Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/151673
Title: DDA based grouting prediction and linkage between fracture aperture distribution and grouting characteristics
Authors: Xiao, Fei
Shang, Junlong
Zhao, Zhiye
Keywords: Engineering::Civil engineering
Issue Date: 2019
Source: Xiao, F., Shang, J. & Zhao, Z. (2019). DDA based grouting prediction and linkage between fracture aperture distribution and grouting characteristics. Computers and Geotechnics, 112, 350-369. https://dx.doi.org/10.1016/j.compgeo.2019.04.028
Journal: Computers and Geotechnics
Abstract: Apertures of rock fractures is frequently considered as one of the most important factors affecting grouting characteristics. The real fracture distribution, however, is inaccessible due to its complex intrinsic properties, making it cumbersome to directly assess its impact on on-site grouting. In this paper, we argued that investigation of the grouting characteristics of a fracture network with a priori aperture distribution is promising to be an alternative approach for understanding the linkage between fracture distribution and grouting characteristics. A grouting module based on the Discontinuous Deformation Analysis (DDA) was developed to explore the linkage, with transient flow of grout studied. It is found that the grout consumed by the preset fracture networks exhibits a lognormal distribution, in agreement with the statistics of grouting data from 1361 grout holes at the Jurong Rock Cavern (Singapore). The observed agreement can be treated as an indirect verification of the robustness of our proposed grouting module. As anticipated, the grouting characteristics are significantly affected by the distribution of fracture apertures and connectivity among fractures around an injection hole, which are controlled by the distribution parameters. The grouting features of some dominant fractures could represent that of an entire fracture network.
URI: https://hdl.handle.net/10356/151673
ISSN: 0266-352X
DOI: 10.1016/j.compgeo.2019.04.028
Rights: © 2019 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:CEE Journal Articles

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