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1.
A stochastic approach for evaluating the risk of vapor cloud explosions is proposed in this work. The proposed methodology aims to incorporate the effect of uncertainty into the risk analysis to produce a better overall view for the risk. Some stochastic variables are used to estimate the probability of vapor cloud explosions: frequency of the release, the probability of not having an immediate ignition, the probability of delayed ignition and the probability of a vapor cloud explosion given a delayed ignition, as well as different possible meteorological conditions. These stochastic variables are represented with probability distribution curves. Different curves for the frequencies of releases from process equipment types (steel process pipes, flanges, manual valves, actuated valves, etc.), different equipment diameters and different leak sizes are also used in this analysis. Monte Carlo simulation is performed to obtain the risk as a probability distribution using the Analytic Solver Platform. Then the risk distribution curve obtained by Monte Carlo simulation is used to estimate the probability of satisfying the risk tolerance criterion. 相似文献
2.
3.
随机模拟在常州运河水质规划中的应用 总被引:1,自引:0,他引:1
以常州运河的水质规划为实例,讨论了确定性水质模型的随机模拟。讨论中引进了主观概率和客观概率的概念,用泰勒级数确定客观概率分布,用可能最大机率法估计主观概率分布,并给出了在实施不同规划方案时的水质概率曲线和水质达标的保证率。计算结果表明,使水质恶化的各种随机因素的作用不容忽视,各种水污染治理措施只能降低水质超标的风险水平。 相似文献
4.
Ilaria Guagliardi Domenico Cicchell Rosanna De Ros Gabriele Buttafuoco 《环境科学学报(英文版)》2015,27(7):179-187
Exposure to lead (Pb) may affect adversely human health. Mapping soil Pb contents is essential to obtain a quantitative estimate of potential risk of Pb contamination. The main aim of this paper was to determine the soil Pb concentrations in the urban and peri-urban area of Cosenza–Rende to map their spatial distribution and assess the probability that soil Pb concentration exceeds a critical threshold that might cause concern for human health. Samples were collected at 149 locations from residual and non-residual topsoil in gardens, parks, flower-beds, and agricultural fields. Fine earth fraction of soil samples was analyzed by X-ray Fluorescence spectrometry. Stochastic images generated by the sequential Gaussian simulation were jointly combined to calculate the probability of exceeding the critical threshold that could be used to delineate the potentially risky areas. Results showed areas in which Pb concentration values were higher to the Italian regulatory values. These polluted areas were quite large and likely, they could create a significant health risk for human beings and vegetation in the near future. The results demonstrated that the proposed approach can be used to study soil contamination to produce geochemical maps, and identify hot-spot areas for soil Pb concentration. 相似文献
5.
In this study, a dual-interval fixed-mix stochastic programming (DFSP) method is developed for planning water resources management systems under uncertainty. DFSP incorporates interval-parameter programming (IPP) and fuzzy vertex analysis (FVA) within a fixed-mix stochastic programming (FSP) framework to address uncertain parameters described as probability distributions and dual intervals. It can also be used for analyzing various policy scenarios that are associated with different levels of economic consequences since penalties are exercised with recourse actions against any infeasibility. A real case for water resources management planning of Zhangweinan River Basin in China is then conducted for demonstrating the applicability of the developed DFSP method. Solutions in association with α-cut levels are generated by solving a set of deterministic submodels, which are useful for generating a range of decision alternatives under compound uncertainties. The results can help to identify desired water-allocation schemes for local sustainable development that the prerequisite water demand can be guaranteed when the available water resource is scarce. 相似文献
6.
In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting
environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming
approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly
incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy
investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover,
it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied
to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations
of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost
and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables
have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized
system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally,
willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a
lower risk will run into a higher system cost. 相似文献
7.
We propose a stochastic dynamic programming framework to model the management of a multi-stand forest under climate risk (strong
wind occurrence). The preferences of the forest-owner are specified by a non-expected utility in order to separately analyze
intertemporal substitution and risk aversion effects. A numerical method is developed to characterize the optimal forest management
policies and the optimal consumption-saving strategy. The stochastic dynamic programming framework is applied to a non-industrial
private forest-owner located in North-East of France. We show that the optimal decisions both depend upon risk and time preferences.
The authors would like to thank participants at the international conference on Economics of Sustainable Forest Management
in Toronto, at the PARIS 1 seminar on Environmental and Natural Resource Economics, at the 2004 Applied Microeconomics Conference
in Lille and at the 13th annual conference of the European Association of Environmental and Resource Economists at Budapest. 相似文献
8.
Standard procedures for evaluating environmental impact involve comparison between before and after conditions or scenarios
or between treatment and control site pairs. In many cases, however, endogenous directional change (natural succession) is
expected to occur at a significant rate over the period of concern, particularly for manmade systems such as impoundments.
Static evaluations do not provide an adequate approach to such problems. A new evaluation frame is proposed. Nominal system
behavior over time is characterized by a stochastic envelope around a nominal trajectory. We show that both the state variance
and the sampling variance can change over time. In this context, environmental regulations can be framed as constraints, targets,
or conformance to ideal trajectories. Statistical tests for determining noncompliance are explored relative to process variance,
sample error, and sample size. Criteria are elucidated for choosing properties to monitor, sample size, and sampling interval. 相似文献
9.
本文根据生产单位事故发生的随机性特点,论证了未来时段中事故次数及其时间分布等各项指标,是能够用多种随机数学模型和灰色系统理论来预测的。用非随机的函数模型预測事故是不合适的。给出了几种事故预測方法,并提出了几种值得研究和试用的方法。 相似文献
10.
An integrated fuzzy-stochastic modeling approach for risk assessment of groundwater contamination 总被引:7,自引:0,他引:7
An integrated fuzzy-stochastic risk assessment (IFSRA) approach was developed in this study to systematically quantify both probabilistic and fuzzy uncertainties associated with site conditions, environmental guidelines, and health impact criteria. The contaminant concentrations in groundwater predicted from a numerical model were associated with probabilistic uncertainties due to the randomness in modeling input parameters, while the consequences of contaminant concentrations violating relevant environmental quality guidelines and health evaluation criteria were linked with fuzzy uncertainties. The contaminant of interest in this study was xylene. The environmental quality guideline was divided into three different strictness categories: "loose", "medium" and "strict". The environmental-guideline-based risk (ER) and health risk (HR) due to xylene ingestion were systematically examined to obtain the general risk levels through a fuzzy rule base. The ER and HR risk levels were divided into five categories of "low", "low-to-medium", "medium", "medium-to-high" and "high", respectively. The general risk levels included six categories ranging from "low" to "very high". The fuzzy membership functions of the related fuzzy events and the fuzzy rule base were established based on a questionnaire survey. Thus the IFSRA integrated fuzzy logic, expert involvement, and stochastic simulation within a general framework. The robustness of the modeling processes was enhanced through the effective reflection of the two types of uncertainties as compared with the conventional risk assessment approaches. The developed IFSRA was applied to a petroleum-contaminated groundwater system in western Canada. Three scenarios with different environmental quality guidelines were analyzed, and reasonable results were obtained. The risk assessment approach developed in this study offers a unique tool for systematically quantifying various uncertainties in contaminated site management, and it also provides more realistic support for remediation-related decisions. 相似文献