Dr Jinsong Huang

© 2015, National Research Council of Canada, All Rights Reserved.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 Taylor & Francis The limit analysis and the finite element method are powerful tools for analysing the bearing capacity of foundations. Previous research mainly focused on the foundations in uniform soils. In realistic conditions, soil properties are always varying spatially due to complex physical, chemical, and biological process in earth evolution. This paper investigates the bearing capacity and failure mechanism of footings buried at various depths in clays with spatially variable distribution of undrained shear strength using the lower bound limit analysis, the upper bound limit analysis, and the finite element analysis. Results show that the bearing capacity increases with increasing buried depths in spatially random soils, which is the same as in the uniform soils. The bearing capacity factors calculated using the finite element method, the lower bound limit analysis, and the upper bound limit analysis for a footing in spatially varied soils are all smaller than the corresponding values in uniform soils. The majority of the bearing capacity factors obtained from the finite element method is bounded by those obtained from the lower bound and the upper bound limit analysis. The shear planes show a clearly unsymmetrical manner in spatially varied soils using the three methods, which is different from the symmetrical shear plane in uniform soils.

© 2015 Elsevier Ltd.The mechanical properties of dry soil mix (DSM) columns can be highly variable. Variability can be accounted for in the construction specification for deterministic design and directly in reliability based design. Design methods and specifications to date adopt simplifications that do not take the variability of the columns fully into account. This paper uses both simple and advanced probabilistic methods to assess the performance/failure and system redundancy of dry soil mix columns. Reliability-based design methods and examples are given for the design of column strength and the adjustment of the column spacing to achieve a target probability of unacceptable performance or failure. An acceptance criteria chart is developed. The pull-out resistance tests on the DSM columns constructed for the Ballina Bypass motorway construction project in NSW Australia are compared to the chart to provide guidance with respect to acceptance criteria required to achieve the desired performance.

Rainfall induced landslides vary in depth and the deeper the landslide, the greater the damage it causes. This paper investigates, quantitatively, the risk of rainfall induced landslides by assessing the consequence of each failure. The influence of the spatial variability of the saturated hydraulic conductivity and the nature of triggering mechanisms on the risk of rainfall-induced landslides (for an infinite slope) are studied. It is shown that a critical spatial correlation length exists at which the risk is a maximum and the risk is higher when the failure occurs due to a generation of positive pore water pressure. © 2014 Elsevier B.V.

In the study of landslides, it is generally assumed that an impermeable boundary exists at a certain depth and failure occurs at this boundary. In reality this is not always the case and failures can occur at any depth. This paper aims to study the effect of boundary conditions on landslides, using a series of seepage and stability analyses performed over a range of rainfall intensities, and for different failure mechanisms, by studying the failure time and depths corresponding to fully drained, partially drained, and impermeable boundaries. It is shown that these conditions can significantly affect the occurrence and depth of rainfall-induced landslides. © 2014 Elsevier Ltd.

The observational method is one of the most successful processes in geotechnical engineering. Performance monitoring data are the most reliable information that engineers can use to predict future performance of geotechnical projects. This paper presents two examples where Bayesian statistical methods can be used for the prediction of future performance. The first example is to update the capacity of piles using load test results. The second example is to update embankment settlement predictions when field settlement monitoring data are available.

Bearing capacity and failure mechanism of a buried footing in uniformsoils have been simulated using limit analysis and finite element analysis in the past decades. In realistic conditions, soil properties always vary spatially. This dramatically affects the failure mechanism of a footing and, in turn, its bearing capacity. This paper illustrates an investigation into the failure mechanism and bearing capacity of a vertically and centrally loaded footing embedded in spatially variable clayey soils using random lower bound limit analysis, random upper bound limit analysis and random finite element analysis. The footing was embedded to 4 times its width. Monte Carlo simulation was performed for 400 realizations of random fields of undrained shear strength. The majority of the bearing capacity factors obtained from the finite element method is bounded by those obtained from the lower bound limit analysis and the upper bound limit analysis, but more close to the upper bound results. A full-flow failure mechanism is observed for the deeply embedded footing in spatially variable soil. The shear path of the footing shows an unsymmetrical pattern, which results from the spatially variable and unsymmetrical random field of soil shear strength. © 2015 Taylor & Francis Group, London.

Rainfall induced landslides can vary in depth and deeper the landslide, greater is the damage it causes. This paper investigates, quantitatively, the risk of rainfall induced landslides by assessing the consequence of each failure. The influence of the spatial variability of the saturated hydraulic conductivity on the risk of landslides is studied. It is shown that a critical spatial correlation length exists at which the risk is a maximum. © 2015 Taylor & Francis Group, London.

In deep drilling operation, borehole collapse due to insufficient drilling fluid pressure and borehole fracturing as a result of excessive drilling fluid pressure are two major modes of borehole failure. The latter may result in severe loss of drilling fluid into the formation, resulting in potential well control issues with influx of high pressure fluid or gas from adjacent formation layers. To prevent drilling fluid loss, the fluid pressure must not exceed an upper limit, otherwise the borehole will fail in tension or fracture. However, if the fluid pressure is too low, the borehole may collapse or fail in compression. Drilling fluid pressure window is therefore typically set by the upper limit of tensile failure and the lower limit of compressive failure. If the stress state and rock strength require a lower limit which is close to the upper limit, then the drilling fluid pressure design needs to stay within a very narrow window and consequently the feasibility of drilling may be questioned. Based on rigorous mechanics principles, this paper shows that it is possible to experience shear failure due to increasing drilling fluid pressure even before it reaches the upper limit of tensile failure. This may mean a more restricting drilling fluid pressure window in drilling weaker rocks. Implications of near wellbore shear failure are also briefly discussed in the context of water injection design which relies on injection at high pressure. © 2015 Taylor & Francis Group, London.

Copyright 2014, International Petroleum Technology ConferenceThe drilling induced tensile fractures can be observed from borehole image logs but they must be differentiated from natural fractures. This paper focuses on the understanding of hydraulically or artificially induced tensile fractures while drilling. We present an inversion method using rigorous principles of mechanics, to determine the in-situ formation stress state from observed induced tensile fractures. Contrary to common practices where only vertical or near vertical wells can be analysed, the present method is applicable to wellbores of all orientations. For a geological rock formation and area where the in-situ stress regime can be assumed to be similar, all the relevant borehole image logs can be included to provide information to yield the most probable subsurface in-situ stress state. The proposed inversion method directly solves for the in-situ stress states given any single set of observed tensile fracture location and orientation. It provides not only an estimate for the minimum horizontal stress magnitude and direction, but also the maximum horizontal stress magnitude which is usually very difficult to pin down. The resultant equations are non-linear and a simple numerical scheme is adopted for the solution. Although published data on borehole images of fractures with corresponding in-situ stress information are scarce, two observed field data from published papers are chosen for comparison.

The mechanical properties of natural materials such as rocks and soils vary spatially. This randomness is usually modelled by random field theory so that the material properties can be specified at each point in space. When these point-wise material properties are mapped onto a finite element mesh, discretization errors are inevitable. In this study, the discretization errors are studied and suggestions for element sizes in relation with spatial correlation lengths are given. © (2014) Trans Tech Publications, Switzerland.

The homogenized stiffness of geomaterials that are highly variable at the micro-scale has long been of interest to geotechnical engineers. The purpose of this study is to investigate the influence of porosity and void size on the homogenized or effective properties of geomaterials. A Random Finite Element Method (RFEM) has been developed enabling the generation of spatially random voids of given porosity and size within a block of geomaterial. Following Monte-Carlo simulations, the mean and standard deviation of the effective property can be estimated leading to a probabilistic interpretation involving deformations. The probabilistic approach represents a rational methodology for guiding engineers in the risk management process. The influence of block size and the Representative Volume Elements (RVE) are discussed, in addition to the influence of anisotropy on the effective Young's modulus. © 2014 Taylor & Francis Group, London.

Analytical probabilistic analysis and Monte Carlo simulation based on elasto-plastic Finite Element Method (FEM) on dry soil mix columns are presented. It is shown that analytical method is over conservative because it ignores the supports from adjacent columns. Probabilistic FEM analysis can provide more accurate predictions, and thus lead to more economic designs. Probabilistic FEM analyses show that the effects of adjacent columns can be destructive when applied load is close to the strength. The reliability of the system of columns is analyzed by setting residual strength to zero. Results show that close spacing has more safety margin than loose spacing. © 2014 Taylor & Francis Group, London.