Rock mass classification and support for cavern analysis

Q-system and Rock Mass Rating (RMR) are common and dependable rock classification systems used widely by rock engineering industry to distinguish different quality of rocks. These rocks have rock mass properties such as rock strength and deformation modulus, which varies according to their qualit...

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Main Author: Chia, Emmanuel Song Jie
Other Authors: Zhao Zhiye
Format: Final Year Project
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10356/70688
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-706882023-03-03T17:19:09Z Rock mass classification and support for cavern analysis Chia, Emmanuel Song Jie Zhao Zhiye School of Civil and Environmental Engineering DRNTU::Engineering::Civil engineering Q-system and Rock Mass Rating (RMR) are common and dependable rock classification systems used widely by rock engineering industry to distinguish different quality of rocks. These rocks have rock mass properties such as rock strength and deformation modulus, which varies according to their qualities and in turn influence the stability of the rock cavern. Other factors such as the use of supports like bolting and shortcrete also contribute to the cavern’s stability but the focus of this report will be on the characterization of rock mass. With the shortage of land, rock engineering has become increasingly important in Singapore as the government explores the use of underground spaces. Even though several excavation projects have been successfully completed in Singapore, such as the Jurong Rock Cavern (JRC) project, much research is still ongoing to discover safer and more efficient ways for underground construction of caverns. This study will explore the effects of cavern dimensions and in-situ stress ratio, applied across five different quality of rocks, through the use of rocscience programme which judges stability based on critical Strength Reduction Factor (SRF) values. It will also evaluate JRC’s choice of 20m by 27m as their primary cavern dimension and suggest an alternate set of dimensions which may be safer. Bachelor of Engineering (Civil) 2017-05-09T06:03:30Z 2017-05-09T06:03:30Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70688 en Nanyang Technological University 60 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
Chia, Emmanuel Song Jie
Rock mass classification and support for cavern analysis
description Q-system and Rock Mass Rating (RMR) are common and dependable rock classification systems used widely by rock engineering industry to distinguish different quality of rocks. These rocks have rock mass properties such as rock strength and deformation modulus, which varies according to their qualities and in turn influence the stability of the rock cavern. Other factors such as the use of supports like bolting and shortcrete also contribute to the cavern’s stability but the focus of this report will be on the characterization of rock mass. With the shortage of land, rock engineering has become increasingly important in Singapore as the government explores the use of underground spaces. Even though several excavation projects have been successfully completed in Singapore, such as the Jurong Rock Cavern (JRC) project, much research is still ongoing to discover safer and more efficient ways for underground construction of caverns. This study will explore the effects of cavern dimensions and in-situ stress ratio, applied across five different quality of rocks, through the use of rocscience programme which judges stability based on critical Strength Reduction Factor (SRF) values. It will also evaluate JRC’s choice of 20m by 27m as their primary cavern dimension and suggest an alternate set of dimensions which may be safer.
author2 Zhao Zhiye
author_facet Zhao Zhiye
Chia, Emmanuel Song Jie
format Final Year Project
author Chia, Emmanuel Song Jie
author_sort Chia, Emmanuel Song Jie
title Rock mass classification and support for cavern analysis
title_short Rock mass classification and support for cavern analysis
title_full Rock mass classification and support for cavern analysis
title_fullStr Rock mass classification and support for cavern analysis
title_full_unstemmed Rock mass classification and support for cavern analysis
title_sort rock mass classification and support for cavern analysis
publishDate 2017
url http://hdl.handle.net/10356/70688
_version_ 1759854339759800320