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.     

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。     

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.     

蒙特卡洛分析在氯气泄漏事故环境风险评价中的应用研究

气体泄漏事故环境风险系统中存在的不确定性问题影响了定量环境风险评价结果的科学性和实用性.因此,本研究采用蒙特卡洛分析方法对氯气泄漏事故风险系统中的6个风险变量进行分析,并进一步对气体泄漏过程进行仿真模拟,得到模拟结果及其概率分布.同时,将蒙特卡洛分析结果、毒性剂量反应指标和风险受体信息在地理信息系统中进行综合分析,以个...     

基于Monte Carlo模拟法对水源水体中微囊藻毒素的健康风险评估

调查水源水体中微囊藻毒素MCs(MC-RR、MC-LR和MC-YR)的污染情况,结合调查情况应用蒙特卡洛法(Monte Carlo)模拟量化人群通过饮水途径摄入微囊藻毒素的风险.在珠江西航道沿线设置5个采样点,在2016年1~6月期间共采集90份水样,根据国标(GB/T 20466-2006)推荐的HPLC方法检测水体中的微囊藻毒素,运用专业风险评估软件@Risk7.0,构建非参数概率评估模型,对通过饮水途径摄入微囊藻毒素(暴露)风险进行概率评估.对随机采集90份水源水体中微囊藻毒素MCs质量浓度检测值进行分布拟合,并运用Chi-Squared、Anderson-Darling、Kolmogorov-Smirnov这3种统计方法进行拟合度检验,根据3种评估拟合结果,确定最佳拟合分布模型.结果表明,在检测的90个水样品中,MC-RR的检出率最高,达到51.11%,质量浓度范围为0.001 7~0.386 3μg·L~(-1);其次为MC-LR和MC-YR,检出率分别是47.78%和21.11%,质量浓度范围分别是0.028 5~0.279 6μg·L~(-1)和0.003 0~0.136 2μg·L~(-1),水源水体中3种微囊藻毒素以MC-RR为主,最大检出质量浓度为0.386 3μg·L~(-1),MC-YR的含量最低.采用软件@Risk7.0分布拟合结果显示,MC-LR质量浓度最适的拟合分布为Ext Value Min模型(0.113 91,0.098 462),MC-RR质量浓度最适的拟合分布为Logistic(0.058 064,0.053 044).健康风险评估表明,MC-LR对人体健康危害的风险高于MC-RR的风险,儿童比成人更易于受到MCs污染的威胁.MC-LR对儿童健康危害的致癌年风险数值大于美国环保署(USEPA)推荐的最大可接受风险水平1×10-4;MC-LR对成人的致癌暴露年风险数值大于国际辐射防护委员会(ICRP)推荐的最大可接受风险水平5×10-5,表明水源水体中的MCs对人体健康存在潜在的危害,有必要加强饮用水源水体的保护与监控,为有效控制水源地水质污染和更好地保障人民健康奠定基础.     

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.     

某储罐区火灾多米诺效应场景推演

化工园区中危险源众多,一旦发生事故很容易在整个园区内蔓延和发展.针对化工园区内储罐密集,容易引发连锁反应导致事故扩大的特点,利用FDS软件对储罐火灾场景进行数值模拟,根据储罐所受热辐射确定化工园区内储罐火灾最可能的事故发生序列,并引入基于设备失效前时间的机械设备故障概率模型对罐区内单个储罐的火灾风险进行研究,得到储罐区...     

Dams in the Amazon: Belo Monte and Brazil’s Hydroelectric Development of the Xingu River Basin

Hydroelectric dams represent major investments and major sources of environmental and social impacts. Powerful forces surround the decision-making process on public investments in the various options for the generation and conservation of electricity. Brazil’s proposed Belo Monte Dam (formerly Kararaô) and its upstream counterpart, the Altamira Dam (better known by its former name of Babaquara) are at the center of controversies on the decision-making process for major infrastructure projects in Amazonia. The Belo Monte Dam by itself would have a small reservoir area (440 km²) and large installed capacity (11, 181.3 MW), but the Altamira/Babaquara Dam that would regulate the flow of the Xingu River (thereby increasing power generation at Belo Monte) would flood a vast area (6140 km²). The great impact of dams provides a powerful reason for Brazil to reassess its current policies that allocate large amounts of energy in the country’s national grid to subsidized aluminum smelting for export. The case of Belo Monte and the five additional dams planned upstream (including the Altamira/Babaquara Dam) indicate the need for Brazil to reform its environmental assessment and licensing system to include the impacts of multiple interdependent projects.