Predicting Tunnel Groundwater Inflow by Geological Investigation Using Horizontal Directional Drilling Technology
Auteur(s): |
Xialin Liu
|
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Advances in Civil Engineering, janvier 2022, v. 2022 |
Page(s): | 1-12 |
DOI: | 10.1155/2022/6578331 |
Abstrait: |
To improve the prediction accuracy of tunnel excavation groundwater inflow, a prediction method based on a horizontal directional drilling geological survey is proposed. It relies on the monitoring and statistical analysis of groundwater inflow into a horizontal directional drilling survey borehole. Moreover, it is based on Goodman’s empirical back-calculation for the surrounding rock penetration coefficient and uses the groundwater dynamics method to predict the amount of inflow into the tunnel excavation. On the basis of an analysis of the Tianshan Shengli Tunnel, the following conclusions were obtained: the tunnel excavation groundwater inflow prediction method based on a horizontal directional drilling geological survey borehole can be used to obtain the permeability coefficient value of the surrounding rock, which can be used in the groundwater dynamics method to improve the prediction accuracy; the groundwater runoff modulus method and the atmospheric precipitation infiltration method underestimate the prediction results for tunnel groundwater inflow; and the groundwater dynamics calculation results based on the horizontal survey hole prediction method are more reliable. Goodman’s empirical formula was used to predict normal groundwater inflow within the 2,271 m length from the tunnel entrance: the normal groundwater inflow into the right tunnel was approximately 6,441 m³/d, and the maximum groundwater inflow was approximately 19,323 m³/d. When the tunnel crosses the fault zone, the groundwater inflow increases significantly. The normal groundwater inflow per unit footage is approximately 7.30 m³/(d·m), and the portion of the tunnel that crosses the fault zone is a medium to strong water-rich section. |
Copyright: | © Xialin Liu et al. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10698187 - Publié(e) le:
11.12.2022 - Modifié(e) le:
15.02.2023