The concept of digital twin (DT) is undergoing rapid transformation and attracting increased attention across industries. It is recognised as an innovative technology offering real-time monitoring, ...simulation, optimisation, accurate forecasting and bi-directional feedback between physical and digital objects. Despite extensive academic and industrial research, DT has not yet been properly understood and implemented by many industries, due to challenges identified during its development. Existing literature shows that there is a lack of a unified framework to build DT, a lack of standardisation in the development, and challenges related to coherent goals of DT in a multi-disciplinary team engaged in the design, development and implementation of DT to a larger scale system. To address these challenges, this study introduces a unified framework for DT development, emphasising reusability and scalability. The framework harmonises existing DT frameworks by unifying concepts and process development. It facilitates the integration of heterogeneous data types and ensures a continuous flow of information among data sources, simulation models and visualisation platforms. Scalability is achieved through ontology implementation, while employing an agent-based approach, it monitors physical asset performance, automatically detects faults, checks repair status and offers operators feedback on asset demand, availability and health conditions. The effectiveness of the proposed DT framework is validated through its application to a real-world case study involving five interconnected air compressors located at the Connected Facility at Devonport Royal Dockyard, UK. The DT automatically and remotely monitors the performance and health status of compressors, providing guidance to humans on fault repair. This guidance dynamically adapts based on feedback from the DT. Analyses of the results demonstrate that the proposed DT increases the facility’s operation availability and enhances decision-making by promptly and accurately detecting faults.
Digital Twin (DT) concept has recently emerged in civil engineering; however, some problems still need to be addressed. First, DT can be easily confused with Building Information Modelling (BIM) and ...Cyber-Physical Systems (CPS). Second, the constituents of DT applications in this sector are not well-defined. Also, what the DT can bring to the civil engineering industry is still ambiguous. To address these problems, we reviewed 468 articles related to DT, BIM and CPS, proposed a DT definition and its constituents in civil engineering and compared DT with BIM and CPS. Then we reviewed 134 papers related to DT in the civil engineering sector out of 468 papers in detail. We extracted DT research clusters based on the co-occurrence analysis of paper keywords' and the relevant DT constituents. This research helps establish the state-of-the-art of DT in the civil engineering sector and suggests future DT development.
•Proposed a definition of Digital Twin and its constituents in the Civil Engineering sector.•Distinguished between Digital Twin and BIM and Cyber-Physical System.•Identified the research clusters of Digital Twin in the Civil Engineering sector.•Suggested future development in the corresponding research clusters.
Alongside advancements in Artificial Intelligence (AI), significant progress has been made in big data processing, edge/cloud computing, and ubiquitous computing in the past two decades. These ...advancements catalyzed the development and adoption of Digital Twins (DT) across various domains, serving as virtual replicas of Physical Objects (POs). DTs provide advanced visualization and simulation capabilities, enabling effective estimation, optimization, and forecasting of PO's behaviors. However, the widespread adoption of DTs has introduced various security threats, vulnerabilities, and attacks. Despite ongoing research in DT applications and security, there is a lack of systematic review of the DT security literature across domains and architectural layers. This study fills this gap by systematically reviewing DT research, focusing on three interrelated aspects: DT applications, architectural layers, and security. We explore DT's architectural layers, functional requirements, application, and creation software to identify potential threats, attacks, and vulnerabilities specific to DT layers and application domains. We then systematize our findings under a unified security framework and pinpoint countermeasures against identified security challenges. Furthermore, our study explores DT's role in mitigating existing cyber threats, and we conclude our work by identifying open challenges and potential research directions.
Digital twin, a core technology for intelligent manufacturing, has gained extensive research interest. The current research was mainly focused on digital twin based on design models representing ...ideal geometric features and behaviors at macroscopic scales, which is challenging to accurately represent accuracy and performance. However, a numerical representation is essential for precision microstructures whose accuracy and performance are difficult to measure. The concept of a digital twin for an accurate representation, proposed in 2015, is still in the conceptual stage without a clear construction method. Therefore, the goal of accurate representation has not been achieved. This paper defines the concept and connotation of an accuracy and performance-oriented accurate digital twin model and establishes its architecture in two levels: geometric and physical. First, a geometric digital twin model is constructed by the contact surfaces distributed error modeling and virtual assembly with nonuniform contact states. Then, based on this, a physical digital twin model is constructed by considering the linear and nonlinear response of the structural internal physical properties to the external environment and time to characterize the accuracy and performance variation. Finally, the models are evaluated. The method is validated on microtarget assembly. The estimated values of surface modeling, center offset, and stress prediction accuracy are 94.22%, 89.3%, and 83.27%. This paper provides a modeling methodology for the digital twin research to accurately represent accuracy and performance, which is critical for product quality improvements in intelligent manufacturing. Research results can be extended to larger-scale precision structures for performance prediction and optimization.
highlights•An overview of state-of-the-art research on the topic of Digital Twins in agriculture.•Machine learning enables Digital Twins to be developed for complex agricultural systems, utilizing ...large amounts of data collected from sensors.•Diverse applications and use-cases were identified, including aquaponic, robotic and greenhouse systems.•Examples of what-if simulation in agricultural Digital Twin applications remain limited
The Digital Twin enables the distinctions between state sensing, entity understanding and physical automation to be eliminated, through high-fidelity modelling and bi-directional data streams. The concept of real-time virtual representation places the Digital Twin in a unique position to enable digitization in agriculture. The union of data, modelling and what-if simulation can provide an approach to overcome current limitations in decision-making support and automation, across a diverse range of agricultural enterprises. This paper conducts a Systematic Literature Review of Digital Twins in agriculture, identifying current trends and open questions with the goal of increasing awareness and understanding of the Digital Twin and its possibilities.
A building digital twin (BDT) can maintain an up-to-date digital model reflecting physical world conditions and has become necessary for building applications. Recent studies on the BDT employed the ...Internet of Things to sense physical-world conditions. Although cameras are one of the most widely used facilities in buildings, their adoption in the BDT remains unexplored. This study proposes a novel computer-vision (CV)-enabled BDT scheme using building information modeling (BIM) taking camera videos as input, which addresses the dimension, coordinate system, and object inconsistencies between BIM and camera videos. First, the proposed BDT scheme detects objects' locations and rotations jointly using a 2-D object detection network and a 3-D object estimation network. Then, theorem and lemmas are presented to compute the 3-D locations in BCS using detected 2-D locations. Thirdly, both cold-start object matching and run-time object matching schemes are proposed to address the object inconsistency between camera videos and BIM. Finally, experiments were conducted in the real-world environment. The experiment results showed that the proposed BDT scheme maintained average location errors of 0.181 m with distortions preserved and 0.165 m with distortions removed in the manual calibration scenario, 0.166 m with distortions preserved, and 0.195 m with distortions removed in automatic calibration scenario. This finding proved the effectiveness of the proposed BDT scheme. This study is the first to explore a BDT scheme on top of BIM using CV. It is anticipated that this study will inspire more intelligent studies in smart buildings jointly employing both CV and BIM.
•Establishing the digital twin approach aimed at monitoring the RUL of the components.•Computationally fast DT models of drivetrain components based on torsional measurements.•Confidence interval for ...components damage by stochastic models and statistical approaches.•A robust and computationally fast method to estimate drivetrain ROM parameters of different DOFs.•Using estimated parameters for automated fault diagnosis and prognosis.•Physics-based degradation model to estimate RUL of shafts by estimated ROM, real-time measurements and load observer.•Taking into account the uncertainties by statistical approaches and stochastic modeling of damage.
This paper presents a digital twin (DT) condition monitoring approach for drivetrains on floating offshore wind turbines. Digital twin in this context consists of torsional dynamic model, online measurements and fatigue damage estimation which is used for remaining useful life (RUL) estimation. At first, methods for system parameter estimation are presented. The digital twin model provides sufficient inputs for the load observers designed in specific points of the drivetrain to estimate the online load and subsequently stress in the different components. The estimated real-time stress values feed the degradation model of the components. The stochastic degradation model proposed for estimation of real-time fatigue damage in the components is based on a proven model-based approach which is tested under different drivetrain operations, namely normal, faulty and overload conditions. The uncertainties in model, measurements and material properties are addressed, and confidence interval for the estimations is provided by a detailed analysis on the signal behavior and using Monte Carlo simulations. A test case, using 10 MW drivetrain, has been demonstrated.
While there has been a recent growth of interest in the Digital Twin, a variety of definitions employed across industry and academia remain. There is a need to consolidate research such to maintain a ...common understanding of the topic and ensure future research efforts are to be based on solid foundations. Through a systematic literature review and a thematic analysis of 92 Digital Twin publications from the last ten years, this paper provides a characterisation of the Digital Twin, identification of gaps in knowledge, and required areas of future research. In characterising the Digital Twin, the state of the concept, key terminology, and associated processes are identified, discussed, and consolidated to produce 13 characteristics (Physical Entity/Twin; Virtual Entity/Twin; Physical Environment; Virtual Environment; State; Realisation; Metrology; Twinning; Twinning Rate; Physical-to-Virtual Connection/Twinning; Virtual-to-Physical Connection/Twinning; Physical Processes; and Virtual Processes) and a complete framework of the Digital Twin and its process of operation. Following this characterisation, seven knowledge gaps and topics for future research focus are identified: Perceived Benefits; Digital Twin across the Product Life-Cycle; Use-Cases; Technical Implementations; Levels of Fidelity; Data Ownership; and Integration between Virtual Entities; each of which are required to realise the Digital Twin.
With significant advancement in information technologies, Digital Twin has gained increasing attention as it offers an enabling tool to realise digitally-driven, cloud-enabled manufacturing. Given ...the nonlinear dynamics and uncertainty involved during the process of machinery degradation, proper design and adaptability of a Digital Twin model remain a challenge. This paper presents a Digital Twin reference model for rotating machinery fault diagnosis. The requirements for constructing the Digital Twin model are discussed, and a model updating scheme based on parameter sensitivity analysis is proposed to enhance the model adaptability. Experimental data are collected from a rotor system that emulates an unbalance fault and its progression. The data are then input to a Digital Twin model of the rotor system to investigate its ability of unbalance quantification and localisation for fault diagnosis. The results show that the constructed Digital Twin rotor model enables accurate diagnosis and adaptive degradation analysis.
•The Digital Twin mimic model is an integrated model containing geometry, behavior and context information.•The Digital Twin modeling method based on biomimicry principles can adaptively construct a ...multi-physics digital twin of the machining process.•The biomimicry-based Digital Twin modeling method is verified with a study of monitoring and controlling the machining process of an air rudder.
High-performance aerospace component manufacturing requires stringent in-process geometrical and performance-based quality control. Real-time observation, understanding and control of machining processes are integral to optimizing the machining strategies of aerospace component manufacturing. Digital Twin can be used to model, monitor and control the machining process by fusing multi-dimensional in-context machining process data, such as changes in geometry, material properties and machining parameters. However, there is a lack of systematic and efficient Digital Twin modeling method that can adaptively develop high-fidelity multi-scale and multi-dimensional Digital Twins of machining processes. Aiming at addressing this challenge, we proposed a Digital Twin modeling method based on biomimicry principles that can adaptively construct a multi-physics digital twin of the machining process. With this approach, we developed multiple Digital Twin sub-models, e.g., geometry model, behavior model and process model. These Digital Twin sub-models can interact with each other and compose an integrated true representation of the physical machining process. To demonstrate the effectiveness of the proposed biomimicry-based Digital Twin modeling method, we tested the method in monitoring and controlling the machining process of an air rudder.
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