Back to Search Start Over

Prediction of tunnel water inflow based on stochastic deterministic three-dimensional fracture network.

Authors :
Shi, Shaoshuai
Guo, Weidong
Li, Shucai
Xie, Xiaokun
Li, Xiansen
Zhao, Ruijie
Xue, Yang
Lu, Jie
Source :
Tunneling & Underground Space Technology. May2023, Vol. 135, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

[Display omitted] • 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. 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08867798
Volume :
135
Database :
Academic Search Index
Journal :
Tunneling & Underground Space Technology
Publication Type :
Academic Journal
Accession number :
162390990
Full Text :
https://doi.org/10.1016/j.tust.2023.104997