Geological Evaluation Ahead Of Tunnel Face Using Tunnel Seismic Prediction Method And Japanese Highway Rock Mass Classification System

The knowing of geological profile in front of tunnel face is noteworthy to limit the hazard in tunnel excavation work and cost control in preventative measure. In order to acquire the geological profile for the Pahang-Selangor Raw Water Transfer project, site investigation with vertical boring is...

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Main Author:	Von, Woei Chew
Format:	Thesis
Language:	English
Published:	2019
Subjects:	T Technology
Online Access:	http://eprints.usm.my/51597/1/Geological%20Evaluation%20Ahead%20Of%20Tunnel%20Face%20Using%20Tunnel%20Seismic%20Prediction%20Method%20And%20Japanese%20Highway%20Rock%20Mass%20Classification%20System.pdf
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spelling	my-usm-ep.515972022-02-21T04:31:20Z Geological Evaluation Ahead Of Tunnel Face Using Tunnel Seismic Prediction Method And Japanese Highway Rock Mass Classification System 2019-08-01 Von, Woei Chew T Technology TA Engineering (General). Civil engineering (General) The knowing of geological profile in front of tunnel face is noteworthy to limit the hazard in tunnel excavation work and cost control in preventative measure. In order to acquire the geological profile for the Pahang-Selangor Raw Water Transfer project, site investigation with vertical boring is not suggested due to mountainous region. Tunnel seismic prediction (TSP) method is therefore implemented to predict the geological profile ahead of the tunnel face. Preliminary study of the TSP results showed that both wave velocities Vp and Vs are showing the downtrend with the lowering of the rock class. In order to evaluate the TSP results, IBM SPSS Statistic 22 is used to run artificial neural network (ANN) analysis. To assess the outcomes of the TSP, IBM SPSS Statistic 22 is used for the evaluation of artificial neural network (ANN). By using Vp, Vs and Vp/Vs from TSP results, a method in the program namely multilayer perceptron (MP) was used to compute the predicted rock grade points (RGP) from actual RGP. The actual RGP was obtained by Japanese Highway (JH) classification. The findings indicate a strong correlation between the anticipated RGP and the real RGP with the 0.851 correlation. Besides, Vp is the most significant parameter in determination of geological condition ahead of tunnel. However, the role of Vs and Vp/Vs are undeniably significant as well in supporting the prediction. The predicted results were then compared to rock mass mapping. The rock mass mapping showed that there were collapse and void for the predicted area. As such, TSP can provide considerably ahead of tunnel face geological profile forecast while enabling for continuous excavation work for TBM. Identifying weak zones or faults in front of the tunnel face is essential for preventive measures to be implemented in advance for a safer tunnelling work. 2019-08 Thesis http://eprints.usm.my/51597/ http://eprints.usm.my/51597/1/Geological%20Evaluation%20Ahead%20Of%20Tunnel%20Face%20Using%20Tunnel%20Seismic%20Prediction%20Method%20And%20Japanese%20Highway%20Rock%20Mass%20Classification%20System.pdf application/pdf en public masters Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Awam
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	T Technology T Technology
spellingShingle	T Technology T Technology Von, Woei Chew Geological Evaluation Ahead Of Tunnel Face Using Tunnel Seismic Prediction Method And Japanese Highway Rock Mass Classification System
description	The knowing of geological profile in front of tunnel face is noteworthy to limit the hazard in tunnel excavation work and cost control in preventative measure. In order to acquire the geological profile for the Pahang-Selangor Raw Water Transfer project, site investigation with vertical boring is not suggested due to mountainous region. Tunnel seismic prediction (TSP) method is therefore implemented to predict the geological profile ahead of the tunnel face. Preliminary study of the TSP results showed that both wave velocities Vp and Vs are showing the downtrend with the lowering of the rock class. In order to evaluate the TSP results, IBM SPSS Statistic 22 is used to run artificial neural network (ANN) analysis. To assess the outcomes of the TSP, IBM SPSS Statistic 22 is used for the evaluation of artificial neural network (ANN). By using Vp, Vs and Vp/Vs from TSP results, a method in the program namely multilayer perceptron (MP) was used to compute the predicted rock grade points (RGP) from actual RGP. The actual RGP was obtained by Japanese Highway (JH) classification. The findings indicate a strong correlation between the anticipated RGP and the real RGP with the 0.851 correlation. Besides, Vp is the most significant parameter in determination of geological condition ahead of tunnel. However, the role of Vs and Vp/Vs are undeniably significant as well in supporting the prediction. The predicted results were then compared to rock mass mapping. The rock mass mapping showed that there were collapse and void for the predicted area. As such, TSP can provide considerably ahead of tunnel face geological profile forecast while enabling for continuous excavation work for TBM. Identifying weak zones or faults in front of the tunnel face is essential for preventive measures to be implemented in advance for a safer tunnelling work.
format	Thesis
qualification_level	Master's degree
author	Von, Woei Chew
author_facet	Von, Woei Chew
author_sort	Von, Woei Chew
title	Geological Evaluation Ahead Of Tunnel Face Using Tunnel Seismic Prediction Method And Japanese Highway Rock Mass Classification System
title_short	Geological Evaluation Ahead Of Tunnel Face Using Tunnel Seismic Prediction Method And Japanese Highway Rock Mass Classification System
title_full	Geological Evaluation Ahead Of Tunnel Face Using Tunnel Seismic Prediction Method And Japanese Highway Rock Mass Classification System
title_fullStr	Geological Evaluation Ahead Of Tunnel Face Using Tunnel Seismic Prediction Method And Japanese Highway Rock Mass Classification System
title_full_unstemmed	Geological Evaluation Ahead Of Tunnel Face Using Tunnel Seismic Prediction Method And Japanese Highway Rock Mass Classification System
title_sort	geological evaluation ahead of tunnel face using tunnel seismic prediction method and japanese highway rock mass classification system
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Awam
publishDate	2019
url	http://eprints.usm.my/51597/1/Geological%20Evaluation%20Ahead%20Of%20Tunnel%20Face%20Using%20Tunnel%20Seismic%20Prediction%20Method%20And%20Japanese%20Highway%20Rock%20Mass%20Classification%20System.pdf
_version_	1747822085350096896

Geological Evaluation Ahead Of Tunnel Face Using Tunnel Seismic Prediction Method And Japanese Highway Rock Mass Classification System

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