# Development and Application of Digital Twin Technique in Steel Structures
## 3 Literature Innovation Discussion
### Definition Evolution  
The definition of the twin model in the digital twin technique has undergone extensive evolution and development. The literature distribution about the evolution of the digital twin definition can be integrated in Table 1. Initially, the digital twin technique emerged from graphic analysis methods based on digital forms, primarily involving digital image correlation and electron backscatter diffraction. These methods were combined and widely used to study the properties of steel materials, with various application aspects such as surface damage in tensile processes [1,131], deformation behavior of steel [35,125], strain mechanism of steel [57,138], plasticity behavior of steel [38,110], fracture mechanism of metallic materials [44,140], quality evaluation of alloys [75,132], instrumented indentation of steel [79,128], dynamic behavior of metal tests [124,134], etc. The situation suggests that while the method can effectively reveal the deformation, fracture, and dynamic properties of steels, it remains confined to the technical level. \begin{table}
\begin{tabular}{l l l} \hline
**Definition** & **Aspect** & **References Number** \\ \hline \multirow{7}{*}{First step: Digital form} & Surface damage in tensile process & [10,82,108,118,131] \\  & Deformation behavior of steel & [35,55,56,94,97,125] \\  & Strain mechanism of steel & [57,83,85,91,96,127,138] \\  & Plasticity behavior of steel & [38,58,100,110] \\  & Fracture mechanism of metallic materials & [44,68,76,123,140] \\  & Quality evaluation of alloys & [75,87,132,129,130,132] \\  & Instrumented indentation of steel & [79,128] \\  & Dynamic behavior of metal tests & [124,134] \\ \hline \multirow{7}{*}{Second step: Virtual model} & Monitoring for steel structures & [6,16,17,62,104,107] \\  & Maintenance for large-span structures & [5,34,45,65,72,104] \\  & Research on strip rolling technique & [14,27,46,115,139] \\ \cline{1-1}  & Additive manufacturing & [51,63,76,126] \\ \cline{1-1}  & Prediction for steel manufacturing & [26,28,29,48,73] \\ \cline{1-1}  & Fatigue evaluation of infrastructure & [7,16,24,34,40,81,92] \\ \cline{1-1}  & Construction of steel materials & [53,70,99] \\ \cline{1-1}  & Digitalization in chemical engineering & [66,101] \\ \hline \multirow{7}{*}{Third step: Surrogate model} & Crack identification and location & [1,8] \\ \cline{1-1}  & Improvement of steel production & [11,13,21,88] \\ \cline{1-1}  & Mechanical mechanism modeling & [23,64,102] \\ \cline{1-1}  & Condition monitoring for steel equipment & [52,104] \\ \cline{1-1}  & Prediction and maintenance of structure & [30,54,78] \\ \hline \end{tabular}
\end{table} 
Table 1: Literature distribution of the digital twin definition. With the sustainable development of computing and the Internet of Things, the digital twin technique has acquired a new definition. A virtual model can be established based on real structures and then updated with real-time monitoring data, represented by the laser scanning and finite element models. This virtual model method is also involved in many typical applications, such as monitoring for steel structures [6, 107], maintenance for large-span structures [5, 65], research on strip rolling techniques [14, 139], additive manufacturing [63, 126], prediction for steel manufacturing [26, 73], fatigue evaluation of infrastructure [7, 92], construction for steel materials [53, 99], digitalization in chemical engineering [66, 101], etc. From the above literature, the virtual model method presents significant advancements in steel material digitalization, steel component manufacturing, and structural condition maintenance, meaning that this technique has gradually evolved from focusing on steel materials to encompassing steel structures. Real-time monitored data enable the model to iterate, advancing beyond the technical level and gaining importance for the Internet of Things.