Evaluation on the state of sand filling layer and the influence on segment deformation of immersed tunnels

Abstract

The immersed tunnel is considered an effective solution for traffic problems across rivers and seas. The sand filling layer, as an important part of immersed tunnel foundation treatments, directly affects segment attitude stability. Due to difficulties in quality control of concealed construction and the complex hydrodynamic environment, the sand filling layer is prone to compaction defects, further leading to changes in segment attitude. However, limited by structural concealment and state complexity, most studies consider the sand filling layer part of the foundation to study its impact on settlement while neglecting its influence on segment attitude. This research proposes an evaluation method for the sand filling layer state based on elastic wave testing and the elastic wave characteristic parameters selected come from analysis of the time domain, frequency domain and time-frequency domain. By classifying the elastic wave characteristic parameters through the K-means clustering method, the relationship between the state of the sand filling layer and the elastic wave characteristic parameters is established. The state of the sand filling layer is divided into dense, incompact, and void. A numerical model is established based on the Guangzhou BI-UT immersed tunnel with incompact and void sand filling layer states to simulate deformation and torsion. The results indicate that the settlement of the tunnel segment is low in the eastern region and high in the western region due to the presence of a less dense sand filling layer, with a maximum differential settlement of 0.04 m. The evaluation method plays a crucial role in guiding the construction of immersed tube tunnels.

Keywords

Sand filling layer state / Immersed tunnel / Elastic wave test / Clustering algorithm

CRediT authorship contribution statement

Ziyao Xu: Writing - review & editing, Writing - original draft. Ailan Che: Conceptualization. Chao Su: Data curation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This work was supported by Yunnan Province Major Science and Technology Special Plan (Grant No. 202303AA080010), the National Natural Science Foundation of China (Grant No. 52122110), the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University, China (Grant No. SL2021PT302), and Academician Special Program of China Communications Construction Company (CCCC).

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