地震灾害下城市供水网络韧性评估及优化研究

为提升城市供水网络应对地震灾害的能力,基于性能响应函数(PRF)方法,引入基础设施网络均衡理论,设计综合考虑城市供水网络物理状态和输送能力的性能时程响应函数,构建贯穿结构和功能双维度的地震灾害下城市供水网络韧性评估方法;从灾害概率、灾害后果、恢复速度、恢复程度等4个关键因素出发,提出城市供水网络网状扩张、管道延性改造、...     

长江三角洲河网地区典型城镇街尘中多环芳烃的污染特征

街尘是一种重要的环境介质,其携带的污染物在城镇化过程中对河网地区的水环境构成了一定的威胁.为初步探讨长江三角洲河网地区典型街尘中多环芳烃(PAHs)的污染特征,以杭嘉湖平原河网地区饮用水水源河流上游典型小城镇的街尘为研究对象,对工业区、交通干道、旧居区、新居区和商业区5种土地利用类型的15个采样点进行街尘样品采集和粒径分级,测试街尘的密度、有机质含量以及16种U.S.EPA优控PAHs含量等指标.结果表明,粒径为<63、63～125、125～250和250～900μm街尘中总多环芳烃(∑PAHs)的平均含量分别为7261、5835、4660和2909μg·kg-1,粒径越小,PAHs含量越高,其生态风险越大.不同土地利用类型的街尘中PAHs的含量顺序依次为:工业区>交通干道>旧居区>新居区>商业区.街尘中PAHs和有机质含量存在显著正相关关系,且街尘粒径越小,有机质和PAHs的相关性越强.源解析结果表明,街尘中的PAHs多为燃烧源.     

受HDPE膜影响下的垃圾填埋场渗滤液水位探测方法研究

渗滤液水位会影响填埋场堆体稳定并有渗漏污染风险,当渗滤液赋存于HDPE防渗膜上方,堆体和渗滤液堆积电阻率特征的极端分异特性以及边界效应等因素使得最小二乘（LS）等传统物探反演方法无法精确反演实际电阻率分布,从而无法根据电阻率差异特征定位HDPE膜上方渗滤液水位的高度。为准确刻画堆体内部特别是渗滤液-HDPE膜局部电阻率精细分布,对传统高密度电法(ERT)装置进行改进,提出了一种川形探测装置(C-ERT),并采用BP神经网络的电阻率反演模型算法。通过COMSOL理论模型和江西某生活垃圾填埋场采集的现场数据对该方法进行验证,并与LS法比较。结果表明：基于川形装置的BP神经网络能有效识别出HDPE膜上方的渗滤液区域,识别准确率约为83.2%,而LS法并不能识别出渗滤液区域。

     

基于UHBs的输气管道高后果区泄漏燃爆事故分析

为探究输气管道高后果区中人的不安全行为(Unsafe Human Behaviors,UHBs)对输气管道泄漏燃爆事故发生的影响,结合模糊Bow-tie模型和贝叶斯网络对输气管道泄漏燃爆事故进行分析.构建基于T-S模糊故障树的输气管道泄漏燃爆模糊Bow-tie模型,并转化为贝叶斯网络;从人的不安全行为发生的可能性出发,...     

斜井送排式通风隧道的火灾救援通风研究

公路隧道发生火灾开启横通道后,形成通风网络。本文以重庆地区吕家梁隧道为工程依托,进行了斜井前后不同位置发生火灾的通风网络模拟。结果表明,斜井前发生火灾时,受斜井浮力效应、风流密度变化等的影响,主风机的工作压力降低,而体积流量增加;当火灾发生在斜井前隧道时,采用斜井单抽方式可实现全部火灾烟流从竖井中排除,斜井前设射流风机增压调节、斜井后设射流风机增阻调节是一较好方案;对于斜井后发生火灾,采用全射流火灾通风和斜井压入两种通风方案均能满足火灾风流控制要求,虽然后者需要开启轴流风机,通风能耗大,但火灾通风的时效性要好于前者。     

Internal corrosion hazard assessment of oil & gas pipelines using Bayesian belief network model

A substantial amount of oil & gas products are transported and distributed via pipelines, which can stretch for thousands of kilometers. In British Columbia (BC), Canada, alone there are over 40,000 km of pipelines currently being operated. Because of the adverse environmental impact, public outrage and significant financial losses, the integrity of the pipelines is essential. More than 37 pipe failures per year occur in BC causing liquid spills and gas releases, damaging both property and environment. BC oil & gas commission (BCOGS) has indicated metal loss due to internal corrosion as one of the primary causes of these failures. Therefore, it is of a paramount importance to timely identify pipelines subjected to severe internal corrosion in order to improve corrosion mitigation and pipeline maintenance strategies, thus minimizing the likelihood of failure. To accomplish this task, this paper presents a Bayesian belief network (BBN)-based probabilistic internal corrosion hazard assessment approach for oil & gas pipelines. A cause-effect BBN model has been developed by considering various information, such as analytical corrosion models, expert knowledge and published literature. Multiple corrosion models and failure pressure models have been incorporated into a single flexible network to estimate corrosion defects and associated probability of failure (PoF). This paper also explores the influence of fluid composition and operating conditions on the corrosion rate and PoF. To demonstrate the application of the BBN model, a case study of the Northeastern BC oil & gas pipeline infrastructure is presented. Based on the pipeline's mechanical characteristics and operating conditions, spatial and probabilistic distributions of corrosion defect and PoF have been obtained and visualized with the aid of the Geographic Information System (GIS). The developed BBN model can identify vulnerable pipeline sections and rank them accordingly to enhance the informed decision-making process.     

A neuro-fuzzy algorithm for assessment of health,safety, environment and ergonomics in a large petrochemical plant

Process plants such as petrochemical units have been continuously trying to improve Health, Safety, Environment and Ergonomics (HSEE) programs. This study proposes an adaptive network-based fuzzy inference system (ANFIS) for assessment of HSEE programs in a petrochemical plant. The proposed neuro-fuzzy approach is applied to a set of operators in the petrochemical unit to show its applicability and superiority. To achieve the objectives of this study, standard questionnaires with respect to HSEE are completed by operators. The average results for each category of HSEE are used as inputs and accomplishment of HSEE programs is used as output for the algorithm. Moreover, this algorithm is used to rank operators performance with respect to HSEE. Finally, the algorithm identifies efficient operators with respect to HSEE. This is the first study that introduces an intelligence algorithm for assessment and improvement of HSEE program in a petrochemical plant.     

非线性理论在开采沉陷中的应用

简要介绍了近年来把非线性理论应用于矿山开采沉陷领域的一些研究成果,主要包括两大部分：（１）神经网络理论在开采沉陷中的应用;（２）离散单元法在开采沉陷中的应用     

大气环境质量综合评价的B－P网络模型

选取大气环境质量的三级标准作为３个学习样本，以ＳＯ＿２，ＮＯ＿ｘ和ＴＳＰ三种污染物的三级标准浓度限值作为样本的输入特征值，建立了三参数的Ｂ－Ｐ网络大气环境质量综合评价模型，用该模型对３１个测点的大气环境质量进行评价，并与模糊数学和灰色系统法的评价结果比较，表明Ｂ－Ｐ网络用于大气环境质量评价具有优越性。     

我校图书馆自动化建设的实践与思考

本文简述了我校图书馆自动化建设的历史进程，分析了图书馆自动化建设的现状、达到的效果和尚存在的问题，并针对这些问题，提出了相应的改进措施。