Rock mass classifications and supports for cavern analysis
Ng, Ignatius Jun Yong
Date of Issue2017-05-09
School of Civil and Environmental Engineering
There has been an increasing rush to find more space in Singapore due to rising populations, urbanization, industrial and recreational usage. Having extensive use for land reclamation and high-rise building construction, more efficient land space alternates are highly sought after. Underground space creation is fairly new and not thoroughly explored upon. After the first success of phase 1 construction for Jurong Rock Cavern (JRC), Singapore wants to do more than just constructing a storage facility but further upon creating recreational and living space under the ground. There have been in depth studies on underground rock conditions and rock mass classification and support systems like Rock Mass Rating or Q-value to understand rock types and rock responses. The methods are able to classify types of rock by looking at the compressive strengths of the materials, discontinuities orientation and spacing, water table, joint roughness, rock quality and others. These in turn generate recommended support systems in line with the different proposed properties for each type of rock. However, this guideline although is highly recommended, is not a standard procedure. Therefore, working side by side with Hyundai, there will be more inductive study on existing underground rock support categories and classifications under passive or active loads in varying conditions for caverns similar to JRC specifically. The support categories will be tested in their reliability and rectifications can be made for better understanding which supports and cavern dimensions improve the overall structure integrity of the cavern. A set of dimensions and Q-values similar to JRC are chosen, following the ratio of span to height of 1:1.35. They were plotted into a geotechnical and civil engineering software called RocScience to see the relationship and reaction of Q-value against the yielded elements and total displacements. From this, the data can thus help to achieve a more optimal support system to carry out better, faster and safer construction methods for future underground tunnels or caverns.
Final Year Project (FYP)
Nanyang Technological University