CFD analysis of the dispersion of toxic materials in road tunnels

The present work is aimed at analyzing the evolution of accidental scenarios deriving from the release of toxic materials inside a tunnel. This scenario, compared to the more frequently investigated cases of fire, followed by smoke dispersion, may involve a large variety of common products characterized by widely differing physical properties; nonetheless it has been analysed in the literature less than expected. The present study compares the dispersion of two common toxic chemicals (chlorine and ammonia), in order to derive some preliminary information about the influence of the physical properties and the release rate. A reference road tunnel geometry is assumed, while the release occurs from ground level, at the centre of one lane and in the middle of the tunnel. Two study cases involving a road tanker, transporting the product as liquefied gas under pressure, were considered: a catastrophic release, from a 220 mm hole, emptying the tanker in a few tens seconds (case A), and a continuous release, from a much smaller hole (15 mm), lasting 5 min (case B). For the sake of simplicity, the release is assumed to be in gaseous phase; the dispersion of the toxic is simulated for the 5 min period following the start of the release using a CFD (Computational Fluid Dynamics) analysis, according to an RANS (Reynolds-Averaged Navier–Stokes) approach with the standard k–ε turbulence model, assuming no ventilation conditions. Structured curvilinear grids with hexaedric cells, refined according to the local concentration gradient, are used. For case A scenarios, especially for the whole release duration, dispersion is mainly governed by the “plug-flow” effect caused by the large volume of toxic entering the tunnel in a rather short time; then, the role of diffusivity and gravity becomes more important. Chlorine, heavier than air and with lower diffusivity than ammonia, progressively accumulates towards the floor; the dispersion of ammonia, which is lighter than air, appears more influenced by diffusivity than by gravity, since a limited stratification is observed. These trends are more evident for case B scenarios, where the toxic flow rates are much lower. It is expected the results will give some useful insight into the dispersion phenomenon within highly confined spaces and maybe also provide some suggestion about ventilation systems design and emergency procedures.     

不规则可燃气云爆炸威力预测方法研究

采用计算流体动力学（CFD ）方法,以实际球罐区甲烷泄漏扩散形成的不规则可燃气云为研究工况,探讨了不规则气云爆炸威力的模拟方法,并对比了实际形状可燃气云、最大直径球可燃气云、重心高度球可燃气云、等体积球可燃气云以及采用 TNT 当量法计算得到的气云爆炸超压值。结果表明,TNT 当量法计算结果过于保守。等体积球、重心高度球、最大直径球与实际形状气云爆炸超压偏差分别为-13．9％、-17．2％、52．3％。采用等体积球法估算不规则可燃气云爆炸威力较为便捷,且精度较高。     

正明矿穿层钻孔有效抽放半径的研究

钻孔有效抽放半径是矿井瓦斯抽放措施中的一个重要参数,直接关系到抽放钻孔的设计、布置以及抽放时间的长短。以气体渗流理论通过fluent6.3建立了钻孔瓦斯抽放流动模型,来模拟在抽放钻孔周围瓦斯的运移规律,确定抽放半径大概范围。结合现场考察,采用SF6示踪法通过对数据的测定及分析,最终得出正明矿4#煤瓦斯抽放钻孔的有效抽放半径与抽放时间之间的关系,为瓦斯抽放钻孔的合理布置提供了科学依据。同时也为其他煤矿抽放半径的确定提供了参考依据。     

基于不同空间插值模型的川西南山地常绿阔叶林叶面积指数估测

叶面积指数（LAI） 是森林经营管理的一个重要参数,亦是众多基于土壤、大气和植被相互作用的森林经营管理动态模型的关键输入变量之一,但目前获得大尺度、高空间分辨率的LAI精确估计仍十分困难。以川西南山地常绿阔叶林为研究对象,基于地面调查的83 个20 m×20 m样地和SPOT5 遥感数据,运用不同的方法,估测了区域森林有效叶面积指数（LAIe）。利用遥感数据作为辅助变量,比较了来自遥感数据的直接辐射关系法（DRR） 和地统计学方法协同克里格（CK）、回归克里格（RK） 的LAIe 空间分布差异。此外,运用反距离权重（IDW）、全局多项式（GPI）、普通克里格（OK）、泛克里格（UK） 等方法也对LAIe进行了估计。结果表明LAIe 与归一化植被指数（NDVI） 回归拟合效果相对不理想（R²=0.679,P<0.001）;由于研究区森林景观不是连续变量,LAIe呈低空间自相关性,各方法间差异不显著,对区域LAIe 估算精度提升不明显;但DRR 和CK、RK 方法能降低统计误差值,且DRR与CK、RK的相关性极高（相关系数分别可达0.91和0.92）。尽管相比于DRR,地统计学方法并没有提高LAIe估计精度,为提高预测的准确性,应探讨更密集的抽样方案和不同的辅助变量。     

液滴撞击超疏水冷表面的反弹/黏附特性对比研究*

为研究液滴撞击超疏水冷表面动力学现象,通过开展去离子水液滴撞击CuO超疏水表面实验,研究表面温度对液滴碰撞后响应方式的影响,分析铺展直径与反弹高度变化规律。结果表明:液滴撞击超疏水冷表面出现反弹与黏附2种响应方式,临界表面温度介于-25 ℃~-20 ℃之间;液滴反弹工况下,表面温度越低,液滴与超疏水冷表面之间接触时间越长,液滴最大反弹高度越小;液滴黏附工况下,随表面温度降低,液滴回缩程度减小,稳定铺展直径增大。研究结果可为表面结冰界面现象与防冰/除冰机理研究提供参考。     

南京北郊秋季高污染大气背景下云凝结核活化特性研究

于2019年10月17日—11月16日在南京北郊地区,采用SMPS-CCNC联用的方式,对8.2~346 nm的气溶胶粒子展开了粒径分辨的CCN活化特征观测.根据PM_2.5浓度范围选取了清洁天和污染天进行分析发现,在高污染大气背景下,由于有机物浓度及占比较高,无机盐浓度较低,故CCN活化率低于清洁天.清洁天SOA组分占比较高,其大气氧化经历更长,氧化态更高,吸湿参数κ也更高;污染天在受到直接排放的影响下,大气氧化经历短,氧化态较低,POA占比相对较高,所以清洁天的吸湿参数κ大于污染天κ(0.28±0.07>0.24±0.09).清洁天的f₄₄平均值为0.14±0.02,污染天的f₄₄平均值为0.12±0.02,进一步表明清洁天的有机气溶胶氧化态更高.因此,高污染大气背景下由于大气中存在很多受排放影响的积聚模态的气溶胶,含有很多低吸湿性物质,降低了CCN的活化能力和吸湿性.     

Treatment of soybean wastewater by a wild strain Rhodobacter sphaeroides and to produce protein under natural conditions

The conventional treatment method of soybean wastewater is expensive and generates waste sludge that requires further handling. Purple nonsulfur bacteria (PNSB) wastewater treatment is a clean technology and can generate single cell protein while degrading pollutants. A wild strain of PNSB, Rhodobacter sphaeroides Z08, was isolated from local soil and was used to treat soybean wastewater. To develop a cost-effective process, the work was performed under natural conditions without artificial light, aeration, nutrients addition, or pH and temperature adjustment. The results showed that the wild strain Rhodobacter sphaeroides Z08 could grow well under natural conditions. The growth curve showed two quick-growth periods and a turning point. The Z08 treatment of soybean wastewater was zero order reaction and COD reduction was 96% after 10 d. The major byproducts of the process were C2-C5 organic acids, predominantly butyric acid. No alcohol was found in the effluent. The initial COD/bacterial-mass ratio (F/M) had a significant effect on soybean wastewater treatment efficiency. When the initial F/M was lower than 10 mg-COD/mg-bacteria, a sufficient amount of time to achieve 90% of COD reduction was only three days. The Z08 biomass yield was 0.28g·g⁻¹, and the bacterial protein content was 52%.     

基于RS-云模型的硫化矿石自燃倾向性综合评价

为实现硫化矿石自燃倾向性的综合评价,应用云理论,选取矿样的氧化质量增加率、自热点和自燃点等定量化指标构建了评价指标体系,运用粗糙集法（Rough Set, RS）计算各评价指标权重,依据分级标准对云模型进行标准化,进而建立硫化矿石自燃倾向性分级的RS-标准云模型。以30组工程实例进行模型检验,并在实际工程中进行应用。结果表明:RS-标准云模型的判别结果与实际结果较吻合,且判别准确率高于贝叶斯(Bayesian, Bayes)方法,表明RS-标准云模型在硫化矿石自燃倾向性综合评价中具有良好的实用性和可靠性,可为矿山的硫化矿石自燃灾害的研究提供一种新思路。     

山西云凝结核时空分布特征观测

选取2011年1~12月山西太原云凝结核(CCN)观测数据,对CCN的季节、月、日变化特征进行了分析,并与国内外同类研究进行了对比.结果发现,冬季CCN数浓度最高,春秋季次之,夏季CCN数浓度最低.CCN数浓度的最高值出现在1月,最低值出现在6月.夏季较多的降水天气对CCN的湿清除作用明显,冬季供暖期间(11~12月及1~3月),CCN数浓度明显增大.CCN数浓度日变化一般呈现两个峰值,分别出现在07:00~11:00和17:00~20:00.利用公式N=CSk拟合了不同季节地面CCN核谱,得到春夏秋冬四季对应的拟合参数C值分别为10983、2454、7614、16421,k值均小于1,为典型的大陆型核谱.通过2013年夏季在山西中部地区开展的CCN飞机观测,研究了CCN数浓度的垂直廓线.CCN数浓度在近地面最大,随高度逐渐降低.在0.3%和0.4%过饱和度下,2000m以下CCN数浓度平均量级均为103cm-3, 3000m以上CCN数浓度平均量级降低至102cm-3.     

基于云模型的隧道塌方风险等级评价

针对造成隧道塌方事故影响因子的复杂性和模糊性,基于云模型理论,选取影响隧道塌方风险的10项因子,建立了4个风险等级的隧道塌方风险评价模型。根据云模型的数字特征计算规则计算各因子隶属于不同风险等级的云模型数字特征,结合正向正态云发生器和各项评价因子的权重,获得云模型的综合确定度,最终由最大综合确定度确定隧道塌方风险等级。工程实例样本应用中,构建的隧道塌方风险评价云模型和模糊综合评价模型的评价结果相符,同时与相应的设计施工方案和施工安全风险评估报告的结果相吻合,表明该模型的可行性与有效性,体现出云模型中定性语言描述和定量数值间不确定转换的优点,且结果便于工程应用。