Settlement-based triple factor framework for long-term safety assessment of immersed tunnel

Abstract

Cracks and leaking water pose significant challenges during the maintenance of immersed tunnels. Current research on immersed tunnels predominantly focuses on settlement monitoring or prediction, leaving a notable gap in assessing tunnel safety performance due to the lack of an appropriate assessment framework. This paper proposes a novel settlement-based triple factor framework for the long-term safety assessment of immersed tunnels, consisting of total settlement, angular distortion, and joint differential settlement. Threshold limit value (TLV) for these factors are defined based on a comprehensive analysis of settlement data from 18 immersed tunnels. Additionally, this framework incorporates a dynamic updating strategy to refine the settlement prediction model, thereby providing a more accurate database for TLV updates by integrating observational information. This strategy enables a more accurate assessment of specific tunnels. The Hong Kong-Zhuhai-Macau Bridge tunnel is used as a case study to illustrate the effectiveness of the proposed framework. The results highlight the importance of considering three key factors and implementing a dynamic updating strategy for TLV in safety assessments. This framework can offer valuable guidance for the long-term maintenance of immersed tunnels.