# Reshaping the Digital Twin Construct with Levels of Digital Twinning (LoDT)
## 4 Assessing the Level of Digital Twinning (LoDT)
### Digital Twinning Level of Road and Rail Case Studies
#### 4.4.2 Case Studies  
Three case studies (Figure 4), covering both road and rail networks, were selected to validate the applicability of the UNI-TWIN model:  
* Case study [A] [104] involves a real-time Dissolved Gas Analysis (DGA) system in a power transformer at the Salreu traction substation, located on Linha do Norte railway line. The Hydran M2-X unit continuously monitors and communicates gas and moisture levels in the power transformer oil. It promptly alerts the user to abnormal readings, minimizing the risk of unplanned outages and reducing the associated costs of reactive interventions. * Case study [B] [105] focuses on the federation and interaction of a Fatigue Analysis System and a BIM model for the Varzeas railway bridge, located on the Linha da Beira Alta railway line. This integrated solution enables decision-makers to simulate traffic scenarios and predict the fatigue life of the bridge, facilitating informed long-term investment decisions. * Case study [C] [106; 107] is a real-time monitoring system for a section of road pavement on the IC5 route, km 75 + 700. The project goal is to develop a pavement condition prediction model, integrated with a geometrical model, to support long-term renewal planning. At the present time, the system has only real-time monitoring capabilities (e.g., strain, temperature, and number of vehicles), so the predictive capabilities and the integration with the geometrical model are still to be achieved. Table 6 provides a brief description of the case studies and their characteristics according to the nine dimensions of digital twinning. Each description is based on available documents and project information provided by the experts of IP. Based on the characteristics of each case study and the levels assigned to each dimension of digital twinning, it is possible to construct the digital twinning radar shown in Figure 5.  
As shown in Figure 5, the case studies of the power transformer ([A]) and road pavement ([C]) have a more pronounced level of digital twinning in the components of connection and synchronization. This is justified by the real-time monitoring purpose of these assets. On the other hand, the metal bridge case study ([B]) exhibit a high degree of development in the geometric representation component, indicating some expertise in this dimension. Case study [B] stands out with the highest level of intelligence, attributed to its goal of predicting the long-term fatigue life of the bridge. Case study [C] also aims to develop predictive capabilities based on collected data but currently only has the capacity \begin{table}
\begin{tabular}{|p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt}|} \hline \hline
**Case Study** & **Hierarchy** & **Connection** & **Synchron.** & **Geom. Rep.** & **NGeom. Rep.** & **Intelligence** & **Interface** & **Accessib.** & **Autonomy** \\ \hline
[A] & (1) & (4) & (5+) & (1) & (3) & (1) & (2) & (1) & (2) \\  & \multirow{4}{*}{Component (oil of a single power transformer)} & Automatic from physical to digital space (via Ethernet) & Automatic from & & & & & & & \\  & & Readings sent to user every 15 s & No representation to user every 15 s & No representation to user by using testing & & & & & & \\  & & & & & & & & & \\  & & & & & & & & & \\  & & & & & & & & & \\  & & & & & & & & & \\ \hline
[B] & (2) & (2) & (1) & (5+) & (3) & (3) & (2) & (1) & (1) \\  & & & & & & & & & \\  & & & & & & & & & \\  & & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & & \\  & & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\ \hline
[C] & (1) & (4) & (5+) & (1) & (3) & (1) & (1) & (1) & (1) \\  & & & & & & & & & \\  & & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\  & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Digital twinning level of road and rail case studies. Figure 4: Identification of case studies. for descriptive analyses.