Controlling tunnel induced ground surface and pile movements using micropiles

Tunnelling in densely populated areas is generally associated with undesirable ground movement and subsequent damage to adjacent buildings. Hence, the main concern of designers are to accurately predict ground movements and propose mitigation measures in severe cases. Nowadays, different techniques are used as a mitigation measure to reduce the impact of tunnel construction on ground settlement. Nevertheless, implementation of some of these methods is a source of unpredictable damage or undesirable effects such as the effect of installing micropiles between existing pile building foundation and tunnel which have yet to be understood. Hence, this research aims to establish a micropiles method as a mean to minimise ground surface settlement, and the settlement and lateral movement of the existing pile due to tunnelling through cohesionless soils. The study was carried out by means of laboratory physical model tests and numerical simulation using ABAQUS software. Three different relative densities of sand; 30%, 50%, and 75% were investigated while the overburden (cover to diameter) ratios used were 1, 2, and 3. A row of 3.7 mm diameter micropiles, dmp with two different lengths (11 cm and 14.5 cm) was embedded in between the tunnel (5 cm diameter, D) and the existing pile at four different locations. In model tests, settlement, bending moment and axial force of the existing pile were monitored accordingly. Generally, the results showed that increasing the value of relative density of sand reduces the ground movements. However, shallow tunnelling in loose sand produces remarkable movement on the ground surface. With the usage of micropiles, the ground surface settlement was reduced to nearly 40%. The micropiles also reduced over 85% and 75% of the piles lateral and axial movements respectively. A good compatibility was found between the experimental and numerical approaches which illustrates that the presented numerical simulation is a reliable model to predict tunnel-pile-soil and tunnel-pile-soil-micropiles interactions. Within the limitation of the study, it is recommended that the most suitable length and location of micropiles to use is 14.5 cm or about 40dmp (closest to the tunnel crown) and located at 0.5D (in the middle between tunnel and pile), based on the reduction observed on the vertical and lateral movements of pile as well as the bending moment and axial force

Numerical and physical modelling of Kaolin as backfill material for polymer concrete retaining wall

The failure mechanism of backfill material for retaining wall was studied by performing a numerical analysis using the finite element method. Kaolin is used as backfill material and retaining wall is constructed by Polymer Concrete. The laboratory data of an instrumented cantilever retaining wall are reexamined to confirm an experimental working hypothesis. The obtained laboratory data are the backfill settlement and horizontal displacement of the wall. The observed response demonstrates the backfill settlement and displacement of the retaining wall from the start to completion of loading. In conclusion, numerical modelling results based on computer programming by ABAQUS confirms the experimental results of the physical modellin

Surface settlement induced by tunneling in greenfield condition through physical modelling

Geotechnical conditions such as tunnel dimensions, tunneling method and soil type are few factors influencing the ground movement or disturbance. This paper presents the effect of tunnel cover to diameter ratio and relative density of sand on surface settlement induced by tunneling using physical modelling. The aluminum casing with outer diameter of 50 mm was used to model the tunnel shield. The size of the casing was 2 mm diameter larger than the tunnel lining. The tunnel excavation was done by pulling out the tunnel shield at constant speed with a mechanical pulley. The tested variables are cover to diameter ratio (1, 2 and 3) and relative density of sand (30%, 50% and 75%). The results demonstrated that the surface settlement decreased as the relative density increased. Also, as the relative density of sand increased, the overload factor at collapse increased. The surface settlement was at the highest when the cover to diameter ratio was 2. It can be concluded that in greenfield condition, the relative density and cover to diameter ratio affect the surface settlement

Effects of excavation sequence and heading distance on settlement in New Austrian tunneling method

The shallow underground excavation may leads to ground movements and surface settlement which may cause damage to structures. Several tunnel excavation methods had been developed during the last decades to minimize the effects of the tunnel construction on the surface settlement. The Karaj Metro tunnel (KMT) had been constructed in accordance with the principles of the New Austrian Tunneling Method (NATM). This method had been used widely to construct large diameter tunnels mainly due to its flexibility to adapt different ground conditions. Tunnel designs by NATM are generally based on empirical and numerical methods and construction process may be changed according to the observed response of the ground. Induced displacements are empirically controlled by adjusting the excavation rate, distance between tunnel face and support, partial heading excavation and closure of invert. This research is aimed at determining the effects of the excavation sequence and heading distance on the surface and subsurface settlement by carrying out two and three-dimensional Finite Element Modelling (FEM). Initially, the FEM is carried out to simulate step by step excavation sequence of KMT which had been constructed in soft soils by NATM method. The settlements obtained from monitoring of KMT had been used to validate the modelling work. The results show that the settlement varies with different excavation sequence and heading distance in NATM. The Side Galleries (SG) excavation model produced the lowest transverse and longitudinal surface settlements compared to KMT excavation model and other excavation sequences. The tunnel heading distance had more effect on both the transverse and longitudinal settlements for the KMT excavation model compared to SG model. Hence, the SG excavation model with heading distance of 2 m is recommended in the construction of KMT using NATM based on the minimum settlement occurring during excavation

Control of pile movements induced by tunnelling using micropiles

The effect of installing micropiles between the existing piles and the tunnel is not well understood. This paper discusses the effectiveness of micropiles as a means to control tunnelling-induced ground movement and movements of an existing pile, located at a distance of one times the tunnel diameter from the tunnel axis. Laboratory physical model tests had been conducted in dry sand of 50% relative density using a row of 3·7 mm dia. micropiles with two different lengths (110 and 145 mm), embedded in between the tunnel (overburden ratio of 3) and the existing pile at four different locations. During the tests, settlement, the bending moment and axial force of the existing pile have been monitored. The results show that the micropiles reduced by more than 85 and 75% of the piles' lateral and axial movements, respectively. Within the limitation of the study, it has been concluded that the most suitable length and location of the micropiles are 145 mm (tip of the micropiles is closest to the tunnel crown), located exactly in the middle between the tunnel axis and the pile. It is based on the reduction observed on the vertical and lateral movements of the pile as well as in the bending moment, and the axial force

Effects of tunnel depth and relative density of sand on surface settlement induced by tunneling

Tunnelling in densely populated areas is generally associated with undesirable ground movement and subsequent damage to adjacent buildings. Many parameters are contributed to the ground movements during tunnelling in which non-linear relationships are established between these parameters and ground movements. This paper presents the effects of tunnel depth and relative density of sand on surface settlement induced by tunneling by means of parametric study through finite element modelling. In this regard, tunnel excavation in sand with two different relative densities of 30% and 75% was investigated. In addition, effects of tunneling in different cover to diameter ratio of 1, 2, 3, and 4 were analysed. The results show that increasing in the value of the relative density of sand reduces the ground movements induced by tunneling. In addition, shallow tunneling in loose sand produces remarkable movements around the tunnel and on the ground surface

Prediction of airblast-overpressure induced by blasting using a hybrid artificial neural network and particle swarm optimization

Blasting is an inseparable part of the rock fragmentation process in hard rock mining. As an adverse and undesirable effect of blasting on surrounding areas, airblast-overpressure (AOp) is constantly considered by blast designers. AOp may impact the human and structures in adjacent to blasting area. Consequently, many attempts have been made to establish empirical correlations to predict and subsequently control the AOp. However, current correlations only investigate a few influential parameters, whereas there are many parameters in producing AOp. As a powerful function approximations, artificial neural networks (ANNs) can be utilized to simulate AOp. This paper presents a new approach based on hybrid ANN and particle swarm optimization (PSO) algorithm to predict AOp in quarry blasting. For this purpose, AOp and influential parameters were recorded from 62 blast operations in four granite quarry sites in Malaysia. Several models were trained and tested using collected data to determine the optimum model in which each model involved nine inputs, including the most influential parameters on AOp. In addition, two series of site factors were obtained using the power regression analyses. Findings show that presented PSO-based ANN model performs well in predicting the AOp. Hence, to compare the prediction performance of the PSO-based ANN model, the AOp was predicted using the current and proposed formulas. The training correlation coefficient equals to 0.94 suggests that the PSO-based ANN model outperforms the other predictive models

Deformation model of sand around short piles under pullout test

Piles as a member of structures can be failed due to structural collapses or soil's body failure. Extensive experimental studies have been conducted in literatures to identify the behavior of piles failure mechanism in sand. Nevertheless, the number of researches with respect to uplift failure of short piles are limited and this issue needs to be studied. In this study, three small-scale physical tests were performed to investigate the uplift resistance of short piles in loose sand with pile diameter of 5 cm and slenderness ratio of 2, 3 and 4. Close photogrammetric technique and Particle Image Velocimetry (PIV) were also employed to observe the deformation patterns due to uplift force. For verification purposes, the results obtained from the laboratory tests were compared to the results of ABAQUS finite element method (FEM) software. It was found that the slenderness ratio is the most influential factor on the pile uplift capacity values obtained by experiments. In addition, a reasonable error was observed between the measured bearing capacities obtained by experiments and the results of the numerical modeling. The minimum and maximum errors of 0.6% and 11% between experimental and numerical results reveal that the ABAQUS software can simulate the experimental tests behavior with high degree of accuracy. Besides, similar failure zone was achieved by both PIV and numerical techniques

Neuro-fuzzy technique to predict air-overpressure induced by blasting

In addition to all benefits of blasting in mining and civil engineering applications, blasting has some undesirable impacts on surrounding areas. Blast-induced air-overpressure (AOp) is one of the most important environmental impacts of blasting operation which may cause severe damage to nearby residents and structures. Hence, it is a major concern to predict and subsequently control the AOp due to blasting. This paper presents an adaptive neuro-fuzzy inference system (ANFIS) model for prediction of blast-induced AOp in quarry blasting sites. For this purpose, 128 blasting operations were monitored in three quarry sites, Malaysia. Several models were constructed to obtain the optimummodel in which each model involved five inputs and one output. Values of maximum charge per delay, powder factor, burden to spacing ratio, stemming length, and distance between monitoring station and blast face were set as input parameters to predict AOp. For comparison purposes, considering the same data, AOp values were predicted through the pre-developed artificial neural network (ANN) model and multiple regression (MR) technique. The results demonstrated the superiority of the ANFIS model to predict AOp compared to other methods. Moreover, results of sensitivity analysis indicated that the maximum charge per delay and powder factor and distance from the blast face are the most influential parameters on AOp