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%.     

泉州市不同功能区土壤铅同位素组成及其来源分析

为查明泉州市土壤铅的污染来源,采集了泉州市不同功能区表层(O～20cm)土壤及城市环境污染端元(燃煤尘、汽车尾气尘、污泥)样品.采用ICP-MS测定土壤Pb含量,用热电质谱仪测定各样品的铅同位素组成.分析结果表明,泉州市不同功能区表层土壤已受到一定程度铅污染;泉州市土壤铅同位素208 Pb/(207+206)Pb和206Pb/207 Pb比值变化较大,分别为1.0769～ 1.1486和1.1150～1.2142;泉州市区各端元组分铅同位素组成差别比较大,可以有效示踪和鉴别泉州市区环境铅的污染来源.运用铅同位素示踪技术追踪土壤铅的污染来源结果表明,泉州市区土壤总铅同位素和可溶相铅同位素组成变化较大,土壤中铅来源较为复杂.交通繁忙区土壤铅污染主要来源于汽车尾气排放,农业区土壤铅主要来源于城市污泥与当地土壤背景,商业区土壤铅主要来源于城市污泥与燃煤尘及其煤渣的排放,居民区土壤铅污染主要受城市污泥与汽车尾气排放影响.     

山区和平原连接处SF6试验及扩散规律研究

为更好了解污染物在复杂地形条件下的湍流扩散规律,2010年9月开展了一系列SF6示踪扩散试验,获取了SF6浓度数据,以此实验数据为基础,计算出SF6浓度分布在水平和垂直方向的扩散标准差、地面峰值浓度等参数,并与P-T-C扩散参数进行对比,总结得出了污染物在山区和平原连接处中性、稳定、强稳定等气象条件下湍流扩散规律。     

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...     

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...     

基于不确定性分析的垃圾焚烧烟气中重金属的土壤沉积及生态风险评估

采用CALPUFF模式模拟某城市垃圾焚烧烟气中重金属Pb和Cd的地面大气浓度,并借助土壤浓度模型以Monte Carlo模拟不确定性处理方法估算重金属经沉降在土壤中的累积,最后利用潜在生态危害指数法对重金属在土壤中的长期累积量进行生态风险评估.结果表明,Pb和Cd的大气浓度最大值分别为5.59×10-3μg·m-3和5.57×10-4μg·m-3,土壤浓度增量中值最大分别为2.26 mg·kg-1和0.21 mg·kg-1;高生态风险区集中在焚烧炉附近的下风向地区,生态风险主要由Cd贡献,Pb基本无污染风险;城市最大污染点达较高生态危害水平概率为55.30%,农村最大污染点达中等生态危害水平概率达72.92%.此外,对土壤浓度模型的参数进行敏感性分析表明,城、乡区域模拟结果分别对土壤混合厚度和干沉降速率敏感性最强.     

大气14CO2的时空分异特征及其在化石源CO2示踪中的应用

大气CO₂中放射性碳同位素(¹⁴C)的水平可以反映化石源CO₂的影响程度,这对于评估我国目前化石源CO₂的排放状况和制定节能减排政策具有重要的指导意义。本文在概述大气¹⁴CO₂采样和分析方法的基础上,简要介绍了大气¹⁴CO₂观测的起源和主要的源汇过程,重点论述了大气¹⁴CO₂的时空分异特征及其驱动因素;阐述了化石源CO₂浓度的估算方法及¹⁴CO₂在国内外化石源CO₂示踪中的应用现状,并对大气¹⁴CO₂观测在我国化石源CO₂示踪中的应用前景进行了展望;旨在为我国正确地开展大气¹⁴CO₂的观测研究,深刻地理解特定区域大气¹⁴CO₂的时空分异特征和化石源CO₂的分布状况提供参考。