Grouting in rock cavern : a case study

Due to the growing population in Singapore, the constant development of its urban landscape has driven it to consider underground space development to mitigate the lack of land space. The construction of the Jurong Rock Cavern (JRC) was designed to store hydrocarbons and was the first kind of deep s...

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Main Author: Lim, Wesley Zhi En
Other Authors: Zhao Zhiye
Format: Final Year Project
Language:English
Published: 2018
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Online Access:http://hdl.handle.net/10356/75757
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-757572023-03-03T17:24:24Z Grouting in rock cavern : a case study Lim, Wesley Zhi En Zhao Zhiye School of Civil and Environmental Engineering JTC corporation DRNTU::Engineering::Civil engineering Due to the growing population in Singapore, the constant development of its urban landscape has driven it to consider underground space development to mitigate the lack of land space. The construction of the Jurong Rock Cavern (JRC) was designed to store hydrocarbons and was the first kind of deep storage facility constructed in Singapore. During the excavation process, water seepage is an inherent obstacle that hinders the tunnelling process and reaps detrimental effects if its risks are not properly managed. Therefore, jet grouting has been one form of measure adopted to alleviate ground water inflows into the caverns and its parameters are being studied in this report to further enhance efficiency of its usage. Due to the large extent of data variables, this project aims to derive grouting parameters as a function of hydrogeological parameters within the rock caverns. The Artificial Neural Network (ANN) has been successful in generating underlying correlations among large data sets with considerable precision and thus, has been employed for this project to derive possible relationships regarding grout volume and pressure. Some characteristic properties of the rock caverns involving RMR, Q tunnelling index and permeability are studied and included in the neural network fitting process. Rock cavern data provided by JTC Corporation will be applied into a neural network code via a software called MATLAB and the data will be trained accordingly. Regression analysis of the data will be conducted to generate a model used to predict respective tunnel conditions. In doing so, this holds the intent to aid engineers in achieving better situational awareness in the rock caverns during grouting practice for future underground excavations. Bachelor of Engineering (Civil) 2018-06-13T08:48:14Z 2018-06-13T08:48:14Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75757 en Nanyang Technological University 51 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Civil engineering
spellingShingle DRNTU::Engineering::Civil engineering
Lim, Wesley Zhi En
Grouting in rock cavern : a case study
description Due to the growing population in Singapore, the constant development of its urban landscape has driven it to consider underground space development to mitigate the lack of land space. The construction of the Jurong Rock Cavern (JRC) was designed to store hydrocarbons and was the first kind of deep storage facility constructed in Singapore. During the excavation process, water seepage is an inherent obstacle that hinders the tunnelling process and reaps detrimental effects if its risks are not properly managed. Therefore, jet grouting has been one form of measure adopted to alleviate ground water inflows into the caverns and its parameters are being studied in this report to further enhance efficiency of its usage. Due to the large extent of data variables, this project aims to derive grouting parameters as a function of hydrogeological parameters within the rock caverns. The Artificial Neural Network (ANN) has been successful in generating underlying correlations among large data sets with considerable precision and thus, has been employed for this project to derive possible relationships regarding grout volume and pressure. Some characteristic properties of the rock caverns involving RMR, Q tunnelling index and permeability are studied and included in the neural network fitting process. Rock cavern data provided by JTC Corporation will be applied into a neural network code via a software called MATLAB and the data will be trained accordingly. Regression analysis of the data will be conducted to generate a model used to predict respective tunnel conditions. In doing so, this holds the intent to aid engineers in achieving better situational awareness in the rock caverns during grouting practice for future underground excavations.
author2 Zhao Zhiye
author_facet Zhao Zhiye
Lim, Wesley Zhi En
format Final Year Project
author Lim, Wesley Zhi En
author_sort Lim, Wesley Zhi En
title Grouting in rock cavern : a case study
title_short Grouting in rock cavern : a case study
title_full Grouting in rock cavern : a case study
title_fullStr Grouting in rock cavern : a case study
title_full_unstemmed Grouting in rock cavern : a case study
title_sort grouting in rock cavern : a case study
publishDate 2018
url http://hdl.handle.net/10356/75757
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