. This paper aims to establish a conceptual framework for harnessing DT technology with data fusion to ensure the efficiency of civil infrastructures throughout their lifecycle. To achieve this objective, a systematic review of 105 papers was conducted to thematically analyze data fusion approaches and DT frameworks for civil infrastructure management, including their applications, core DT technologies, and challenges. Several gaps are identified, such as the difficulty in data integration due to data heterogeneity, seamless interoperability, difficulties associated with data quality, maintaining the semantic features of big data, technological limitations, and complexities with algorithm selection. Given these challenges, this research proposed a framework emphasizing multilayer data fusion, the integration of open building information modeling (openBIM) and geographic information system (GIS) for immersive visualization and stakeholder engagement, and the adoption of extended industry foundation classes (IFC) for data integration throughout the asset lifecycle. Full article
(This article belongs to the Special Issue Digital Twin in the AEC Industry – Advances and Challenges)
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34 pages, 13707 KiB  
Article
Feasibility of Digital Twins to Manage the Operational Risks in the Production of a Ready-Mix Concrete Plant
by Vihan Weerapura, Ranil Sugathadasa, M. Mavin De Silva, Izabela Nielsen and Amila Thibbotuwawa
Buildings 2023, 13(2), 447; https://doi.org/10.3390/buildings13020447 - 6 Feb 2023
Cited by 11 | Viewed by 4459
Abstract
The ready-mix concrete supply chain is highly disruptive due to its product perishability and Just-in-Time (JIT) production style. A lack of technology makes the ready-mix concrete (RMC) industry suffer from frequent production failures, ultimately causing high customer dissatisfaction and loss of revenues. In [...] Read more.
The ready-mix concrete supply chain is highly disruptive due to its product perishability and Just-in-Time (JIT) production style. A lack of technology makes the ready-mix concrete (RMC) industry suffer from frequent production failures, ultimately causing high customer dissatisfaction and loss of revenues. In this paper, we propose the first-ever digital twin (DT) system in the RMC industry that can serve as a decision support tool to manage production risk efficiently and effectively via predictive maintenance. This study focuses on the feasibility of digital twins for the RMC industry in three main areas holistically: (1) the technical feasibility of the digital twin system for ready-mix concrete plant production risk management; (2) the business value of the proposed product to the construction industry; (3) the challenges of implementation in the real-world RMC industry. The proposed digital twin system consists of three main phases: (1) an IoT system to get the real-time production cycle times; (2) a digital twin operational working model with descriptive analytics; (3) an advanced analytical dashboard with predictive analytics to make predictive maintenance decisions. Our proposed digital twin solution can provide efficient and interpretable predictive maintenance insights in real time based on anomaly detection, production bottleneck identification, process disruption forecast and cycle time analysis. Finally, this study emphasizes that state-of-the-art solutions such as digital twins can effectively manage the production risks of ready-mix concrete plants by automatically detecting and predicting the bottlenecks without waiting until a production failure happens to react. Full article
(This article belongs to the Special Issue Digital Twin in the AEC Industry – Advances and Challenges)
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22 pages, 1527 KiB  
Article
Digital Twins for Construction Assets Using BIM Standard Specifications
by Mohamed Nour El-Din, Pedro F. Pereira, João Poças Martins and Nuno M. M. Ramos
Buildings 2022, 12(12), 2155; https://doi.org/10.3390/buildings12122155 - 7 Dec 2022
Cited by 27 | Viewed by 7859
Abstract
Digital twins (DTs) are one of the latest technology trends in all industries. However, DT development in the architecture, engineering, and construction (AEC) industry is still in its infancy. Digital twins have been proposed as tools that can be applied to several challenges [...] Read more.
Digital twins (DTs) are one of the latest technology trends in all industries. However, DT development in the architecture, engineering, and construction (AEC) industry is still in its infancy. Digital twins have been proposed as tools that can be applied to several challenges in various areas of the built environment. However, their widespread use is hampered due to the slow pace of digitization of the AEC industry, in addition to the absence of a formalized standard for digital twins’ implementation. We began this study by systematically reviewing publications related to DT applications in the AEC industry in four databases, resulting in 229 publications after applying the proposed criteria. The systematic review highlighted the lack of standardization for DTs in the AEC industry. Additionally, this study assessed the current status of DTs and analyzed the evolution of the concept of DTs in the AEC industry. We also proposed a conceptual framework for DT development for construction assets, using the existing BIM information management standards (i.e., ISO 19650) to promote a better interoperable digitalized built environment. Full article
(This article belongs to the Special Issue Digital Twin in the AEC Industry – Advances and Challenges)
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19 pages, 1384 KiB  
Article
Digital Twins in Built Environments: An Investigation of the Characteristics, Applications, and Challenges
by Muhammad Shahzad, Muhammad Tariq Shafiq, Dean Douglas and Mohamad Kassem
Buildings 2022, 12(2), 120; https://doi.org/10.3390/buildings12020120 - 25 Jan 2022
Cited by 159 | Viewed by 21691
Abstract
The concept of digital twins is proposed as a new technology-led advancement to support the processes of the design, construction, and operation of built assets. Commonalities between the emerging definitions of digital twins describe them as digital or cyber environments that are bidirectionally-linked [...] Read more.
The concept of digital twins is proposed as a new technology-led advancement to support the processes of the design, construction, and operation of built assets. Commonalities between the emerging definitions of digital twins describe them as digital or cyber environments that are bidirectionally-linked to their physical or real-life replica to enable simulation and data-centric decision making. Studies have started to investigate their role in the digitalization of asset delivery, including the management of built assets at different levels within the building and infrastructure sectors. However, questions persist regarding their actual applications and implementation challenges, including their integration with other digital technologies (i.e., building information modeling, virtual and augmented reality, Internet of Things, artificial intelligence, and cloud computing). Within the built environment context, this study seeks to analyze the definitions and characteristics of a digital twin, its interactions with other digital technologies used in built asset delivery and operation, and its applications and challenges. To achieve this aim, the research utilizes a thorough literature review and semi-structured interviews with ten industry experts. The literature review explores the merits and the relevance of digital twins relative to existing digital technologies and highlights potential applications and challenges for their implementation. The data from the semi-structured interviews are classified into five themes: definitions and enablers of digital twins, applications and benefits, implementation challenges, existing practical applications, and future development. The findings provide a point of departure for future research aimed at clarifying the relationship between digital twins and other digital technologies and their key implementation challenges. Full article
(This article belongs to the Special Issue Digital Twin in the AEC Industry – Advances and Challenges)
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Review

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19 pages, 970 KiB  
Review
Drivers for Digital Twin Adoption in the Construction Industry: A Systematic Literature Review
by De-Graft Joe Opoku, Srinath Perera, Robert Osei-Kyei, Maria Rashidi, Tosin Famakinwa and Keivan Bamdad
Buildings 2022, 12(2), 113; https://doi.org/10.3390/buildings12020113 - 24 Jan 2022
Cited by 57 | Viewed by 9598
Abstract
Digital twin (DT) is gaining increasing attention due to its ability to present digital replicas of existing assets, processes and systems. DT can integrate artificial intelligence, machine learning, and data analytics to create real-time simulation models. These models learn and update from multiple [...] Read more.
Digital twin (DT) is gaining increasing attention due to its ability to present digital replicas of existing assets, processes and systems. DT can integrate artificial intelligence, machine learning, and data analytics to create real-time simulation models. These models learn and update from multiple data sources to predict their physical counterparts’ current and future conditions. This has promoted its relevance in various industries, including the construction industry (CI). However, recognising the existence of a distinct set of factors driving its adoption has not been established. Therefore, this study aims to identify the drivers and integrate them into a classification framework to enhance its understanding. Utilising popular databases, including Scopus, Web of Science, and ScienceDirect, a systematic literature review of 58 relevant DT adoptions in the CI research was conducted. From the review, the drivers for DT adoption in the CI were identified and classified. The results show that developed countries such as the UK, US, Australia, and Italy have been the top countries in advancing DT adoption in the CI, while developing countries have made commendable contributions. A conceptual framework has been developed to enhance the successful adoption of DT in the CI based on 50 identified drivers. The major categories of the framework include concept-oriented drivers, production-driven drivers, operational success drivers, and preservation-driven drivers. The developed framework serves as a guide to propel DT adoption in the CI. Furthermore, this study contributes to the body of knowledge about DT adoption drivers, which is essential for DT promotion in the CI. Full article
(This article belongs to the Special Issue Digital Twin in the AEC Industry – Advances and Challenges)
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