Real Case Histories Research Articles

An evolutionary approach to predict slope displacement of earth embankments under earthquake ground motions

Accurate slope stability analysis of earth embankments under ground shaking is of great importance for practical use in earthquake geotechnics. This study aims to predict soil slope displacements of earth embankments subjected to earthquake loading using evolutionary algorithms. Comprehensive real case histories of slope displacement of earth embankments under past earthquakes in different areas of the world were gathered and analyzed. A robust model was then developed to predict earthquake induced soil slope displacements using gene expression programming (GEP). Characteristics of earthquake ground motion including earthquake magnitude, earthquake predominant period, maximum earthquake acceleration and also geotechnical specifications of earth embankment including yield acceleration and fundamental period of earth embankment were taken as most influential factors on the slope displacements of earth embankments under earthquakes. Subsequently, performance of developed GEP-based predictive model was assessed using a sensitivity analysis under various effective factors. Finally, the accuracy of the predictive model was evaluated through comparison with the available relationships for estimation of seismic soil slope displacements. The results clearly indicate favorable accuracy of developed GEP-based model to predict slope displacements of earth embankments subjected to earthquake ground motions.

Geotechnical correlation field-informed and data-driven prediction of spatially varying geotechnical properties

Geotechnical measurements are often limited, leading to the use of interpolation techniques for interpreting spatial variations in geotechnical properties from sparse geo-data. Traditional geostatistical methods suffer from significant computational complexity. On the other hand, data-driven approaches often lack integration with geotechnical domain knowledge, potentially oversimplifying or complicating predictions related to the spatial variability of geotechnical properties. This study introduces a novel framework that combines geotechnical knowledge with data-driven methods to model inherent soil spatial variability incorporating Geotechnical Correlation Field (GCF) that reflects domain knowledge. The GCF, influenced by Autocorrelation Function (ACF) types and Scale of Fluctuation (SOF), provides a flexible basis for accurately representing spatially varying geotechnical properties. Using a large synthetic database comprising known ACF types and SOFs, we constructed a series of specialized neural networks. These networks identify random field parameters at different sites based on sparse data, and the estimated parameters can be directly used to calculate GCFs for a given site. The performance of the proposed method is validated using a set of synthetic data and a real case history in New Zealand. The results demonstrate the model can accurately predict random field parameters for irregularly spaced geo-data, even with limited information. Significantly, the GCFs offer improved physical interpretations and enhance the performance of subsurface modeling. The computational complexity of this method is independent of the number of soil cells, making it highly efficient and scalable.

Optimal selection of dictionary atoms for sparse dictionary learning of time-varying monitoring data in two-dimensional geotechnical problems

Geotechnical monitoring data (e.g., settlement monitoring data) are often sparsely measured at limited locations, but the corresponding geotechnical quantities of interest (e.g., ground settlement) usually vary in both temporal and spatial dimensions. The sparsely measured monitoring data can be efficiently leveraged under a sparse dictionary learning (SDL) framework, which represents a spatio-temporally varying quantity (e.g., settlement) by a weighted summation of dictionary atoms. However, selection of dictionary atoms in SDL greatly affects the SDL performance, and under-fitting or over-fitting problems are frequently encountered, particularly when dealing with limited monitoring data. To tackle these problems, a knee point-based method is proposed in this study to properly select dictionary atoms for optimizing the SDL performance. The proposed method not only automatically determines dictionary atom IDs and weights, but also strikes a balance between the under-fitting and over-fitting. The proposed approach is illustrated using a real case history of embankments constructed on soft clay in Australia. The proposed approach significantly improves the prediction of time-varying settlements that also spatially vary over a two-dimensional (2D) space (e.g., a vertical cross-section), particularly at subsequent time steps and spatial locations without monitoring data. Effects of the dictionary atom quantity on settlement predictions are also investigated.

Effect of soil heterogeneity on seismic tunnel lining forces

The crucial role that underground structures play today in transportation and utility networks makes their seismic vulnerability a fundamental topic.The present paper deals with the role of soil heterogeneity in tunnel seismic behaviour. Starting from a real case history regarding a cross-section of the Catania (Italy) underground network, a finite element parametric study was carried out, focusing the attention on the soil discontinuity in terms of the impedance ρ∙VS of each layer crossed by the tunnel, being ρ and VS the soil layer density and shear wave velocity, respectively. Different tunnel depths and seismic inputs were assumed. The numerical dynamic lining internal forces were compared with the analytical solutions proposed by Wang (1993) and Penzien (2000) for homogeneous soil deposits; two new approaches were proposed to use them for heterogeneous soils, highlighting the limitations of the original solutions and the range of applicability of the proposed approaches.

Data-driven subsurface modelling using a Markov random field model

ABSTRACT This paper presents a method of subsurface modelling based on a Markov random field (MRF) model called Potts model. Potts model is an undirected graphical model and has been applied in image processing such as image denoising, restoration and inpainting. The proposed method is simple and requires only a few borehole data on soil types in both training and inference stages. Current implementations of the Potts model require substantial data for training, and they are not suitable for subsurface modelling. The proposed method was demonstrated through numerical examples for 2D and 3D virtual grounds and a real case history. In the numerical examples, the effect of the number of training datasets on the estimation results was also investigated. The proposed method can provide not only the most probable inference of subsurface model but also the spatial distribution of geological uncertainty and is compatible with reliability-based analysis in geotechnical engineering. The spatial distribution of uncertainty is informative in its own right. It directs the engineer to focus on mechanically important zones where the critical failure mechanism passes through if they coincide with the low-accuracy zones.

The case method in the teaching of contemporary Arab political thought: The shutdown of the pan-Arab newspaper al-Ḥayāt as a case study

Backed by the development of postcolonial studies and subaltern studies, the teaching of contemporaryArab political thought as a “border” and interdisciplinary subject must provide students with the theoretical and conceptual tools to respond to the ideological, social, political and intellectual dynamism of contemporary Arab societies in transformation. To apply this methodological approach, this article presents a practical activity based on the case method (CM). As its general objective, the method challenges students to assume learning as a space for cross-cultural reflection through the analysis and argumentation of a real case history: in this instance, the definitive closureof the influential pan-Arab newspaper al-Ḥayāt in March 2020, after almost 75 years of existence. The activity trains students in general and instrumental competences, such as critical text analysis, by positioning them face-to-face with the case under study. After analyzing and evaluating the caseelements provided in the classroom, students can apply any previously acquired knowledge aboutreform, identity, democracy, culture, Arab nationalism, capitalism, etc. Responding to the case in question, students proved to be able to develop alternatives and synthesize their own views. This method also encourages students to analyze their self-perception of this process.

Analysis of floating and end-bearing pile foundations affected by deep-excavations

This paper investigates the response of pile foundations to deep-excavations. An elastoplastic two-stage model is used to study the response of pile groups (with free- or rigidly capped-heads) and of piled structures (grade beams or bearing walls), considering piles embedded in either uniform or layered ground. The model is validated using results of analytical solutions, as well as data from centrifuge tests and from real case histories. Then, a parametric study investigates excavation-induced displacements and internal forces of piles, and deformations of the superstructure. Soil–pile transfer mechanisms and pile–superstructure interactions are analysed for various foundations and ground conditions, with results showing that settlements and slopes between piles are larger for floating piles than for end-bearing piles. Results show that rigidly capped piles and semi-flexible piled structures cause bending moments at the foundation heads that increase with the excavation-induced slope between piles, whereas the risk for tensile failure of piles is low. Also, results indicate that the superstructure stiffness is more relevant to decrease the slope and deflection ratio of foundations when composed of floating piles, compared to end-bearing piles. Finally, modelling end-bearing piles embedded in a stiff base using hinged connections to such stiff base may not be appropriate.

Tagging and tracking oil-gas mixtures in multiphase pipelines

Pipeline transportation of multiphase products, such as gas and oil mixtures, exhibits complex and varying flow regimes: as a result, analytical approaches or conventional methods cannot accurately describe the composition or the propagation characteristics of the fluid mix inside the transportation system itself. We address such an issue by presenting a methodology, driven by the data and applied to a real case history, where basic pressure transients are used to tag and track, along a pipeline, different batches of a multiphase medium. Several statistical indicators, computed from the pressure data and on different window lengths, are employed to train a machine learning model, which learns to distinguish the characteristic behavior of two different oil-gas slugs: in practice, each different combination of fluid phases (in terms of gas/oil ratio in a given batch of product) and each different sequence of slugs (in terms of gas/oil ratio variability between successive batches) behaves like a coded tag linked to the flowing fluid. The key innovation consists in the possibility of tracking such multiphase slugs along the flowline and at each monitoring station: this allows one to determine in real-time the fluid composition entering/exiting the line, its position, and its movement along the pipe. As such, we obtain also a virtual metering system, able to provide estimates of the flow rate and phases ratio. Moreover, by having several recording stations accurately synchronized, one can also leverage real-time transmission and multichannel processing of the data, enabling the opportunity for online monitoring applications. The results on the test cases and the accuracy scores obtained for the metrics considered validate the tagging and tracking approach.

Simulation of runout behavior of submarine debris flows over regional natural terrain considering material softening

Evaluation of regional submarine debris flows is critical for quantitative assessment of vulnerable areas and reasonable design of geohazard mitigation measures. In this article, an efficient numerical model for kinematics of regional submarine debris flows is developed. The proposed model can simulate the runout process and morphological evolution of submarine debris flows over natural 3D terrain by solving 1D depth-averaged governing equations in a geographic information system (GIS). A strength softening equation is introduced to capture the degradation of sliding material strength during the runout process. The model is validated by a flume test, two slump tests, and a real case history of submarine debris flow (St Niklausen slide). Applications to Shenhu area, South China Sea, are presented to demonstrate the ability of the proposed model over complex natural terrain and the importance of considering material softening. Results show that the proposed model is capable of simulating the whole debris flow process and tracking the propagation of the sliding material. Simulation of submarine debris flow without material softening will underestimate the disaster consequences. In addition, the influences of the ambient fluid and the yield strength of the sliding material on its runout behavior are also discussed.

Damage and contour quality in rock excavations for quarrying and tunnelling: assessment for properties and solutions for stability

Excavations in rock masses determine the creation of temporary or final exposed surfaces. Features of these surfaces are depending on both geostructural pattern of the rock mass and adopted excavation method: among the others, roughness, quality of the contour and induced damage inside the rock left in place. These aspects are important as they are requirements expected during the excavation and construction procedures, such those involving dam sidewalls, quarry benches, tunnel profile, slope scaling.This methodological paper describes a list of the possible cases, with a particular emphasis on quarrying and tunneling. By following current modes for profile surveying, the damages are reported, in order to obtain suitable indices for induced damage. Finally the proper techniques for excavation are commented on the basis of real case histories of tunnels and quarries in order to reach the primary objectives of damage reduction and stability/productivity goals.

Development and Application of an Intelligent Evaluation and Control Platform for Tunnel Smooth Blasting

Many tunnels around the world are still being constructed by drilling and blasting because these methods have an unmatched degree of flexibility relative to machine excavations using tunnel boring machines. At present, a large gap exists between evaluation theory and the control application of tunnel smooth blasting (TSB) quality. In this study, a handheld mobile platform that is based on the Android system and is written in the Java language is proposed to evaluate and control the performance of TSB. The function of this handheld mobile platform mainly includes data input, data modification, data deletion, weight setting for smooth blasting evaluation, smooth blasting quality assessment, and smooth blasting quality control. Using the proposed mobile platform, end users can evaluate and control TSB quality after each blast. The proposed handheld mobile platform is also applied to the real case history of line 6 in Guangzhou, China.

CLINICAL TRIAGE OF RADIATION CASUALTIES-THE HEMATOLOGICAL MODULE OF THE BUNDESWEHR INSTITUTE OF RADIOBIOLOGY.

Novel treatment regimens for therapy of the acute radiation syndrome (ARS) were developed over the last years. Their application relies on an early and high-throughput diagnosis. Based on the database SEARCH a new scientific triage tool (called H-module) was developed for early prediction of the later developing ARS. Based on peripheral blood cell counts measured within the first three days after a radiation exposure a prediction of the H-ARS severity (as well as therapeutic recommendations) can be performed with this tool. The H-module was tested within two table top exercises. Contributors were either radiation experts or radiobiology students and the required patient data were generated from real case histories. The H-module proved to be an easy to train and easy to use precise and promising new tool to assist and guide the treating physician in a large-scale radiation scenario. An introduction into this new tool and other diagnostic tools will be provided in the context of a NATO-teaching class in October/November 2019 in Paris.

Successful Teaching of Radiobiology Students in the Medical Management of Acute Radiation Effects From Real Case Histories Using Clinical Signs and Symptoms and Taking Advantage of Recently Developed Software Tools.

In 2015, the Bundeswehr Institute of Radiobiology organized a North Atlantic Treaty Organization exercise to examine the significance of clinical signs and symptoms for the prediction of late-occurring acute radiation syndrome. Cases were generated using either the Medical Treatment Protocols for Radiation Accident Victims (METREPOL, n = 167) system or using real-case descriptions extracted from a database system for evaluation and archiving of radiation accidents based on case histories (SEARCH, n = 24). The cases ranged from unexposed [response category 0 (RC 0, n = 89)] to mild (RC 1, n = 45), moderate (RC 2, n = 19), severe (RC 3, n = 20), and lethal (RC 4, n = 18) acute radiation syndrome. During the previous exercise, expert teams successfully predicted hematological acute radiation syndrome severity, determined whether hospitalization was required, and gave treatment recommendations, taking advantage of different software tools developed by the North Atlantic Treaty Organization teams. The authors provided the same data set to radiobiology students who were introduced to the medical management of acute effects after radiation exposure and the software tools during a class lasting 15 h. Corresponding to the previous results, difficulties in the discrimination between RC 0/RC 1 and RC 3/RC 4, as well as a systematic underestimation of RC 1 and RC 2, were observed. Nevertheless, after merging reported response categories into clinically relevant groups (RC 0-1, RC 2-3, and RC 3-4), it was found that the majority of cases (95.2% ± 2.2 standard deviations) were correctly identified and that 94.7% (±2.6 standard deviations) developing acute radiation syndrome and z96.4% (±1.6 standard deviations) requiring hospitalization were identified correctly. Two out of three student teams also provided a dose estimate. These results are comparable to the best-performing team of the 2015 North Atlantic Treaty Organization exercise (response category: 92.5%; acute radiation syndrome: 95.8%; hospitalization: 96.3%).

Interpretation of pile lateral response from deflection measurement data: A compressive sampling-based method

The performance of piles under lateral loading, i.e., the lateral response of piles, may be evaluated by in situ lateral loading tests. Inclinometers are frequently installed along the pile depth to measure the pile lateral deflection during the loading tests. Other pile responses, such as the bending moment and shear force, may be further obtained through high-order differentiation of the deflection measurement data with respect to depth. As inclinometers measure the pile deflection at a number of pre-specified depths, the deflection measurement data are discrete. Performing high-order derivatives on discrete deflection data is tricky and sometimes provides misleading results, particularly when the pile response is nonlinear. This paper proposes an innovative approach for interpreting the lateral response of piles from discrete deflection measurement data. The proposed method is based on a new sampling theorem in digital signal processing called compressive sensing/sampling (CS). The method is illustrated using a real case history in the USA, and the results show that the proposed method can provide reasonable interpretations of the lateral response of piles. A sensitivity study is also carried out to systematically explore the performance of the proposed method.

Numerical modelling of slope–vegetation–atmosphere interaction: an overview

The behaviour of natural and artificial slopes is controlled by their thermo-hydro-mechanical conditions and by soil–vegetation–atmosphere interaction. Porewater pressure changes within a slope related to variable meteorological settings have been shown to be able to induce soil erosion, shrinkage–swelling and cracking, thus leading to an overall decrease of the available soil strength with depth and, ultimately, to a progressive slope collapse. In terms of numerical modelling, the stability analysis of partially saturated slopes is a complex problem and a wide range of approaches from simple limit equilibrium solutions to advanced numerical analyses have been proposed in the literature. The more advanced approaches, although more rigorous, require input data such as the soil water retention curve and the hydraulic conductivity function, which are difficult to obtain in some cases. The quantification of the effects of future climate scenarios represents an additional challenge in forecasting slope–atmosphere interaction processes. This paper presents a review of real and ideal case histories regarding the numerical analysis of natural and artificial slopes subjected to different types of climatic perturbations. The limits and benefits of the different numerical approaches adopted are discussed and some general modelling recommendations are addressed.

Runout of submarine landslide simulated with material point method

Most of the present knowledge on submarine landslides relies upon back-analysis of post-failure deposits identified using geophysical techniques. In this paper, the runout of slides on rigid bases is explored using the material point method (MPM) with focus on the geotechnical aspects of the morphologies. In MPM, the sliding material and bases are discretised into a number of Lagrangian particles, and a background Eulerian mesh is employed to update the state of the particles. The morphologies of the slide can be reproduced by tracking the Lagrangian particles in the dynamic processes. A real case history of a submarine slide is back-analyzed with the MPM and also a depth-averaged method. Runout of the slides from steep slopes to moderate bases are reproduced. Then different combinations of soil and basal parameters are assumed to trigger runout mechanisms of elongation, block sliding and spreading. The runout distances predicted by the MPM match well with those from large deformation finite element analysis for the elongation and block sliding patterns. Horst and grabens are shaped in a spreading pattern. However, the current MPM simulations for materials with high sensitivities are relatively mesh sensitive.

Runout of Submarine Landslide Simulated with Material Point Method

Most of the present knowledge on submarine landslides relies upon back-analysis of post-failure deposits identified using geophysical techniques. In this paper, the runout of slides on rigid bases is explored using the material point method with focus on the geotechnical aspects of the morphologies. In MPM, the sliding material and bases are discretised into a number of Lagrangian particles, and a background Eulerian mesh is employed to update the state of the particles. The morphologies of the slide can be reproduced by tracking the Lagrangian particles in the dynamic processes. A real case history of a submarine slide is back-analyzed with the MPM and also a depth-averaged method. Runout of the slides from steep slopes to moderate bases are reproduced. Then different combinations of soil and basal parameters are assumed to trigger runout mechanisms of elongation, block sliding and spreading. The runout distances predicted by the MPM match well with those from large deformation finite element analysis for the elongation and block sliding patterns. Horst and grabens are shaped in a spreading pattern. However, the current MPM simulations for materials with high sensitivities are relatively mesh sensitive.

3D Skull Reconstruction with Selective Laser Sintering for Endoscopic Cranial Base Surgical Simulation and Training

Introduction: The training of surgeons is not dissimilar to that of pilots. Each profession has a responsibility to achieve a minimum safety standard and technical proficiency. This in most instances may only be achieved by many hours of experience, as well as practicing in mock or simulated emergency scenarios. Each quality airline provides its pilots with regular simulator events to train for particular emergency scenarios as well as simulator certification requirements. Surgeons have no such training requirement. Since there is no formal assessment of surgical skills for board and state licensure, surgeons are expected to self-regulate their own training. As advancements in medicine are made, surgeons are expected to know more and to be able to perform more types of procedures. In the USA, increasing restrictions on residency work hours are adding a new hurdle to surgical training. Restrictions on resident work hours means that many residents will not have optimum operating experience once they graduate from residency. For this reason, just as pilots spend hundreds of hours training in simulation suites, surgeons may also augment and complement their technical skills with simulation based training. In fields such as neurosurgery or otolaryngology, the endoscope is used in minimally invasive surgery. Junior residents may not have adequate exposure to this as their time practicing with endoscopes is limited by the dynamics of their residency program and case-load. By being able to train these residents in a realistic scenario, patient safety and quality of care can be improved. Data has shown that surgeons trained with simulation systems have shown improved parameters in the operating room such as technical profiency with the endoscope, as well as faster mean operating time. Materials and Methods: Current 3D printed training models on the market are prohibitively expensive and do not have tactile properties which accurately mimic real bone. Current methods also have difficulty in replicating the bony architecture of the skull base. We have developed a method of producing an anatomically accurate and realistic 3D printed skull with selective later sintering (SLS), using a material made from a polymer of polylactic acid (PLA) and limestone (Fig. 1). Our institute is developing the models around a suite of training features: various pathologies will be included, paired with real patient case histories and imaging for surgeons to review before they embark to practice on the skull model. Discussion: Methods for training surgeons in endoscopic surgery include virtual simulators, cadaveric training, and skull model based training. Virtual simulators are limited by the lack of tactile feedback, and cadaveric training is limited by ethical and cost issues. Training with skull based models has been shown to have comparative tactile feedback to the cadaveric model and actual surgery. Conclusion: Our institution has developed a method of manufacturing accurate 3D printed skull based models as part of an endoscopic surgery training suite.

TrueDepth prestack depth migration: an essential tool for mitigating drilling risk

The utilisation of non-seismic data in the structural imaging arena has been shifting its importance from an afterthought to an essentially a priori ingredient. The necessity to image complex subsurface structures that are at the right depth, at the correct geographical loca¬tion and with the correct geometry and topology has become paramount for a successful business model that combines drilling, geosteering, completion, fracking and re-fracking, as well as production and EOR efforts. This article can be thought of as an update and continu¬ation on our 2013 First Break publication (Stein et al., 2013) that introduced the concept of TrueDepth. Here we will describe the new developments in the technology suite, primarily spawned by our experiences processing many surveys around the world that pointed to some shortcomings in the original ideas and implementation. Particularly important has been the development of a new workflow that increases the efficiency and robustness of the techniques. The new workflow incorporates several new pieces of technology making the resulting images more accu¬rate. The new technologies include a global delta anisotropy tool, a tomography capable of inverting for velocity and anisotropy, and 3D QC visualisation techniques. We will finish the article by demonstrating the value of the new workflow and technologies by applying them to a real case history. It has become increasingly obvious that an accurate depth prediction, as well as a very detailed description of the geomet¬ric and topological nature of the reservoirs, is paramount for a cost-effective exploration and production effort. It has always been accepted that the incorporation of non-seismic data into the imaging effort is essential to the outcome. The shift in this mindset that has occurred in the last few years is that such data is not only valuable as a calibration or QC tool, but that it can, and we would argue it must, be part of the input data and combined with the seismic in our algorithms to produce exceptionally accurate results. This philosophy is at the core of the TrueDepth methodology; the use of a priori information in the imaging process. For a detailed description of the geophysical and math¬ematical basis of TrueDepth as well as some earlier examples, we will refer the reader to our earlier publications (Stein et al., 2013; Stein, 2014; Hellman et al., 2015; Baptiste et al., 2015).

Calibration of model uncertainties in base heave stability for wide excavations in clay

In this study, the statistical properties for the model factor [the ratio of actual factor of safety (FS) to the calculated FS] of three popular base heave calculation methods are calibrated based on real case histories with wide excavation. The statistical properties of concern include the mean value and coefficient of variation (COV) of the model factor. It is found that the mean values of the model factors for the modified Terzaghi׳s and Bjerrum-Eide׳s methods are close to 1, whereas that for the slip circle method is significantly greater than 1. The COVs associated with the modified Terzaghi׳s and Bjerrum-Eide׳s methods are relatively low, while that associated with the slip circle method is relatively high. Based on the calibration results, reliability-based design charts are provided. It is concluded that the required factor of safety (FS) depends on two factors: (a) the target reliability index and (b) the COV of the calculated FS. For the case where this COV=10%, the required FS in codes for the modified Terzaghi׳s and slip circle methods (FS=1.5 and 1.2, respectively) seems reasonable. In contrast, the required FS for Bjerrum-Eide׳s method (FS=1.2) seems insufficient.