Risk section classification of tunnel settlement based on land-use development simulation and uncertainty analysis

Abstract

• Propose a method to identify the settlement risk section along metro lines. • Extend Artificial Neural Network–Cellular Automata on uncertainty analysis. • Present a detailed case study for verification. “Metro economy” has led to intensive land development along the metro lines. However, engineering activities associated with land development inevitably disturb the service environment, causing severe settlement of adjacent metro tunnel structures in soft soil areas. As a reference point for pre-treating this type of tunnel settlement, a method is proposed to classify settlement risk sections along metro lines based on a land-use development simulation and corresponding uncertainty analysis. First, the land-use development along the metro line was simulated by Artificial Neural Network–Cellular Automata (ANN-CA). Second, the land-use development process was considered a random event rather than a deterministic prediction as in a typical ANN-CA, with its probability quantified based on the cells’ conversion probability. The classification of the surrounding land-use development probability was used to allocate the settlement risk sections of metro lines. This method was applied to the Han–You section of the Nanjing Metro Line 2. The predicted settlement risk sections corresponded suitably with the actual settlement troughs, demonstrating the effectiveness of this method. Thus, this method provides a novel consideration for the pre-treatment of metro tunnel settlement from the perspective of interactions between the metro line and surrounding land development.