地铁区间隧道竖井送风有效风量研究*

为得到地铁区间隧道竖井送风有效风量的无量纲计算模型,通过推导地铁区间隧道竖井送风有效风量的无量纲公式,并采用数值模拟方法明确竖井送风有效风量与火源功率、火源距离、阻塞比和竖井送风量之间的量化关系。结果表明:火源功率、火源距离与竖井送风有效风量之间不存在函数关系;阻塞比对竖井送风有效风量影响显著,随着阻塞比的增大,有效风量逐渐减小,单侧列车停靠时,无量纲有效风量Qe*与阻塞比β呈-1.08次方减小关系,两侧列车停靠时,无量纲有效风量Qe*与阻塞比β呈-0.22次方减小关系;有效风量随竖井送风风量的增大逐渐增大,且有效风量增大比例高于送风风量,单侧列车停靠时,无量纲有效风量与无量纲送风风量呈1.11次方增大关系,两侧列车停靠时,无量纲有效风量与无量纲送风风量呈1.07次方增大关系。     

城市污泥两相厌氧消化沼气产量的技术分析

城市污水处理厂所产生的污泥,数量巨大,成分复杂。如何经济、有效地加以利用已成为目前环境工程中深为关注的课题之一。文章探讨了污泥资源化工作中厌氧消化工艺的温度、时间、污泥成分的最佳工艺备件和沼气产生量,以实现污泥工业化利用。     

城市轨道交通多层地下车站公共区排烟方案设计

随着城市轨道交通线网建设的发展,后建线路深埋将会加大,地下车站也将由原来常规的两层变为多层。车站深埋后对人员疏散和排烟系统提出了新的课题。在分析了地铁排烟系统设计与民用建筑的区别的基础上,研究提出了多层车站排烟系统设计及运行模式,包括站台、站厅及中间层的排烟系统方案及运行模式设计,可为同行提供参考。     

典型三床RTO设备燃爆危险性数值模拟研究*

为研究苯、甲苯、二甲苯混合废气在三床蓄热式废气焚烧炉内部的燃烧过程,基于FLUENT软件建立典型的三床蓄热式废气焚烧炉的物理模型和数值模型,重点分析进气风量和混合可燃气体-空气摩尔占比对其内部压力变化规律的影响,以期可为其安全设计提供借鉴。研究结果表明:燃烧室内的温度变化与燃烧速度变化保持一致,可通过监测RTO燃烧室内的温度来定性评估气体燃烧速度,随着进气风量的增加,混合废气燃烧速度先升高后下降后再升高;从能源损耗和安全生产2个方面综合考虑,得出RTO运行的最佳进气风量为15 000 m3/h到30 000 m3/h,最佳的混合可燃气体-空气摩尔占比为0.15~0.2,这与RTO实际工况相符合,解释RTO装置内废气积聚导致爆炸事故的原因,燃烧过程中压力出现2次峰值超压,实际生产中需在2个时间节点多加防范。     

基于植被指数和神经网络的热带人工林地上蓄积量遥感估测

热带森林作为陆地生态系统的组成成分之一,研究其蓄积量估测对我们了解其在全球碳循环中的地位和作用有很重要的意义.但遥感估测森林生态参数的精度如何,还是个不确定的问题.利用LANDSAT-TM数据,基于森林清查数据和遥感技术,以尾叶桉和加勒比松为例,对中国南方地区人工林蓄积量估测进行了尝试研究.首先,通过测量样方胸径、树高,建立森林蓄积量估算模型.其次,通过对比分析不同植被指数与森林蓄积量之间的关系,选择合适植被指数组合,建立多元回归和神经网络模型.结果表明:单波段TM数据和大多数植被指数与蓄积量相关性并不好.神经网络比回归分析模拟效果好.而多元回归和神经网络模型大大提高预测精度.本研究方法对大面积的森林蓄积量估测具有一定的参考价值.     

The Reynolds transport theorem: Application to ecological compartment modeling and case study of ecosystem energetics

The Reynolds transport theorem (RTT) from mathematics and engineering has a rich history of success in mass transport dynamics and traditional thermodynamics. This paper introduces RTT as a complementary approach to traditional compartmental methods used in ecological modeling and network analysis. A universal system equation for a generic flow quantity is developed into a generic open-system differential expression for conservation of energy. Nonadiabatic systems are defined and incorporated into control volume (CV) and control surface (CS) perspectives of RTT where reductive assumptions in empirical data are then formally introduced, reviewed, and appropriately implemented. Compartment models are abstract, time-dependent systems of simultaneous differential equations describing storage and flow of conservative quantities between interconnected entities (the compartments). As such, they represent a set of flexible and somewhat informal, assumptions, definitions, algebraic manipulations, and graphical depictions subject to influence and selectively parsed expression by the modeler. In comparison, RTT compartment models are more rigorous and formal integro-differential equations and graphics initiated by the RTT universal system equation, forcing an ordered identification of simplifying assumptions, ending with clearly identified depictions of the transfer and transport of conservative substances in physical space and time. They are less abstract in the rigor of their equation development leaving less ambiguity to modeler discretion. They achieve greater consistency with other RTT compartment style models while possibly generating greater conformity with physical reality. Characteristics of the RTT approach are compared with those of a traditional compartment model of energy flow in an intertidal oyster-reef community.     

Impact of bias in predicted height on tree volume estimation: A case-study of intrinsic nonlinearity

Bias originating from intrinsic nonlinearity in nonlinear models is caused by excess curvature in the solution locus of parameter estimates derived from least squares procedures. Bias due to intrinsic nonlinearity varies according to sample size as well as model specification. This paper analyses consequences of fractionising data into smaller sub-samples. Based on measurements of stem diameter and total tree height from the first Danish national forest inventory, it is demonstrated how data splitting at random may cause the intrinsic nonlinear curvature to exceed the critical F-value. Application of a Taylor-series expansion shows that, for all practical purposes, the bias in predictions of individual tree volume (based on stem diameter and tree height) is negligible. To minimize residual variance, intrinsic curvature and, in turn, prediction bias, it is recommended that data be stratified according to site conditions, stand characteristics or other relevant criteria. Finally, the preferred model should exhibit close-to-linear behaviour.     

基于SPOT5影像多辐射校正水平的植被绿量遥感估算

选用南京市SPOT5图像的灰度值(DN)、星上辐射率(SR)、表观反射率(TOA)和地物反射率(PAC)数据,提取了两种植被指数(VI),即归一化植被指数(NDVI)和比值植被指数(RVI),并与地面实测的绿量(LVV)进行相关分析,建立了165个关系模型.结果表明,LVV与VI呈极显著的相关关系,其相关系数多以相对均质植被高于植被总体,基于灰度值高于常用的地物反射率为主.LVV-VI关系模型的R~2均值以多元线性回归模型最高(0.821),指数模型最低(0.536),而1～3次多项式模型均接近0.7.每种植被样方优选出一个模型,即阔叶林LVV-7.802 RVI_(PAC)-2.455(R~2=0.827,RMSE=0.498);针阔叶混交林LVV=-15.421 RVI_(TOA)+26.971 RVI_(DN)-8.261(R~2=0.918,RMSE=0.356);灌木LVV=-342.591 NDVI_(DN)~3-20.553 NDVI_(DN)~2+14.013 NDVI_(DN)+1.509(R~2=0.764,RMSE=0.689);草地LVV=2.934 RVI_(PAC)+2.147 RVI_(TOA)-3.193(R2=0.903,RMSE=0.464);总体植被LVV=1.789RVI_(PAC)-6.814NDVIs+4.258NDVI_(PAC)+12.854 NDVI_(DN)-0.342(R~2=0.810,RMSE=0.638).这些优选模犁的自变量包括了4种辐射校正水平下提取的两种植被指数,显示基于不同辐射校正水平的植被指数在植被LVV遥感反演中具有一定的应用潜力.     

LSH-02G克劳斯尾气加氢催化剂的开发及应用

介绍了LSH-02G克劳斯尾气加氢催化剂的生产工艺及工业应用情况。LSH-02G催化剂具有一定的大孔,可减少CO在催化剂孔道中的停留时间,显著提高催化剂的COS水解率。LSH-02G催化剂工业应用结果表明：装置在80％、100％和110％负荷下运行,各项参数运行正常,急冷水pH稳定在7.8~8.0,急冷塔顶在线氢气含量（φ）维持在1.8%~2.2%,加氢反应器无SO₂穿透。加氢反应器中SO₂加氢转化率均为100％,COS水解率均在92%以上,符合普光天然气净化厂加氢催化剂技术规格书要求（SO₂加氢转化率100％,COS水解率达90%以上）。     

预应力螺栓安装的力学性能计算方法

采用张拉器安装螺栓能使其产生比较一致的预紧力,因而得以广泛使用,推导出张拉量和残余预紧力之间的函数关系式,并给出计算实例,为这种预紧螺栓安装法提供了理论依据。