Efficient conditional modeling for geotechnical uncertainty evaluation

A first‐order Taylor series method including direct derivative coding (DDC) is presented as a computationally efficient method for producing the probability distribution associated with calculated geotechnical performance. The probability distribution is employed in reliability analyses to calculate the probability of failure, valuable information that is not typically associated with deterministic analyses. The probability distribution also is used to identify important input parameters and to direct sampling efforts. Another approach to generate the probability distribution is the Monte Carlo (MC) method, however, Taylor series results generally are calculated in less time than the MC approach. One key to the implementation of the Taylor series approach is efficient approximation of the sensitivities required by the Taylor series calculation. DDC provides the technique to produce an efficient Taylor series algorithm. Directly coding the sensitivity analysis into the engineering model is accomplished by automatic and hand programming of derivatives. ADIFOR 2.0 was employed to automatically add derivatives to an existing engineering analysis model. For this paper a meshing program and 3D FEM for soil deformation is used to demonstrate the DDC approach. Although DDC requires a large up‐front programming effort, it is not site or data specific. Therefore, once the derivative programming has been performed, the numerical model can be applied to a wide variety of problems without additional user intervention. Copyright © 2001 John Wiley & Sons, Ltd.     

Drought assessment and uncertainty analysis for Dapoling basin

In the present study, the Standardized precipitation index (SPI) was employed to analyze the drought status of the Dapoling basin over a period of autumn from September to November, because drought events frequently occur during this period. Three time scales were used, 3-, 6- and 12-month time scale. Daily precipitation data from 13 weather stations covering a period of 31 years from 1980 to 2010 were collected, and the Tyson polygon method was used to calculate the monthly precipitation of the basin. Based on the SPI value, the classification of drought was provided. Besides, considering the fact that the length of sample used to calculate the SPI influences the accuracy on SPI estimation, in turn to lead to the uncertainty of drought classification, the bootstrap technique was employed to analyze the uncertainty of SPI estimation and drought assessment. Results showed that, for September, October or November, drought event mainly occurred in 1985, 1986, 1988, 1990, 1992, 1993, 1994, 1997, 1999, 2001, 2002 and 2007. Especially in 1999 and 2001, severe drought and extreme drought occurred. And the uncertainty analysis results indicated that in term of expected estimation, the two methods with consideration and no-consideration of impact of sample on SPI calculation has no considerable difference, while in term of confidence interval estimation of SPI, there are obviously different between the two methods. This means the impact of the sampling uncertainty on SPI calculation and drought assessment should be noted and not ignored.     

Interpretation of shear strength uncertainty and reliability analyses of slopes

The variance of the friction angle or friction coefficient (tan ?) is often considered in geotechnical reliability analyses, which implies that the variance of the shear strength as defined by a Mohr-Coulomb envelope increases as the normal stress on the shearing surface increases. However, shear strength data sometimes has approximately constant variance, and most simple regression techniques assume constant variance. Four effective stress shear strength data sets are evaluated using both the constant variance (homoscedastic) and constant coefficient of variation (heteroscedastic) interpretations. The impact of the variance interpretation on slope stability is evaluated using infinite slope, homogeneous dam, and zoned dam examples. For relatively shallow infinite slope surfaces, the reliability index for the heteroscedastic interpretation of shear strength variance was about twice the reliability index obtained using the homoscedastic approach. In the dam examples, the difference in the reliability indices resulting from the heteroscedastic and homoscedastic interpretations was about one, indicating a tenfold increase in the probability of failure. The typical assumption of constant coefficient of variation of shear strength may result in unconservative estimates of the reliability of shallow failure surfaces and overly conservative results for deeper failure surfaces.     

Communicating uncertainty: lessons learned and suggestions for climate change assessment

Assessments of climate change face the task of making information about uncertainty accessible and useful to decision-makers. The literature in behavior economics provides many examples of how people make decisions under conditions of uncertainty relying on inappropriate heuristics, leading to inconsistent and counterproductive choices. Modern risk communication practices recommend a number of methods to overcome these hurdles, which have been recommended for the Intergovernmental Panel on Climate Change (IPCC) assessment reports. This paper evaluates the success of the most recent IPCC approach to uncertainty communication, based on a controlled survey of climate change experts. Evaluating the results from the survey, and from a similar survey recently conducted among university students, the paper suggests that the most recent IPCC approach leaves open the possibility for biased and inconsistent responses to the information. The paper concludes by suggesting ways to improve the approach for future IPCC assessment reports. To cite this article: A. Patt, S. Dessai, C. R. Geoscience 337 (2005).     

Bayesian assessment of site‐specific performance of geotechnical design charts with unknown model uncertainty

Soil properties are indispensable input parameters in geotechnical design and analysis. In engineering practice, particularly for projects with relatively small or medium sizes, soil properties are often not measured directly, but estimated from geotechnical design charts using results of some commonly used laboratory or in situ tests. For example, effective friction angle ?′ of soil is frequently estimated using standard penetration test (SPT) N values and design charts relating SPT N values to ?′. Note that directly measured ?′ data are generally not available when (and probably why) the use of design charts is needed. Because design charts are usually developed from past observation data, on either empirical or semi‐theoretical basis, uncertainty is unavoidably involved in the design charts. This situation leads to two important questions in engineering practice: 1 how good or reliable are the soil properties estimated in a specific site when using the design charts? (or how to measure the performance of the design charts in a specific site?); and 2 how to incorporate rationally the model uncertainty when estimating soil properties using the design charts? This paper aims to address these two questions by developing a Bayesian statistical approach. In this paper, the second question is firstly addressed (i.e., soil properties are probabilistically characterized by rationally incorporating the model uncertainty in the design chart). Then, based on the characterization results obtained, an index is proposed to evaluate the site‐specific performance of design charts (i.e., to address the first question). Equations are derived for the proposed approach, and the proposed approach is illustrated using both real and simulated SPT data. Copyright © 2016 John Wiley & Sons, Ltd.     

Application of uncertainty analysis to groundwater pollution modeling

Prediction and evaluation of pollution of the subsurface environment and planning remedial actions at existing sites may be useful for siting and designing new land-based waste treatment or disposal facilities. Most models used to make such predictions assume that the system behaves deterministically. A variety of factors, however, introduce uncertainty into the model predictions. The factors include model and pollution transport parameters and geometric uncertainty. The Monte Carlo technique is applied to evaluate the uncertainty, as illustrated by applying three analytical groundwater pollution transport models. The uncertainty analysis provides estimates of statistical reliability in model outputs of pollution concentration and arrival time. Examples are provided that demonstrate: (a) confidence limits around predicted values of concentration and arrival time can be obtained, (b) the selection of probability distributions for input parameters affects the output variables, and (c) the probability distribution of the output variables can be different from that of the input variables, even when all input parameters have the same probability distribution     

A numerical modeling approach for assessment of progressive caving of strata and performance of hydraulic powered support in longwall workings

A numerical modeling approach is proposed for predicting the progressive caving behaviour of strata and performance of powered roof support in a given geo-mining and strata condition. The study suggests that face convergence slope of 75 mm/m of face advance may be considered as the maximum permissible value for selection of optimal capacity support for safe working in a given strata condition. The study also reveals that en masse caving of strata is responsible for dynamic loading leading to collapse of supports if they are not designed to discharge the fluid at the desired rate.     

Refined modeling and movement characteristics analyses of irregularly shaped particles

Irregularly shaped (IRS) particles widely exist in many engineering and industrial fields. The macro physical and mechanical properties of the particle system are governed by the interaction between the particles in the system. The interaction between IRS particles is more complicated because of their complex geometric shape with extremely irregular and co‐existed concave and convex surfaces. These particles may interlock each other, making the sliding and friction of IRS particles more complex than that of particles with regular shape. In order to study the interaction of IRS particles more efficiently, a refined method of constructing discrete element model based on computed tomography scanning of IRS particles is proposed. Three parameters were introduced to control the accuracy and the number of packing spheres. Subsequently, the inertia tensor of the IRS particle model was optimized. Finally, laboratory and numerical open bottom cylinder tests were carried out to verify the refined modeling method. The influence of particle shape, particle position, and mesoscopic friction coefficient on the interaction of particles was also simulated. It is noteworthy that with the increase of mesoscopic friction coefficient, the fluidity of IRS particle assembly decreases, and intermittent limit equilibrium state may appear. Copyright © 2014 John Wiley & Sons, Ltd.     

基于不确定性的地下水污染风险评价研究进展

地下水污染风险研究在工程决策中具有重要意义。但地下水系统本身具有各种不确定性,基于这些不确定性的地下水污染风险评价也因此具有不确定性,而且贯穿整个地下水污染风险评价过程。所以,进行不确定性分析是对地下水污染风险进行评价时的必要步骤。一般来讲,基于不确定性分析的地下水污染风险评价结果更可靠,因此也更具有实用价值。本文在对不确定性进行分类（随机不确定性和模糊不确定性）的基础上,通过大量文献调研和分析,对目前国内外用于地下水污染风险评价分析的不确定性分析方法（包括随机理论方法、模糊理论方法、随机-模糊耦合方法等）进行了归纳总结,并基于各种方法目前的研究现状,分析了不确定性理论在地下水污染风险评价研究中的发展前景。     

岩溶塌陷不确定性预测评价综述

文章梳理了岩溶塌陷不确定性预测评价的发展历程和最新进展,总结形成了预测评价的一般思路,认为评价时应立足于评价区的地质背景和实际塌陷情况,遵守“从定性到定量”的原则,按照评价区实际情况,依次完成影响因素分析、评价因子选取、评价模型构建3个步骤,并对如何完成好这3个步骤进行了详细阐述;还针对常用的模糊综合评价模型、灰色模糊综合评判模型、信息量模型、证据权模型、人工神经网络模型、支持向量机模型,在特点、核心步骤、优势、弊端4个方面进行了分类对比分析。文章认为目前国内的岩溶塌陷不确定性预测评价还存在较大滞后,仍有许多问题亟待解决。      

Taking the uncertainty in climate-change vulnerability assessment seriously

Climate-change vulnerability assessment has become a frequently employed tool, with the purpose of informing policy-makers attempting to adapt to global change conditions. However, we suggest that there are three reasons to suspect that vulnerability assessment often promises more certainty, and more useful results, than it can deliver. First, the complexity of the system it purports to describe is greater than that described by other types of assessment. Second, it is difficult, if not impossible, to obtain data to test proposed interactions between different vulnerability drivers. Third, the time scale of analysis is too long to be able to make robust projections about future adaptive capacity. We analyze the results from a stakeholder workshop in a European vulnerability assessment, and find evidence to support these arguments. To cite this article: A. Patt et al., C. R. Geoscience 337 (2005).     

Boundary assessment under uncertainty: A case study

Estimating certain attributes within a geological body whose exact boundary is not known presents problems because of the lack of information. Estimation may result in values that are inadmissible from a geological point of view, especially with attributes which necessarily must be zero outside the boundary, such as the thickness of the oil column outside a reservoir. A simple but effective way to define the boundary is to use indicator kriging in two steps, the first for the purpose of extrapolating control points outside the body, the second to obtain a weighting function which expresses the uncertainty attached to estimations obtained in the boundary region.     

Numerical modeling assessment of three-gate structures for capturing contaminated groundwater

This modeling study evaluated the capability of alternative funnel-and-gate structures with three gates for capturing contaminated groundwater in a hypothetical unconfined aquifer. Simulated interceptor structures were linear and 45 m wide, consisting of three gates and two funnels (walls). One gate occupied the center and two gates occupied the ends of the interceptor structures. The structures, positioned perpendicular to regional groundwater flow, traversed the entire thickness of the aquifer. A total of four structures were evaluated (numbers designate widths of end, center, and end gates, respectively, in meters): 3-3-3, 2-5-2, 1-7-1, and 4-1-4. Particle tracking and zonal water budgets identified shapes of capture zones and discharge patterns for each interceptor structure. A mass transport model, accounting for advection and hydrodynamic dispersion, tested the capability of each structure for capturing a contaminant plume. Results suggest that: time-dependent capture zones underestimate the amount of time to capture a contaminant plume, wide center gates facilitate plume capture, and wide end gates facilitate lateral containment of contaminants. Of the structures simulated, the 2-5-2 configuration was relatively efficient at processing and containing the simulated contaminant plume.