Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH₄⁺-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m³/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH₄⁺-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH₄⁺-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH₄⁺-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R²) and lower root mean squared errors (RMSE) values.     

Body fluid analog chlorination: Application to the determination of disinfection byproduct formation kinetics in swimming pool water

Disinfection by-products(DBPs) are formed in swimming pools by the reactions of bather inputs with the disinfectant.Although a wide range of molecules has been identified within DBPs,only few kinetic rates have been reported.This study investigates the kinetics of chlorine consumption,chloroform formation and dichloroacetonitrile formation caused by human releases.Since the flux and main components of human inputs have been determined and formalized through Body Fluid Analogs(BFAs),it is possible to model the DBPs formation kinetics by studying a limited number of precursor molecules.For each parameter the individual contributions of BFA components have been quantified and kinetic rates have been determined,based on reaction mechanisms proposed in the literature.With a molar consumption of 4 mol Cl_2/mol,urea is confirmed as the major chlorine consumer in the BFA because of its high concentration in human releases.The higher reactivity of ammonia is however highlighted.Citric acid is responsible for most of the chloroform produced during BFA chlorination.Chloroform formation is relatively slow with a limiting rate constant determined at 5.50 × 10~(-3) L/mol/sec.L-histidine is the only precursor for dichloroacetonitrile in the BFA.This DBP is rapidly formed and its degradation by hydrolysis and by reaction with hypochlorite shortens its lifetime in the basin.Reaction rates of dichloroacetonitrile formation by L-histidine chlorination have been established based on the latest chlorination mechanisms proposed.Moreover,this study shows that the reactivity toward chlorine differs whether L-histidine is isolated or mixed with BFA components.     

土与结构相互作用体系振动台模型试验数值模拟研究(英文)

运用土与结构动力相互作用 (SSI)有限元三维分析软件 SASSI2 0 0 0对一个土与结构动力相互作用体系振动台模型试验进行了模拟计算。对振动台模型试验作了简单的介绍 ,并详细叙述了试验的建模方法。对于试验中的刚性地基和柔性地基条件 ,El- centro波、Taft波和 5 0年超越概率为 10 %的南京人工波等三种地震波输入 ,三个加速度峰值水平 0 .1g、0 .2 g、0 .3g及两个水平向地震波输入的各种组合工况均进行了计算。在数值计算中 ,假设地基土为覆盖于基岩上的半无限粘弹性水平成层土 ,采用等效线性模型考虑土的动力非线性的影响 ;上部结构用三维杆系有限元单元模拟 ,楼板用四结点壳单元模拟 ,每个结点有三个平动自由度和三个转动自由度 ,模型试验中所施加的人工质量均匀分布于壳单元上 ;基础视为平板基础 ,用八结点块体单元模拟 ,每个结点有三个平动自由度。将试验结果与计算结果进行对比较 ,结果表明 :计算所建立的模型较好地模拟了相互作用体系在地震荷载下的反应性状 ,计算结果与试验结果吻合较好 ,SSI效应对结构地震反应有很大影响     

结合外场观测分析珠三角二次有机气溶胶的数值模拟

结合2008年11月18~25日期间珠三角地区的二次有机气溶胶(SOA)外场观测数据,验证区域空气质量模式WRF/Chem(weather research and forecasting model with chemistry)中两种SOA化学机制——VBS(volatile basis set)和SORGAM(secondary organic aerosol model)对珠三角SOA的模拟效果.VBS机制考虑了更为广泛的SOA前体物和化学老化过程,SOA模拟值更接近观测值,能合理反映SOA观测值的逐天变化趋势,与观测值的平均绝对偏差和相关性分别是-4.88μg·m-3和0.91,而SORGAM机制的分别为-5.32μg·m-3和0.18.利用VBS机制模拟区域内SOA的时空分布,结果显示SOA浓度具有显著的昼夜变化特征,浓度峰值出现在中午时段.受到输送和臭氧区域分布的影响,各城市SOA浓度差异显著,下风向的城市(如中山、珠海、江门)SOA浓度较高.     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

锂离子电池安全性特点及热模型研究

锂离子电池的安全问题越来越受到重视.本文从锂离子电池热安全性特点着手,分析了锂离子电池的着火、爆炸和电解液泄漏等安全事故特点.简单介绍了锂离子电池主要材料的产热特性、相互反应产热特性.讨论了锂离子电池热模型建立的两种途径,即量热仪途径和化学反应途径,通过这些热模型的建立,来指导锂离子电池的安全设计和管理.     

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO₂ emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH₄ emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (− 0.64) as the most important variables. The adjusted coefficient is suitable and equals R² = 0.90. For N₂O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N₂O emission is the peat and wood fuel consumption.     

METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL1

ABSTRACT: The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.     

四川省米易县新农村建设可持续发展SD分析——用系统观透视

县域新农村建设必然受到当地自然—社会—经济中众多因素及其复杂关系的制约.为了从长期性与整体性角度考察四川省米易县社会、经济、生态环境与新农村建设之间的相互作用关系,建立了由米易县系统动力学模型为主干,生态足迹模型和SWOT模型为支撑的米易县新农村建设可持续发展分析模型,以透视米易县新农村建设的前景,探讨规划的理论依据.