Digital twin-driven virtual sensor approach for safe construction operations of trailing suction hopper dredger

Li, Mingchao; Lu, Qi; Bai, Shuo; Zhang, Mengxi; Tian, Huixin; Qin, Liang

doi:10.1016/j.autcon.2021.103961

Cited by 38 publications

(13 citation statements)

References 36 publications

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“…Later, General Motors (GE), a giant in the industrial manufacturing field, also pivoted its attention to DTT. Soon, with the attention of Siemens, Germany, DTT began to sweep the internet and the industry until today [ 21 ]. In industrial manufacturing, modifying the design and assembling product components usually demand repeated attempts and consume extensive human and material resources.…”

Section: Methodsmentioning

confidence: 99%

Application of Digital Twins and Metaverse in the Field of Fluid Machinery Pumps and Fans: A Review

Yang

et al. 2022

Sensors

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Digital twins technology (DTT) is an application framework with breakthrough rules. With the deep integration of the virtual information world and physical space, it becomes the basis for realizing intelligent machining production lines, which is of great significance to intelligent processing in industrial manufacturing. This review aims to study the application of DTT and the Metaverse in fluid machinery in the past 5 years by summarizing the application status of pumps and fans in fluid machinery from the perspective of DTT and the Metaverse through the collection, classification, and summary of relevant literature in the past 5 years. The research found that in addition to relatively mature applications in intelligent manufacturing, DTT and Metaverse technologies play a critical role in the development of new pump products and technologies and are widely used in numerical simulation and fault detection in fluid machinery for various pumps and other fields. Among fan-type fluid machinery, twin fans can comprehensively use technologies, such as perception, calculation, modeling, and deep learning, to provide efficient smart solutions for fan operation detection, power generation visualization, production monitoring, and operation monitoring. Still, there are some limitations. For example, real-time and accuracy cannot fully meet the requirements in the mechanical environment with high-precision requirements. However, there are also some solutions that have achieved good results. For instance, it is possible to achieve significant noise reduction and better aerodynamic performance of the axial fan by improving the sawtooth parameters of the fan and rearranging the sawtooth area. However, there are few application cases of the Metaverse in fluid machinery. The cases are limited to operating real equipment from a virtual environment and require the combination of virtual reality and DTT. The application effect still needs further verification.

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Section: Methodsmentioning

confidence: 99%

Application of Digital Twins and Metaverse in the Field of Fluid Machinery Pumps and Fans: A Review

Yang

et al. 2022

Sensors

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“…In the manufacturing industry, DT has been used for a variety of applications, including product lifecycle management [50], production planning and control [51], and process redesign [27]. In the construction industry, DT has been used in building operations and maintenance [52], fragility assessment [53], construction safety [54], performance-based smart contracts [55], and building energy simulations [56]. A recent survey by McKinsey estimates 70% of manufacturers to use DTs by 2022 [57].…”

Section: Application Areas Of Dtmentioning

confidence: 99%

Digital Twin: Where do humans fit in?

Agrawal

Thiel²,

Jain³

et al. 2023

Automation in Construction

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“…Benefits of Digital Twin to the construction industry (Madubuike et al, 2022), (Akanmu et al, 2021), (Boje et al, 2020), (Khajavi et al, 2019) Emerging technology and trends to support evolution from BIM to Digital Twin (Menassa, 2021), (Chiachío et al, 2022), (Jiang et al, 2022), (Li et al, 2021), (Pan and Zhang, 2021), (Seghezzi et al, 2021), (Tariq et al, 2022), (Zhang et al, 2022), (Almatared et al, 2022), (Deria et al, 2022) Digital Twin knowledge transfer (Elsehrawy et al, 2021) Cybersecurity for Digital Twin (Alshammari et al, 2021) Cyber-Physical System (Alshammari et al, 2021), (Akanmu et al, 2021), (Jiang et al, 2022), (Pregnolato et al, 2022), (Pan and Zhang, 2021), (Yuan and Anumba, 2020) Smart Infrastructure Digital Twin (Broo et al, 2022), (Pregnolato et al, 2022) Simulation (Chiachío et al, 2022), (Yuan and Anumba, 2020), (Zhang et al, 2022) Real-time information exchange (Jiang et al, 2022) Workflow for the development of Digital Twin (Pregnolato et al, 2022), (Pan and Zhang, 2021), (Broo et al, 2022), (Sobhkhiz and El-Diraby, n.d.) The adoption of Digital Twins in the A/E/C/FM industry remains low as compared to other industries. The slow rate of adoption can be attributed to three factors (Madubuike et al, 2022):…”

Section: Research Domain Literaturementioning

confidence: 99%

A tool-based system architecture for a digital twin: a case study in a healthcare facility

Harode¹,

Thabet²,

Dongre³

2023

ITcon

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Changes in the local and global markets are forcing A/E/C/FM (Architecture, Engineering, Construction, and Facility Management) organizations to deliver more robust and innovative operational BIMs (Building Information Models). It is hypothesized that BIMs will transform from a static 3D model to a Digital Twin providing a truly digital representation of the physical asset or the building it represents. This transformation to a dynamic Digital Twin will allow the A/E/C/FM industry to visualize, monitor, and optimize operational assets and processes to support better inspection and analysis for a more efficient facility operations and maintenance. To support the adoption and implementation of Digital Twin in A/E/C/FM, the authors have defined two clear objectives. First, we discuss requirements for a functionality-based canonical architecture to create a digital twin followed by proposing two tool-based system architecture options for its implementation. Second, we use a case study approach to develop a proof-of-concept Digital Twin of an operating room in a healthcare facility using Power BI Desktop and Azure Services. The prototype aims to monitor room air quality as per INAIL (National Institute for Insurance against Accidents at Work) and ISO (International Organization for Standards) standards. Multiple sensors connected to a Raspberry Pi 4 are used to capture real-time data for various air quality parameters including temperature, humidity, airflow, particulate contamination, and Nitrous Oxide (N2O) gas. Multiple dashboards are also created to visualize, monitor, and analyze the data harnessed from the OR sensors. The implementation addresses critical issues including security, data storage, visualization, processing, data streaming, collection, and analysis. As an initial validation, the Digital Twin prototype was presented and discussed with a healthcare BIM manager. Initial feedback from the industry expert indicated that the prototype could decrease the required time to respond to facility maintenance issues such as decreased air flow due to possible obstructions.

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Digital twin-driven virtual sensor approach for safe construction operations of trailing suction hopper dredger

Cited by 38 publications

References 36 publications

Application of Digital Twins and Metaverse in the Field of Fluid Machinery Pumps and Fans: A Review

Application of Digital Twins and Metaverse in the Field of Fluid Machinery Pumps and Fans: A Review

Digital Twin: Where do humans fit in?

A tool-based system architecture for a digital twin: a case study in a healthcare facility

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