橡胶拉伸强度的测量不确定度评定解析

本文在介绍测量不确定度的概念、分类和评定方法的基础上,以橡胶拉伸强度的测试为例,对如何评定破坏性试验的测量不确定度进行了有益的尝试,并详细阐述了测量不确定度评定方法的具体应用。     

数控机床电气安全检测技术探讨

依据电气安全通用标准GB 5226.1-2008,并结合数控机床电气结构特点,总结分析出了适合于数控机床的电气安全检测内容和方法。对电气系统检查内容划分了等级,提出了检查的方法和部位;同时也对电气三项试验方法特别是对试验中电路的设置进行了分析,提出了检测的难点、重点和测量不确定度的评定方法。结果表明,该方案的执行能够完整评价数控机床的电气安全性能,有利于促进电气安全标准的执行,可为今后机床电气安全设计、检测提供参考。     

毒气泄漏扩散风险的参数不确定性分析

有毒气体泄漏扩散受很多不确定性因素的影响,为了分析和评估影响毒气泄漏扩散的风速和泄漏速率的变化和不确定性,采用蒙特卡罗模拟和基于Wilks公式容许限的非参数统计法,通过抽样计算得到“95/95准则”下的毒气泄漏扩散地面浓度分布,计算了有毒气体泄漏扩散的不同风险等级的影响范围和风险概率曲线。以氨气泄漏事故为例进行实例分析,结果表明,相对于以确定性参数得出的氨气泄漏扩散浓度分布,引入参数的不确定性评估,更能贴合泄漏现场存在不确定性因素的实际情况,更有利于人员的安全和应急疏散管理。     

基于Monte Carlo与Markov法参数不确定性条件下SIL评估

为了避免由参数不确定性因素导致较大的Markov法SIL评估偏差,且减少计算工作量和复杂性,采用Monte Carlo（MC）仿真方法处理含不确定性参数的Markov模型,并借助Matlab GUI编程开发MC仿真处理参数不确定性条件下Markov法SIL评估可视化仿真计算软件。在理论研究的基础上,为说明该研究方法与计算软件的可行性,以石油天然气工业高完整性压力保护系统（HIPPS）为算例进行SIL评估。结果表明:MC仿真方法可以有效处理Markov法SIL评估中参数不确定性问题;基于Matlab GUI编程设计出的仿真计算软件在一定程度上可以提高计算效率。     

多因素耦合作用下建筑火灾后加固施工过程风险性评估

为降低火灾后建筑结构加固施工过程中事故的发生率,保障加固施工作业过程的 安全,针对我国建筑火灾后加固施工项目的特点,构建了多因素耦合作用下的基于熵权 -未确知测度理论的建筑火灾后加固施工过程风险性评估模型,并将模型应用于五个工 程实例中,取得了良好的效果。研究结果表明,该模型是熵权理论、未确知测度理论的 的有机结合,为定量研究建筑火灾后加固施工过程安全风险,并有效的控制安全风险, 确保施工安全提供了新的思路。     

多应急点多需求点物资调度的灰色多目标规划

为了研究在信息不确定情况下,应急物资需求量和应急时间为区间数的物资调度问题,基于灰色系统理论构建多目标规划模型,结合实例并采用灰色区间数求解方法,计算物资调度方案。结果表明:应急物资调度与区间参数取值无关,相关调度模型与算法对应急初期的实际物资调度具有参考意义;运用灰色区间数描述调度中的不确定因素,有助于提高实际物资调度过程中的准确性。     

基于气象灾害的青岛市域生态风险评价

根据美国环保局（USEPA）的生态风险评价框架和相对风险模型（Relative Risk Model,RRM）,对青岛市域县级行政区的干旱、洪涝、大风和冰雹4种气象灾害进行了生态风险评价。评价结果表明,研究区内干旱生态风险最为严重,洪涝其次;耕地承受的风险最高,城镇和居民地其次;胶州的生态风险最大,青岛市区其次。而且胶州的干旱灾害、市区的大风灾害、平度的冰雹灾害以及胶南的草地成灾比较突出,成为风险分区的依据。最后,不确定性分析表明RRM不确定性的模拟值与计算值接近,验证了RRM在县级尺度上的适用性;敏感性分析说明相对风险值对干旱等级4最为敏感,且对生境分级敏感程度高于风险源分级。此外,利用生态系统生态服务功能的损失率确定暴露系数,降低了确定暴露系数带来的随机性。同时,生境变化需要进一步考虑以明确生态风险在时间尺度上的变化特点。     

Uncertainty,Irreversibility and the Timing Problems of Environmental Policy

Most environmental issues and policy designing are uncertain and irreversible;therefore,the timing of environmental policy implementation becomes especially important.This paper establishes a random dynamic programming model and analyzes the optimal timing problems in environmental policy under uncertain variables.This model results indicate that two variables have a significant impact on the timing of environmental policy implementation and they work in opposite directions:on one hand,the more uncertain the economy is,the higher the cost of policies implementation will be,and consequently the incentive to immediately adopt the policy will be stronger.On the other hand,the higher the uncertainty of the environment is,the stronger the irreversibility of ecological harm caused by pollutants per unit will be.Therefore,the government should implement new environmental policies as early as possible in order to gain more ecological benefits.     

DETERMINING NUTRIENT EXPORT COEFFICIENTS AND SOURCE LOADING UNCERTAINTY USING IN‐STREAM MONITORING DATA1

ABSTRACT: Over a three‐year period, flow and nutrients were monitored at 13 sites in the upper North Bosque River watershed in Texas. Drainage areas above sampling sites differed in percent of dairy waste application fields, forage fields, wood/range, and urban land area. A multiple regression approach was used to develop total phosphorus (TP) and total nitrogen (TN) export coefficients for the major land uses in these heterogeneous drainage areas. The largest export coefficients were associated with dairy waste application fields followed by urban, forage fields, and wood/range. An empirical model was then established to assess nutrient contribution by major sources using developed export coefficients and point source loadings from municipal wastewater treatment. This model was verified by comparison of estimated loadings to measured in‐stream data. Monte Carlo simulation techniques were applied to provide an uncertainty analysis for nutrient loads by source, based on the variance associated with each export coefficient. The largest sources of nutrients contributing to the upper North Bosque River were associated with dairy waste application fields and forage fields, while the greatest relative uncertainty in source contribution was associated with loadings from urban and wood/range land uses.     

TROPICAL EUTROPHIC LAKE MODELING AND PARAMETER DISCRIMINATION1

ABSTRACT: Water quality data collected between 1978 and 1981 in a highly lake in Northern Venezuela, Lake Valencia, were analyzed to detect spatial and temporal trends. Based on the results of the analyses, an appropriate nutrient-algae dynamics model was formulated. Because many parameters, such as the algae concentration were constant over time, and the model is time dependent, the model had to be calibrated with the use of a large and structured trial-and-error calibration process. Through the calibration process, the most sensitive parameters of the model were identified, and are in order of importance: the chlorophyll-to-nitrogen ratio for algae, the algae settling velocity, the phosphorus release rate from the sediments, the chlorophyll-to-phosphorus ratio for algae, and the exchange coefficient in the upper layer of the lake. Model simulations showed that a reduction in the nitrogen load to the lake as well as a reduction in the phosphorus load will decrease the algae population. These model simulations had a high degree of uncertainty associated with them, making additional sampling directed towards the measurement of the sensitive parameters desirable.