A stochastic approach for risk analysis in vapor cloud explosion

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.     

Spatial modelling of the probability of obtaining a detectable concentration of ammonia in Moreton Bay, Australia

Ammonia is an important water quality variable, which in excess, can be detrimental to waterways and their ecosystems. In the Ecosystem Health Monitoring Program in South-east Queensland ammonia is monitored monthly, however, often more than 50% of the ammonia observations in Moreton Bay are below detection limit, making it difficult to draw useful inferences. In this paper a clipped Gaussian random field is used to spatially model and map the probability of detectable concentration of ammonia. The methodology is applied to the Moreton Bay samples collected in February 2005. The results suggest that for this month the oceanic impacted areas have higher probability of detectable ammonia concentration than the areas closer to the main sources of anthropogenic inputs.     

爆炸事故过程分析中不确定性问题处理方法

针对事故过程分析中的不确定性问题,指出了不确定问题在危险分析中的重要性及处理该问题的复杂性和难点,列出了几种基于非线性数学方法处理不确定问题的基本方法,如微分法、MonteCarlo模拟、Fourier方法、响应表面法等,并对之进行了比较.建议在处理事故过程的不确定性时采用Monte Carlo模拟.     

新疆D矿田金矿资源定量评价

本文在建立D矿田找矿信息层次模型基础上,确定矿田统计单元划分和地质变量提取的赋值原则,将该矿田划分出466个统计单元,提取25个地质变量并进行二态赋值,而后应用数量化理论Ⅲ。特征分析法及勃尔法等方法,建立了矿田金矿资源定量评价模型,定位预测了45个勘探靶区。     

海洋疏浚Mont Carlo数值计算

利用Mont Carlo方法模拟海洋疏浚过程中悬浮泥沙的扩散.结合洋浦近岸海域疏浚工程,计算了悬沙输运轨迹及浓度分布,计算结果较为合理.该模型在近海工程环境影响评价中具有应用价值.     

Dynamic Bayesian networks for reliability evaluation of subsea wellhead connector during service life based on Monte Carlo method

The subsea wellhead connector is a critical connection component between subsea Christmas tree and subsea wellhead for preventing the leakage of oil and gas in the subsea production system. Excited by cyclical loadings due to environmental forces and the other support forces, the subsea wellhead connector is prone to the failure, which could lead to the loss of subsea tree or wellhead integrity and even catastrophic accidents. With the Monte Carlo simulation method, this paper presents a reliability analysis approach based on dynamic Bayesian Networks, aiming to assess the failure probability of the subsea wellhead connector during service life. Take the driving ring component of the subsea wellhead connector as an example to demonstrate the reasonability of the proposed model. The generation data is processed by the transform between the numerical value and the state variable. Based on the stress-strength interference theory, the structure reliability of the driving ring with 96.26% is achieved by the proposed model with the consideration the aging of the material strength and the most influential factors are figured out. Meanwhile, the corresponding control measures are proposed effectively reduce the failure risk of the subsea wellhead connector during service life.     

复杂气井套管力学分析与可靠度评价

为建立考虑地层和套管参数随机性的套管可靠度评价理论方法，以便得到复杂井况下套管传统设计安全系数与可靠指标之间的关系，提出了非均匀地应力和内压联合作用下，沿套管最大外挤力方向管壁任意位置发生屈服失效时外壁等效均匀外挤力的计算方法；建立了套管抗挤和抗内压三轴强度计算公式以及有效内压计算方法；根据套管载荷和强度影响因素统计参数以及评价过程中参数测试标准值，利用蒙特卡洛法（MC）建立了完整的套管可靠度计算和评价方法；通过实例对传统安全系数与可靠指标的对应关系进行了研究。研究结果表明:指定条件下，套管安全系数与可靠指标之间存在对应关系；利用建立的方法编制计算程序可以为传统设计法中安全系数代表的安全程度进行量化；可靠度评价方法能够为安全系数的选取提供指导。     

Evaluating the impact of uncertainty and variability on the value chain optimization of a forest biomass power plant using Monte Carlo Simulation

Mathematical programming models have been used to optimize the design and management of forest bioenergy supply chains. A deterministic mathematical model is beneficial for making optimum decisions; however, its applicability to real-world problems may be limited because it does not capture all the complexities, including uncertainties in the parameters, in the supply chain. In this paper, a combination of Monte Carlo Simulation and optimization model is used to evaluate the impact of uncertainty in biomass quality, availability and cost, and electricity prices on the supply chain of a forest biomass power plant. The optimization model is a deterministic mixed integer non-linear model with monthly time steps over a 1-year planning horizon. Variability in biomass quality, i.e. moisture content (MC) and higher heating value (HHV), based on the historical data of a real case study is studied in detail and fitted probability distributions are used in the model, while for electricity prices different scenarios are considered. The results show that the impact of variability in the MC on profit is higher than that of uncertainty in HHV. It is observed that the annual profit ranges between $13.3 million and $17.9 million in the presence of all possible uncertainties while its average is $15.5 million. Uncertainty in biomass availability and cost and electricity price results in the risks of having annual profit of less than $14 million and low monthly storage levels.     

基于蒙特卡罗模拟的土壤环境健康风险评价:以PAHs为例

为获得更为合理的健康风险评价结果,并辨识对健康风险影响最大的因素,基于蒙特卡罗随机模拟,运用概率风险评价模型,定量评估了中国上海某居民区土壤中16种PAHs对居民的健康风险水平,并对各参数进行敏感性分析.结果表明,土壤中PAHs造成的健康风险服从对数正态分布,总的致癌风险为3.43×10~(-5)±2.63×10~(-5),最小值为8.10×10~(-7),最大值为2.39×10~(-4),超过10-6的概率为95%,超过10~(-5)的概率为75%,超过10~(-4)的概率小于5%;总的危害商为4.74×10~(-2)±3.42×10~(-2),不超过1,风险较小;在7种具有致癌效应的PAHs中,苯并(a)芘、二苯并(a,h)蒽和苯并(a)蒽是总致癌风险的主要贡献物质,贡献率分别占60.41%、26.84%和6.56%;3种暴露途径中,经口途径是造成致癌风险的主要途径,贡献率为73.22%;对于总致癌风险,人体暴露参数中每日土壤摄入量、暴露周期、暴露皮肤面积敏感度较大,分别为58.35%、50.21%和20.51%;体重具有负敏感性,敏感度为-11.66%.     

基于非线性响应函数和蒙特卡洛模拟的滇池流域污染负荷削减情景分析

为定量了解滇池外海水质对流域污染负荷削减率的响应变化程度,并评估相关决策的潜在风险,在长期的水质模拟结果基础之上,本文使用内嵌非线性响应函数的蒙特卡罗模拟方法,在2个不确定性水平下（5%和10%的变异范围）分析滇池外海为达到3个水质目标情景（Ⅲ类、Ⅳ类和Ⅴ类）的污染负荷削减及其不确定性.模型结果表明,在2种不确定性水平...