Dispersion modeling approach for quantification of methane emission rates from natural gas fugitive leaks detected by infrared imaging technique

Recently, infrared optical imaging has been applied in the oil and gas industry as a method to detect potential leaks in pipelines, components and equipment. The EPA suggested that this impending technique is considered as a smart gas LDAR (leak detection, monitoring and repair) for its rapid recognition of leaks, accuracy and robustness. In addition, compared to the conventional method using Total Vapor Analyzer (TVA) or gas sniffer, it has several other advantages, such as the ability to perform real-time scanning and remote sensing, ability to provide area measurement instead of point measurement, and provide an image of the gas which is not visible to naked eye. However, there is still some limitation in the application of optical imaging techniques; it does not give any measurement of gas emissions rates or concentrations of the leaking gas. Infrared cameras can recognize a target gas and distinguish the gas from its surrounding up to a certain concentration, namely the minimum detectable concentration. The value of the minimum detectable concentration depends on the camera design, environmental conditions and surface characteristics when the measurement is taken. This paper proposed a methodology to predict gas emissions rates from the size of the dispersed gas plume or cloud to the minimum detectable concentration. The gas emissions rate is predicted from the downwind distance and the height of the cloud at the minimum detectable concentration for different meteorological conditions. Gas release and dispersion from leaks in natural gas pipeline systems is simulated, and the results are presented.     

基于MATLAB的火灾探测报警系统寿命分布和可靠度研究

基于不同的系统可靠性寿命分布类型对应的可靠度模型,介绍4种常见的系统可靠性寿命分布模型的适用情况、特征、规律。根据概率论和数理统计相关理论,研究在MATLAB下判断系统寿命分布模型的方法,利用MATLAB函数对模型参数进行估计,构建系统可靠度模型。并以某商场的火灾探测报警系统作为研究对象,收集一段时间的系统故障数据,运用MATLAB数值分析方法,得出火灾探测报警系统的可靠度模型,找出系统可靠度随使用寿命的变化规律。结果表明:计算得到的商场火灾探测报警系统的可靠度随着使用时间变化规律与实际情况基本吻合。     

信息融合技术在火灾探测中的应用研究

为减少火灾探测中的误报警,基于信息融合技术对火灾传感器输出的信息进行处理。充分利用火灾探测系统的在线和离线数据,采用改进的主元分析法(PCA)、粗糙集(RS)理论、支持向量机(SVM)等3种方法的融合与互补,通过对系统的输入数据进行简化,消除原有信息的各分量之间的相关性,降低特征信息维数;实施最优最小约简,特征提取优化;构造自适应核函数,确定最优分类超平面,进行样本训练,获得火灾探测结果。从数据级、特征级、决策级3个层次上实现火灾信息融合。结果表明:该方法减少了融合过程中的信息损失,降低了计算的复杂性,有效地提高了火灾探测系统的可靠性和准确度。     

大空间中庭内热分层环境下环境温度对烟气上升高度的影响

根据稳定线性热分层环境下羽流积分控制方程,分析了温度因素对羽流中性浮力点高度和羽流最大上升高度的影响,在大空间实验室开展了一系列实验,采集环境温度,计算竖向温度梯度,利用摄像机拍摄并记录烟气层上升高度,通过实验数据对理论分析结果进行了验证。     

我国东南地区饮用水源地多种农药的赋存特征及健康风险评估

为阐明我国东南地区典型饮用水源地农药类微污染物的污染特征及生态风险,检测评估了某省7个水库的苯并咪唑类、酰胺类、三唑类和有机磷类等19类共55种常用农药的检出频率、检出浓度以及每种农药对于绿藻、水蚤和鱼类这3种不同营养级生物的风险商.在分析的55种农药中,多菌灵和乙草胺的检出频率为100%,12种农药的检出频率在80%以上.多菌灵的检出浓度最高(77.7 ng·L^-1),其次是乙草胺(51.6 ng·L^-1).风险评估结果显示,大部分农药在目标区域都处于低风险状态.对于3种生物来说,乙草胺是绿藻的风险主导型农药,而多菌灵是鱼类和水蚤的风险主导型农药.     

国外石油天然气行业非金属管道检测技术*

为了解国外石油天然气非金属管道缺陷检测技术发展现状,在调研相关文献报告、企业信息、设备手册基础上,介绍国外先进非金属管道检测技术及其原理、优缺点、具体设备、应用范围和未来发展趋势。研究结果表明:先进的超声相控阵和低能辐射电磁波技术对非金属管道检测难点（如:分层和接头处等特殊位置检测）具有较好的检测能力;非金属管道检测技术正在向自动化、集成化和在线监测方向发展;塑料和纤维增强复合材料大量应用于给排水、船舶、航空航天、汽车和风电叶片行业,非金属管道检测可以借鉴该类领域相关技术。研究结果可为保障石油天然气非金属管道安全运行、拓展行业应用范围、降低管道全生命周期成本提供参考。     

气候旱涝指标方法及其分析

在前人研究的基础上，提出了计算单站旱涝指标和区域旱涝指标的方法。并根据１９５１～１９９６年各月降水资料，对华北地区和长江流域地区的旱涝进行了计算和分析，取得了较好的结果。     

填埋场渗漏检测偶极子法的影响因素分析

偶极子法属于高压直流电法的一种,具有操作简便、费用低廉,可操作性强,并能对防渗层进行百分之百的无损检测,已成为防渗层施工验收采用的主要方式.分析了影响偶极子法灵敏度的主要因素.在回路电压一定的情况下,膜上介质电阻率、膜上介质厚度、偶极子与HDPE膜的距离、偶极子间距等因素皆可对偶极子法的灵敏度产生影响.结果表明:①膜上介质电阻率越大,偶极子检测灵敏度越高.②膜上介质厚度越大,偶极子检测灵敏度越低.③偶极子与HDPE膜的距离越小,偶极子检测灵敏度越高.④偶极子间距越大,检测灵敏度越高.但偶极子间距过大,会有漏检情况发生.⑤对于多漏洞情况,当漏洞之间的距离大于偶极子的间距时,偶极子法可准确分辨出多个漏洞.      

Use of ambiguous detections to improve estimates from species distribution models

As large carnivores recover throughout Europe, their distribution needs to be studied to determine their conservation status and assess the potential for human-carnivore conflicts. However, efficient monitoring of many large carnivore species is challenging due to their rarity, elusive behavior, and large home ranges. Their monitoring can include opportunistic sightings from citizens in addition to designed surveys. Two types of detection errors may occur in such monitoring schemes: false negatives and false positives. False-negative detections can be accounted for in species distribution models (SDMs) that deal with imperfect detection. False-positive detections, due to species misidentification, have rarely been accounted for in SDMs. Generally, researchers use ad hoc data-filtering methods to discard ambiguous observations prior to analysis. These practices may discard valuable ecological information on the distribution of a species. We investigated the costs and benefits of including data types that may include false positives rather than discarding them for SDMs of large carnivores. We used a dynamic occupancy model that simultaneously accounts for false negatives and positives to jointly analyze data that included both unambiguous detections and ambiguous detections. We used simulations to compare the performances of our model with a model fitted on unambiguous data only. We tested the 2 models in 4 scenarios in which parameters that control false-positive detections and true detections varied. We applied our model to data from the monitoring of the Eurasian lynx (Lynx lynx) in the European Alps. The addition of ambiguous detections increased the precision of parameter estimates. For the Eurasian lynx, incorporating ambiguous detections produced more precise estimates of the ecological parameters and revealed additional occupied sites in areas where the species is likely expanding. Overall, we found that ambiguous data should be considered when studying the distribution of large carnivores through the use of dynamic occupancy models that account for misidentification.     

层次化的菌落自动检测方法

本文阐述了一种层次化的菌落自动检测方法。该方法以计算机视觉和模式识别理论为依据,通过从宏观到微观的层次化图像分析方法,逐步实现了菌落区域的粗定位和细分割。在此基础上,实现了菌落区域的自动检测和计数。实验证明,该方法可以快速准确的实现菌落的自动计数,从而改进现有基于人力的"平板检测"菌落计数法。