# A Review of Deep Learning Applications in Tunneling and Underground Engineering in China
## 3 Intelligent Application of Deep Learning in Tunnel Engineering
### Subsea Tunnel
#### 3.3.2 Seawater Seepage Erosion  
In seepage erosion problems in submarine tunnels, the non-linear variation of the seepage coefficient has a great influence on the stability of the seepage field [85]. In general, the water pressure is transferred to the lining structure through the surrounding rock and the grouting reinforcement ring, so the coupling effect of seepage and stress fields on the lining structure must be considered when solving the unsteady seepage problem. [PERSON] et al. [86; 87] established an elastic-plastic stress-seepage-damage coupling model for rock based on analyzing the effect of groundwater on the stability of the surrounding rock in submarine tunnels and water-rich tunnels offshore. The coupling model takes into account the seepage and stress effects caused by rock cracks and inverts the coupling parameters according to observed data such as head and displacement. The stress field, seepage field, and damage field of the rock surrounding the tunnel through the river under the subway station of Dalian Maritime University were analyzed by combining the intelligent inversion analysis method with the principle of the differential evolution algorithm.  
At the same time, due to the existence of a large number of inorganic salts in seawater, the contents of chlorine salt, sulfate, and magnesium salt are much higher than those in freshwater, including the influence of chemical attack medium, the climate environment, and concrete structure factors [88]. With the passage of time, this will cause corrosion damage to the lining structure and have a great impact on the durability of the tunnel (as shown in Figure 9). [PERSON] et al. [89] think that grouting material is an essential guarantee for the subsea tunnel to operate throughout its design service life. Sulfate erosion resistance, seawater penetration resistance, chloride ion penetration resistance, and volume stability are selected as the durability evaluation indexes of grouting material, which is evaluated via a fuzzy comprehensive evaluation method. [PERSON] et al. [90] analyzed the durability of the subsea tunnel with respect to chloride ion diffusion, steel bar corrosion, and protective layer cracking in three stages and established a life prediction model of the subsea tunnel, which was used to predict the life of the Xiang'an subsea tunnel.  
Because of the seepage problem in subsea tunnels, the finite element method combined with neural networks is still used for analysis. Due to their high risks, strong uncertainty,  
Figure 9: The construction process of the coupling degree model.  
and the difficulties in geological survey and construction, subsea tunnels are more challenging when it comes to obtaining and calculating parameters and have higher monitoring requirements. The realization of an intelligent analysis model also requires more reliable data. In addressing the erosion problem, traditional fuzzy mathematics, risk assessment, and other methods are widely used. However, there is still a certain distance from achieving intelligent analysis. The reasons are mainly attributed to the long erosion time, the poor timeliness of data acquisition, and the low accuracy in predicting the erosion area and scope, which represent significant challenges that need to be addressed in the future.