Digital twin and its implementations in the civil engineering sector

Feng, Jinteng; Ma, Ling; Broyd, Tim; Chen, Ke

doi:10.1016/j.autcon.2021.103838

Cited by 247 publications

(146 citation statements)

References 125 publications

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“…Based on reviews done by (Opoku et al 2021;Al-Sehrawy and Kumar 2021;Jiang et al 2021), applications of DT have been demonstrated throughout an asset lifecycle in the AEC industry. DT has been implemented in the design and engineering phase by using a combination of Building Information Modelling (BIM) and Wireless Sensor Network (WSN) to provide designers with efficient real-time information during project design (Lin and Cheung 2020).…”

Section: What Is a Dt?mentioning

confidence: 99%

Digital Twin: From Concept to Practice

2022

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Recent technological developments and advances in Artificial Intelligence (AI) have enabled sophisticated capabilities to be a part of Digital Twin (DT), virtually making it possible to introduce automation into all aspects of work processes. Given these possibilities that DT can offer, practitioners are facing increasingly difficult decisions regarding what capabilities to select while deploying a DT in practice. The lack of research in this field has not helped either. It has resulted in the rebranding and reuse of emerging technological capabilities like prediction, simulation, AI, and Machine Learning (ML) as necessary constituents of DT. Inappropriate selection of capabilities in a DT can result in missed opportunities, strategic misalignments, inflated expectations, and risk of it being rejected as just hype by the practitioners. To alleviate this challenge, this paper proposes the digitalization framework, designed and developed by following a Design Science Research (DSR) methodology over a period of 18 months. The framework can help practitioners select an appropriate level of sophistication in a DT by weighing 1the pros and cons for each level, deciding evaluation criteria for the digital twin system, and assessing the implications of the selected DT on the organizational processes and strategies, and value creation. Three real-life case studies illustrate the application and usefulness of the framework.

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Section: What Is a Dt?mentioning

confidence: 99%

Digital Twin: From Concept to Practice

2022

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“…Scholars in the construction industry have gradually realized that digital twin technology is the key technology to realize intelligent construction [ 44 ], which can meet the needs of data fusion and interaction. The application and components of digital twin in the construction industry have not been clearly defined, but some scholars have made preliminary explorations in design, construction, operation, and maintenance in the construction field [ 45 ]. Akula et al realized the real-time monitoring of drilling process hazards by processing and integrating point clouds from 3D imaging technology to the drilling process [ 46 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Digital Twin-Based Risk Control during Prefabricated Building Hoisting Operations

Liu

Sun

et al. 2022

Sensors

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Prefabricated buildings have advantages when it comes to environmental protection. However, the dynamics and complexity of building hoisting operations bring significant safety risks. Existing research on hoisting safety risk lacks a real-time information interaction mechanism and lacks scientific control decision-making tools based on considering the correlation between safety risks. Digital twin (DT) has the advantage of real-time interaction. This paper presents a safety risk control framework for controlling prefabricated building hoisting operations based on DT. In the case of considering the correlation of the safety risk index of hoisting, the safety risk hierarchy model of hoisting is defined in the process of building the DT model. The authors have established a Bayesian network model into the process of the integrated analysis of the digital twin mechanism model and monitoring data to realize the visualization of the decision analysis process of hoisting safety risk control. The key degree of the indirect inducement variable to direct inducement variable was calculated according to probability. The key factor leading to the occurrence of risk was found. The effectiveness of the hoisting safety risk control method is verified by a large, prefabricated building project. This method provides decision tools for hoisting safety risk control, assists in formulating effective control schemes, and improves the efficiency of information integration and sharing.

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“…Digital twins have two key characteristics, interactive feedback and self-evolution, and can realize intuitive observations and predictions of the working state, which makes operation and maintenance work more efficient, timely, and intelligent [22]. Leser et al [23] applied digital twin technology to the health management of fatigue-critical structures and noted that it has application potential in the operation and maintenance processes of multiple fields, from engineering to medical treatment.…”

Section: Introductionmentioning

confidence: 99%

Construction Theory for a Building Intelligent Operation and Maintenance System Based on Digital Twins and Machine Learning

et al. 2022

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The operation and maintenance (O&M) of buildings plays an important role in ensuring that the buildings work normally, as well as reducing the damage caused by functional errors. There are obvious problems in the traditional O&M modality, and an effective way to solve them is to make the model smarter. In this paper, a digital twin framework for building operation is proposed, which consists of two key components: a digital twin O&M model and a machine learning algorithm. The process of establishing the digital twin model is introduced in detail, and the method is explained according to the structure, equipment, and energy consumption characteristics of the model. A mechanism of fusing the digital twin and machine learning algorithm is proposed and the prediction process based on an artificial neural network (ANN) is shown. Finally, based on a systematic summary of the modeling process and fusion mechanism, the development path and overall structure of the intelligent O&M system utilizing digital twins is proposed.

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Digital twin and its implementations in the civil engineering sector

Cited by 247 publications

References 125 publications

Digital Twin: From Concept to Practice

Digital Twin: From Concept to Practice

Digital Twin-Based Risk Control during Prefabricated Building Hoisting Operations

Construction Theory for a Building Intelligent Operation and Maintenance System Based on Digital Twins and Machine Learning

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