实际野外条件下的污染场地土壤和地下水污染限值计算(英文)

加拿大联邦及Alberta省级环境导则为石油烃污染场地提供了多级环境标准及评价方法。其中二级环境标准评价,准许根据污染场地的实际条件计算土壤和地下水污染限值。环境导则限定了计算污染限值的模型和方法。这些模型大都是基于十分简化的野外条件的解析解模型,并根据导则规定的方法使用,以简化应用与审批程序。这些模型的用途和方法与一般通用地下水和土壤污染物运移模型有所不同,在实际运用时这些差别常常被忽略。同时,在复杂野外条件下运用这些模型时,经常遇到确定模型输入参数的困难。介绍了加拿大环境导则中计算污染场地土壤和地下水污染限值以保护地表水环境的模型方法,强调这些模型方法只适用于计算污染限值的特殊目的,不适用于预测污染物运移或套用一般模型拟和调参方法。结合具体计算实例,探索运用Monte Carlo方法评价与表示模型输入参数带来的不确定性。这种方法用参数变化区间(或概率分布)来表示输入参数的变化或不确定性,以求得具有统计意义的保险污染限值。这种方法简单易行,却将二级环境标准评价方法推广到较为复杂(更真实)的野外条件。     

岩土参数的不确定性及其统计方法

通过诠释土性参数不确定性统计工作的重要性,着手分析、对比了各种统计方法的理论基础和优越性,随后基于近年来国内外相关文献的回顾与整理,系统地总结了有关土性参数变异性方面的研究成果,具体包括试验室指标参数、变形参数、强度参数、固结参数以及原位测试中的静力触探测试值、十字板剪切强度和标准贯入击数。结果表明：传统方法和三 法都是基于随机变量理论,无论如何改进也无法克服模型本身所固有的缺陷;基于随机场理论的方法用更加优越的模型建模土层剖面,显示了强大的生命力,随着原位测试手段的日渐成熟,这一方法必将取代传统方法;图形三 法集理论先进性和适用性于一体,是一种值得推荐的方法。参数变异性的总结显示,试验室指标参数变异性普遍较小、固结参数较大、变形和强度参数以及原位测试各指标位于其中,具体结果还对实际工程中参数的选取、优化以及部分重要工程的可靠性分析具有重要的指导意义。     

有限数据条件下边坡可靠度分析的Bootstrap方法

基于Bootstrap抽样技术提出了有限数据条件下边坡可靠度分析方法。简要介绍了传统的边坡可靠度分析方法。采用Bootstrap方法模拟了抗剪强度参数概率分布函数的统计不确定性。以无限边坡为例研究了抗剪强度分布参数和分布类型不确定性对边坡可靠度的影响规律。结果表明：基于有限数据估计的样本均值、样本标准差和AIC值具有较大的变异性,这种变异性进一步导致了抗剪强度参数概率分布函数存在明显的统计不确定性。在考虑抗剪强度参数概率分布函数的统计不确定性时,边坡可靠度指标应为具有一定置信度水平的置信区间,而不是传统可靠度分析中的固定值。边坡可靠度指标的置信区间变化范围随安全系数的增加而增大,同时考虑分布参数和分布类型不确定性计算的可靠度指标具有更大的变异性和更宽的置信区间变化范围。Bootstrap方法为有限数据条件下抗剪强度参数概率分布函数统计不确定性的模拟以及边坡可靠度的评估提供了一条有效的途径。     

Stochastic seismic slope stability assessment using polynomial chaos expansions combined with relevance vector machine

This paper presents probabilistic assessment of seismically-induced slope displacements considering uncertainties of seismic ground motions and soil properties.A stochastic ground motion model representing both the temporal and spectral non-stationarity of earthquake shakings and a three-dimensional rotational failure mechanism are integrated to assess Newmark-type slope displacements.A new probabilistic approach that incorporates machine learning in metamodeling technique is proposed,by combining relevance vector machine with polynomial chaos expansions(RVM-PCE).Compared with other PCE methods,the proposed RVM-PCE is shown to be more effective in estimating failure probabilities.The sensitivity and relative influence of each random input parameter to the slope displacements are discussed.Finally,the fragility curves for slope displacements are established for sitespecific soil conditions and earthquake hazard levels.The results indicate that the slope displacement is more sensitive to the intensities and strong shaking durations of seismic ground motions than the frequency contents,and a critical Arias intensity that leads to the maximum annual failure probabilities can be identified by the proposed approach.     

Uncertainty in dam safety risk analysis

The character and importance of uncertainty in dam safety risk analysis drives how risk assessments are used in practice. The current interpretation of uncertainty is that, in addition to the aleatory risk which arises from presumed uncertainty in the world, it comprises the epistemic aspects of irresolution in a model or forecast, specifically model and parameter uncertainty. This is true in part but it is not all there is to uncertainty in risk analysis. The physics of hazards and of failure may be poorly understood, which goes beyond uncertainty in its conventional sense. There may be alternative scenarios of future conditions, for example non-stationarity in the environment, which cannot easily be forecast. There may also be deep uncertainties of the type associated with climate change. These are situations in which analysts do not know or do not agree on the system characterisation relating actions to consequences or on the probability distributions for key parameters. All of these facets are part of the uncertainty in risk analysis with which we must deal.     

Probabilistical distribution statistical analysis of Tianjin soft soil indices

In the design of soft ground treatment, the soft soil indices are the basic design parameter, and their changes have a strong geographical feature and significant uncertainty. Today, the soft soil indices statistical analysis content is mainly in the correlation and distribution regularity of physico-mechanical indices, which lack systematic study in different regions for different types of soft soils, and the statistical samples are from indoor tests and in-situ tests, without considering the impact of different test methods. In this paper, taking the soft soil in Tianjin as an independent statistical unit body, based on studying the change confines, variability, correlation, probabilistical distribution model of soil indices, some statistical relationship empirical formulas and probabilistical distribution models for physical indices, compression index, strength index were obtained; moreover, the correlation of shear strength results by straight shear test, triaxial test, vane shear test are analyzed; and a method for using random factor to evaluate the uncertainty involved in different test methods of soft soil parameters is proposed. The study results provide a basis and reference for defining the values of geotechnical parameters for soft soil.     

天津软土土性指标概率分布统计分析

软土土性指标作为软基处理设计的基本参数,其变化具有很强的地域特征和显著的不确定性。目前,对软土土性指标统计分析集中在软土物理力学指标的相互关系和分布规律等方面,采用的样本为室内试验和原位测试数据,没有考虑不同试验方法对土性指标不确定性分析的影响。将天津软土作为一个独立的统计单元体,研究了该地区软土物理力学指标的变化范围、变异性、指标间的相互关系和各指标的概率分布模型,得到了天津软土物理指标与压缩指标、强度指标间的统计关系经验公式以及土性指标的概率分布模型;并分析了直剪试验、三轴试验、十字板剪切试验3种不同方法抗剪强度试验结果的相互关系,提出了利用随机因子分析法对试验方法不确定性进行概率评定。研究成果为软土地区工程土工参数的取值提供了依据和参考。     

基于MODFLOW参数不确定性的地下水水流数值模拟方法

考虑到模型不确定性引起的地下水数值模拟不确定性对模拟过程的影响,在简要介绍含水层水文地质参数变异性研究进展和地质统计学的基础上,基于常用的确定性地下水流数值模拟软件MODFLOW开发了MODFLOW-Gslib软件,相较于传统的数值模拟方法,将地质统计学与数值模拟结合的方法能够模拟非均质含水层中的参数变异性问题。将MODFLOW-Gslib软件运用于模拟实例中,选择常见的不确定性因素进行模拟,并对其模拟产生的数据进行统计分析,结果表明,软件转化后的参数符合水文地质参数不确定性的相关特征;与原模拟结果进行对比,该软件能够更加真实地刻画含水层参数变异性特征。     

电感耦合等离子体光谱法测定农业地质调查土壤样品中铈的不确定度评定

采用《测量不确定度评定与表示指南》，以等离子体发射光谱法测定土壤中的稀土元素铈为例，对测定结果进行不确定度评定。分析了不确定度的重要来源，包括溶液制备过程中引入的不确定度、样品称量引入的不确定度、标准物质外标法测量不确定度及仪器重复测定的不确定度。提供了引入不确定度各参数的采集和计算方法，对各不确定度分量进行分析计算，最后合成标准不确定度，通过乘以95％概率下的扩展因子2，获得测量结果的扩展不确定度。     

Probabilistic comparative analysis between design rules of a shallow foundation safety

ABSTRACT

A fact that is generally overlooked in many geotechnical uncertainty analyses is that input data of the model may be correlated. While this correlation may influence the system response, epistemic uncertainties i.e. lack of knowledge of this correlation appears as a risk factor. This paper discusses how a negative correlation between cohesion (c’) and friction angle (Ø’) with their associated uncertainties can influence both the bearing resistance of a shallow strip foundation footing and the estimation of its safety. A probabilistic approach that considers both the negative correlation and the uncertainty is used in this work as a reference. This method is compared to Eurocode 7 variants that do not for the correlation. These variants, resistance and material factoring methods appears to be more or less conservative depending on the negative correlation degree between (c’–Ø), their associated uncertainties and soil configurations. Finally, the proposed probabilistic comparison shows that the material factoring method is more conservative than the resistance one.     

Quantifying sensitivity of local site response models to statistical variations in soil properties

We perform a combined stochastic-deterministic analysis of local site response using two computer codes, an equivalent linear analysis program SHAKE and a fully nonlinear finite element code SPECTRA. Our goal is to compare the relative sensitivity of the two codes to statistical variations in soil properties. For the case studies, we re-analyze two ground motion records in Lotung, Taiwan, and one ground motion record in Gilroy, California, utilizing the recorded ground motions at the site deterministically as input into the two codes while treating the uncertain soil parameters as random variables. We then obtain empirical cumulative distribution functions of the Arias intensity and acceleration spectrum intensity, two measures of cumulative damage, to compare the relative sensitivity of the two codes to variations in model parameters. We show that the two codes exhibit comparable sensitivities to statistical parameter variations, indicating that even in the presence of fluctuations in the soil parameter values it is possible to pursue a fully nonlinear site response analysis with SPECTRA and benefit from its superior accuracy.     

大型浅水湖泊水动力模型不确定性和敏感性分析

选取国内外常用的水动力学模型(EFDC)和典型的浅水湖泊(太湖),采用拉丁超立方取样(LHS),研究湖泊水动力模块中常用的5个重要参数(风拖曳系数、床面粗糙高度、涡粘性系数、紊流扩散系数以及风遮挡系数)对湖体水位和流速的影响。结果表明:针对大型浅水湖泊,湖泊岸线形状和湖底地形、湖泊周围地形、湖泊水面风场对模拟结果产生决定性影响。尤其是在湖湾区和周边地形比较复杂的地区,风场参数对水动力模拟结果不确定性的贡献率最大。在垂向上,表层流速受到参数不确定性的影响最大,底层次之,中层最小。床面粗糙高度对水动力模拟结果不确定性贡献率较风场参数要小,水体涡粘滞系数和扩散系数影响则更小。故在选择大型浅水湖泊水动力模型参数时,要充分考虑湖泊岸线和周围地形,着重率定风场参数以及床面粗糙高度。     

Insight into the seismic response of earth dams with an emphasis on seismic coefficient estimation

This paper presents a numerical investigation of the seismic response of earth dams by employing results from 110 nonlinear two-dimensional (2D) dynamic analyses of four different cross-sections with heights ranging from 20 to 120 m. The analyses were of a parametric nature, considering the effects of seismic excitation characteristics (intensity and frequency content), foundation soil stiffness, and the existence of typical stabilising berms and/or an impounded reservoir. The results of these studies indicated that the predominant period of a dam’s vibration was strongly affected by its height and the input motion characteristics. The results also indicated that the peak acceleration at the dam’s crest was governed by its height, the input motion characteristics, and the stiffness of the foundation soil, but not by the other parameters. These same analyses yielded results on pseudo-static seismic coefficients for a total of 1084 potential sliding masses within the analysed cross-sections, demonstrating that the seismic coefficients decreased as the sliding mass became deeper and bulkier, increased if the mass was located upstream rather than downstream, and were strongly affected by the seismic excitation characteristics and stiffness of the foundation soil. Moreover, these results allowed for a thorough evaluation of existing methodologies for seismic coefficient estimation, quantifying their accuracy and depicting their limitations. This evaluation process also illustrated the fact that there is currently no methodology accounting for all significant problem parameters.     

Uncertainty in spatial average undrained shear strength with a site-specific transformation model

ABSTRACT

Transformation models are used to infer geotechnical properties from indirect measurements. A site-specific transformation model can be calibrated with direct and indirect measurements from a site. When such a model is used, then spatial variability, measurement errors and statistical uncertainty propagate into the uncertainty of the spatial average, which is the variable of interest in most geotechnical analyses. This research shows how all components enter the total uncertainty of a transformation model for undrained shear strength from cone resistance. A method is proposed to estimate the uncertainty in the spatial average undrained shear strength, particularly focusing on the role of averaging of all spatially variable error components. The main finding is that if a considerable share of the measurement and transformation errors is random or spatially variable, the uncertainty estimates can be considerably lower compared to methods proposed earlier, and hence, characteristic values can be considerably higher.     

基于IBUNE方法的水文模型不确定性分析

在贝叶斯理论框架下,根据一种可结合多个水文模型给出模拟或预报结果的IBUNE方法探讨了水文模型的输入、参数以及结构的不确定性问题。将SCEM-UA算法和EM算法嵌入新安江和TOPMODEL水文模型用于参数优化和模型平均,进而将输入与参数的综合不确定性处理后得到的预报量后验分布进行多模型综合,据此对水文模型的不确定性及其对水文模拟结果的影响进行评价。以湖南洣水流域龙家山水文站以上集水区域为例进行了应用研究,结果表明,IBUNE方法能够有效估计水文模型的不确定性,并能给出合理的概率预报区间。     

Probabilistic methodology for the analysis of paleoliquefaction features

Paleoliquefaction features can be used to estimate lower bounds on the magnitude and ground motion associated with the earthquake that caused the liquefaction feature. The engineering back-analysis of paleoliquefaction features is usually conducted using state of the practice liquefaction-triggering analysis methodologies. Recent studies have shown that these methodologies are associated with variable probabilities of liquefaction depending on the soil parameters. This would imply that estimates of magnitude and ground motion intensity obtained from these methodologies would not be consistent for all soil sites. Moreover, these estimates could be unconservative. In this paper, the use of a probabilistic methodology for the back-analysis of paleoliquefaction features is proposed. The proposed methodology permits the incorporation of model and parameter uncertainty into the analysis and results in more robust estimates of past magnitude and a measure of the uncertainty associated with these predictions. Previously published paleoliquefaction data are used to demonstrate the applicability of the proposed method. Magnitude estimates obtained with the proposed method do not differ significantly from those obtained using deterministic methodologies, but the proposed methodology permits a quantification of the uncertainty associated with magnitude estimates.     

考虑计算参数不确定性的边坡稳定分析

岩土体当中存在大量的不确定因素,给边坡的稳定性分析判断带来了困难。在分析了计算参数的不确定性是影响分析可靠性的主要原因的基础上,运用模糊集理论考虑计算参数的不确定性,提出了模糊参数的具体构造方法和边坡稳定的不确定性分析思路。该方法可以根据不同隶属度下的参数截集区间,计算出相应隶属度下的安全系数区间,并可由此得到边坡的可靠性指标和安全系数建议值。通过不同算例研究表明,使用此方法能充分考虑计算参数的不确定性,得到的安全系数更加科学可靠。     

Probabilistic parameter estimation and predictive uncertainty based on field measurements for unsaturated soil slope

A key issue in assessment of rainfall-induced slope failure is a reliable evaluation of pore water pressure distribution and its variations during rainstorm, which in turn requires accurate estimation of soil hydraulic parameters. In this study, the uncertainties of soil hydraulic parameters and their effects on slope stability prediction are evaluated, within the Bayesian framework, using the field measured temporal pore-water pressure data. The probabilistic back analysis and parameter uncertainty estimation is conducted using the Markov Chain Monte Carlo simulation. A case study of a natural terrain site is presented to illustrate the proposed method. The 95% total uncertainty bounds for the calibration period are relatively narrow, indicating an overall good performance of the infiltration model for the calibration period. The posterior uncertainty bounds of slope safety factors are much narrower than the prior ones, implying that the reduction of uncertainty in soil hydraulic parameters significantly reduces the uncertainty of slope stability.     

Effect of soil variability on the bearing capacity of clay and in slope stability problems

Site-specific geotechnical data are always random and variable in space. In the present study, a procedure for quantifying the variability in geotechnical characterization and design parameters is discussed using the site-specific cone tip resistance data (q_c) obtained from static cone penetration test (SCPT). The parameters for the spatial variability modeling of geotechnical parameters i.e. (i) existing trend function in the in situ q_c data; (ii) second moment statistics i.e. analysis of mean, variance, and auto-correlation structure of the soil strength and stiffness parameters; and (iii) inputs from the spatial correlation analysis, are utilized in the numerical modeling procedures using the finite difference numerical code FLAC 5.0. The influence of consideration of spatially variable soil parameters on the reliability-based geotechnical deign is studied for the two cases i.e. (a) bearing capacity analysis of a shallow foundation resting on a clayey soil, and (b) analysis of stability and deformation pattern of a cohesive-frictional soil slope. The study highlights the procedure for conducting a site-specific study using field test data such as SCPT in geotechnical analysis and demonstrates that a few additional computations involving soil variability provide a better insight into the role of variability in designs.