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...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2019
|
| Subjects: | |
| 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 http://eprints.usm.my/51597/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|