Article

Updating the "Decision Aids for Tunneling"

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Abstract

The "Decision Aids for Tunneling" are a procedure and computer code that can be used to assess the effect on construction cost and time of geologic/geotechnical uncertainties and uncertainties in the construction process. Previously, it was only possible to make predictions prior to construction. There is, however, a need for updated predictions while construction is in progress. Such predictions can be used to improve scheduling, resource allocation, financial planning, and so on. This article presents an updating procedure that allows one to refine predictions during construction. Updating not only involves replacing the original prediction with actual data from the excavation, but also includes a learning component using information from the actual excavation to arrive at an improved prediction for the unexcavated part of a tunnel.

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... The construction progress of underground projects is highly uncertain because of uncertainties in both the geology and the construction process (Min et al. 2003). Worker morale, reliability and performance of equipment, weather conditions, and material supplies are all contributing factors (Haas and Einstein 2002). This uncertainty dictates the time-varying nature of both construction productivity and project completion probability of underground cavern group projects. ...
... Some relevant studies have been conducted to address time-varying uncertainty. Haas and Einstein (2002) pointed out the need for updating processes and presented an updating procedure to refine predictions during construction. Chung et al. (2004Chung et al. ( , 2006 explained how Bayesian updating techniques could be applied to improve simulation input and output. ...
... Those methods are S-curve-based, so they are not suitable for underground cavern group projects. Haas and Einstein (2002) applied Bayesian techniques to Decision Aids for Tunneling (DAT) and updating the mean length of geological and geotechnical parameters. Chung et al. (2004Chung et al. ( , 2006 collected data from a tunneling project using a tunnel boring machine (TBM) and used them to improve simulation input models adopting Bayesian updating techniques on the assumption that the observed data derived from a normal distribution with known variance σ 2 . ...
Article
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Real-time simulation is powerful in forecasting the completion probability of long-term projects with repetitive tasks but fails to consider the time-varying uncertainty of inputs caused by construction process variabilities. In this paper, an improved method is introduced for predicting the time-varying probability of project completion of ongoing underground cavern group projects using Bayesian updating techniques. Within a tailor-made hierarchical simulation model, the Bayesian approach is adopted to constantly update duration distributions of unfinished project activities according to onsite data. The probability of project completion can therefore be increasingly refined during the process. The methodology is further explained in a case study where its feasibility and advantage over traditional approaches are verified. The success may also be replicated in addressing other similar time-varying uncertainty issues inherently present in almost all construction projects.
... In monitoring the data is continuously measured and sometimes the strength and deformability parameters also experience some change in value due to several factors like aging of structure, atmospheric conditions, decay, etc. The Flowchart of Figure 3.10 represents the general decision engineering cycle [30] which can be adapted to our case of updating parameters of San Torcato church. It starts from determining the parameters under some uncertainty and included in engineering models. ...
... The decision cycle[30] ...
Thesis
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The main objective of this thesis is to combine information gathered from different Non Destructive tests (NDT) (direct and indirect) and fuse it by using Bayesian approach. Many time practitioners working with NDT data want to choose parameters based on results of different NDT tests with different levels of reliability and uncertainty quantification. As suggested by literature the use of a single technique might not suffice to gain information and the combination of different techniques is recommended. Also for the case of masonry structures it might not be possible to perform destructive tests but since the parameter has to be estimated based on information provided by various NDT data sources coupled with literature information. NDT data from San Torcato Church was used in this thesis to test a Methodology to transform the data into a single and uniform format by the help of Bayesian approach. A simple Matlab Toolbox NDT_FUSION was developed and tested with different models available and modified later by using a Trust Factor which takes into account the weightage of different NDT tests. The developed toolbox is very easy to use since it has Graphical user interface (GUI) and does not required practitioner to learn the complex mathematics involved in calculation behind the Bayesian black box. The data fusion was done at different levels and steps so every time an updating takes place we arrive to a more realistic value of parameter. Two geomechanical parameters namely the Elastic modulus (E) and compressive strength ( fc) of granite blocks from St. Torcato Church were studied in this thesis. The normal probability distribution function for the parameter of interest was calculated by using Jeffrey’s Prior and Conjugate Prior, considering different levels of initial knowledge. The Elastic modulus (E) was updated by using data from Literature knowledge, sonic, ultrasonic and direct compressive strength tests to arrive to a more certain value in form of a posterior distribution. In both the cases the raw data from direct and indirect sources was processed and combined with data fusion toolbox to transform values into statistical distribution. The reliability confidence intervals of parameters were updated every time a new data becomes available providing more broad information. Different levels of uncertainty are present in data fusion system proposed in this report starting from the literature knowledge to direct compression test core data which were quantified and addressed in this thesis. The tests of different reliability levels were weighed by circulating a survey form among professors and graduate students experts in the field to take their opinion. The results of the surveys come was the calculation of Trust Factor to update the spread of the parameters and incorporate in the model to obtain better predication of the parameters. The application developed comes with a Matlab compiler runtime (MCR) installer which allows the application to run on computers without the prerequisite of having Matlab installed.
... These uncertainties stem from two major problems: First the geologic conditions are never exactly known particularly for deep and long tunnels construction. But even if the geologic conditions are known, there is still considerable uncertainty about the construction process itself (Mahmoodzadeh et al., 2019;Mahmoodzadeh et al., 2020c;Haas and Einstein, 2002). Second, from various case studies reported around the world (Dalgıç, 2002;Senent and Jimenez, 2015;Wang et al., 2012;Yassaghi and Salari-Rad, 2005), it can be inferred that uncertainties in the geology and complexity of tunnel construction processes often result in construction delays and cost overruns. ...
... Reduction in uncertainty by replacing predicted progress with actual progress(Haas and Einstein, 2002). ...
Article
The cost and time estimation play a vital role in successfully completing a tunnel construction, however in most cases the estimation falls short compared to the actual time and cost that a tunnel construction consumes due to a number of geological and geotechnical reasons. This creates uncertainties in tunnel construction in terms time and cost. In this article, the effects of geological/geotechnical uncertainties in tunnel construction time and costs are being minimized through continuous updating techniques. The forecasting of geological conditions is based on continuous space-discrete state Markov process. Whereas, predicting the construction time and costs are based on Monte-Carlo (MC) simulation. To verify the tool applicability, it has been applied to Hamru tunnel in Iran. Also, to assess the updating effect on obtained outcomes during construction, the tool has been updated two times. In the first update, the total uncertainty in construction time and costs (measured by standard deviation) has been reduced by about 45% and 52%, respectively, followed by a reduction by about 66% and 61% in the second update. Finally, we can conclude that, the presented methodology is a helpful tool for tunnel project managers to identify risks and the possibility of deviations in their construction time and costs.
... The formation of the geological stratum will obey the basic physical and chemical laws, despite numerous other random influences. For instance, many geological processes are related to the Markov properties, such as occurrence stratum, stratigraphic accumulation, sedimentary diffusion and magnetic activity [20]. The value of the minimum total cost of a project corresponds to the optimal number of observation points. ...
... The formation of the geological stratum will obey the basic physical and chemical laws, despite numerous other random influences. For instance, many geological processes are related to the Markov properties, such as Entropy 2017, 19, 332 3 of 12 occurrence stratum, stratigraphic accumulation, sedimentary diffusion and magnetic activity [20]. Therefore, the Markov model can be applied to changes in lithology. ...
Article
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Based on the Markov model and the basic theory of information entropy, this paper puts forward a new method for optimizing the location of observation points in order to obtain more information from limited geological investigation. According to the existing data from observation points data, classification of tunnel geological lithology was performed, and various lithology distribution were determined along the tunnel using the Markov model and theory. On the basis of the information entropy theory, the distribution of information entropy was obtained along the axis of the tunnel. Therefore, different information entropy could be acquired by calculating different classification of rocks. Furthermore, uncertainty increases when information entropy increased. The maximum entropy indicates maximum uncertainty and thus, this value determines the position of the new drilling hole. A new geology situation will be decided by the maximum entropy for the lowest accuracy. Optimal distribution will be obtained after recalculating, using the new location of the geology situation. Taking the engineering for the Bashiyi Daban water diversion tunneling in Xinjiang as a case, the maximum information entropy of the geological conditions was analyzed by the method proposed in the present study, with 25 newly added geology observation points along the axis of the 30-km tunnel. The results proved the validity of the present method. The method and results in this paper may be used not only to predict the geological conditions of underground engineering based on the investigated geological information, but also to optimize the distribution of the geology observation points.
... The empirical equation proposed by (O'Reilly and New, 1982) is used as a predictive model for DAT to relate the settlement profile to factors of ground movement (Aoyagi, 1995). To overcome the needs of updating predictions while construction is in progress, DAT includes an updating procedure that allows one to refine predictions (Christoph and Herbert, 2002). ...
Thesis
Evaluating the impact of tunnelling on above ground structures in urban areas highly relies on prediction of the settlement trough at surface level. Uncertainties in soil properties and other system characteristics for soft ground (e.g. Alluvium soil) can significantly affect the prediction. Classically, empirical formulas are used for prediction of the settlement using the experience from previous tunnelling projects. Empirical formulas do not consider the soil-lining interaction or the method of construction and lack a theoretical background for ground movement in continuum mechanics. Analytical and numerical approaches have developed to address some of these deficits, but have not to date, taken account of the many uncertainties involved in the process. This thesis introduces a stochastic method in the context of discrete random finite element theory to probabilistically predict the tunnelling-induced surface settlement. The method proposes a single mechanism (i.e. an uncertainty and sensitivity analysis framework) in which multiple sources of uncertainty can be considered within a single model (e.g. heterogeneity of the soil profile, variability in surcharge loads, and material properties). The power of the method is then examined through application to case studies involving two large-scale, shallow tunnelling projects excavated in alluvium soil. The results are compared with monitoring data, with estimations from deterministic finite element (FE) models and empirical formulas. Compared to the results of classical FEs and empirical approaches, application of the new probabilistic approach provides better understanding of the development of the settlement trough at surface level in both case studies. The output parameters for the tunnelling-induced settlement trough (volume loss and maximum settlement) are in good agreement with actual monitoring data in both case studies. Notably, the prediction result of the empirical formula in the first case study is conservative and for the second one is quite non-conservative. The new approach, on the other hand, provides more accurate predictions and insights into the effect of different sources of uncertainty.
... Even though the above issue has been investigated by many researchers, it still concerns the tunnelling society. Amongst other researchers, the efforts of Einstein [5] [6] [7] introducing the decision aids in tunnelling—DAT, should be noted. DAT simulates tunnel construction and studies the effects of different methods on the construction cost and time schedule. ...
Article
Unexpected ground conditions have always been a major problem for the tunnelling industry. As demand for the development of new underground structures, regardless of the ground conditions, has increased, safety and risk considerations have become even more important. The methodology presented in this paper aims at the identification of risk-prone areas, incorporating, at the same time, the uncertainty of ground conditions. It is focused on TBM tunnelling and can be implemented in the early stages of the project. The methodology assesses the hazards by introducing the concept of a vulnerability index, which is based on the principles of rock engineering systems, to identify the weighting of the parameters, and on probabilistic modelling to address the uncertainty in the parameters’ values. The proposed model is illustrated via the Athens Metro case study, used also for validating its performance under actual construction conditions.
... In engineering construction, the geology and construction processes are often characterized by high degrees of uncertainty (Haas and Einstein 2002). Because of the uncertainty and complexity of the construction process and the variability of different environments, construction progress and structure safety should be closely scrutinized and controlled throughout each stage of construction. ...
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Because of the uncertainties present in geology and construction processes, construction projects in underground cavern groups are typically characterized by high degrees of uncertainty. The real-time safety analysis of underground caverns during construction has been a key technological issue because previous three-dimensional simulations have commonly failed to consider the time-varying changes in construction schedules and geological conditions. Thus, this study couples a construction progress simulation with a real-time dynamic analysis of engineering safety. In this study, a real-time online safety analysis approach based on four-dimensional technology during the construction of underground caverns is introduced, and a dynamic visualization management system of safety information in underground caverns during construction is developed using the OpenGL (Open Graphics Library) Tao Framework and C#, with which integrated management of information related to safety, including geological information, construction progress information, monitoring information, and numerical simulation data, is considered. This study also demonstrates that real-time safety evaluation based on a construction safety information model during the construction of underground caverns is feasible and practical, as shown in a real example in China.
... The Decision Aids for Tunneling (DAT) allow engineers to simulate tunnel construction considering uncertainties in geology and construction processes for a given tunnel and, as a result, obtain distributions of the total cost and duration of tunnel construction (Sinfield and Einstein, 1996). Several options and modifications have been added to take into account of the geologic information obtained during excavation or to deal with special condition such as crossover connections and linings (Haas and Einstein, 2002). The DAT consist of an interactive computer program with which tunnel construction cost and time as well as required resources such as construction materials and produced resources such as muck can be computed. ...
Article
Full-text available
Applicability of the Decision Aids for Tunneling (DAT) technique is investigated in this study to better understand the efficiency of the decision making process during tunnel construction. For this, a traffic tunnel under construction is adopted and information on the construction procedure, i.e., overall geology, unit cost and construction time for each excavation process, is provided periodically. Various scattergrams in which cost-time simulation results are plotted are obtained according to the simulation methods and final prediction on the construction time/cost is made. It is found that the uncertainty in the cost distribution is greater than the uncertainty in the time distribution foreach cycle simulation and the uncertainties in time and cost for theone time simulations are comparable. Future work will be concentrated on the updating scheme using the face mapping data and various parametric studies will also be performed.
... (3) Expert systems and decision support systems, e.g. the Decision Aids for Tunnelling (DAT), are well-known programs that focus on tunnel construction schedule arrangement, cost analysis and decision making. However, professional knowledge and skills are required to use these programs [13] [14]. By using the fuzzy set theory and GIS, Cheng et al. developed a monitoring-data-based risk decision support system for foundation pit excavation [15]. ...
... Several studies have investigated probabilistic back analysis problems of uncertain parameters for the shield tunnels by combining probability theory and statistics. For example, Haas and Einstein [17] employed a Markov chain Monte Carlo (MCMC) method to update the posterior distributions of surrounding rock mass parameters of tunnels based on the monitoring data.Špačková and Straub [18] proposed a dynamic Bayesian network based-tunneling process model to update the probability of tunnel failure by utilizing the observation data from geological survey and construction stages. Park and Park [19] conducted a probabilistic back analysis of uncertain parameters for tunnel surrounding rock masses by adopting a response surface method. ...
Article
Full-text available
This paper proposes a new sequential probabilistic back analysis approach for probabilistically determining the uncertain geomechanical parameters of shield tunnels by using time-series monitoring data. The approach is proposed based on the recently developed Bayesian updating with subset simulation. Within the framework of the proposed approach, a complex Bayesian back analysis problem is transformed into an equivalent structural reliability problem based on subset simulation. Hermite polynomial chaos expansion-based surrogate models are constructed to improve the computational efficiency of probabilistic back analysis. The reliability of tunneling-induced ground settlements is updated in the process of sequential back analyses. A real shield tunnel project of No. 1 Nanchang Metro Line in China is investigated to assess the effectiveness of the approach. The proposed approach is able to infer the posterior distributions of uncertain geomechanical parameters (i.e., Young’s moduli of surrounding soil layers and ground vehicle load). The reliability of tunneling-induced ground settlements can be updated in a real-time manner by fully utilizing the time-series monitoring data. The results show good agreement with the variation trend of field monitoring data of ground settlement and the post-event investigations.
... In brief, a Monte Carlo model consists of three sub-models: probabilistic geologic prediction model, probabilistic tunnel cost model, and risk-sensitive dynamic decision model (Likhitruangsilp et al., 2004). In addition , there have been some studies on the tunnel cost from risk management viewpoint and not necessarily for cost estimation purposes (Haas and Einstein, 2002). Bottero and Peila (2005) used Analytic Hierarchy Process (AHP) to compare traditional trench excavation and micro-tunneling as excavation methods for an urban sewer construction in Turin, Italy and suggested that microtunneling is preferable approach to traditional trench excavation in this case. ...
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2005. Includes bibliographical references (leaf 121). Tunnels are subsurface passages which are often constructed without removing the overlying rock or soil. It follows that the lack of a priori knowledge of subsurface conditions poses major challenges in their preliminary design and planning. Considerable construction savings may be achieved through the proper collection and interpretation of information obtained through site exploration. However, exploration results are often not completely reliable and site exploration in itself involves a cost. Exploration planning is therefore a process of decision making under uncertainty. Einstein et al. (1978) provide a model that applies decision analysis to the tunnel exploration problem. This thesis first describes the model devised by Einstein et al. and provides numerical techniques for implementing it in a programming package. A package in Visual Basic for Applications is presented which implements the model for a generic tunnel. The thesis concludes by applying the devised package to the North Kenmore Tunnel (Washington State). by Jad S. Karam. S.M.
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The increasing constraints that construction companies face due to the prolonged financial crisis and the contracting construction market necessitate the need for more and more realistic and efficient approaches to the planning, scheduling and monitoring of their projects. A deterministic approach to project management that has preset parameters of time and cost and in which decisions are taken based on independent analyses of time or cost, even if they are interrelated, has a low likelihood to be successful. Construction projects are typically confronted with delays and additional costs, which reduce a company's profit and can lead to its bankruptcy. Therefore, a more efficient approach should take into account the risk of these events, the uncertainties and resources limitations in construction project planning, scheduling and monitoring and also the correlation between the time, cost and resource limitation parameters. This paper provides a practical approach to quantitative risk analysis using the Monte Carlo Method and highlights the correlation between the parameters of time, cost and resource limitation in construction projects. The project execution is analyzed not only by the probability of the parameters of time and cost together but also by the trends of them together. This approach integrates the scope, time, cost, resources and risks of a project and provides a better tool for decision-making. To demonstrate the advantages of this approach, a case study of a construction project is analyzed using Spider Project software.
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Schedules are fundamental parameters for decision making in the design phase of tunnel construction projects. Schedule estimates of tunnel construction projects are subject to major uncertainties caused by uncertain geologic conditions and risks. This research presents an adaptive cyclic operation network simulation (CYCLONE) simulation technique to predict the schedule of tunnel boring machine (TBM) tunneling and quantifies the impacts of geologic risks along a tunnel in the design phase. A geologic prediction model is integrated with expert judgments to evaluate the probabilistic geologic risks along the tunnel alignment. An adaptive CYCLONE simulation technique is developed to flexibly adjust the durations, arrangements, and modes of construction operations in response to the occurrences of geologic risks and changes of geologic conditions. The applicability of the proposed method was demonstrated by an illustrative case study - Jinping (JP) hydraulic tunnel project in southwest China. The simulation results indicate that this project has a high risk of delays caused by geologic hazards. The analysis of the simulation results reveals that the schedules of tunneling and the uncertainty in the schedules will be underestimated if geologic risks are not considered well in the simulation. The incorporation of geologic risks and the adaptability of the simulation model would lead to a more accurate and robust simulation.
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Fractures and fracture networks govern the mechanical and fluid flow behavior of rock masses. Tunneling and other rock mechanics applications therefore require the characterization of rock fractures based on geological data. Field investigations produce only a limited amount of data from boreholes, outcrops, cut slopes, and geophysical surveys. In tunneling, the process of excavation creates a priceless opportunity to gather more data during construction. Typically, however, these data are not utilized due to the impedance of sampling and analysis on the flow of construction, and safety concerns with sampling within unlined tunnel sections. However, the use of this additional data would increase the overall safety, quality, and cost savings of tunneling. This study deals with several aspects of the above, with the goal of creating methods and tools to allow engineers and geologists to gather and analysis fracture data in tunnels without interrupting the excavation and without compromising safety. Distribution-independent trace density and mean trace length estimators are developed using principles of stereology. An optimization technique is developed utilizing Differential Evolution to infer fracture size and shape from trace data obtained on two or more nonparallel sampling planes. A method of producing nearly bias free empirical trace length CDF's is also introduced. These new methods and tools were validated using Monte Carlo simulations. A field study was conducted in an existing tunnel allowing the above methods and tools to be further validated and tested. A relational database was developed to aid in storage, retrieval, and analysis of field data. Fracture models were built and updated using fracture data from within the tunnel. Utilization of state of the art imaging techniques allowed for remote sampling and analysis, which were enhanced by the use of 3d visualization techniques. System requirements: PC, World Wide Web browser, and PDF reader. Available electronically via the Internet. Title from electronic submission form. Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 2007. Vita. Abstract. Includes bibliographical references.
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The decision aids for tunneling (DAT) are a computer-based tool with which tunnel construction cost and time as well as required and produced resources can be computed. The DAT work with standard information such as geologic/geotechnical, structural, and material characteristics as well as construction performance. The two major components of the DAT, the "description of geology" and "construction simulation and construction management" are reviewed followed by descriptions of major applications of the DAT. Specifically, this involves application in the projects of two new transalpine rail tunnels in Switzerland (Gotthard, 57 km; Lotschberg, 36 km), investigation of different alternatives for a Metro project, and, finally, use of the DAT for assessing the effect of new tunneling technology on cost and time of construction.