点火因素对于重大井喷事故的影响分析

本文主要分析了高含硫气井点火时间的影响.首先分析国内某重大高含硫井喷事故的调查结果[1],其次采用大涡模拟方法对井喷气体扩散进行模拟,并将计算结果与现场实际调查结果进行对比.通过计算不同点火时间在事故中造成的灾难后果,得出点火时间对于灾难的影响.通过计算不同的气象条件下的扩散距离,提出15min的点火时间标准.     

基于涡度相关技术的农田生态系统碳收支评估

以涡度相关技术为主要观测手段,连续观测冬小麦和水稻生态系统主要生长季净生态系统CO₂交换（NEE）的变化规律,评估两种农田生态系统CO₂的源/汇功能.结果表明,整个观测期间,两种作物生态系统CO₂浓度的日变化曲线呈现白天低、晚上高的"一峰一谷"型,冬小麦生态系统变化较为平缓,而水稻生态系统变化则比较剧烈.冬小麦和水稻生态系统白天30 min CO₂通量的平均值分别为-13.4 μmol·m^-2·s^-1和-12.9 μmol·m^-2·s^-1,通量最高值分别出现冬小麦的孕穗期与水稻的开花期.此外,两种作物生长季CO₂通量表现出"U"形曲线的日变化特点,白天以吸收CO₂为主,冬小麦和水稻生态系统分别于12：00和11：30达到吸收峰值;夜间CO₂通量变化较为稳定,表现为呼吸排放CO₂.两种农田生态系统均表现为碳汇,冬小麦与水稻生态系统净碳交换分别为188.2 g·m^-2与233.8 g·m^-2.     

凤阳山森林生态系统碳交换及其物候特征

凤阳山位于浙江省龙泉市南部,为亚热带典型森林生态系统保护区,受海洋性气候和季风的影响,是研究森林生态系统碳预算及其物候特征的理想之地。采用位于浙江凤阳山的涡动相关通量观测系统（EC）观测的2017年（除去9月）CO₂通量数据、气象数据并结合物候模型来分析本地尺度亚热带森林生态系统总初级生产力（GPP）、生态系统呼吸（Re）动态特征、不同时间尺度下的影响因子及其物候特征,结果表明：该生态系统全年扮演着碳汇的角色,净生态系统碳交换量（NEE）（除去9月）为?89 g?m^?2?a^?1（以碳计）,GPP总量为1377.75 g?m^?2?a^?1,Re总量为1288 g?m^?2?a^?1,GPP和Re的日变化和季节变化均呈单峰型,先增加后降低。GPP在不同的物候时期均为倒“U”型的变化趋势,而Re在夜间的生态系统呼吸略高于白天,且在日夜交替时刻会出现陡降现象。整个生态系统在174 d GPP增长率达到峰值0.25 μmol?m^?2?s^?1,达到最大恢复率;202 d的GPP增长率为0 μmol?m^?2?s^?1;228 d的GPP增长率最低,为?0.21 μmol?m^?2?s^?1,达到最大衰退率。不论是日尺度还是月尺度上,GPP和Re变化的主要驱动因素为空气温度,日尺度上Re较GPP对环境因子的变化更加敏感;反之,在月尺度上GPP对环境因子变化的响应比Re更加敏感。总体而言,凤阳山森林生态系统全年表现为碳汇,能够调节当地的二氧化碳浓度;生长季森林生态系统生长旺盛,稳定阶段的GPP与Re达到峰值;在不同的时间跨度上生态系统对环境因子的响应存在差异。     

卡鲁塞尔氧化沟水力学特性的大涡模拟

本文基于大涡模拟中的Smagorinsky-Lilly模型,对Carrousel氧化沟模型进行了水力学特性模拟,并研究了沟内流速和涡量分布规律.速度与压力耦合求解使用了压力隐式算子分裂PISO(Pressure-Implicit with Splitting of Operators)算法,采用VOF(Volume of fluid)方法追踪自由液面.模拟结果表明,回流现象主要出现在上中层混合液中,逆流现象主要出现于上层混合液中;转轮与转刷的推流作用是造成水面变化剧烈的原因;距转轮与转刷较近的区域、转速较快的转轮与转刷区域及直道段转刷下游水面较高一侧中上层区域的涡量较大.根据实验验证,本次模拟结果和实验值吻合度较好,Smagorinsky-Lilly模型可以准确模拟氧化沟水力学特性.     

城市复杂环境下涡度相关通量观测的适用性分析

利用涡度相关技术,于2008—2009年对北京325 m铁塔47 m、140 m和280 m高度处CO2和能量通量进行了观测.研究了涡度相关技术应用于城市环境通量长期观测中的理论问题和方法适用性.结果表明,平面拟合方法受地面建筑物的影响明显,不同的坐标旋转方法所计算CO2通量差异在15%以内,这种差异随着观测高度的增加而减小.稳态检验表明,城市环境下低质量的数据分布没有明显的日变化趋势.CO2通量在各自通量贡献区内明显受到平流输送的影响,47~140 m之间的平流约占140 m日累计CO2通量的33%.白天对流混合,污染物浓度梯度很小,垂直平流不大,水平平流占据了平流输送的绝大多数,夜间水平平流和垂直平流则具有相同量级.     

Simulation of Ekman Boundary Layers by Large Eddy Model with Dynamic Mixed Subfilter Closure

Theoretical analysis of boundary layer turbulence has suggested a feasibility of sufficiently accurate turbulence resolving simulations at relatively coarse meshes. However, large eddy simulation (LES) codes, which employ traditional eddy-viscosity turbulence closures, fail to provide adequate turbulence statistics at coarse meshes especially within a surface layer. Manual tuning of parameters in these turbulence closures may correct low order turbulence statistics but severely harms spectra of turbulence kinetic energy (TKE). For more than decade, engineering LES codes successfully employ dynamic turbulence closures. A dynamic Smagorinsky turbulence closure (DSM) has been already tried in environmental LES. The DSM is able to provide adequate turbulence statistics at coarse meshes but it is not completely consistent with the LES equations. This paper investigates applicability of an advanced dynamic mixed turbulence closure (DMM) to simulations of Ekman boundary layers of high Reynolds number flows. The DMM differs from the DSM by explicit calculation of the Leonard term in the turbulence stress tensor. The Horizontal Array Turbulence Study (HATS) field program has revealed that the Leonard term is indeed an important component of the real turbulence stress tensor. This paper presents validation of a new LES code LESNIC. The study shows that the LES code with the DMM provides rather accurate low order turbulence statistics and the TKE spectra at very coarse meshes. These coarse LES maintain more energetic small scale fluctuations of velocity especially within the surface layer. This is critically important for success of simulations. Accurate representation of higher order turbulence statistics, however, requires essentially better LES resolution. The study also shows that LES of the Ekman boundary layer cannot be directly compared with conventionally neutral atmospheric boundary layers. The depth of the boundary layer is an important scaling parameter for turbulence statistics.     

Diapycnal Mixing in the Thermocline of Lakes: Estimations by Different Methods

In order to evaluate the performance of different methods for estimation of the vertical eddy diffusivity in thermally stratified lakes, two field studies were conducted in Lake Biwa, Japan and Lake Kinneret, Israel. Lake Biwa experienced three typhoons during the campaign while Lake Kinneret experienced high winds in the afternoons. Microstructure profiles were collected by a portable flux profiler (PFP) during calm and disturbed periods. Then, the vertical eddy diffusivity was estimated by three indirect methods. The estimated vertical eddy diffusivities varied more than one order of magnitude, from 4.7× 10⁻⁷ to 7.7× 10⁻⁶ m² s⁻¹. The comparison of results with previous buoyancy flux measurements and scaling arguments showed that the Dillon–Park’s method is not appropriate and Osborn–Cox method performs better than Osborn method in the studied case. Furthermore, the low value of vertical eddy diffusivity within the thermocline suggests that within the thermocline of these lakes, diffusive vertical transport can be neglected.     

造纸废水处理过程的高斯过程回归软测量建模

针对造纸废水处理系统的时变性、非线性和复杂性等特点,本文提出一种基于高斯过程回归的软测量模型.基于平方指数协方差、线性协方差和周期性协方差函数组合构建了7种高斯过程回归模型,分别对出水化学需氧量和出水悬浮固形物浓度进行回归预测.此外,还对比了多元线性回归模型、主成分回归模型、偏最小二乘模型、人工神经网络模型和高斯回归模型的预测效果.对比计算结果表明无论是对输出变量的训练拟合还是预测,高斯过程回归模型的拟合效果均优于非高斯过程回归模型.高斯过程回归模型的预测结果表明：对于出水化学需氧量,线性协方差函数与周期性协方差函数的组合模型可以取得最好的预测结果;对于出水悬浮固形物,平方指数协方差函数与线性协方差函数组合模型可以取得最好的预测结果.     

PM_(2.5)和PM_(2.5~10)资料同化及在南京青奥会期间的应用试验

建立了面向PM_(2.5)和PM10观测资料的三维变分同化系统,并在南京地区青奥会期间进行了同化和预报试验.同化系统的控制变量为PM_(2.5)和PM_(2.5~10)(PM10中扣除PM_(2.5)后剩余部分),利用南京地区2014年8月的WRF-Chem模拟结果,估计了PM_(2.5)和PM_(2.5~10)的背景误差协方差,发现在水平和垂直方向上PM_(2.5)的相关系数随距离的衰减均小于PM_(2.5~10),这可能与PM_(2.5)粒径小、生命史长,在大气中传播地更远有关.利用南京及周边区域的134个监测站PM_(2.5)和PM_(10)逐时观测资料,对青奥会期间(2014年8月16~28日)进行滚动同化和预报试验,并利用模式最内层观测资料进行检验分析,结果表明同化对初始场有显著改进,PM_(2.5)和PM10的相关系数均提高53%以上,均方根误差降低55%以上,平均偏差则降低了90%左右;同化试验对其后的预报场也有明显改进,正效应可以持续到20h以后,模式对PM10的预报效果好于PM_(2.5).     

Ozone Dry Deposition Velocities for Coastal Waters

Air-sea exchange rates for ozone were measured by the eddy correlation technique at a site on the north Norfolk coast in the UK. The average surface resistance to ozone uptake was found to be, r_s(O₃) = 1,000 ± 100 s m^-1. Micrometeorological measurements of trace gas fluxes to ocean surfaces are rare but a review of available measurements suggests that we can constrain sea water surface resistance for ozone to between 1,000 (Regener (1974), and this work) and 1,890 s m^-1 (Lenschow et al., 1982), yielding surface deposition velocities between 0.53 and 1.0 mm s^-1. These values are more than an order of magnitude greater than can be explained by laboratory determined mass accommodation coefficients for ozone to water. The importance of dry deposition with respect to process air-sea exchange models is highlighted. A trend in surface deposition velocity with wind speed was also observed supporting a surface chemical enhancement mechanism of ozone uptake which in turn is enhanced by near surface mixing processes.