Grouting in rock cavern by data mining 2

• Main Author: Chang, Cherie Jingting
• Other Authors: Zhao Zhiye
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2021
• Subjects: Engineering::Civil engineering::Geotechnical
• Online Access: https://hdl.handle.net/10356/150218
• Institution: Nanyang Technological University

With Singapore’s continuous development and progress, the issue of land scarcity is ever so prominent. Hence, Singapore has been looking to making use of underground spaces to better utilise Singapore’s land. However, one main challenge faced in underground construction is the problem of water seepage due to high water table. It is essential to tackle the problem of water seepage so to be able to effectively and efficiently carry out underground construction without any major delays. By carrying out pre-grouting, the water seepage will then be reduced. To effectively carry out pre-grouting, it is important to know the amount of grout volume to be used. In this report, using the rock grouting data from project reports together with the Artificial Neural Network, an analysis of the results derived from the neural network code will be done to determine the relationship between the different input parameters and the output parameter which is grout volume.