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Prediction of Pipe-Jacking Forces Using a Bayesian Updating Approach
Abstract
An accurate estimation of the jacking forces likely to be experienced during microtunnelling is a key design concern for the design of pipe segments, the location of intermediate jacking stations and the efficacy of the pipe jacking project itself. This paper presents a Bayesian updating approach for the prediction of jacking forces during microtunnelling. The proposed framework is applied to two pipe jacking case histories completed in the UK including a 275 m drive in silt and silty sand and a 1237 m drive in mudstone. To benchmark the Bayesian predictions, a ‘classical’ optimisation technique, namely genetic algorithms, is also implemented. The results show that predictions of pipe jacking forces using the prior best estimate of model input parameters provide a significant over-prediction of the monitored jacking forces for both drives. This highlights the difficulty in capturing the complex geotechnical conditions during tunnelling within prescriptive design approaches and the importance of robust back-analysis techniques. Bayesian updating is also shown to be a very effective option where significant improvements in the mean predictions, and associated variance, of the total jacking force are obtained as more data is acquired from the drive.
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Friction resistance usually constitutes one of the two main components for the calculation of required jacking force. This paper provides a new approach to predict the friction resistance of slurry pipe jacking. First, the existing prediction equations and their establishment methods and essential hypotheses used were carefully summarized and compared, providing good foundations for the establishment of the new model. It was found that the friction resistance can be uniformly calculated by multiplying an effective friction coefficient and the normal force acting on the external surface of the pipe. This effective friction coefficient is introduced to reflect the effect of contact state of pipe-soil-slurry, highly affected by the effect of lubrication and the interaction of pipe-soil-slurry. The critical quantity of pipe-soil contact angle (or width) involved may be calculated by Persson’s contact model. Then, the equation of normal force was rederived and determined, in which the vertical soil stress should be calculated by Terzaghi’s silo model with parameters proposed by the UK Pipe Jacking Association. Different from the existing prediction models, this new approach has taken into full consideration the effect of lubrication, soil properties (such as internal friction angle, cohesion, and void ratio), and design parameters (such as buried depth, overcut, and pipe diameter). In addition, four field cases and a numerical simulation case with various soils and design parameters were carefully selected to check out the capability of the new model. There was greater satisfaction with the measured data as compared to the existing models and the numerical simulation approach, indicating that the new approach not only has higher accuracy but is also more flexible and has a wider applicability. Finally, the influence of buried depth, overcut, and pipe diameter on the friction resistance and lubrication efficiency were analyzed, and the results can be helpful for the future design.
Trenchless technology is often used in congested urban areas or river crossings to install underground pipelines to minimize disturbance to surface traffic or other activities. Pipe jacking is a typical technique applied to jack pipe segments between two working shafts. However, the design of the jacking force is usually implemented using empirical methods. It should be emphasized that the jacking force will change for each site, depending on the magnitude of overcut, lubricants, work stoppages, geology and misalignment. A particle method is proposed to estimate the jacking force along the pipe. The microparameters are calibrated for sandy soils in Shenyang, so that the macroscale material behavior can be reproduced using the particle model. Hence, the normal force around the pipe circumference can be derived in the particle model, after which the interface friction coefficient is applied to evaluate the friction resistance mobilized at the soil-pipe interface. A modified Protodyakonov’s arch model can be used to assess the magnitude of earth pressure acting on the shield face. In the end, the combination of friction resistance and face pressure provides the jacking force. The efficacy of the proposed particle method is demonstrated by comparing calculated jacking forces with those measured in the field for three types of jacking machines in sandy soils under the Hun River, Shenyang. Keywords: Pipe jacking, Jacking force, Particle methods, Distinct element
This paper provides a review of the history and development of pipe jacking and microtunneling methods with extensive referencing to the published literature. The application of such methods in comparison with other trenchless technologies is discussed and the various planning, design and construction aspects are introduced. The emphasis of the paper is to trace the academic research and field monitoring results covering critical aspects of design and construction with a particular emphasis on jacking force estimation and the effect of lubrication on jacking forces.
Assessing the potential for a punch-through failure during spudcan installation in sand-over-clay is crucial for reducing risk in the operations of mobile jack-up platforms. Typically, in the offshore industry, the peak penetration resistance and the depth at which it occurs are determined deterministically without rigorously considering the uncertainties in the soil. This paper proposes a probabilistic approach to estimate the peak resistance and the corresponding depth, as well as a Bayesian method of incorporating installation data to update the predictions. Instead of a single value in the deterministic analysis, a range of the potential peak resistances and depths can be estimated by accounting for the uncertainties in the soil, the spudcan’s geometry and in the calculation method itself, with a database of 66 geotechnical centrifuge tests characterising the model. This prior probability is then updated using the monitored data, allowing a real-time update of the probabilities associated with candidate values of peak resistance and depth during the installation. The advantage of such a probabilistic updating model is shown in a retrospective simulation of a mobile jack-up platform in sand-over-clay conditions in the Gulf of Mexico. The results show that the prior estimation can be effectively refined by incorporating the monitored data. The proposed method provides a powerful tool for assisting decision-making during the installation of jack-ups offshore.
There are several well-established jacking force models available for determining the jacking loads. However, their ability to characterise the tunnel bore conditions is limited. A simple approach to characterise the tunnel bore conditions is proposed and applied to a case study where four sewer pipelines of the Shulin district sewer network in Taipei County, Taiwan were constructed to verify its validity. In this paper, four jacking force models are reviewed. Based upon the given soil properties and pipe dimensions as well as the pipe buried depth, the normal contact pressure (σ’) in each jacking force model and the measured frictional stress (τ) in each baseline section are utilised for back-analysis of the frictional coefficient (μavg). The μavg values outside the range of 0.1-0.3 recommended for lubricated drives can be attributed to the increasing pipe friction resulting from excessive pipe deviation or ground closure or due to the gravel formation not being long enough to establish lower face resistance or total jacking load. JMTA (Japan Microtunnelling Association) has indicated a further potential use in assessment of the interface performance during pipe-jacking works.
The observational method in geotechnical engineering is an acceptable verification method for limit states in Eurocode 7, but the method is rarely used despite its potential savings. Some reasons may be its unclear safety definition and the lack of guidelines on how to establish whether the observational method is more favourable than conventional design. In this paper, we challenge these issues by introducing a reliability constraint on the observational method and propose a probabilistic optimization methodology that aids the decision-making engineer in choosing between the observational method and conventional design. The methodology suggests an optimal design after comparing the expected utilities of the considered design options. The methodology is illustrated with a practical example, in which a geotechnical engineer evaluates whether the observational method may be favourable in the design of a rock pillar. We conclude that the methodology may prove to be a valuable tool for decision-making engineers’ everyday work with managing risks in geotechnical projects.
An open-dug caisson shaft is a form of top-down construction in which a concrete shaft is sunk into the ground using the weight of the shaft and additional kentledge, if required. Excavation at the base of the caisson shaft wall allows the structure to descend through the ground. A thorough understanding of the interaction between the caisson shaft and soil is essential to maintain controlled sinking of the caisson. In this paper, the failure mechanisms developed beneath caisson blades in sand are investigated. A series of laboratory tests were carried out at the University of Oxford to explore how varying blade angles affect the performance of the bearing capacity beneath the caisson. Cutting angles of 30°, 45°, 60°, 75° and 90° (flat) were penetrated into sand under plane strain conditions; forces were monitored using a Cambridge-type load cell while soil displacements were recorded using Particle Image Velocimetry (PIV) techniques. The aim of this study is to understand how the soil failure mechanism develops and to determine the optimum cutting angle. The results of the laboratory tests can be scaled to predict the likely behaviour in the field. Results show that the bearing capacity is significantly dependent on the cutting angle; in a dense sand a steep cutting angle may be used to aid sinking of the caisson.
Slope monitoring is routinely conducted, and observational information such as surface/underground displacements, groundwater levels, and rock bolt forces at multiple locations is collected. How to make use of the monitoring information to reveal failure mechanisms and assess the slope stability is a key issue in slope engineering. This paper presents a method for assessing the slope stability by integrating monitoring parameters with physical analysis. The observed information first was used to back analyze the strength and loading parameters, and then the updated basic parameters were used to calculate the factor of safety or failure probability of the slope. The dominant basic parameters whose uncertainties influence the observed results the most were identified from the probabilistic back analysis. Alert levels were defined in the monitoring parameter space on the basis of a factor of safety or failure probability criterion. A rock slope example was worked out to illustrate the application of the proposed method.
Microtunnelling is an important trenchless construction technique that is used to successfully install essential utility pipelines in increasingly congested urban centres around the world. An important consideration for a microtunnelling project is the magnitude of the jacking force that will be required to advance the microtunnelling shield and the string of product pipes from the starting shaft to the receiving shaft. Frictional resistances along the surface of the pipeline have a major contribution to the total jacking force. This paper considers the frictional resistance mechanism involved in advancing concrete pipes through a coarse-grained soil and describes laboratory testing carried out with the aim of physically modelling the process. Comparisons are made with case histories from microtunnelling projects recently completed in coarse-grained soils. Recommendations are made on predicting likely jacking forces in advance of future projects.
After a geotechnical design has been developed, it is common to monitor performance during construction using the observational method by Peck (published in 1969). The observational method is a process where data are collected and geotechnical models updated, allowing timely decisions to be made with respect to risk and opportunity by asset owners or contractors. The observational method is similar to the mathematical formulation for Bayesian updating of material parameters based on measurements. A proof of concept study has been performed to assess the potential for Bayesian updating to be combined with the observational method to allow timely and accurate decision-making during construction of embankments on soft soils. The method was able to converge to an accurate solution prior to 50% consolidation assuming small measurement errors. It is also demonstrated that confidence in the predicted settlement is relatively low at the prior “design” stage and rapidly increases with three or four measurements spaced over time during the posterior “construction” phase. © 2015, National Research Council of Canada, All Rights Reserved.
The installation of underground trunk sewer lines in the Tuang formation of Kuching City, Malaysia, used trenchless technology in the form of the pipe-jacking method. The evaluation of pipe-jacking forces mainly involves empirical models developed for soils, with rather limited considerations for drives through weathered rock. Therefore, a novel approach is proposed to evaluate strength parameters by reconstituting and subsequently shearing scalped tunneling rock spoils in the direct shear apparatus. The direct shear results are then applied to a well-established pipe-jacking force model, which considers arching theory. The outcomes indicate that the backanalyzed frictional coefficients μavg are not only reliable but also related to their surrounding geologies because of soil-structure interaction. This study also highlights the significance of lubrication and effect of rock arching in assessing jacking forces. The successful characterization of reconstituted tunneling rock spoils in this paper has shown potential use in assessing jacking forces during microtunneling works.
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Supplementary Material: http://ascelibrary.org/doi/suppl/10.1061/%28ASCE%29GT.1943-5606.0001348
A Bayesian framework using field observations for back-analysis and updating of soil parameters in a multistage braced excavation is presented. Because of the uncertainties originating from the poorly known soil parameters, the imperfect analysis model, and other factors such as construction variability, the soil parameters can only be inferred as probability distributions. In this paper, these posterior distributions are derived using the Markov chain Monte Carlo (MCMC) sampling method implemented with the Metropolis-Hastings algorithm. In the proposed framework, Bayesian updating is first realized with one type of response observation (maximum wall deflection or maximum settlement), and then this Bayesian framework is extended to allow for simultaneous use of two types of response observations in the updating. The proposed framework is illustrated with a quality excavation case and shown effective regardless of the prior knowledge of soil parameters and type of response observations adopted.
The use of supporting fluids to stabilise excavations is a common technique adopted in the construction industry. Rapid detection of incipient collapse for deep excavations and timely decision making are crucial to ensure safety during construction. This paper explores a hybrid framework for forecasting the collapse of fluid−supported circular excavations by combining physics-based and data-driven modelling. Finite element limit analysis is first used to develop a numerical database of stability numbers for both unsupported and fluid−supported circular excavations. The parameters considered in the modelling include excavation geometry, soil strength profile and support fluid properties. A data-driven algorithm is used to ‘learn’ the numerical results to develop a fast ‘surrogate’ amenable for integration within real−time monitoring systems. By way of example, the proposed forecasting strategy is retrospectively applied to a recent field monitoring case history where the observational method is used to update the input parameters of the data-driven surrogate.
‘Clogging’ is a common issue encountered during tunnelling in clayey soils which can impede tunnel excavation, cause unplanned downtimes and lead to significant additional project costs. Clogging can result in a drastic reduction in performance due to reduced jacking speeds and the time needed for cleaning if it cannot be fully mitigated. The data acquired by modern tunnel boring machines (TBMs) have grown significantly in recent years presenting a substantial opportunity for the application of data-driven artificial intelligence (AI) techniques. In this study, a baseline assessment of clogging in slurry-supported pipejacking is performed using a combination of TBM parameters and the semi-empirical diagram proposed in the literature. The potential for one-class support vector machines (OCSVM), isolation forest (IForest) and robust covariance (Robcov) to assess the tendency to clayey clogging is then explored in this work. The proposed approach is applied to a pipejacking case history in Taipei, Taiwan, involving tunnelling in soft alluvial deposit. The results highlight an exciting potential for the use of OCSVM, IForest and Robcov to detect clogging during slurry-supported pipejacking.
Microtunnelling is an increasingly popular means of locating utilities below ground. The ability to predict the total jacking force requirements during a drive is highly desirable for anomaly detection, to ensure the available thrust is not exceeded, and to prevent damage to the pipe string and/or launch shaft. However, prediction of the total jacking force is complicated by site geology, the use of a lubricated overcut, work stoppages, tunnel boring machine driving style and pipe misalignment. This paper introduces a probabilistic observational approach for forecasting jacking forces during microtunnelling. Gaussian process regression is adopted for this purpose which allows forecasts to be performed within a probabilistic framework. The proposed approach is applied to two recent UK microtunnelling monitoring projects and the forecasts are appraised through comparisons to predictions determined using design methods currently applied in industry. The results show that the proposed framework provides excellent forecasts of the monitored field data and highlights a significant opportunity to complement existing prescriptive design methods with probabilistic forecasting techniques.
The proliferation of data collected by modern tunnel boring machines (TBMs) presents a substantial opportunity for the application of machine learning (ML) to support the decision-making process on site with timely and meaningful information. The observational method is now well-established in geotechnical engineering and has a proven potential to save time and money relative to conventional design. ML advances the traditional observational method by employing data analysis and pattern recognition techniques, predicated on the assumption of the presence of enough data to describe the modelled system’s physics. This paper presents a comprehensive review of recent advances and applications of ML to inform tunnelling construction operations with a view to increasing their potential for uptake by industry practitioners. This review has identified four main applications of machine learning to inform tunnelling, namely TBM performance prediction, tunnelling-induced settlement prediction, geological forecasting and cutterhead design optimisation. The paper concludes by summarising research trends and suggesting directions for future research for ML in the tunnelling space.
Detecting sudden changes in geological conditions (e.g., karst cavern and fault zone) during tunnelling is a complex task. These changes can cause shield machines to jam or even induce geo-hazards such as water ingress and surface subsidence. Tunnelling parameters that relate closely to the surrounding geology have proliferated in recent years and present a substantial opportunity for the application of data-driven artificial intelligent (AI) techniques that can infer patterns from data without reference to known, or labelled, outcomes. This study explores the potential for support vector machines (SVM) to identify changes in soil type during tunnelling towards reducing the possibility of jamming and geo-hazard development. All tunnelling data were pre-processed to convert time series data into feature-based sub-series. A selection of the most popular parameter optimisation algorithms was explored to improve the accuracy of the AI predictions. Their relative merits were evaluated through comparisons with a recent pipejacking case history undertaken in gravel and clayey gravel soils. The results highlight an exciting potential for the use of optimisation algorithm-based SVMs to identify changes in soil conditions during pipejacking.
The proliferation of data collected by modern tunnel boring machines presents a substantial opportunity for the application of data-driven anomaly detection (AD) techniques that can adapt dynamically to site specific conditions. Based on jacking forces measured during microtunnelling, this paper explores the potential for AD methods to provide more accurate and robust detection of incipient faults. A selection of the most popular AD methods proposed in the literature, comprising both clusteringand regression-based techniques, are considered for this purpose. The relative merits of each approach is assessed through comparisons to three microtunnelling case histories where anomalous jacking force behaviour was encountered. The results highlight an exciting potential for the use of anomaly detection techniques to reduce unplanned downtimes and operation costs.
In recent years, there has been an increased resort to microtunnelling/pipe-jacking as a means of constructing underground conduits (for water, sewage, gas, and other utilities) to avoid on-street disruption in urban areas. In this paper, technical details of two 1 200 mm internal diameter microtunnels in silty sand totalling over 550 m in length are discussed. While average skin friction values are extremely low for both drives suggesting effective lubrication practice, differences in normalised bentonite volumes appear to be responsible for differences in skin friction. Full or near full buoyancy of the pipeline has been demonstrated for the majority of the drive. The frictional stress increase after a stoppage is shown to depend on stoppage duration but also on the normalised lubriation volume. Interpretation of data in the manner presented in the paper is an important means of assimilating experience of microtunnelling in different ground conditions.
Since guidelines for choosing 'most probable' parameters in ground engineering design codes are vague, concerns are raised regarding their definition, as well as the associated uncertainties. This paper introduces Bayesian inference for a new rigorous approach to obtaining the estimates of the most probable parameters based on observations collected during construction. Following the review of optimisation-based methods that can be used in back-analysis, such as gradient descent and neural networks, a probabilistic model is developed using Clough and O'Rourke's method for retaining wall design. Sequential Bayesian inference is applied to a staged excavation project to examine the applicability of the proposed approach and illustrate the process of back-analysis. © 2018 Published with permission by the ICE under the CC-BY 4.0 license.
Large-diameter open caissons are a widely-adopted solution for deep foundations, underground storage and attenuation tanks, pumping stations, and launch and reception shafts for tunnel boring machines. The sinking process presents a number of challenges including maintaining verticality of the caisson, controlling the rate of sinking, and minimizing soil-structure frictional stresses through the use of lubricating fluids. A bespoke monitoring system has been developed at University of Oxford to provide early warning of adverse responses during the sinking phase (e.g. excessive soil-structure interface friction). The monitoring system was trialled on a recent pilot project in the UK involving the construction of a 32 m internal diameter, 20 m deep reinforced concrete caisson. This paper describes the monitoring system that was developed and its impact on the construction process of the pilot project. Early indications are that real-time feedback of live construction data has a major impact on the efficiency and safety of the construction process.
Jacking force is one of the crucial parameters for pipe structure design, selection of pipe jacking machine and shaft structure design during jacking process. To predict the jacking force more accurately, this paper summarizes four calculation methods of curved jacking force. The Japan Micro Tunneling Association (JMTA) Method is based on Terzaghi arching theory with full contact between pipe and soil. However, according to the elastic contact theories, Hertz contact method, Shimada method and Persson contact method assume that pipe and soil contact partially in stable excavation cavity. The three methods are considering the influences of frictional resistance of pipe-soil and pipe-mud concurrently. By field monitoring of jacking force data in different types of soil and cover depth in the curved pipe jacking roof of Gongbei tunnel, the cutterhead resistance, dynamic and static frictional resistance have been analyzed. Also, the additional frictional resistance caused by stoppage effect has been presented. The results show that the mud pressure is more convenient to calculate the cutterhead resistance than active soil pressure. The Persson contact model is applicable to calculate the friction in stable condition of excavation cavity while the Shimada model is capable of predicting frictional resistance values for unstable condition.
Settlement prediction is critical for soft ground projects. Traditional predictions using laboratory and field test data, however, can suffer from a lack of accuracy, which results in a lack of confidence by the designer. This paper employs the Bayesian approach with laboratory data, field test data, and monitoring data to yield accurate predictions during the construction and consolidation periods for the test embankment built at Ballina, New South Wales, Australia. We show that surface settlement can be well predicted using 116 days of observed settlements, while the pore pressure can be predicted using 292 days of pore pressure measurements. The predictions are shown to converge to the field measurements, regardless of some assumptions about the measurement errors. Finally, it is demonstrated that incorporating more monitoring data into the Bayesian updating process enables more accurate predictions.
A comparative study of optimization techniques for identifying soil parameters in geotechnical engineering was first presented. The identification methodology with its 3 main parts, error function, search strategy, and identification procedure, was introduced and summarized. Then, current optimization methods were reviewed and classified into 3 categories with an introduction to their basic principles and applications in geotechnical engineering. A comparative study on the identification of model parameters from a synthetic pressuremeter and an excavation tests was then performed by using 5 among the mostly common optimization methods, including genetic algorithms, particle swarm optimization, simulated annealing, the differential evolution algorithm and the artificial bee colony algorithm. The results demonstrated that the differential evolution had the strongest search ability but the slowest convergence speed. All the selected methods could reach approximate solutions with very small objective errors, but these solutions were different from the preset parameters. To improve the identification performance, an enhanced algorithm was developed by implementing the Nelder-Mead simplex method in a differential algorithm to accelerate the convergence speed with strong reliable search ability. The performance of the enhanced optimization algorithm was finally highlighted by identifying the Mohr-Coulomb parameters from the 2 same synthetic cases and from 2 real pressuremeter tests in sand, and ANICREEP parameters from 2 real pressuremeter tests in soft clay.
Hamiltonian Monte Carlo has proven a remarkable empirical success, but only recently have we begun to develop a rigorous under- standing of why it performs so well on difficult problems and how it is best applied in practice. Unfortunately, that understanding is con- fined within the mathematics of differential geometry which has limited its dissemination, especially to the applied communities for which it is particularly important. In this review I provide a comprehensive conceptual account of these theoretical foundations, focusing on developing a principled intuition behind the method and its optimal implementations rather of any ex- haustive rigor. Whether a practitioner or a statistician, the dedicated reader will acquire a solid grasp of how Hamiltonian Monte Carlo works, when it succeeds, and, perhaps most importantly, when it fails.
This study investigates the influencing factors that affect the jacking loads during slurry pipe-jacking works at four drives in the Shulin district sewer network in Taipei County, Taiwan, with lengths varying from 73 to 126 m. The main factors which affect the jacking loads during tunnelling may include (1) overcut annulus and volume of injected lubricant, (2) work stoppages, (3) geology, and (4) misalignment. In the four pipe-jacking drives, the jacking forces are represented using the baseline technique. The pipe-jacking results show that the local variations (increasing or decreasing) of jacking force are ascribed to the varying face resistance due to driving between coarse soil and fine soil governed sand or gravel deposit or driving into and away from a buried wooden log. The increase in the jacking loads could also be due to the increasing friction resistance resulting from the pipe deviation being greater than a threshold value of 60 mm. Excessive injected volumes of lubricant result in very low pipe frictions incurred during pipe-jacking of the four drives and are reflected through the back-analysed μavg values which vary from 0.02 to 0.09. The jacking load increases due to either overnight stoppages or short breaks are more pronounced in poorly graded gravel or sand deposit than in clayey gravel or clayey sand deposit.
Pipe jacking is a technique used to construct tunnels by pushing prefabricated pipes through the ground from an entrance shaft to an exit shaft. This technique is referred as microtunneling in U.S. terminology, therefore, in the rest of the text, pipejacking and microtunneling will be used as having the same meaning. Pipe jacking is a more economical alternative to segmental lined tunnels. However, the main limitation of pipe jacking is the jacking distance, which is directly dependent on the friction between the pipe and the soil. Therefore,
reducing the friction between the pipe and soil is a critical issue in terms of economy and construction speed. In pipe jacking, in order to reduce the friction between pipe and soil, a bentonite injection is applied. In this paper, a new laboratory test setup was prepared to simulate pipe jacking. The main aim of this test setup was to find the effects of bentonite pressure on the lubrication efficiency, which has not been clarified in the literature yet. In order to verify the test method, results of laboratory tests were compared with measurements of the friction between jacked pipe and soil in several real life projects. The measurements were compared with the coefficient of friction values obtained from three different field measurements conducted in different projects. According to the results, it can be stated that by applying continuous bentonite injection even under very low pressure, an interface can be created between bentonite slurry and a concrete pipe, and this bentonite
interface is able to reduce the friction coefficient tremendously to approximately 10% of the sand–concrete pipe interface friction coefficient. But when the injection is not applied continuously, the application of bentonite slurry injection decreases the coefficient of friction to half of that in the case of no bentonite injection.
Based on FEM analysis, the response surface method for simulating the nonlinear interaction between parameter and displacement was applied instead of the finite element method (FEM) numerical simulation. Considering the random characteristics of displacement measurement, combining the response surface equation, optimal method and Monte-Carlo technique, according to the least square method, a random method to identify the geotechnical parameters was established. The results of back analysis give sample means, variances and their type distribution which are necessary in estimating stability and reliability of tunnel. Analytical results show that this method has good efficiency and accuracy.
This book includes recommendations prepared by members of the French Society for Trenchless Technology (FSTT), based on their recent national multi-year project. Comprehensive guidelines, techniques and theories in the areas of both microtunneling and horizontal drilling are given, encompassing the fields of application for each method, what investigations should be undertaken, which machines and equipment should be used, how the work should be managed and potential problems that may arise. The recommendations, the analytical methods used and their verification with laboratory and field data should not only improve the rate of success of trenchless projects, but will also be of great value to engineers in other countries, who can compare the results with their own findings and assess the international state of the art.
The purpose of this paper is to introduce some simple theoetical models of pipe-soil interaction during pipe jacking, and relate these to observations made in the field. Ground conditions, construction techniques and the degree of site control all influence the resistance to jacking of pipes, but if an appropriate model is chosen it should be possible to predict jacking forces with a reasonable degree of accuracy. Deviations of the pipeline from a straight line increase the jacking resistance. A new analysis, based on observations from the field monitoring, provides an explanation for the measured increases in pipeline resistance for pipes jacked through a stable bore; it highlights the important factors and emphasizes the need for careful control of pipeline alignment. Explanations are also sought for the apparently frictional behaviour in terms of total stress at the pipe-soil interface in firm and stiff cohesive soils. Time effects are shown to be important in high plasticity clays.
Jacobs Creek is a tributary draining into the Monongahela River, southwestern Pennsylvania. The topography is characterized by a narrow stream valley with steep walls on both sides. Pennsylvania State Route 166 crosses Jacobs Creek just upstream of its confluence with the Monongahela River and passes over a fill approximately 52 ft above the stream bed. The new Grays Landing Dam will raise the level of the river to a new pool elevation 15 ft higher. This raise would cause the partial submergence of a preexisting concrete culvert. The proposed solution was to install an auxiliary culvert at a higher invert elevation which would be capable of maintaining the required flow capacity. A pipe jacking installation procedure was undertaken and is described in this paper. -from Authors
Prediction of jacking forces has been well-established for pipe-jacking drives traversing soils. However, the accrual of jacking forces for drives negotiating weathered rock formations has not been well understood. Three pipe-jacking drives in Kuching City, Malaysia spanning weathered lithological units of sandstone, phyllite and shale were studied. In the absence of in-situ pressuremeter testing during the investigation stage, tunneling rock spoils were collected and characterized through direct shear testing. The “generalized tangential” technique was applied to the nonlinear direct shear test results to obtain linear Mohr–Coulomb parameters, c′p and ϕ′p. This allowed for back-analysis of frictional coefficient, μavg through the use of a well-established predictive jacking force model. The reliability of using c′p, ϕ′p and μavg was assessed through 3D finite element modeling of the studied pipe-jacking drives. Based on these parameters, the results obtained from the numerical analyses of the studied pipe-jacking drives show good agreement with the jacking forces measured in-situ. The outcome of this research demonstrates that the derived strength parameters from direct shear testing of tunneling rock spoils has the potential to be used as reliable input parameters in finite element modeling to predict pipe-jacking forces in highly weathered geological formations.
There is currently no published guidance on the excavatability of Irish rock for microtunnelling applications. In this paper, new data and experiences of microtunnelling through rock (using a Herrenknecht AVN slurry shield machine with a rock head) at five Irish sites are presented and interpreted. The rock type is limestone at three of the sites, with mudstone/conglomerate and sandstone at the other two sites. The jacking forces are separated into face and friction (between the concrete pipe and rock) components. Useful relationships have been established between the excavatabilityindex andthe uniaxial compressive strength and brittleness index of rock.Cutter head wear is discussed in the context of rotational distance travelled and rock strength. In addition, the suitability of a number of prediction models documented in the literature for the prediction of microtunnel boring machine performance in Irish rock is examined.
For a pipe jacking construction, reducing the soil–pipe interface friction and providing enough jacking force are the most common approach to optimize the construction efficiency. In practice, jacking force is generally estimated by various empirical equations. However, the estimations of empirical equations frequently deviate from the reality. In this study, a model coupling finite element method and a displacement control method were applied to estimate the required jacking force in pipe jacking. Two cases were examined from Central Taiwan, where the primary geological foundation composed of gravel formations. Case A pertained to pipe jacking construction during which sewage pipes with a diameter of 2.4 m were utilized. The monitoring data from this case were used to establish the jacking force estimation model. The jacking force history observed in Case B, in which sewage pipes of 1.0 m diameter were used, was compared with those obtained by the developed model to demonstrate the applicability of the model. The results suggested the developed model can estimate the jacking force with a better accuracy towards the middle and the final stage of the pipe jacking process.
Pipe ramming is a cost-effective trenchless pipe installation method in which percussive blows generated by a pneumatically or hydraulically powered encased piston rammer are used to advance a pipe or culvert through the ground. To evaluate the feasibility of a pipe ramming installation, engineers must be able to reliably predict the pipe drivability and installation stresses. Assessment of the drivability of the pipe and selection of the optimal hammer for pipe ramming installation requires that the static and dynamic soil resistance to ramming at the pipe face and along the casing be reliably estimated. However, pipe ramming-specific models are not currently available, and engineers often resort to the existing traditional pipe-jacking and microtunneling models for static soil resistance computations. This paper describes the results of four full-scale pipes rammed in the field and the corresponding static soil resistance to ramming in granular soils. A companion paper addresses dynamic soil resistance and pipe drivability. The accuracy of the existing pipe jacking and microtunneling-based static soil resistance models is evaluated herein and found to provide unsatisfactory estimates of the face and casing resistance. New semiempirical pipe ramming-specific models are proposed based on the field observations and are found to produce good estimates of static soil resistance for use in pipe drivability evaluations. (C) 2014 American Society of Civil Engineers.
The evaluation of the drivability of a proposed pipe is a critical task in the planning and execution of pipe-ramming installations, because it results in increased efficiency, safe installations, and significant cost savings. The analysis of drivability provides a means for optimizing the hammer energy required for a given pipe-ramming installation, and it minimizes potential damage to the pipe due to overstressing the pipe material. Four full-scale pipes with diameters ranging from 610 to 3,660 mm installed using pipe-ramming hammers were instrumented to observe the measurement of hammer-pipe energy transfer, driving stresses, and total (static and dynamic) soil resistance to penetration and formed the basis for evaluating drivability. First, the hammer-pipe energy transfer calculated from the observed force and velocity time histories was characterized, indicating the quantity of energy that actually results in the penetration of the pipe through soil. Then, the dynamic model parameters known as the soil quake and damping were back-calculated using common signal-matching analyses and presented as a function of normalized soil resistance. Wave-equation analyses used routinely to assess the constructability of pile foundations were adapted to estimate the observed force time histories and driving curves or the variation of penetration resistance with static soil resistance. Wave-equation analyses were also used to estimate the observed compressive and tensile driving stresses and the accuracy of the estimates characterized. The results of this study and those used to develop equations for static soil resistance to ramming can be used as the basis for the evaluation of the drivability of rammed pipes. (C) 2014 American Society of Civil Engineers.
Foreword Preface Part I. Principles and Elementary Applications: 1. Plausible reasoning 2. The quantitative rules 3. Elementary sampling theory 4. Elementary hypothesis testing 5. Queer uses for probability theory 6. Elementary parameter estimation 7. The central, Gaussian or normal distribution 8. Sufficiency, ancillarity, and all that 9. Repetitive experiments, probability and frequency 10. Physics of 'random experiments' Part II. Advanced Applications: 11. Discrete prior probabilities, the entropy principle 12. Ignorance priors and transformation groups 13. Decision theory: historical background 14. Simple applications of decision theory 15. Paradoxes of probability theory 16. Orthodox methods: historical background 17. Principles and pathology of orthodox statistics 18. The Ap distribution and rule of succession 19. Physical measurements 20. Model comparison 21. Outliers and robustness 22. Introduction to communication theory References Appendix A. Other approaches to probability theory Appendix B. Mathematical formalities and style Appendix C. Convolutions and cumulants.
For a pipejacking, the jacking force is critical to balance the resistance force and to move the pipe string forwards. The driving mechanism of a curved pipejacking is more complicated than a straight-line pipejacking, and its jacking force is also more difficult to be determined. The paper theoretically studies the jacking force of a curved pipejacking by considering the static equilibrium of earth pressure, resistance at cutting face, friction at pipe surface, and the driving force behind the pipe string. The derived theoretical formula can be used to estimate the driving forces of a straight-line or a curved pipejacking. Case study was performed by applying the theoretical and empirical formulae. After calibration, the corrected formula is more accurate and more applicable.
This paper presents an approach for the probabilistic inverse analysis of braced excavations based on the maximum likelihood formulation. Here, the soil parameters are updated using the observations of the maximum ground settlement and/or the maximum wall deflection measured in a staged excavation. The updated soil parameters are then used to refine the predicted wall and ground responses in the subsequent excavation stages, as well as to assess the building damage potential at the final excavation stage. Case study shows that the proposed approach is effective in improving the predictions of the excavation-induced wall and ground responses. More-accurate predictions of the wall and ground responses, in turn, lead to a more accurate assessment of the damage potential of buildings adjacent to the excavation. The proposed approach offers an effective means for a probabilistic inverse analysis of braced excavations.
This paper presents a new geotechnical design concept, called robust geotechnical design (RGD). The new design methodology seeks to achieve a certain level of design robustness, in addition to meeting safety and cost requirements. Here, a design is considered robust if the variation in the system response is insensitive to the variation of noise factors such as uncertain soil parameters and construction quality. When multiple objectives are considered, a single best design may not exist, and a trade-off may be necessary. In such a case, a genetic algorithm is adopted for multi-objective optimization and a Pareto Front, which describes a trade-off relationship between cost and robustness at a given safety level, is established. The new design methodology is illustrated with an example of spread foundation design. The significance of the RGD methodology is demonstrated.
Field observed performance of slopes can be used to back calculate input parameters of soil properties and evaluate uncertainty of a slope stability analysis model. In this paper, a new probabilistic method is proposed for back analysis of slope failure. The proposed back analysis method is formulated based on Bayes’ theorem and solved using the Markov chain Monte Carlo simulation method with a Metropolis–Hasting algorithm. The method is very flexible as any type of prior distribution can be used. The method is also computationally efficient when a response surface method is employed to approximate the slope stability model. An illustrative example of back analysis of a hypothetical slope failure is presented. Effects of jumping distribution functions and number of samples on the efficiency of Markov chains are studied. It is found that the covariance matrix of the jumping function can be set to be one half of the covariance of the prior distribution to achieve a reasonable acceptance rate and that 80,000 samples seem to be sufficient to obtain robust posterior statistics for the example. It is also found that the correlation of cohesion and friction angle of soil does not affect the posterior statistics and the remediation design of the slope significantly, while the type of the prior distribution seems to have much influence on the remediation design.
In this paper, a Bayesian approach for updating a semi-empirical model for predicting excavation-induced maximum ground settlement using centrifuge test data is presented. The Bayesian approach involves three steps: (1) prior estimate of the maximum ground settlement and model bias factor, (2) establishment of the likelihood function and posterior distribution of the model bias factor using the settlement measurement in the centrifuge test, and (3) development of posterior distribution of the predicted maximum settlement. This Bayesian approach is demonstrated with a case study of a well-documented braced excavation, and the results show that the accuracy of the maximum settlement prediction can be improved and the model uncertainty can be reduced with Bayesian updating.
This paper describes the application of a finite-element analysis for modeling the top-down construction of a seven-story, underground parking garage at Post Office Square in Boston. The analysis incorporates couples flow and deformations within the soil for real-time simulation of construction activities; a numerically accurate algorithm for excavation in nonlinear soil; and advanced constitutive modeling of clay behavior. Predictions are evaluated through comparisons with extensive field data. including wall deflections, soil deformations, surface settlements, and piezometric elevations. Differences between predicted and measured wall movements arc attributed primarily to postconstruction shrinkage of the roof and floor system. while settlements are affected by unrealistic modeling of piezometric elevations in the underlying rock. A modified analysis, incorporating these factors, greatly improves agreement with the measured data. The results demonstrate that reliable and consistent predictions of soil deformations and groundwater flow can be achieved by advanced methods of analysis without recourse to parametric iteration, but emphasizes the need for adequate characterization of engineering properties for the entire soil profile.