基于人工神经网络的街道峡谷NO_x浓度的数值模型研究

通过对反向传播人工神经网络的算法和网络结构的研究,发现拟牛顿算法训练速度较快,能够较好地接近误差目标值,同时建立了包括输入层、隐含层、输出层的人工神经网络三层拓扑结构。通过对街道峡谷人工神经网络的训练,模拟计算了街道峡谷NOx浓度分布值。结果显示,训练误差和测试误差比为1.11,训练样本的模拟值与实测值的相关系数为0.93,测试样本的模拟值与实测值的相关系数为0.87,模拟值与实测值的相关系数均高于显著水平为α=0.05与α=0.01所对应检验性表的相关系数临界值。该模型能够用于街道峡谷污染物浓度的模拟计算,具有较好的泛化能力。     

街道峡谷机动车尾气污染扩散模拟与影响因子分析研究

为预测和分析街道峡谷污染物浓度,研究了街道峡谷污染物浓度影响因子.利用重庆市交通干线街道峡谷两侧NOx浓度的监测数据,验证了街道峡谷机动车尾气污染扩散模型--OSPM模型.风速转换系数修正后的OSPM模型的模拟值与实测值的R达0.862 58;风场因子验证了风速转换系数修正后的OSPM模型能较好地模拟重庆市街道峡谷的污染物浓度,一定程度上能满足环境空气质量评价要求.同时,通过分析OSPM模型的影响因子,提出了控制街道峡谷机动车尾气污染状况的建议.     

道路路障对街道峡谷内污染物扩散的影响

采用数值模拟,研究不同风向角α(α=0°、45°、90°)及道路屏障位置(中间单路障和两侧双路障)对街道峡谷内机动车尾气污染物扩散的影响。数值模拟采用标准κ-ε湍流模型且Sc_t选择0.3时,计算结果与风洞实验结果较好吻合。结果表明,2种路障布置方式可有效降低人行道内污染物浓度,特别是,当α=45°时,污染物浓度最多可降低46.23%。同时,风向角α对街道峡谷内污染物扩散影响较大。当α=90°时,空气流通不良使得污染程度最为严重,且污染集中在背风侧近地面。单路障比双路障布置对污染物扩散影响更大,前者使污染物主要集中在街道中心背风侧,其他位置浓度明显降低;双路障时仅在一定范围内改善人行道内空气品质,但对街道整体污染物分布影响不大。     

孤立与非孤立城市街道峡谷内污染物扩散

通过求解二维不可压N-S方程、k-ε方程及污染物对流扩散方程,模拟了孤立街道峡谷与非孤立街道峡谷内的流场及交通污染物浓度场.计算结果与风洞试验结果总体趋势一致.非孤立街道峡谷内污染物壁面浓度要大于孤立街道峡谷内的壁面浓度.通过计算街道峡谷建筑屋顶高度处的垂直方向污染物通量,说明了湍流扩散是污染物扩散出街道峡谷的主要原因,其污染物通量总为正,而平均流通量可以为负.非孤立街道峡谷由于平均流流动和湍流流动的总扩散通量减少,造成污染物在街道峡谷内集聚,从而理论上解释了非孤立街道峡谷与孤立街道峡谷污染扩散的差别.     

基于TUD模型模拟优化MSBR工艺反硝化脱氮除磷

基于TUD模型（delftuniversityoftechnologymodel）对实验室MSBR（modifiedsequencingbatchreactor）工艺进行了模拟与优化，强化反硝化除磷，以提高系统脱氮除磷效率。结果表明，工艺运行参数为厌氧池90min、好氧池90min、SBR池缺氧段150min、污泥回流比1．0和污泥龄15d时，MSBR工艺COD、TN以及磷酸盐去除效率达95％，92％和83％；SBR池缺氧段吸磷量达到23．20mg／L，占系统总吸磷量43％左右；好氧池和SBR池缺氧段平均吸磷速率分别为0．35—0．42和0．12～0．17mgPO4^3-P／（L·min）。TUD模型能够较好模拟各水质组分在MSBR工艺空间和时间上的浓度分布，COD和NH4＋-N的模拟误差低于15％，PO4^3-P模拟值高于实测值5％左右。     

计算流体力学模拟街道峡谷特征和风向对细颗粒物污染扩散的影响

街道峡谷结构和风向会对街道峡谷内的污染物浓度和扩散特征带来一定影响。利用计算流体力学(CFD)软件,针对街道峡谷高宽比、建筑物间隔(建筑物间空隙与街道总长度的比值)和风向对街道峡谷内细颗粒物扩散的影响进行数值模拟。模拟结果表明,建筑物间隔为20%,风向为北风,风速为3m/s,街道峡谷高宽比分别为1∶2、1∶1和2∶1时,街道中心线距地面1.5m高度细颗粒物最大质量浓度分别位于-19.3、-88.0、-19.3m(以与街道中心点的距离计,正值表示在街道中心点以东,负值表示在街道中心点以西,下同)位置,为37.5、46.4、28.4μg/m3。街道峡谷高宽比为1∶1,风向为北风,风速为3m/s,建筑物间隔分别为0、20%和40%时,街道中心线距地面1.5m高度的细颗粒物最大质量浓度分别位于148.0、-92.3、-186.7m位置,为88.1、31.6、33.7μg/m3。街道峡谷高宽比为1∶1,建筑物间隔为20%,风速为3m/s,且分别处于西风、北风和西南风时,街道中心线距地面1.5m高度的细颗粒物最大质量浓度分别位于165.3、58.0、1.5m位置,为10.6、11.2、16.0μg/m3。可见,CFD模拟近地面污染物扩散时应考虑街道峡谷结构和风向的影响。     

基于BioWin软件对A~2/O工艺的模拟与优化

为了优化控制A2/O工艺的污染物去除效果,基于ASDM数学模型,以Bio Win软件为模拟平台,对A2/O工艺进行模拟与优化。先根据实际工艺构建模型且对其进行校正,通过模型模拟值与实验实测值的对比,得知COD、TN、TP与氨氮的模拟值与实测值误差较小。后通过调节运行参数对校正后模型进行优化,优化结果表明,在维持混合液内回流比为250%、污泥回流比为60%、污泥停留时间为9 d与好氧池溶解氧浓度为1.75~2.25 mg/L的工况下,A2/O工艺能得到较好的脱氮除磷与有机物去除效果。     

生物脱氮除磷活性污泥系统复合模拟方法

为避免繁琐的参数校核工作,提出了活性污泥2 d号模型(ASM2d)和人工神经网络(ANNs)相结合的复合模拟方法。考察了复合方法在某污水处理厂生物脱氮除磷工艺中的应用情况。研究表明,ANNs能够准确地模拟出水实测值与未经校核的ASM2d机理模型的估计值之间的差值。利用Levenberg-Marquardt算法,对出水氨氮、总氮和总磷分别建立网络结构为5-12-1、5-8-1和5-8-1的ANNs子模型,将这些子模型输出同ASM2d机理模型输出相加便得到复合模型输出。复合模型估计值对前10.4 d(ANNs子模型训练数据时段)出水氨氮、总氮和总磷浓度的拟合平均绝对百分比误差分别为0.267、0.055和0.048;其对后2.6 d(ANNs子模型测试数据时段)出水氨氮、总氮和总磷浓度的预测平均绝对百分比误差分别为0.332、0.083和0.069。均方根误差、平均绝对误差等评价指标也表明复合模型能够给出合理的模拟结果。     

T型街道内空气流动与污染物扩散特性研究

为研究T型街道峡谷内空气流动与污染物扩散传质的特性,利用数值模拟研究来流风向角(θ)的变化(θ为45°、90°和135°)对T型街道交叉路口内空气流动与机动车尾气污染物扩散传递的影响,并与风洞实验测量数据进行验证。3种湍流模型中,可实现k—ε模型计算的速度相对偏差小于8%,与风洞实验结果一致性最好。结果表明,来流风向角的变化,会造成从街道顶部或侧面进入街道内的气流方向及通量发生改变,从而显著影响T型街道交叉口内及其附近的流动结构和污染物浓度分布。污染物容易在建筑尾流区等流动不畅的区域产生聚集,造成污染浓度偏高。当θ=135°时,T型街道内通风条件最好,街道内行人呼吸高度和建筑临街立面附近污染物浓度水平均相对较低。由于流动结构的改善,T型街道峡谷内的污染水平低于一般街道峡谷。     

利用复介电常数和BPAT神经网络进行环境监测的可行性研究

土壤中的污染物成分复杂，其含量与复介电常数之间具有很强的非线性关系。以土壤样品复介电常数的实部、虚部分别作为输入，以其含水率、体密度和所含6种已知离子的浓度分别作为输出，建立BP人工神经网络。把吉泰兰地区的土壤样品数据分为训练样本集和检验样本集，网络训练后，其学习效果显示模型的性能很好，检验样本的预测结果也与实测值较好吻合，说明利用复介电常数和BP人工神经网络进行环境监测是一种好的方法。     

Influence of trees on the dispersion of pollutants in an urban street canyon—Experimental investigation of the flow and concentration field

Flow field and concentration measurements have been performed in an idealized model of an urban street canyon with one row of trees arranged along the center axis. The model was set up in an atmospheric boundary layer wind tunnel and the approach flow was directed perpendicular to the street axis. A line source embedded in the bottom of the street was used to release tracer gas for the simulation of traffic exhaust emissions. Trees with spherical crowns were modeled and positioned inside the street canyon, varying crown diameter, crown permeability, trunk height and tree spacing. Traffic-induced turbulence was simulated by rotating belts with thin plates. Concentrations were measured at the facades of the street canyon. For small tree crowns, only little changes in concentration were measured, however, increasing crown diameters led to increasing concentrations at the leeward street canyon wall associated with a reduction of local concentrations at the windward wall. For some cases, a variation of trunk height led to a modification of the concentration pattern on the walls. Increasing the tree spacing resulted in a noticeable concentration decrease. When compared to the situation with standing (but emitting) traffic, the traffic-induced turbulence by two-way car movements always contributed to a more homogenous concentration field inside the street canyon yielding to reduced mean concentration levels.     

基于人工神经网络和遗传算法研究锰过氧化酶脱色甲基橙

基于锰过氧化物酶(MnP)氧化脱色偶氮类染料的原理,实验研究MnP对甲基橙的脱色工艺,采用人工神经网络(ANN)和遗传算法(GA)建立脱色模型并优化工艺。建立的ANN模型的误差、相关系数、均方根误差和绝对平均偏差分别为0.0009、0.9971、1.21和6.82,模型有效且能够用于预测和工艺优化。采用GA对ANN模型进行数值寻优,得到的最佳工艺条件为酶液量0.6 mL,Mn2+浓度4 mmol/L,H2O2浓度0.49 mmol/L。该条件下脱色率达到(90.74±0.59)%。ANN耦合GA有效地建立了锰过氧化物酶脱色甲基橙的模型,并优化了工艺参数,为甲基橙脱色的研究提供一定参考。     

Vertical transport of accumulation mode particles between two street canyons and the urban boundary layer

Concentrations and turbulent fluxes of accumulation mode particles were measured during the 2004–2005 ‘Canopy and Aerosol Particle Interaction in Toulouse Urban Layer’ project (CAPITOUL) at the top of two intersecting street canyons and in the urban boundary layer (UBL) in Toulouse, France. Particle numbers were strongly affected by boundary layer depth and showed limited sensitivity to local emissions. Differences in the diurnal patterns of particle numbers were observed between the finer fraction (0.3–0.4 μm) and coarser fraction (1.6–2.0 μm) of accumulation mode particles, indicating different processes of formation, evolution and transportation may be dominant. Highest particle numbers were observed in the narrow street canyon which had more limited local emissions and comparatively small particle fluxes. However, the improved ventilation rate in the wider canyon was also associated with the downward mixing of particles into the street canyon from the UBL. The results from this study clearly illustrate the temporal and spatial variability of particle numbers and fluxes in the urban atmosphere.     

Wind-tunnel study of concentration fields in street canyons

The paper presents results from a case study of gaseous pollutant dispersion in street canyons. Tracer-gas experiments were performed in a neutrally stratified wind tunnel. Vehicle emissions were simulated as line sources. Concentration profiles along building walls were measured. A two-dimensional street canyon was considered as the reference case. The influence of systematic parameter variations on the concentration field is studied and discussed. Building dimensions, upwind building configuration, wind direction and roof geometry were found to be important parameters. Data sets from the study may be used for evaluation of numerical models and for expert estimates of air quality in the urban environment     

A concentration correction scheme for Lagrangian particle model and its application in street canyon air dispersion modelling

Pollutant dispersion in street canyons with various configurations was simulated by discharging a large number of particles into the computation domain after developing a time-dependent wind field. Trajectory of the released particles was predicted using a Lagrangian particle model developed in an earlier study. A concentration correction scheme, based on the concept of “visibility”, was adopted for the Lagrangian particle model to correct the calculated pollutant concentration field in street canyons. The corrected concentrations compared favourably with those from wind tunnel experiments and a linear relationship between the computed concentrations and wind tunnel data were found. The developed model was then applied to four simulations to test for the suitability of the correction scheme and to study pollutant distribution in street canyons with different configurations. For those cases with obstacles presence in the computation domain, the correction scheme gives more reasonable results compared with the one without using it. Different flow regimes are observed in the street canyons, which depend on building configurations. A counter-clockwise rotating vortex may appear in a two-building case with wind flow from left to right, causing lower pollutant concentration at the leeward side of upstream building and higher concentration at the windward side of downstream building. On the other hand, a stable clockwise rotating vortex is formed in the street canyon with multiple identical buildings, resulting in poor natural ventilation in the street canyon. Moreover, particles emitted in the downstream canyon formed by buildings with large height-to-width ratios will be transported to upstream canyons.     

T-S模糊神经网络在厌氧反应器预测中的应用

3个厌氧反应器运行稳定后,用三氯甲烷和2、4-二硝基酚作为毒物负荷对它们进行了冲击试验.利用负荷冲击试验所得的数据集建立了T-S模糊神经网络,并用其预测了反应器的容积产气率、挥发性脂肪酸和CH4体积含量.研究结果表明,基于某一反应器建立的T-S模糊神经网络可以很好地预测毒物负荷冲击下该反应器的容积产气率、挥发性脂肪酸和CH4变化规律,实测值与预测值的相关系数均＞0.850;但是基于某一反应器建立的模糊神经网络用来预测其他反应器时,其预测能力较差,预测值和实测值的相关系数基本上＜0.500.     

Influence of cetane improvers on the air quality in an urban street canyon

The concentration distributions of NO_x, PM, HC and CO in an urban street canyon have been estimated using a two-dimensional air quality numerical model based on the k– turbulent model and the atmospheric convection diffusion equation when various cetane improvers were used in diesel fuels. A wind vortex can be found within the street canyon, and the pollutants emitted from the bottom of the street canyon tend to follow the course of the wind field, moving circularly. The addition of cetane improvers can improve the air quality in a street canyon, all of the pollutants were found to decrease with increasing centane number.     

Modelling dispersion of traffic pollution in a deep street canyon: Application of CFD and operational models

In this study, numerical modelling of the flow and concentration fields has been undertaken for a deep street canyon in Naples (Italy), having aspect ratio (i.e. ratio of the building height H to the street width W) H/W = 5.7. Two different modelling techniques have been employed: computational fluid dynamics (CFD) and operational dispersion modelling. The CFD simulations have been carried out by using the RNG k–? turbulence model included in the commercial suite FLUENT, while operational modelling has been conducted by means of the WinOSPM model. Concentration fields obtained from model simulations have been compared with experimental data of CO concentrations measured at two vertical locations within the canyon. The CFD results are in good agreement with the experimental data, while poor agreement is observed for the WinOSPM results. This is because WinOSPM was originally developed and tested for street canyons with aspect ratio H/W ≌ 1. Large discrepancies in wind profiles simulated within the canyon are observed between CFD and OSPM models. Therefore, a modification of the wind profile within the canyon is introduced in WinOSPM for extending its applicability to deeper canyons, leading to an improved agreement between modelled and experimental data. Further development of the operational dispersion model is required in order to reproduce the distinct air circulation patterns within deep street canyons.