扰动法在风网解算中的应用研究*

为简化矿井通风复杂风网的解算,提出将扰动法引入到风网解算中,并介绍扰动法的原理、风网解算的基本定律;给出常见的固定风压、固定风量和给定风机性能函数3种风机工况下的扰动方程矩阵表达式及详细的计算过程;对所提风网解算方法进行实例验证。结果表明:扰动法作为固定运算次数的近似方法,在工程实际允许的误差范围内,相比于以牛顿法为代表的迭代法耗时少、不依赖初值,是1种简单实用的风网解算方法。     

驾驶员道路安全感评价虚拟现实技术研究

针对公路线形、交通环境与驾驶员的协调性实时检测的定量化评价方法问题,围绕虚拟现实技术和驾驶员道路安全感认知评价,在对210国道西万三级路典型路段建模生成三维模型的基础上,组织53名驾驶人员在虚拟仿真实验室中对虚拟三级路进行现场认知评价试验.采用模糊统计的方法对评价试验得到的795组数据进行分析处理,建立虚拟三级路安全性认知因素的模糊评价隶属函数.采用计算虚拟和实测道路模糊评价隶属函数的贴近度的方法,与基于实际道路的三级路安全性认知因素的模糊评价隶属函数对比,证明虚拟现实技术在驾驶员道路安全感认知评价研究中的可行性.     

智能物联网在环境在线监控中的应用研究

目前的环境在线监控网络,虽然已经具备了物联网的一些基本特征,并且具备一定环境反应、故障诊断以及应急处理能力,但智能化程度普遍不高,仅停留在了简单的被动式反应,没有实现真正意义上与多智能体技术的结合,所以对于环境监测数据利用还不够充分,深度和广度还有待扩展。本文提出了一种多智能技术与环境在线监控物联网结合的设计方法,以及由此产生的对环境保护工作的提升作用。     

广州城市电网工频电磁环境影响分析及建议

高压输变电工程进入城市中心地带是发展的趋势,而工频电磁环境是居民关注的问题,根据目前广州城市电网建设的现状,对广州城区110 kV、220 kV各类型变电站、多种形式的输电线路产生的工频电磁环境影响进行分析,对比国家现行标准限值,评价广州城市电网工频电磁环境影响的总体情况,认识电网的未来发展趋势,并结合输变电电磁环境影响特点提出相应广州电网建设的意见与建议。     

基于投入产出法的中国虚拟水国际贸易分析

文章引入虚拟水和虚拟水贸易的概念,基于投入产出方法,对中国虚拟水贸易进行研究分析。选取2002年、2005年和2007年相关数据,计算中国17个行业及全国的虚拟水进出口量,分析中国虚拟水进出口情况,指出中国是一个虚拟水净出口国,并且虚拟水净出口量始终处于增长状态,主要出口到美洲、欧洲和亚洲。在中国虚拟水贸易中,对虚拟水净出口贡献较大的行业为服装皮革羽绒及其制品业、纺织业、木材加工及家具制造业和农业,而对虚拟水净进口有贡献的行业为能源行业、金属矿采选业、化学工业、仪器仪表及文化办公用机械制造业,由于净出口行业基本上为耗水量比较大的行业,净进口行业耗水量相对较小,这就导致了中国虚拟水始终处于净出口状态。这些都为行业战略调整提供了一定的依据。     

Method to map human and infrastructure vulnerability using CNN land cover: Case study of floating tank explosion at petrochemical plants of LaemChabang,Thailand

Industrial storage tanks, used to store flammable materials in the petrochemical industry, can induce potential fire and explosion under specific conditions. Therefore, it is necessary to map the population and environment vulnerability, and, to develop procedures for emergency responses in order to reduce potential casualties. In order to achieve this, Convolutional Neural Networks (CNN) are used in this study using 6 classes: floating tank, forest, house, road, wasteland and water. Datasets are built for a total of approximately 1.4 million tiles with a resolution of 0.33m/pixel and their size are optimized in function of the class. The 6 associated CNN models are built and optimized to classify each class. The validation of the models shows that, with the exception of road and wasteland where the precision is only 73% and 89% respectively, the other 4 classes have a value higher than 95%. Post-processing is performed on each prediction before aggregating these results to obtain the land cover. For the floating tank class, a 5 step post-processing is used based on a Density-Based Spatial Clustering of Applications with Noise algorithm (DBCAN) after which blast simulation is applied and effects on people, buildings and trees are obtained through 4 steps. Finally, the petrochemical site of LaemChabang in Thailand is used as study case. Except for the road class that is difficult to detect, land cover is well performed. Human casualties and surface of damaged buildings are finally estimated demonstrating the usefulness of the tool to be used for the emergency planning of industrial disasters.     

Research on the prediction model of hazardous chemical road transportation accidents

In recent years, hazardous chemicals road transport accidents have occurred frequently, causing huge casualties and property losses, and accident risk assessment has become the focus of researchers' research. To predict the risk probability value of hazardous chemical road transport accidents, first, we compiled data on road transportation accidents of hazardous chemicals in China in the past five years. And the nine nodes in the Bayesian network (BN) structure were defined in combination with relevant classification standards. The optimal Bayesian network structure for hazardous chemical road transport accidents was determined based on the K2 algorithm and the causalities between the nodes. Second, the node conditional probabilities were derived by parameter learning of the model using Netica, and the validity of the model was verified using the 5-fold cross-validation method. Last, the Bayesian network model of hazardous chemical road transport accidents is used to analyze accident examples, and the accident chain of “rear-end-leakage” is predicted, and the accident is most likely to be disposed of within 3–9 h. The study shows that the derived accident prediction model for hazardous chemical road transportation can reason reasonably about the evolution of accident scenarios and determine the probability values of accident risks under different parameter conditions.     

基于BP神经网络的义水河水环境质量评价研究

水质质量涉及多个影响因子,因子间大多具有非线性相关性,因此,水质评价是一个具有多因子的非线性系统。人工神经网络具有非线性映射的特点,能够有效地处理非线性相关问题,将其应用于水质评价中能够获得更为准确的信息。文章以溶解氧、高锰酸盐指数、化学需氧量、氨氮、总磷、石油类等6个指标作为评价因子,通过构造BP网络模型对义水河水质进行评价,分析了义水河4个断面的水质状况,并与单因子评价法结果进行了比较分析。     

基于生态服务的城乡景观生态安全格局的构建

以安徽淮北市为例,针对城市发展所造成的城乡生态环境品质降低等问题,期望通过景观生态安全格局的构建,维护区域生态系统健康与稳定。文章基于生态系统服务和景观生态安全格局理论,利用生态服务功能价值评价以及耗费距离模型等分析方法,通过模拟重要生态廊道,与现有廊道进行对比,发现问题并提出优化策略,优化城市景观结构与功能,改善城乡生态系统服务。研究结果表明,淮北城市森林在空间上的衔接性不高;研究区域内众多湿地没有足够的廊道相连,尚未形成良好的湿地生态网络;主城区交通廊道密度较高,但连接度不够,乡村地区交通廊道分布较少且稀疏。因而进行城乡景观生态安全格局的构建十分重要和必要。研究结果可为淮北生态城市建设提供一定的参考,为其他相关研究提供思路和方法上的借鉴。