新疆干旱区气溶胶间接效应区域性分析

利用MODIS气溶胶和云资料以及实测的降水数据,可从宏观角度分析新疆区域气溶胶时空分布特征,研究气溶胶与云和降水之间的相互影响关系.结果表明：近十年来受区域暖-干趋势的转变影响,新疆地区气溶胶光学厚度空间分布呈现显著的区域性和季节性差异;南疆地区气溶胶光学厚度整体高于北疆地区,春、夏高,秋、冬低,整体呈现增加趋势,其中,北疆地区气溶胶光学厚度变化程度相对较为显著;受气候变化和颗粒粒径差异影响,新疆干旱区云光学厚度与气溶胶光学厚度呈负相关变化趋势,相关系数北疆地区高于南疆地区;云水路径受温度、湿度影响较大,对气溶胶光学厚度的变化的敏感程度北疆大于南疆,夏季最高,冬季最低;气溶胶光学厚度与云滴粒子有效半径关系复杂,受水汽影响较大,在云层含水量较低的情况下,云滴粒子有效半径与气溶胶光学厚度呈负相关,说明在干燥地区或季节,气溶胶的增加,抑制云滴粒子的增长;整体来看,新疆干旱区气溶胶的增加抑制了区域降水的形成.     

基于云模型的运营隧道结构健康安全评价

为了实现运营隧道结构健康安全评价,选取19个指标因素作为评价指标,并基于大量工程实践和专家经验,进行云模型连续型影响因素属性离散化,得到运营隧道风险评价因子云模型分级标准。根据风险因子的不确定性,建立运营隧道结构健康安全评价云模型,并通过实例进行验证。结果表明,基于云模型的运营隧道结构健康安全等级具有较好可行性与适用性。同时,通过敏感性分析得到影响运营隧道结构健康安全的敏感性因素,为运营隧道结构健康安全控制提供支持。     

Evaluation and sensitivity of cyanobacteria,Nostoc muscorum and Synechococcus PCC 7942 for heavy metals stress – a step toward biosensor

This study attempted to determine the effects of heavy metals on the photosynthetic blue-green algae for their potential to use as a biosensor. The bioaccumulation of metals and its effects on pigments of Nostoc muscorum and Synechococcus PCC 7942 were assessed. The culture was grown in BG 11 liquid medium supplied with different metals like mercury (Hg), lead (Pb), and cadmium (Cd) and incubated (µM 20 concentrations) for 10 days under optimal conditions. The accumulated amounts of metals were determined by atomic absorption spectroscopy (AAS). The stress effects on photosynthetic pigment chlorophyll a (Chl a) were monitored by laser-induced fluorescence (LIF). Bio-concentration factor (BCF) reached a peak in cells on the 2nd day of incubation followed by a gradual reduction. The highest reduction in the pigment concentrations (Chl a and β carotene) was observed at 20?µM?L^?1 Hg treatment. The results indicate that, cyanobacteria may serve as both potential species to be used as a biosensor and used to clean up heavy metals from contaminated water. These changes were analyzed with the long-term goal of exploiting cyanobacterial cells as biosensors.     

基于反赋权与MBCT-SR多维云模型算法岩爆预测研究

基于岩爆事故的模糊性与随机性特征,为解决在当前岩爆烈度等级预测研究中,通过正向云发生器经验式计算多维云模型特征值进而导致预测结果主观性较强的问题.本文选取应力比Ts=σθ/σt、岩石脆性指数B=σc/σt以及弹性应变储能指数Wet作为评价指标,结合机器学习理论,采用多维逆向MBCT-SR云发生器算法对岩爆等级进行预测,...     

双光谱卫星云图的模糊推理云分类

基于观测事实和分类经验,在对卫星云图上云系形态特征定性分析的基础上,采用模糊推理方法,提取出云类识别的诊断判别因子和模糊推理规则。通过对判别因子的模糊化处理和隶属度函数的调制优化,建立了卫星云图定量化的模糊推理云分类模型。4种常见云系的模糊推理分类试验结果表明,模糊推理方法在定量性、客观性和自动化等方面优于传统卫星云图目视判读方法,在卫星遥感资料的分析处理和天气预报等领域有较好的实用意义。     

应用高效离子交换色谱分析青枯菌的致病力分

应用高效离子交换色谱和激光光散射仪检测器对不同致病力的青枯菌进行分析,建立了一种快速检测青枯菌致病力分化的新方法青枯菌纯培养物经过高效离子交换色谱分离得到3个致病力不同的特征峰,大小依次为峰3组分>峰2组分>峰1组分.对10株青枯菌进行色谱分析,并结合番茄组培苗感染试验检测其致病力,结果发现,强致病力菌株经过色谱分离只在峰3的保留时间位置出现单一特征峰,在9 d内即可引起100%的番茄组培苗发病;若菌株经过色谱分离形成3个特征峰,则峰3所占的面积比越大,该菌株的致病性相对就越强.25株不同致病力青枯菌的验证试验表明了该方法的可行性,番茄组培苗发病率x与峰3面积比y之间呈现出良好的线性关系,回归方程y=0.9581x+5.4984,相关系数r=0.986.通过对青枯菌色谱行为、致病力、细胞表而黏附的EPS Ⅰ含量三者之间相互关系的进一步研究,发现青枯菌的致病力越强,则细胞表面黏附的EPSⅠ越多,峰3所占的面积比就越大.图3表6参15     

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。     

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.     

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。