# Development and Application of Digital Twin Technique in Steel Structures
## 3 Literature Innovation Discussion
### Methodology Development  
The methodologies of the digital twin technique have experienced tremendous development over the past decade, primarily involving building information modeling (BIM), machine learning algorithms, laser scanning with point clouds, finite element modeling, and digital image correlation. Digital image correlation can be considered the predecessor of digital twins, and, hence, the quantity proportion of the literature for digital twin methodology mainly comprises the other four methods mentioned above, as illustrated in Figure 9. The figure indicates that finite element modeling appears more prevalent than other methods reported in the literature. The finite element method can be regarded as a digital twin technique equipped with a numerical simulation model, primarily conducted in the program \"Abaqus 2024\". It possesses the advantage in mechanical property of high precision, as shown as the mesh element of steel spindle provided by reference [48] in Figure 9. Through comparing the prediction results of the digital twin model with the actual performance of a physical structure, this type of model can simulate structural behavior under different conditions for reflecting its current state, and then the model can be optimized and adjusted to improve the prediction accuracy combined with real-time performance. Some research in the literature focuses on the combination of the finite element model and analysis algorithm to enhance simulation effects [3,109], while some research focuses on novel monitoring techniques for updating finite element models with real-time data [4,117] and others on the application effects of the finite element method [18,119], where the advantages of the finite element model are represented as efficient computing power, intuitive result displays, and high mechanical accuracy. The BIM method is another digital twin technique stringing structural design, construction, and management together, often performed in the program \"Revit 2024\". The core purpose of BIM is to achieve the integration of building information, ensuring that all relevant information throughout the entire life management (e.g., design, construction, and maintenance) is concentrated in a three-dimensional model information database, such as the virtual roll combined with an optical fiber, provided by reference [74] in Figure 9. Based on this method, three-dimensional graphics and an object-oriented technique combined with computer-aided design are utilized in construction projects. Some research in the literature focuses on the establishment of the BIM framework [6,115], some on the data exchange within the BIM model [5,101], and others on the effectiveness of the BIM model in  
Figure 9: Quantity proportion of the literature for digital twin methodology [48,74,78,90]. structural management [63, 103]. The research findings indicate that the BIM method offers advantages in improving efficiency in structural maintenance and facilitating collaborative information work. The laser scanning method relies on high-speed laser scanning measurements to obtain three-dimensional coordinates, reflectance, and color data of structural surfaces over large areas with high resolution and speed, usually conducted in the program \"CloudCompare 2.13\". It allows for the rapid reconstruction of the three-dimensional point-cloud model, as shown as the steel building measured by terrestrial laser scanning, provided by reference [90] in Figure 9. In the collected literature, some research focuses on the establishment process of point-cloud models through laser scanning [37, 90], some on model analysis to improve monitoring accuracy [12, 67], and others on model functionality for structural management enhancement [26, 122]. Moreover, these research findings highlight the advantages of the laser scanning method, which involves real-time dynamic monitoring, digital functionality, and high measurement efficiency.