Risk acceptance criterion for tanker oil spill risk reduction measures

This paper is aimed at investigating whether there is ample support for the view that the acceptance criterion for evaluating measures for prevention of oil spills from tankers should be based on cost-effectiveness considerations. One such criterion can be reflected by the Cost of Averting a Tonne of oil Spilt (CATS) whereas its target value is updated by elaborating the inherent uncertainties of oil spill costs and establishing a value for the criterion’s assurance factor. To this end, a value of $80,000/t is proposed as a sensible CATS criterion and the proposed value for the assurance factor F = 1.5 is supported by the retrieved Protection and Indemnity (P&I) Clubs’ Annual Reports. It is envisaged that this criterion would allow the conversion of direct and indirect costs into a non-market value for the optimal allocation of resources between the various parties investing in shipping. A review of previous cost estimation models on oil spills is presented and a probability distribution (log-normal) is fitted on the available oil spill cost data, where it should be made abundantly clear that the mean value of the distribution is used for deriving the updated CATS criterion value. However, the difference between the initial and the updated CATS criterion in the percentiles of the distribution is small. It is found through the current analysis that results are partly lower than the predicted values from the published estimation models. The costs are also found to depend on the type of accident, which is in agreement with the results of previous studies. Other proposals on acceptance criteria are reviewed and it is asserted that the CATS criterion can be considered as the best candidate. Evidence is provided that the CATS approach is practical and meaningful by including examples of successful applications in actual risk assessments. Finally, it is suggested that the criterion may be refined subject to more readily available cost data and experience gained from future decisions.     

Probabilistic analyses of a strip footing on horizontally stratified sandy deposit using advanced constitutive model

An advanced hypoplastic constitutive model is used in probabilistic analyses of a typical geotechnical problem, strip footing. Spatial variability of soil parameters, rather than state variables, is considered in the study. The model, including horizontal and vertical correlation lengths, was calibrated using a comprehensive set of experimental data on sand from horizontally stratified deposit. Some parameters followed normal, whereas other followed lognormal distributions. Monte-Carlo simulations revealed that the foundation displacement u_y for a given load followed closely the lognormal distribution, even though some model parameters were distributed normally. Correlation length in the vertical direction θ_v was varied in the simulation. The case of infinite correlation length was used for evaluation of different approximate probabilistic methods (first order second moment method and several point estimate methods). In the random field Monte-Carlo analyses with finite θ_v, the vertical correlation length was found to have minor effect on the mean value of u_y, but significant effect on its standard deviation. As expected, it decreased with decreasing θ_v due to spatial averaging of soil properties.     

在同一钻孔中水压致裂法地应力测量与套钻孔应力解除法测量成果的比较

本文叙述了在同一钻孔中水压致裂法地应力测量和套钻孔应力解除法进行对比测量，获得基本一致实测成果的两个实例。     

珠江三角洲地震烈度概率危险性分析

根据我国东南沿海区域地质构造背景、地震活动的时空分布特征，对珠江三角洲地区的地震烈度水平进行概率危险性分析。基于区域内各统计单元及其潜在震源之间地震活动的时空非均匀性，本文给出的结果具有特定的统计意义。     

Probabilistic sensitivity and modeling of two-dimensional transport in porous media

A reliability approach is used to develop a probabilistic model of two-dimensional non-reactive and reactive contaminant transport in porous media. The reliability approach provides two important quantitative results: an estimate of the probability that contaminant concentration is exceeded at some location and time, and measures of the sensitivity of the probabilistic outcome to likely changes in the uncertain variables. The method requires that each uncertain variable be assigned at least a mean and variance; in this work we also incorporate and investigate the influence of marginal probability distributions. Uncertain variables includex andy components of average groundwater flow velocity,x andy components of dispersivity, diffusion coefficient, distribution coefficient, porosity and bulk density. The objective is to examine the relative importance of each uncertain variable, the marginal distribution assigned to each variable, and possible correlation between the variables. Results utilizing a two-dimensional analytical solution indicate that the probabilistic outcome is generally very sensitive to likely changes in the uncertain flow velocity. Uncertainty associated with dispersivity and diffusion coefficient is often not a significant issue with respect to the probabilistic analysis; therefore, dispersivity and diffusion coefficient can often be treated for practical analysis as deterministic constants. The probabilistic outcome is sensitive to the uncertainty of the reaction terms for early times in the flow event. At later times, when source contaminants are released at constant rate throughout the study period, the probabilistic outcome may not be sensitive to changes in the reaction terms. These results, although limited at present by assumptions and conceptual restrictions inherent to the closed-form analytical solution, provide insight into the critical issues to consider in a probabilistic analysis of contaminant transport. Such information concerning the most important uncertain parameters can be used to guide field and laboratory investigations.     

Probabilistic time planning for underground mines

Summary The advantages of probabilistic time planning techniques, compared to deterministic ones, are discussed and an approach to probabilistic planning is presented. The approach includes an analysis of disturbancy factors, and a method of estimating the distribution of project completion time by using Monte Carlo simulation. It is shown how this result may be used to calculate the need for development buffers, which also has been demonstrated on a particular case, the Oscar project, a sublevel stoping operation in the Kiruna mine, Sweden.     

Probabilistic modeling of aerated lagoons: A comparison of methodologies

Two stochastic models are developed to describe the BOD output (i.e. effluent) variation of facultative aerated lagoons in series. One of the models uses the uncertainty analysis (UA) technique and the other is based on the moment equation solution methodology of stochastic differential equations (SDE's). The former considers a second-order approximation of the expectation (SOAE) and a first-order approximation of the variance (FOAV). The SDE model considers that output variability is accounted for by random variations in the rate coefficient. Comparisons are provided. Calibration and verification of the two models are aciieved by using field observations from two different lagoon systems in series. The predictive performances of the two models are compared with each other and with another SDE model, presented in a previous paper, that considers input randomness. The three methods show similar predictive performances and provide good predictions of the mean and standard deviation of the lagoon effluent BOD concentrations and thus are considered as appropriate methodologies.     

Slope reliability analysis accounting for spatial variation

A practical and transparent procedure is described for implementing a generalized limit equilibrium method via cell-object-oriented constrained optimization in the spreadsheet platform. The formulation allows switching among the Spencer, Bishop simplified and wedge methods on the same template by specifying different side-force inclination and different constraints of optimization. Search for the critical circular or non-circular slip surface is possible. The deterministic procedure is extended probabilistically by implementing the first-order reliability method via constrained optimization of the equivalent dispersion ellipsoid in the original space of the random variables. This procedure is illustrated for an embankment on soft ground, and for a clay slope in southern Norway, both involving spatially correlated soil properties. The effects of autocorrelation distance on the results of reliability analysis are studied. Shear strength anisotropy is modelled via user-created simple function codes in the programming environment of the spreadsheet. The meaning of probability of failure is discussed.