航天器总装事故原因事件重要度分析

为解决传统安全性定量分析方法不能描述航天器总装这一复杂人-机-环系统的失效数据波动性和非严格逻辑关系的问题,结合生产实际,采用问卷调查的方法找出影响总装事故的风险因素,即导致事故的事件发生可能性、输入事件对输出事件的影响程度等。在验证调查数据的有效性之后,应用基于模糊数的模糊因果图(FCD),计算某航天器与支架车连接作业的事故风险可能性。提出原因事件重要度的计算方法。通过计算发现,人员注意力和发动机保护罩作用是导致发动机损伤的关键事件。与模糊事故树(FFT)、贝叶斯网络(BN)重要度计算结果对比表明,模糊重要度计算结果能反映事故发生可能性对原因事件发生可能性值的增减的敏感度。     

二氧化碳灭火系统扑灭风电机组舱内火灾试验研究

为有效遏制全国多地风力发电机组火灾事故的势头,基于灭火系统在风电机组防火设计中的重要性,提出采用二氧化碳灭火系统对风电机舱进行灭火保护的解决方案。在建造国内首台风电机组火灾模拟试验装置的基础上,通过试验研究二氧化碳灭火系统在常温状态和低温状态下对风电机组火灾的灭火能力。结果表明,该灭火系统能够对风力发电机组进行全淹没灭火保护,适用于空间狭小且结构复杂的风电机舱;在低温条件下,其喷放时间和灭火时间虽比常温状态下长,但灭火效能并未降低。     

高速公路安全水平仿真分析

为深入研究高速公路安全系统,用系统动力学(SD)方法分析驾驶员、车辆、道路、应急救援等组成要素以及环境、管理等影响因素之间的关系,建立高速公路安全系统因果关系模型和存量流量模型。用层次分析法(AHP)确定各影响因素的权重。以三福高速公路为例,用Vensim软件模拟高速公路运营期间系统安全的变化情况。结果表明,在该高速公路运营期间,系统安全与车辆安全度呈先上升后下降的趋势、道路安全度呈下降趋势、驾驶员安全度与应急救援能力呈上升趋势。通过与实际数据对比,验证了模型的有效性。     

地铁运营突发事件应急响应模式的马尔科夫链分析

为研究城市轨道交通网络化运营线路的风险传导规律和耦合关系,构建基于随机Petri网的同构马尔科夫链模型。通过模型分析突发事件应急响应模式中线路之间的相互影响,以及各线路启动突发事件应急响应模式对整个系统稳态的影响。结果表明,用该模型可从数学上研究城市轨道交通运营线路之间的传导规律和耦合关系,找出影响整个应急指挥系统效率的关键因素,最终提高地铁应对突发事件的能力。     

An easy method to design gas/vapor relief system with rupture disk

Tank discharge gas/vapor flow problems are frequently encountered in both practice and design. To perform this type of design calculation, the first step is to identify whether the flow is choked or not through a trial-and-error solution of an equation for adiabatic flow with friction from a reservoir through a pipe. Developing a direct method without any trial-and-error to identify a choking condition would be helpful for expediting the flow calculations. This paper presents an easy and quick method to identify the choking of gas flow for an emergency relief system consisting of a rupture disk and vent piping. This greatly simplifies the design calculations. The proposed method for validating the venting adequacy of existing ERS circumvents the iteration calculation and the use of Lapple charts. Three case studies for the design of vent piping for rupture disks support the proposed method.     

台风影响期间石家庄秋季典型空气污染过程研究

利用PM2.5污染监测数据、气象资料和WRF模式,研究了2013年10月2日至10日石家庄地区秋季一次典型的空气污染过程,结果表明,PM2.5质量浓度的上升和下降阶段与相继出现的台风"菲特"和"丹娜丝"输送气流及其背景场有关,本次污染过程同时受台风系统背景场、副热带高压系统和大陆高压系统协同控制.石家庄PM2.5质量浓度演变分为上升、下降、再上升和下降4个阶段,浓度曲线呈现双峰特征,分别对应台风"菲特"加强、减弱、台风"丹娜丝"加强和减弱阶段.污染过程中,PM2.5日均质量浓度最高值是425μg·m-3,导致这一现象的原因是由于台风"菲特"和"丹娜丝"系统外围东南暖湿气流进入石家庄地区,高空1000、1800和2600 m处出现逆温层,下沉气流最大风速是0.2 m·s-1,覆盖并影响石家庄地区,形成稳定的大气条件,利于PM2.5污染物持续积累,造成石家庄地区PM2.5浓度达到峰值并出现重污染事件.     

新形势下我国环境管理与改革取向

在"十三五"我国经济新常态的大逻辑下,环境管理机遇和挑战并存。污染欠账多、污染随着产业转移、政策执行走样、排污收费覆盖面窄、收取率低等,制约环境管理和环保产业的发展。对环境污染的严重性和复杂性、生态环境形势的十分严峻性,以及对污染治理的艰巨性和长期性,应当有一个清醒认识。扭转环境保护与经济发展不协调、不可持续状况,满足城乡居民日益高涨的环境诉求,必须调整环境管理思路,加快改革步伐,扭转环境保护"弱势"格局,厘清环境管理、环境事业和环境市场之间的关系,形成以排污许可证为依据的管理主线、以环境标准为准绳的倒逼机制,以环境司法裁定为常态的终身责任追究制度,创造一个人人守法、企业自觉治理污染和保护环境的社会氛围。     

基于前向神经网络的广义环境系统评价普适模型

为了建立由水环境、空气环境、生态环境、水资源环境、灾害环境、遥感环境、社会经济环境等不同环境系统组成的广义环境系统评价都能普适、通用的神经网络模型,针对BP神经网络因收敛速度慢、易于陷入局部极值而使实用性受限的缺陷,提出以双极性sigmoid函数作为网络隐层节点(神经元)的激活函数,而网络输出为所有隐层节点输出的线性求和的前向神经网络的广义环境系统评价模型.在设置广义环境系统指标参照值和指标值规范变换式,并对指标值进行规范变换的基础上,分别构建了适用于广义环境系统评价的任意2个指标规范值的前向神经网模型(NV-FNN(2)结构)和任意3个指标规范值的前向神经网模型(NV-FNN(3)结构).而对于指标较多的广义环境系统评价,只要将多指标分解为以上2个指标和3个指标的两种简单结构的前向神经网络的广义环境系统评价模型的组合表示即可.理论分析和实例检验结果表明:该模型对任意广义环境系统的规范指标值皆普适、通用,因而使不同环境系统的评价变得简洁、统一.规范变换和优化算法相结合的建模思想和方法对简化广义环境系统评价的多元回归、投影寻踪回归、回归支持向量机和径向基神经网络建模亦有借鉴和启迪作用.     

Microcystis aeruginosa/Pseudomonas pseudoalcaligenes interaction effects on off-flavors in algae/bacteria co-culture system under different temperatures

We conducted an experiment to study the interaction effects of Microcystis aeruginosa and Pseudomonas pseudoalcaligenes on off-flavors in an algae/bacteria co-culture system at three temperatures (24, 28 and 32°C). Gas chromatography–mass spectrometry was applied to measure off-flavor compounds dimethyl sulfide (DMS), dimethyl trisulfide (DMTS), 2-methylisoborneol, geosmin (GEO) and β-cyclocitral. During the lag phase of co-cultured M. aeruginosa (first 15 days), P. pseudoalcaligenes significantly increased the production of DMS, DMTS and β-cyclocitral at all three temperatures. In the exponential phase of co-cultured M. aeruginosa (after 15 days), M. aeruginosa became the main factor on off-flavors in the co-culture system, and β-cyclocitral turned to the highest off-flavor compound. These results also indicated that DMS, DMTS and β-cyclocitral were the main off-flavor compounds in our M. aeruginosa/P. pseudoalcaligenes co-culture system. Univariate analysis was applied to investigate the effects of M. aeruginosa and P. pseudoalcaligenes on the production of off-flavors. The results demonstrated that both M. aeruginosa and P. pseudoalcaligenes could increase the production of DMS and DMTS, while β-cyclocitral was mainly determined by M. aeruginosa. Our results also provide some insights into understanding the relationship between cyanobacteria and heterotrophic bacteria.     

Microcystis aeruginosa/Pseudomonas pseudoalcaligenes interaction effects on off-flavors in algae/bacteria co-culture system under different temperatures

We conducted an experiment to study the interaction effects of Microcystis aeruginosa and Pseudomonas pseudoalcaligenes on off-flavors in an algae/bacteria co-culture system at three temperatures(24, 28 and 32℃). Gas chromatography–mass spectrometry was applied to measure off-flavor compounds dimethyl sulfide(DMS), dimethyl trisulfide(DMTS),2-methylisoborneol, geosmin(GEO) and β-cyclocitral. During the lag phase of co-cultured M. aeruginosa(first 15 days), P. pseudoalcaligenes significantly increased the production of DMS, DMTS and β-cyclocitral at all three temperatures. In the exponential phase of co-cultured M. aeruginosa(after 15 days), M. aeruginosa became the main factor on off-flavors in the co-culture system, and β-cyclocitral turned to the highest off-flavor compound. These results also indicated that DMS, DMTS and β-cyclocitral were the main off-flavor compounds in our M. aeruginosa/P. pseudoalcaligenes co-culture system. Univariate analysis was applied to investigate the effects of M. aeruginosa and P. pseudoalcaligenes on the production of off-flavors. The results demonstrated that both M. aeruginosa and P. pseudoalcaligenes could increase the production of DMS and DMTS, while β-cyclocitral was mainly determined by M. aeruginosa. Our results also provide some insights into understanding the relationship between cyanobacteria and heterotrophic bacteria.