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Drilling and sampling to obtain borehole logs, together with various in-situ testing, are usually performed to determine subsurface soil and rock profiles and their associated engineering propertie...

It is well recognised that the severity of pipeline external corrosion is highly related to the corrosivity of the surrounding soil environment. However, in practice, the explicit effects of the so...

This paper presents a novel Bayesian machine-learning approach for unsupervised and simultaneous soil stratigraphic interpretation of cone penetration test (CPT) soundings at the site scal...

This paper presents a novel perspective to understanding the spatial and statistical patterns of a cone penetration dataset and identifying soil stratification using these patterns. Both local consistency in physical space (i.e., along depth) and statistical similarity in feature space (i.e., logQt–logFrspace, where Qtis the normalized tip resistance and Fris the normalized friction ratio, or the Robertson chart) between data points are considered simultaneously. The proposed approach, in essence, consists of two parts: (i) a pattern detection approach using the Bayesian inferential framework and (ii) a pattern interpretation protocol using the Robertson chart. The first part is the mathematical core of the proposed approach, which infers both spatial pattern in physical space and statistical pattern in feature space from the input dataset; the second part converts the abstract patterns into intuitive spatial configurations of multiple soil layers having different soil behavior types. The advantages of the proposed approach include probabilistic soil classification and identification of soil stratification in an automatic and fully unsupervised manner. The proposed approach has been implemented in MATLAB R2015b and Python 3.6, and tested using various datasets including both synthetic and real-world cone penetration test soundings. The results show that the proposed approach can accurately and automatically detect soil layers with quantified uncertainty and reasonable computational cost.

Borehole drilling and cone penetration test (CPT) are frequently employed site investigation methods for identifying subsurface stratification. However, these two methods have their respective pros and cons, and their corresponding soil type classification protocols are different. Therefore, an approach that can jointly interpret raw data from both investigation methods and provide unified soil classification results is in great demand. Motivated by the aforementioned point, this paper presents a novel semi-supervised clustering based stratification identification approach using information from both boreholes and CPT logs. The proposed approach is established on a hidden Markov random field (HMRF) framework so that the supervision constraints could be introduced by using borehole data during the clustering of CPT sounding samples. Further, the presented approach employs a Monte Carlo Expectation Maximization (MCEM) algorithm to perform the clustering process, which enables estimating the subsurface stratification in a probabilistic manner. The performances of the proposed approach are evaluated using real-world site investigation data. The test results indicate that the proposed approach is effective and robust for identifying subsurface stratification.

The premature failure of repaired concrete structures has become a big concern for civil engineers in recent years. While premature failure can be greatly reduced through the selection of an appropriate repair material, civil engineers must take into account a large number of conflicting criteria for candidate repair materials to make the final decision. In this paper, a procedure coupled with the VIKOR method is proposed to obtain the best repair material for concrete structures. This procedure can aid civil engineers in modeling and selecting suitable repair materials according to a set of predefined criteria. A case study is included to validate the accuracy of the outcomes of the proposed procedure. Since weights play a significant role in the ranking of results for the repair materials, sensitivity analysis is conducted using three different methods for assigning weights to find more reliable results. Keywords: Repair material, Concrete, Decision making, MCDM

This paper presents a new probabilistic site characterization approach for both soil classification and property estimation using sounding data from multiple cone penetration tests (CPTs) at a project site. A hidden Markov random field (HMRF) model based Bayesian clustering approach is developed, which can describe not only the heterogeneity of properties in statistically homogeneous soil layers, but also the correlation between spatial distributions of different soil layers. The latter has not been well considered in the existing CPT interpretation methods. A Monte Carlo Markov chain based expectation maximization (MCMC-EM) algorithm is adopted to calibrate the established HMRF model, so that both the subsurface soil/rock stratification and the pertinent soil properties can be estimated in a probabilistic manner. The proposed CPT interpretation approach is validated and demonstrated using a series of numerical examples, including using real CPT data. It is shown that the proposed method is able to accurately identify soil layers, pinpoint their boundaries, and provide reasonable estimates of the associated soil properties. In addition, comparative studies show that combining analysis of CPT data from multiple soundings, rather than interpreting them separately, can significantly enhance the accuracy of interpretation and simplify the subsequent task of interpreting stratigraphic profiles.

The accuracy of stability evaluation of a natural slope consisting of multiple soil and rock layers, regardless the adopted analysis methods, can be highly dependent upon a precise description of the subsurface soil/rock stratigraphy. However, in practice, due to the limitation of site investigation techniques and project budget, stratigraphy of the slope cannot be observed completely and directly; therefore, there remains a considerable degree of uncertainty in the interpreted subsurface soil/rock stratification. Therefore, estimating and minimizing the uncertainty of the computed factor of safety (FS) due to the uncertain site stratigraphy is an important issue in gaining confidence on the stability evaluation outcome. Presented in this paper is a practical analysis approach for evaluating the stability of slopes considering uncertain stratigraphic profiles by incorporating a recently developed stochastic stratigraphic modeling technique into a conventional finite element simulation approach. The stochastic modeling techniques employed for simulating the stratigraphic uncertainty will be briefly described. The main efforts are focused on elucidating the additional benefits from the proposed analysis approach, including a more reasonable probabilistic estimation of FS with consideration of stratigraphic uncertainty, as well as an effective approach for finding the optimum location of additional borehole logs to reduce the uncertainty of FS due to uncertain subsurface stratigraphy.

Despite the rapid development of risk analysis, there is a relative absence of risk criteria for dams in developing countries recently, which restrained the practical application of the research results. This paper proposes guidelines for establishing risk criteria of dams in developing countries in considering the coordination of social, economic and engineering factors, then establishes a method of targeted analysis and demonstrates relevant parameters selected according to the ALARP principle and F-N curves, using China as an example. Different individual life risk criteria are established based on different safety levels for existing dams and newly built dams. Social life risk criteria and economic risk criteria are established on the basis of the different safety levels of all size reservoirs, the seriousness of the consequences of accidents, and the acceptability of social risks. The process of establishing risk criteria of dams and the analysis of the parameters demonstrated in this paper are meaningful to provide a reference and promote the required level of management for developing countries.

A reliability-based method was developed for predicting the initiation time and the probability of flexural failure for continuous slab bridges with load-induced cracks exposed to chloride environment resulting from de-icing salts. A practical methodology was used for predicting the diffusion coefficient of chloride ingress into the pre-existing load-induced cracks in concrete. The reduction in the cross-sectional area of the reinforcement due to corrosion was included in the model. The proposed methodology accounts for uncertainties in the strength demand, structural capacity, and corrosion models, as well as uncertainties in environmental conditions, material properties, and structural geometry. All probabilistic data on uncertainties were estimated from the information contained in previous experimental and statistical studies. As an application of the proposed model, a three-span continuous slab bridge in Ohio is presented for demonstration of the developed methodology. A comparison of results clearly shows the importance of considering the effects of the load-induced cracks for correct prediction of the initiation of corrosion time and the critical time to maintain structural integrity.

This paper introduces a mathematical procedure to analyze slope/pile systems. Limiting equilibrium method of slices is extended to account for the pile in the slope. Force and moment equilibrium for each individual slice is satisfied. The proposed procedure allows two separate predefined failure slip surfaces (one in the upslope side and the other in the downslope side) with a unique factor of safety for each slip surface. An illustrative example is presented to elucidate the use of the solution in comprehending the interrelationships among the pile location, the desired factor of safety of the slope/pile system, and the interactive soil/pile forces.

With the development of intelligent and automated information system in the information era, the need for more efficient decision making method is growing. An effective method used to rank concrete bridge projects affected by reinforcement corrosion damage will help decision makers of bridge management agencies to better understand the different degrees of urgency for each project. The priority ranking process of different bridge repair projects is complex, since it is hard for decision makers to directly decide which bridge has higher priority when considering many criteria at the same time. The ranking of the different bridge repairing projects can be similar to solving multiple criteria decision making (MCDM) problems. The VIKOR (VlseKriterijumska Optimizcija I Kaompromisno Resenje in Serbian) method is a distance-to-target method which is developed and used to solve MCDM problems in material selection research. Since weights play a significant role in the priority ranking problems, objective weights based on Entropy concept and Target-based standard deviation method and dependent weights are also applied in this study. Several important criteria, which have not been considered in previous literatures, are proposed and the influence of these criteria to the bridge condition is checked and verified by using data information in NBI databased. A numerical example is proposed to illustrate the application of proposed method. Therefore, in this research a new ranking system methodology based on weighted VIKOR method with proposed criteria for ranking bridge projects is presented. Keywords: VIKOR method, Decision making, Concrete bridge, MCDM

Stochastic modeling methods and uncertainty quantification are important tools for gaining insight into the geological variability of subsurface structures. Previous attempts at geologic inversion and interpretation can be broadly categorized into geostatistics and process-based modeling. The choice of a suitable modeling technique directly depends on the modeling applications and the available input data. Modern geophysical techniques provide us with regional data sets in two- or three-dimensional spaces with high resolution either directly from sensors or indirectly from geophysical inversion. Existing methods suffer certain drawbacks in producing accurate and precise (with quantified uncertainty) geological models using these data sets. In this work, a stochastic modeling framework is proposed to extract the subsurface heterogeneity from multiple and complementary types of data. Subsurface heterogeneity is considered as the “hidden link” between multiple spatial data sets. Hidden Markov random field models are employed to perform three-dimensional segmentation, which is the representation of the “hidden link”. Finite Gaussian mixture models are adopted to characterize the statistical parameters of multiple data sets. The uncertainties are simulated via a Gibbs sampling process within a Bayesian inference framework. The proposed modeling method is validated and is demonstrated using numerical examples. It is shown that the proposed stochastic modeling framework is a promising tool for three-dimensional segmentation in the field of geological modeling and geophysics.

Subsurface formations with multiple soil/rock strata are a common geological condition for shield-driven tunnel (i.e., tunnel constructed using shield-driven machines) construction. The excavation face, under such conditions, often encounters a frequently changing stratigraphic configuration that consists of various lithological units. Furthermore, due to a lack of direct and continuous observations of the subsurface region, it is difficult to predict the stratigraphic profile along the entire excavation path with a high degree of certainty. Such a widely changing and uncertain excavation environment may lead to wide variation in the state of stress and deformation of the tunnel structure along the longitudinal direction. This poses a challenge for design engineers in obtaining accurate performance evaluations or reasonable design outcomes for tunnel construction in subsurface ground with multiple strata. This paper aims to address this challenge by presenting a stochastic geological modeling framework for uncertainty quantification of stratigraphic profiles using sparsely located observation information from geotechnical site investigations. In the proposed modeling framework, the underground soil stratigraphic profile is regarded as a Markov random field with specific energy functions, which is able to describe the inherent anisotropic and non-stationary spatial correlation of lithological units in the subsurface stratigraphic structure. By incorporating the developed stochastic geological modeling framework with a finite element simulation of the tunnel excavation, a probabilistic analysis approach is established to evaluate the effects of stratigraphic uncertainty on the structural performance of a shield-driven tunnel.

Stratigraphic (or lithological) uncertainty refers to the uncertainty of boundaries between different soil layers and lithological units, which has received increasing attention in geotechnical engineering. In this paper, an effective stochastic geological modeling framework is proposed based on Markov random field theory, which is conditional on site investigation data, such as observations of soil types from ground surface, borehole logs, and strata orientation from geophysical tests. The proposed modeling method is capable of accounting for the inherent heterogeneous and anisotropic characteristics of geological structure. In this method, two modeling approaches are introduced to simulate subsurface geological structures to accommodate different confidence levels on geological structure type (i.e., layered vs. others). The sensitivity analysis for two modeling approaches is conducted to reveal the influence of mesh density and the model parameter on the simulation results. Illustrative examples using borehole data are presented to elucidate the ability to quantify the geological structure uncertainty. Furthermore, the applicability of two modeling approaches and the behavior of the proposed model under different model parameters are discussed in detail. Finally, Bayesian inferential framework is introduced to allow for the estimation of the posterior distribution of model parameter, when additional or subsequent borehole information becomes available. Practical guidance of using the proposed stochastic geological modeling technique for engineering practice is given.

Stochastic soil modeling aims to provide reasonable mean, variance, and spatial correlation of soil properties with quantified uncertainty. Because of difficulties in integrating limited an...

In this work, a novel stochastic model framework for predicting the external corrosion growth in buried pipeline structures has been developed, and a reliability-based temporal and spatial maintenance strategy is presented. The spatial correlation of soil properties is modelled via hidden Markov random field. The temporal correlation of the corrosion rate is characterised by the geometric Brownian bridge process. A Bayesian inferential framework is employed to estimate the model parameters of the corrosion growth model using in-line inspection data. The proposed corrosion growth model was validated with actual inspection data. In the reliability analysis, the impact of device detectability is considered and hence the estimated failure probability is more realistic. The proposed maintenance strategy is directly based on the time-specific and location-specific failure probability. The application of the proposed model and maintenance strategy is illustrated through a real-life pipeline system. The r...

Toppling failure of rock slopes is a complicated mode due to a combination of both continuous and discontinuous deformation, especially in dealing with anti-dip rock slopes. In this paper, a novel continuum-based discrete element method (CDEM), which is useful in modeling the entire progressive process from continuous to discontinuous deformation, is proposed to analyze the deformation characteristics, the failure mechanism and the evolution process of a large-scale open pit slope with a typical anti-dip structure. To simulate the slope deformation, the shear strength reduction method (SSR) is adopted to represent the strength degradation of rock mass in the deterioration process. The simulated results are validated using data obtained from a field investigation and continuous monitoring by employing an advanced remote sensing technique called ground-based interferometric synthetic aperture radar (GB-InSAR). To analyze the evolution trend of the anti-dip slope, the subsequent toppling failure mode is predicted using the validated CDEM models. Based on a case study of a slope at the Fushun open pit mine (in Fushun, China), the unique geological structure with various joints and discontinuities, ground-water, intense rainfall, and mining activities are identified as the main triggers for different failure stages. The comparison between the field data and the simulation shows that CDEM accurately depicts the rock deformation and the failure pattern of the studied slope. The proposed numerical modeling techniques can be used for predicting failures of other similar excavated rock slopes. The simulated evolution process and the recorded deformation patterns help engineers to gain a better understanding of rock mass movement of anti-dip slopes, and the presented methodology could be utilized for similar studies and engineering designs. (C) 2015 Elsevier B.V. All rights reserved.

This paper describes the use of a clustering approach based on hidden Markov random field to extract potential homogeneous segments from a large length right-of-way of a pipeline structure with heterogeneous soil properties. This approach extends the conventional finite mixture model so that the spatial correlation of external corrosion sites can be taken into consideration. An algorithm is established for classifying corrosion defects using soil properties from an in-situ survey and location information from in-line inspection reports. The categorized corrosion defects reveal the hidden patterns of corrosion degradation in different segments along a pipeline structure. Stochastic simulation is employed to test this clustering approach. An example involving a 110-km pipeline interval is employed to illustrate the implementation of the clustering approach. The results indicate that the process of external corrosion propagation in a buried pipeline is position-dependent and is highly related to the soil environment. In addition, the results show that this phenomenon can be interpreted by segmentation using the proposed clustering method. A clustering-based inspection strategy is discussed as a way to apply the present approach.

In the petroleum industry, oil and gas pipeline operators routinely employ non-destructive in-line inspection (ILI) tools to perform integrity assessment, in which corrosion defects are detected, located and sized. However, the inspection technology is not perfect, and its accuracy is influenced by intrinsic measurement error of the ILI device as well as measurement noise. The quality of the inspection result should be assessed, and the inspection device should be calibrated before further assessment is performed. In the present work, a calibration model for an ultrasonic ILI device is proposed based on physical principles, and both systematic error and random error are able to be estimated. In addition to the errors from inspection devices, the soil environment introduces various uncertainties into the corrosion propagation. This paper presents a methodology to infer the actual corrosion defect depth based on detection theory and to account for the effect of soil property variation by combining cluster analysis with a Bayesian inferential framework. A numerical study on calibration uncertainty shows the influence of the number of field verifications. The proposed model framework is applied to a 110-km pipeline system to illustrate its application.

In reliability analysis, the crude Monte Carlo method is known to be computationally demanding. To improve computational efficiency, this paper presents an importance sampling based algorithm that can be applied to conduct efficient reliability evaluation for axially loaded piles. The spatial variability of soil properties along the pile length is considered by random field modeling, in which a mean, a variance, and a correlation length are used to statistically characterize a random field. The local averaging subdivision technique is employed to generate random fields. In each realization, the random fields are used as inputs to the well-established load transfer method to evaluate the load–displacement behavior of an axially loaded pile. Failure is defined as the event where the vertical movement at the pile top exceeds the allowable displacement. By sampling more heavily from the region of interest and then scaling the indicator function back by a ratio of probability densities, a faster rate of convergence can be achieved in the proposed importance sampling algorithm while maintaining the same accuracy as in the crude Monte Carlo method. Two examples are given to demonstrate the accuracy and the efficiency of the proposed method. It is shown that the estimate based on the proposed importance sampling method is unbiased. Furthermore, the size of samples can be greatly reduced in the developed method.

One important category of transportation infrastructure is underground pipelines. Corrosion of these buried pipeline systems may cause pipeline failures with the attendant hazards of property loss and fatalities. Therefore, developing the capability to estimate the soil corrosivity is important for designing and preserving materials and for risk assessment. The deterioration rate of metal is highly influenced by the physicochemical characteristics of a material and the environment of its surroundings. In this study, the field data obtained from the southeast region of Mexico was examined using various data mining techniques to determine the usefulness of these techniques for clustering soil corrosivity level. Specifically, the soil was classified into different corrosivity level clusters by k-means and Gaussian mixture model (GMM). In terms of physical space, GMM shows better separability; therefore, the distributions of the material loss of the buried petroleum pipeline walls were estimated via the empirical density within GMM clusters. The soil corrosivity levels of the clusters were determined based on the medians of metal loss. The proposed clustering method was demonstrated to be capable of classifying the soil into different levels of corrosivity severity.

Rockfall hazards are present throughout the state of Ohio. The Ohio Department of Transportation (DOT) employs Test Level 3 standard concrete barriers along the edges of roadways to contain rockfalls in high-risk areas. The performance of these barriers under impact from rocks on the ditch side and their effectiveness for rockfall catchment are relatively unknown. Full-scale impact tests were performed on concrete barriers to simulate the effects of impacts from rocks of various sizes and shapes. Numerous impacts were made at different sections and levels of the barriers to test their structural integrity and energy absorption capacity. The results from this study revealed that 32-in.-high precast concrete barriers with current Ohio DOT details had an impact energy absorption capacity of up to 24 kJ under a single impact. The corresponding energy absorption capacity of 42-in.-high cast-in-place concrete barriers was about 56 kJ under a single impact. Moreover, these barriers experienced severe cracking and spalling of concrete under impact loading. Several design modifications were studied in this test program. These modifications included reducing the spacing of rebars and rebar sizes, using welded wire fabric, and using different types of fibers in the concrete. The tests conducted on the modified concrete barriers showed an impact energy increase of more than 100% with the modifications suggested in this study. Barriers made from the modified designs also experienced significantly reduced extent and severity of cracking and a reduction in spalling and splashing of concrete under impact loading.

Very few models have been developed to estimate shrinkage of concrete containing pozzolans, and most existing models (particularly the ACI model) are not calibrated with pozzolanic concrete. This paper presents an improvement of the ACI model for shrinkage of concrete containing three types of pozzolans including silica fume (SF), fly ash (FA), and slag (SL). A comprehensive database is collected from the literature to cover a wide range of mixture components and mix proportions. In particular, to capture the effect of the dosage and type of each pozzolan, the time function in the ACI model is modified and a new correction factor associated with compressive strength is added. The model parameters in the modified time function and the new correction factor are assessed using a computational intelligence method called particle swarm optimization. The results of several statistical indicators show better prediction performance for the modified ACI model (M-ACI) than the original ACI formula.

In this paper, a methodology using Monte Carlo simulation method was developed in conjunction with the modified limiting equilibrium method of slices. Additionally, the time-dependent deterioration of bond capacity of corroding soil anchors was developed in this methodology due to the attack of chlorides. Uncertainties of anchor-related variables and soil parameters were considered using pertinent statistical descriptors. Furthermore, the inherent stochastic nature of the corrosion and degradation process for the anchor/slope system was identified and incorporated in the simulation. A PC-based software, C-UASLOPE, has been coded to allow for handling of complex slope geometry, soil profile and groundwater conditions. An illustrative example was presented to clarify the application of the C-UASLOPE software in modelling the deterioration process to aid in determining the system reliability. The importance of using a system reliability-based algorithm was illustrated by showing that the anchor/slope system ...

In this study, a model is developed to assess external corrosion in buried pipelines based on the uni- fication of Bayesian inferential structure derived from Markov chain Monte Carlo techniques using clustered inspection data. This proposed stochastic model com- bines clustering algorithms that can ascertain the simi- larity of corrosion defects and Monte Carlo simulation that can give an accurate probability density function es- timation of the corrosion rate. The metal loss rate is cho- sen as the indicator of corrosion damage propagation, obeying a generalized extreme value (GEV) distribution. Bayesian theory was employed to update the probability distribution of metal loss rate as well as the GEV param- eters in order to account for the model uncertainty. The proposed model was validated with direct and indirect inspection data extracted from a 110-km buried pipeline system.

A simplified approach was proposed to analyze the negative skin friction calculation of special-shaped pile considering pile-soil interaction under surcharge. Based on the concentric cylinder shearing theory, considering the changes of pile shape (such as, taper angle and diameters of pile base, etc.), the load-transfer of special-shaped pile was built. The accuracy of the developed simplified approach was verified by numerical simulation model with the same condition. Then, the influence factors, such as, taper angles, the diameter of pile base, surcharge, and pile-soil interface parameters were analyzed and discussed. The results show that the developed simplified approach can calculate NSF of special-shaped pile under surcharge effectively. A limited parametric study indicates that in many practical situations special-shaped piles (such as belled wedge pile shown in this work) offer a design option that is more economical than traditional uniform cross-section piles.

In this paper, a limiting equilibrium based methodology, incorporating the method of slices and arching effects of the drilled shafts, is developed for optimizing the use of multiple rows of drilled shafts. This proposed method is focusing on the number of rows, the location of each row, the dimension and spacing of the drilled shafts. Three design criteria are used for optimization: target global factor of safety, the constructability and service limit. A PC-based program called M-UASLOPE has been coded to allow for handling of complex slope geometry, soil profile, and ground water conditions. A design example is presented to illustrate the application of the M-UASLOPE program in the optimized design of multiple rows of drilled shafts for stabilizing the example slope.

In most limit state design codes, the serviceability limit checks for drilled shafts still use deterministic approaches. Moreover, different limit states are usually considered separately. This paper develops a probabilistic framework to assess the serviceability performance with the consideration of soil spatial variability in reliability analysis. Specifically, the performance of a drilled shaft is defined in terms of the vertical settlement, lateral deflection, and angular distortion at the top of the shaft, corresponding to three limit states in the reliability analysis. Failure is defined as the event that the displacements exceed the corresponding tolerable displacements. The spatial variability of soil properties is considered using random field modeling. To illustrate the proposed framework, this study assesses the reliability of each limit state and the system reliability of a numerical example of a drilled shaft. The results show the system reliability should be considered for the serviceability performance. The importance measures of the random variables indicate that the external loads, the performance criteria, the model errors of load transfer curves and soil strength parameter are the most important factors in reliability analysis. Moreover, it is shown that the correlation length and coefficient of variation of soil strength can exert significant impacts on the calculated failure probability.

In this paper, a method for estimating yield acceleration of a slope reinforced with a row of equally spaced drilled shafts under a seismic excitation is presented. The method is based on a concept of soil arching due to rigid inclusions of drilled shafts on slope, which in turn reduces the driving force on the down-slope side of drilled shafts. Considering soil arching effects and earthquake-induced inertia forces, a limiting equilibrium based formulation was derived. A computer program was coded to allow for calculations of yield acceleration of a drilled shafts reinforced slope with complex slope geometry and soil profiles. Once yield acceleration is determined, then Newmark's method can be evoked to estimate permanent displacement of a slope reinforced with a row of drilled shafts under an earthquake excitation. A total of seven cases were presented to show that the proposed Newmark type calculation is adequate when compared to 3-D finite element analysis results.

Analysis of laterally loaded piles or drilled shafts is a complex soil–structure interaction problem for which the p–y method has been widely accepted as a computational tool for predicting the load-displacement behavior. This paper presents a sampling-based method that can be applied to reliability analysis of the load-deflection behavior for laterally loaded piles. Various sources of uncertainties arising from soil properties, analysis model, and p–y criteria can be taken into account in the proposed method. In particular, soil properties needed as input for determining site-specific p–y curves were modeled as random fields. To statistically characterize the random field of a soil parameter, the field mean, the field variance, and the correlation structure are required. The performance of a pile under lateral loading is evaluated using a different set of random samples in each realization. The probability of failure, in which failure is defined as the event of not meeting the prescribed performa...

Developing predictive models for quantitative assessment of the deterioration of rock bolts exposed to corrosive environments is essential for rational planning of maintenance activities for anchorage structures. This article presents a probability-based computational model for predicting the time-dependent deterioration of bond capacity of corroding rock bolts due to the attack of chlorides. The inherent stochastic nature involved in the corrosion and degradation process is identified and simulated. A method is developed based on fundamental Mohr–Coulomb theory to evaluate the effect of corrosion on the bond strength due to a failure mode involving splitting of grout cover. Parameters affecting both strength and stress state at the bolt–grout interface are quantitatively related to the degree of corrosion. Integrating the realised corrosion stochastic process and the developed bond loss evaluation method, a computational algorithm based on Monte Carlo simulation is presented for evaluating the bond deter...

A new pile type with tapered pile body and an enlarged pile tip, referred herein as belled wedge pile, has been developed to improve both side resistance and tip resistance of pile when compared to the conventional tapered or belled cross-section piles. The new pile shape, due to wedge shape, can also reduce the development of negative skin friction when the surrounding soils are deforming under the applied surcharge loads. The construction method, quality assurance and quality control of the belled wedge piles are described. A numerical modelling technique using FLAC3D is used to perform numerical simulations to gain insight on the load carrying capacity and the load transfer behaviour of the belled wedge piles, in comparison to other pile shapes including the conventional belled piles, the tapered piles and uniform cross-section circular piles. The comparison study of the performance of these four pile shapes under compression loads, uplift loads and surcharge loads indicates that the belled wedge pile ...

SUMMARY In this paper, a reliability-based computational algorithm was developed and coded into a computer program, P-UASLOPE, for design of a row of equally spaced drilled shafts to stabilize an unstable slope while achieving the required target reliability index with minimum volume of drilled shafts. The Monte Carlo simulation technique was used in the previously developed deterministic computational program, in which the limiting equilibrium method of slices was modified to incorporate the arching effects of the drilled shafts in a slope. Uncertainties of soil parameters in the slope were considered by statistical descriptors, including mean, coefficient of variance, and distribution function. Model errors of the semi-empirical predictive equation for the load transfer factor for characterizing the soil arching effects were considered by statistics of bias. A total of 41 cases of 3-D finite element simulation results were used to determine the statistics of bias. Two design examples, one is a two-layer slope and the other one is an actual failed slope, were given to demonstrate the use of P-UASLOPE program for optimized design of drilled shafts reinforced slope system to achieve the most economic combination of design variables (i.e., location, spacing, diameter, and length of drilled shafts) to satisfy the design requirements in terms of target reliability index and the structural performance of the drilled shafts. A single value of factor of safety chosen in the deterministic approach may not yield the desired level of reliability as uncertainties of soil parameters and model errors cannot be accounted for systematically. Copyright © 2013 John Wiley & Sons, Ltd.

A new probabilistic methodology for landslide hazard assessment in regional scale using Copula modeling technique is presented. The current probabilistic landslide hazard analyses are performed under the assumption that landslide hazard elements, such as magnitude, frequency, and location, are independent. In this paper, a general approach is proposed to consider the possible dependence among hazard elements. Part of the Seattle, WA area was selected to evaluate the competence of the presented method. A total of 357 slope failure events and their corresponding topography and geology data were included in the study to develop and test the model. Based on the results, the mean success rates of the presented model in predicting landslide occurrence are 90 % in hazardous area and 12 % in safe locations on average, while these success rates are 63 and 44 % when these hazard elements were treated as mutually independent.

This paper presents a performance-based, probabilistic framework for design of a drilled shaft under axial and lateral loading that can consider spatial variability of soil properties at a project site. The performance criteria of a drilled shaft are stated in relation to the limiting tolerable deformations for strength limit and service limit, respectively. The computational algorithm for calculating the deformation of a drilled shaft is based on the commonly adopted load transfer method and the p-y method. “Geotechnical failure” is defined as an event in which the specified performance criteria are not met. Three failure modes are considered: axial movement, lateral deflection, and angular distortion. The spatial variability of soil properties is considered by using random field modeling techniques in which correlation length is introduced to account for site variability in addition to mean and variance. The method of fitting a sample autocorrelation function to a prescribed correlation function by using the method of ordinary least squares is introduced for determining site-specific correlation length for soil parameters. Geostatistical principles known as kriging are employed to estimate unknown parameters at unsampled locations from neighboring sampled locations. A numerical example is given to illustrate the application of the proposed methodologies. The example demonstrates that correlation length is an important statistical descriptor for characterizing site variability. Performance-based design provides unified consideration for both strength limit and service limit. Finally, the overall probability of failure for a drilled shaft when all three failure modes are considered is greater than the failure probability for any individual failure mode.

In order to calculate negative skin friction (NSF) of pile group embedded in a consolidating soil, the dragload calculating formulas of single pile were established by considering Davis one-dimensional nonlinear consolidation soils settlement and hyperbolic load-transfer of pile-soil interface. Based on effective influence area theory, a simple semiempirical mathematical model of analysis for predicting the group effect of pile group under dragload was described. The accuracy and reliability of mathematical models built in this paper were verified by practical engineering comparative analysis. Case studies were studied, and the prediction values were found to be in good agreement with those of measured values. Then, the influences factors, such as, soil consolidation degree, the initial volume compressibility coefficient, and the stiffness of bearing soil, were analyzed and discussed. The results show that the mathematical models considering nonlinear soil consolidation and group effect can reflect the practical NSF of pile group effectively and accurately. The results of this paper can provide reference for practical pile group embedded in consolidating soil under NSF design and calculation.

Deep foundation designs for service limit state are still deterministic in the current AASHTO LRFD Specifications. To address this deficiency, a performance-based reliability design methodology is developed using the Monte Carlo statistical techniques. In the proposed methodology, the design criteria are defined in terms of the allowable displacement. The spatial variability of soil parameters is considered in the proposed methodology by modeling soil parameters as random fields. Failure is defined as the event that the induced displacement exceeds the limiting displacement. The probability of failure by Monte Carlo approach is the ratio of the number of unsatisfactory performance events to the sample size. Three numerical examples are given to illustrate the application of the proposed methodology for laterally loaded and axially loaded drilled shafts, respectively. The spatial variability and correlation of soil properties were shown to exert significant influences on the foundation design.

In the present study, new empirical models are derived to predict the compressive strength of preformed foam cellular concrete using volumetric and weighted approaches. The proposed models are generated by utilizing a robust predictive tool known as genetic programming. A comprehensive database is collected from the literature to cover a wide range of mixture components (such as sand and pozzolans) and mix proportions. The models link the compressive strength to binder, water, and foam volume. Validation of the best model is carried out by using a portion of the data set that is not employed in the calibration process. A comparative study is conducted to evaluate the performance of the proposed model versus other models presented in the literature. Sensitivity and parametric analyses were conducted. The final model has a simple formulation and provides better prediction performance than the other models in the literature.

SUMMARY This paper presents a performance-based reliability design methodology for axially loaded drilled shaft foundations using the Monte Carlo statistical methods. The performance criteria for an axially loaded drilled shaft are defined in terms of the drilled shaft head displacement. The load transfer method is used as the computational model for solving the nonlinear soil–foundation interaction problem and to predict the load–settlement curve at the drilled shaft head. The input to the computational model and the model error are treated as random variables. Particularly, soil properties such as soil strength parameters are modeled as random fields to account for soil spatial variability. Random field samples are generated using local averaging subdivision according to the prescribed statistical descriptors, including mean, variance, and correlation length. Given performance-based acceptance criteria, the probability of failure can be evaluated for the prescribed load effects. A computer program is developed to facilitate the computation of the load–displacement curves of the drilled shaft head by using the commonly adopted load transfer concepts (t–z curves and q–w curves for shaft side and toe, respectively). Two design examples are presented, one for uplift and the other for compression, to illustrate the application of the developed performance-based reliability design methodology. One of the important observations from the examples is that the computed probability of failure can be sensitive to the spatial variations of soil strengths characterized by the correlation structures. It is strongly recommended that spatial variation of soil properties be considered in the reliability-based foundation design. Copyright © 2012 John Wiley & Sons, Ltd.

Understanding of cracking behavior of cover concrete is important for assessment of the remaining service life of corrosion-affected concrete structures. Predicting initiation of concrete cracking is commonly based on the evolution of stresses caused by the volume expansion of corrosion products on reinforcing bars. This paper presents an analytical method that is capable of providing the solution to two-dimensional (2D) elastic stress field caused by nonuniform volume expansion around the corroding reinforcing bars. The developed method features the formulation of a displacement model, which is applied as a boundary condition to simulate the effect of nonuniform corrosion on the deformation of the surrounding concrete. A closed-form solution to the stress field is obtained using the complex variable method of Muskhelishvili. Validation of the solution is supported by a comparison with finite-element-based simulation results. The solution reveals the evolution of stresses surrounding two typical locations...

A unified nonlinear strength criterion (i.e UNS criterion) is proposed, for the sake of versatility, to capture the complex strength behaviors of frictional materials in geotechnical field. It covers wide ranges on the meridian and octahedral planes to describe nonlinear strength behaviors of soils. The Modified Cam-Clay model, incorporating the unified nonlinear strength criterion, is employed as an example to derive working mathematical equations and to illustrate yielding surfaces in three-dimensional stress space for improving the model’s predictive capability. The unified nonlinear strength criterion, demonstrated here, is capable of capturing the experimental results of different types of soils on the meridian and octahedral planes. In addition, the revised model, based on this unified nonlinear strength criterion, though very simple, is versatile to predict the true triaxial test results from literature when considering the influences of the intermediate principal stress on strength and deformation under complex stress conditions.

Most of the rock medium possesses intrinsic grain orientation or preferred bedding and joint directions, thus requiring the use of at least transverse isotropy to describe its elastic behavior. This paper presents a series of charts, based on extensive finite element parametric studies along with nonlinear regression analysis of FE simulation results, for estimating the subgrade reaction modulus (or initial tangent to the p-y curve) using five elastic constants of a transversely isotropic rock mass. The proper characterization of subgrade reaction modulus is critical for accurate prediction of the elastic lateral deflection of a rock socketed drilled shaft under the applied lateral loads. The sensitivity of the response of a laterally loaded drilled shaft to the degree of anisotropy and orientation of the plane of anisotropy (bedding plane direction of the rock medium) was demonstrated in this paper for an actual lateral load testing case in Ohio. It is highly recommended to use five elastic constants to estimate subgrade reaction modulus of rock medium exhibiting high degree of cross anisotropy.

Instability of roadway slopes and embankments is a type of geohazard that can endanger the traveling public and the nearby roadway facilities when large and sudden slope movement occurs. Frequently, the decision regarding managing the hazards associated with potential highway slope failures or incipient failures is based on subjective judgment. In this paper, the linguistic fuzzy theory is used to express the hazard level associated with each selected hazard assessment criterion. The multicriteria decision-making technique is also used in this paper to allow for combination of the hazard criteria involving different units. As an example illustrating the application of the developed method for assessing the hazard level and priority for repair in regard to the slope instability related geohazard, the pertinent information of a database containing 37 landslides sites in Ohio is used to go through the exercise of hazard assessment. From the presented illustrative example, it is shown that the proposed multicriteria decision-making approach promotes a better decision for managing the geological hazards due to roadway slope failures.

The use of drilled shafts to stabilize an unstable slope has gained popularity in highway applications, mainly because it is a structural fix that does not require additional right-of-way. An analysis method for determining the factor of safety of a drilled shaft or slope system and for determining the earth thrust on the drilled shafts for structural design is introduced. The concept of the analysis is cast in the limiting equilibrium approach via the method of slices, while incorporating the drilled shaft–induced arching effects as the soil mass moved downslope and around the drilled shafts. The mathematical equations based on the limiting equilibrium calculation, together with the load transfer factor for accounting for the drilled shaft–induced arching effects, are presented. The three-dimensional finite element model parametric study using ABAQUS program was used to derive the semiempirical equations for quantifying the arching effect. A UASLOPE computer program was written to incorporate these algorithms for applications to real cases. A case study of a fully instrumented and monitored slope stabilization project, ATH-124, in Ohio, is presented. The analysis of the slope at the project site using finite element modeling and the computer code UASLOPE is presented, together with field-monitored data. On the basis of field monitoring data and the comparison between the finite element analysis results with the computer code UASLOPE results, the suggested analysis and design approach appears to be reasonable.

The transient electromagnetic (TEM) method is a geophysical exploration technique used in a wide range of applications such as mineral exploration, hydrogeology surveys, and underground geological mapping. In recent years, it has been applied in tunnel construction to forecast geological anomalies in front of the excavation face. However, the TEM response can be affected by metallic objects such as excavation carts and metallic support structures, which makes interpretation more difficult. The purpose of this study is twofold: to introduce a new method for extracting and eliminating TEM interference from metallic bodies in a tunnel excavation environment and to gain insight regarding the influence of metallic objects on the TEM response by physical modeling in the laboratory and studies conducted in the field. The concept of resistive limits is introduced; these limits can be used as eigenvalues in the inversion process, thus achieving more accurate identification of both the location and size of ball-shaped, low-resistivity anomalies (gouge materials) in surrounding rock that has high resistivity. Both the physical laboratory simulations and the field experiments provide insight on the interference effect of metal objects such as a steel arches or excavation carts on the TEM response. Field experiments inside a tunnel indicate that the maximum distance between the excavation cart tested and the tunnel face that can influence the TEM response is 30 m, while the maximum influence distance of a steel arch is 1 m in the vertical plane of the coil and 2 m in the axial direction. The proposed inversion process was shown to be capable of extracting the interference of metallic objects from TEM responses and improve the accuracy of TEM interpretation in identifying geological anomalies.

The use of drilled shafts to stabilize an unstable slope has been a widely accepted practice. There are two basic design and analysis issues involved: one is to determine the global factor of safety of the drilled shafts stabilized slope and the other one is to determine the design earth thrust on the drilled shafts for structural design of the shafts. In this paper, a limiting equilibrium method of slices based solution for calculating global factor of safety (FS) of a slope with the presence of a row of drilled shafts is developed. The arching mechanisms due to the presence of the drilled shafts on slope were taken into account by a load transfer factor. The method for calculating the net force applied to the drilled shaft from the soil mass was also developed. The interrelationships among the drilled shaft location on the slope, the load transfer factor, and the global FS of the slope/shaft system were derived utilizing the developed numerical closed-form solution. An illustrative example is presented to elucidate the use of the solution in optimizing the location of the drilled shafts on slope to achieve the desired global factor of safety of the slope/shaft system. Copyright © 2009 John Wiley & Sons, Ltd.

The drilled shafts have been widely used to support lateral loads (active load case) or as a means to stabilize an unstable slope (passive load case) due to their large lateral load resistance and structural capacity for shear and bending moments. However, there is a need to develop an analytical procedure that can use the actual measured deflection data of a drilled shaft subject to either active or passive load case to interpret the soil-drilled shaft interaction behavior. The mathematical formulation and the accompanied numerical procedure based on the principle of superposition were developed in this paper to allow for deducing the relevant soil-drilled shaft interaction behavior under the applied lateral load (i.e. net soil reaction force on the drilled shaft, the shear and bending moment in the shaft) from the measured deflection data. Both compatibility and force equilibrium conditions were utilized in formulating the mathematical equations for common single drilled shaft boundary conditions (free head and fixed bottom). The current application is limited to small deformation to meet the requirement that the drilled shaft responds in a linear elastic range. A total of three theoretical cases, along with two actual field cases, were used to demonstrate the validity of the proposed method and its engineering applications. Copyright © 2009 John Wiley & Sons, Ltd.