Prediction of tunnel water inflow based on stochastic deterministic three-dimensional fracture network. (May 2023)

• Record Type: Journal Article
• Authors: Shi, Shaoshuai; Guo, Weidong; Li, Shucai; Xie, Xiaokun; Li, Xiansen; Zhao, Ruijie; Xue, Yang; Lu, Jie
• Is Part Of: Tunnelling and underground space technology. Volume 135(2023)
• Publication Date: 2023-05
• Subjects: 3D fracture network simulation -- Connectivity analysis -- Full space parallel search -- Water inflow prediction; Tunneling -- Periodicals; Underground construction -- Periodicals; Tunnels -- Periodicals; Underground areas -- Periodicals; 624.193
• DOI: 10.1016/j.tust.2023.104997
• Languages: English
• ISSNs: 0886-7798

Abstract

Graphical abstract: Highlights: The random deterministic three-dimensional fracture coupling model is constructed. A new fracture search algorithm: full space parallel search algorithm is proposed. Based on this, the accurate prediction of water inflow of the tunnel is realized. Abstract: With the rapid development of national infrastructure construction, the water inrush disaster of "strong burst, high water pressure and large flow" is more and more frequent in the construction process. To achieve high-precision prediction of tunnel water inflow, based on the Yue Longmen Tunnel, according to the structural plane detection data in the study area, combined with the Monte Carlo algorithm and using "parent-daughter" and "step–structure" correction mode, this paper constructs a random deterministic three-dimensional fracture network seepage model. Based on the three-dimensional fracture network seepage model and the principle of flow balance, the water inflow of each mileage section of the Yue Longmen Tunnel is solved by numerical calculation method, and good results are obtained through comparison and verification. The research results have important theoretical significance and engineering application value for tunnel water inflow prediction.