PSI - Issue 64

Chongjie Kang et al. / Procedia Structural Integrity 64 (2024) 1232–1239 Chongjie Kang, Maria Walker, Steffen Marx / Structural Integrity Procedia 00 (2019) 000 – 000

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physical entity in a virtual space, and a bidirectional information flow between the physical entity and the virtual twin. The DT serves as a service platform that provides all the necessary information on the real twin for the respective application. Kritzinger et al. (2018) proposed a classification of DT into three subcategories, according to their level of data integration.: digital model, digital shadow, and digital twin. In this scope, a digital model is a digital representation of a physical object that does not involve any automated data exchange between the physical and digital objects. If there is a one-way automated data flow between the physical and the digital objects, it is called a digital shadow. In comparison, a DT involves a two-way data flow and can act as a controlling instance of the physical object. However, this classification does not consider other important characteristics of digital twins, such as use cases in practice or classification in a specific product class like a civil engineering structure. To address this, maturity levels have been used to grade digital twins according to the scope and complexity of their capabilities. This approach enables the formulation of specific requirements for a digital twin. Other characteristics, like the level of hierarchy and the life cycle phases, can also be used for digital twin classification. According to Lueth (2020), a classification cube was developed to provide a three-dimensional view of a digital twin's capabilities, considering temporal and spatial relationships; see Fig. 2.

Fig. 2. Classification cube for digital twins in the construction industry, own illustration according to Lueth (2020)

Based on the level of hierarchy, individual components of a bridge structure, like bridge piers or sensors, can be represented as component twins, while the combination of these components forms an asset twin that represents the entire structure. Connecting multiple asset twins creates a system twin. Moreover, network twins are formed when system twins from different domains are combined, such as linking bridge twins with the vehicles crossing them. Besides, the digital twins should be ideally used throughout the entire life cycle of structures, including design, construction, operation, maintenance, and demolition, according to Jiang et al. (2021a). In the construction sector, Building Information Modelling (BIM) has become an effective method to design, plan, and build structures. The concept of maturity levels for a BIM-based digital twin has been defined by BuildingSMART (2020), which is an extension of the BIM methodology. These levels describe the capabilities of a digital twin, with higher levels including functionalities of lower levels; see Tab. 1.

Tab. 1. Definition of maturity levels according to buildingSMART (2020) DT maturity level Description of capabilities

Question

1. 2. 3. 4. 5.

Descriptive Informative Predictive Prescriptive

Collecting and visualizing data Aggregating and analyzing data Real-time monitoring and prediction Prescriptive analytics propose interventions

What happened? Why did it happen? What will happen? What should I do?

Transformative

Autonomously taking actions

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