Groundwater lowering for construction of the Kilsby Tunnel – pumping and tunnelling

The Kilsby Tunnel, constructed in the 1830s under the direction of Robert Stephenson, faced severe problems when a section of the tunnel, almost 400 m long, was driven through water-bearing unstable ‘quicksand’ conditions. Contemporary methods were not well suited to tunnelling through such conditions, and in previous decades, several canal tunnels had been planned to specifically divert around expected ‘bad ground’, and others took years to complete at great expense. Stephenson’s team, drawing on their experience from the mining industry, did not take this approach and ultimately worked through the unstable ground, albeit with considerable delays and cost increases. This was achieved in part by establishing a large-scale groundwater pumping system, unique for the time, that lowered groundwater levels and stabilised the quicksand, which resulted from a buried channel of glaciofluvial sands, cut into bedrock, that had been missed by trial borings. Steam engines were used to pump from multiple shafts (including four dedicated pumping shafts, off set from the tunnel alignment), with a reported pumping rate of 136 l/s for several months. One unusual feature was the use of flatrod systems to transmit mechanical power horizontally; this allowed a single engine to drive pumps in several different shafts.

TUNNEL MODELING USING MOBILE MAPPING LIDAR POINTS

In this paper, a method to model a tunnel using lidar points is presented. The data used was collected using Leica Pegasus Two Ultimate with a Z+F 9012 Profiler mounted on a mobile platform. The tunnel was approximately 151 m long. Visual inspection of a cross-section of the tunnel showed two rail tracks supported on ballast and sidewalks along both sidewalls of the tunnel. The walls and the ceiling of the tunnel were made of five planar surfaces. The tunnel alignment was straight, without any horizontal or vertical curves. The bearing of the central axis of the tunnel was N12.2oW. The following methodology was developed to model just the planar surfaces of the tunnel by excluding the rails, ballast, sidewalks, powerlines, and other accessories. The entire methodology was divided into three broad parts. In the first part, a model cross-section was created. Since the design plans of the tunnel were not available, the model cross-section polyline was created using mean tunnel dimensions from random cross-section points. The model cross-section consisted of the walls and the ceiling of the tunnel. Points were placed at every 1 cm along the model polyline. Six of the model points that represented the shape of the tunnel were selected as salient points. The lower-left salient point was considered as the seed point. In the second part, to define a reference axis of the tunnel, an approximate centerline was manually defined by selecting points at its start and end. Lidar points within 1 m at the start and the end of the tunnel were modeled using the model points to determine the centroids. The reference axis was determined by connecting the centroids at the start and the end of the tunnel. In the third part, the tunnel points were sliced along the reference axis at 5 cm intervals. The model cross-section was matched to points within each tunnel slice using a three-stage approach. In the first stage, the pattern of salient points was matched to the tunnel points by placing the seed point at every tunnel point location. The distances between salient points and their nearest tunnel points were calculated. Ten sets of tunnel points with the least differences to the salient points were shortlisted. In the second stage, a dense point-to-point matching was performed between the model and sliced tunnel data at the shortlisted points. The shortlisted point location with the least difference between the tunnel and the model points was considered as a match. At this point, the model points were hinged to the tunnel points at the seed point location. Hence, in the last stage, a six-parameter affine transformation was performed to match the model points to the tunnel data. The transformed model points at every 5 cm of the length of the tunnel were considered as current shape of the tunnel.

Use of saturation diving technique for tunnel boring machine cutterhead intervention in the Tuen Mun–Chek Lap Kok Link Sub-sea Tunnel Project, Hong Kong

The entire Tuen Mun–Chek Lap Kok Link (TM-CLKL) was commissioned on 27 December 2020 and it comprises a 9km-long dual 2-lane carriageway between Tuen Mun and North Lantau, Hong Kong. Construction of the 5km-long sub-sea tunnels was carried out by two 14m diameter Tunnel Boring Machines (TBMs). The tunnel alignment for the TM-CLKL sub-sea tunnel section is in mixed ground condition with the first 500 m in mixed geology of slightly to moderately decomposed granite and completely decomposed granite (CDG), followed by soft ground condition with CDG, alluvial sand, alluvial clay and marine deposit. This mixed ground geology requires regular TBM cutterhead interventions to change the worn-out cutting tools during the tunnelling operation. As the tunnel alignment is up to 55 m below the sea level with the deepest seabed level at -21 mPD, in order to maintain the cutting face stability during the intervention, the intervention pressure could be up to 6 bars. This paper describes different techniques used for TBM interventions under the sea such as trimix bounce mode and saturation mode that appears first time in Hong Kong under a high hyperbaric pressure to change the worn-out cutting tools at the TBM cutterhead.

Ground Deformation Characteristics Induced by Mechanized Shield Twin Tunnelling along Curved Alignments

This paper investigates the ground deformation characteristics induced by mechanized shield twin tunnelling along curved alignments by adopting the nonlinear three-dimensional (3D) finite element method (FEM). The performance of the adopted FEM is demonstrated to be satisfactory by comparing the numerical analysis results with the field monitoring data in a typical case history and with the predicted results generated by a modified version of the Peck’s empirical Gaussian formula. It has been found that the tunnelling-induced transverse ground surface settlement troughs and the distributions of the subsurface horizontal and vertical ground displacements are mostly similar in both form and magnitude for the considered various radii of curvature of tunnel alignment including 50 m, 100 m, 150 m, 200 m, 250 m, 300 m, 400 m, and infinity (i.e., straight-line tunnel). Considering the variational characteristics of the ground deformations with the magnitude of the radius of curvature, the radius of curvature of 100 m can be regarded as a critical tunnel alignment radius of curvature controlling the transformation of the curved tunnelling-induced ground deformational behaviors. For the benefit of geotechnical engineers interested in curved tunnelling with a small radius of curvature, a discussion of the technologies for reducing the overexcavation and improving the accuracy of tunnel lining segment installation is also presented.

Vertical and Horizontal Support Pressure Along The Kulekhani Iii Hep Tunnel Alignment, Nepal

Support pressure obtained in tunnel is considered as stresses for applied support. Therefore, estimation of support pressure in tunnel is important task for tunnel support design. Several equations are proposed to estimate support pressures. In this study, Barton equation was used for estimation support pressures along the tunnel of Kulekhani III HEP. The calculated support pressures were highly dependent on Q value and joint characteristics. Vertical and horizontal support pressures in the Marble and Quartzite followed the pattern as followed by Q but for other rocks support pressures were not only dependent on Q but had high influence of the joint characteristics. Support pressures obtained from the equation can also be used to estimate support pressure to some extent but modification is necessary. The equations can be considered for obtaining maximum support pressures for support design.Journal of Institute of Science and TechnologyVolume 21, Issue 1, August 2016, page: 112-118