# A Comprehensive Review of Open Caisson Modeling Technology: Current Practices and Future Prospects
## 3 Advances in Physical Modeling Method  
Physical model tests in the geotechnical engineering field played a crucial and fundamental role in studying complex geo-structure problems [17]. Physical modeling involves creating scaled-down models that simulate the behavior of various geotechnical problems/prototypes. By using appropriately sized models, researchers have gained valuable insights [18; 19]. Physical models play a vital role in evaluating complex open caisson systems. These systems are often dependent on factors such as construction techniques, non-linear soil-structure interactions, and variable geometries. These tests can serve as substitutes for numerical models or as valuable supplements. To verify the validity of the various assumptions and approaches of the numerical models, data from physical model tests are often used. Moreover, physical model results can also be used to rectify numerical models to better represent anticipated loading conditions. The initial physical model was offered by [20], which utilized sand to simulate and explain the subsidence phenomenon. While numerical and analytical tunneling research  
Figure 3: Framework for review of advance modeling approaches. has expanded due to advancements in computational techniques, geotechnical engineering researchers continue to use physical modeling to explore different facets of tunneling, such as failure mechanisms and deformation patterns. The important goal of any model testing is to extend model behavior to the corresponding behavior of the prototype. However, in most physical models, prototypes are based on proposed excavations. It is therefore usually not possible to directly compare the behavior of a model with that of a field. To evaluate how well physical models represent field behavior, the model findings should be contrasted to field data that have features similar to theoretical prototypes and to existing prediction approaches for ground deformation associated with excavations. The physical model findings were assessed using the projected settlement profiles provided by [21; 22], which are two reputable methods for predicting excavation-induced deformation. In open caisson construction, 1-g modeling is typically used because it is less expensive [21; 22; 23; 24; 25; 26]; however, because the simulated stress state was reasonable [27; 28; 29], the n-g type grows quickly. Also, 1-g modeling can be carried out at a greater scale than n-g modeling. According to [21; 30], 1-g model tests exhibited the following characteristics: (1) they can be carried out with more control over the model's parameters, (2) eliminate adverse impacts linked to small models, such as the grain size impact, (3) allow information about the expected patterns of reaction to be received more quickly, (4) provide more space for monitoring components while causing the least disruption to soil behavior, and (5) can potentially be repeated at a relatively low cost. The effectiveness of 1-g models was constrained by their inability to simulate in situ stresses realistically. Notwithstanding this constraint, 1-g models have been utilized in soft ground tunneling studies [31]. Numerical models can be calibrated and validated using data from physical models. Many researchers worldwide have created and applied a range of methods to replicate the deep excavation process over the course of several decades. Tests conducted on a smaller scale in 1-g conditions provide complete control over the excavation process. Physical modeling has recently been used at various scales and study domains, from the laboratory scale to full scale, to calibrate behavior under real-world conditions [32; 33]. The technical and economic aspects of the physical modeling influenced the test efficiency and the quality of the results [18; 33]. Finally, it is usually not practicable to fully comply with scaling laws. When compared to centrifuge modeling, physical modeling under single gravity (1-g) is typically more cost-effective.