# Performing Fatigue State Characterization in Railway Steel Bridges Using Digital Twin Models
###### Abstract  
Railway infrastructures play a pivotal role in developing the national transportation system. Recently, the strategy of the railway engineer has been significantly shifted; along with the development of new assets, they tend to pay increasing attention to the operation and management of existing railway assets. In this regard, this paper proposes a Digital Twin (DT) model to improve fatigue assessment efficiency in the operational processes of railway steel bridges (RSBs). The DT concept mainly lies in the federation and interaction of a Fatigue Analysis System (FAS), which is based on Eurocodes principles, and a model in Building Information Modeling (BIM). Along with the proposed DT concept, a prototyping system for a real bridge is initiated and curated. The FAS is validated in good-agreement results with the ambient vibration test of the bridge (about 1.6% variation between numerical and experimental values), and close values were found between numerical and experimental stresses, the latter obtained by installing strain gauges on the bridge. The BIM model provides access to the numerical values of fatigue state results in a given bridge connection detail but also automatically represents that information in a 3D environment using a color-scale-based visualization process. Furthermore, a simulation model with the main input variables being the traffic and geometric conditions of the bridge is continuously updated for timely re-evaluation of the damage state, which shows promise for the lifecycle management of the bridge. digital twin; fatigue damage; Fatigue Analysis System; BIM; railway steel bridge +
Footnote †: journal: Applied Sciences  
In the range of methodologies for structural integrity monitoring or that assist bridge operation and maintenance processes, including fatigue-related cases, the use of Digital Twin (DT) models currently stands out. Several definitions are attributed to Digital Twins (DTs) in the literature and extensive reviews on these models [8; 9; 10; 11; 12; 13]. The origin of DTs dates back to 1970 when NASA created mirror images of the Apollo 13 (physical twin) [14]. The modern concept of DT was first proposed in 2003 by [PERSON] [15] in an executive course on \"Product Lifecycle Management\", which can be considered a white paper for modern DT research. It was gradually updated to different contexts and fields, which is defined as a digital representation of a physical entity (asset, process, or system) that serves as a living digital simulation model fed by continuously collected data, such as operational data collected at bridges and other processing data linked to specific routines [16]. Although the basic definition of DT seems consensual, certain aspects surrounding it have still generated discussion. For instance, some consider that similar to Building Information Modeling (BIM), DTs are a process, not a technology [17]. However, regardless of the controversy, everything suggests that the application of DTs extends to engineering and non-engineering fields. Although the elemental composition of the DT follows a nearly universal pattern, there is no clear guideline or rule for creating these models. Three components are typically mentioned as making up the basic structure of DT: the physical entity in real space, the virtual entity (virtual model), and the connection between the physical and virtual parts through data flow [18]. In creating the DT model (e.g., for structural integrity assessment of a bridge), two approaches to virtual model processing should be highlighted: the physics-based approach and the data-driven approach. The first one, the virtual model, is built according to known physical laws and principles, i.e., it is a surrogate representation of a preconceived physical reality.