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1.
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.  相似文献   
2.
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.  相似文献   
3.
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  相似文献   
4.
针对四川石油天然气工业环境统计中存在的非稳定污染源监测数据的统计价值不高,统计调查方法单一,个别统计指标计算未使用国家统一标准等现状,从环境监测站改组入手,改革统计调查方法,建立以必要的周期性普查为基础,以经常性的抽样调查为主体,同时辅之以全面统计报表,重点调查和科学推算综合运用的统计调查方法体系。  相似文献   
5.
6.
模糊集值统计法在煤矿安全评价指标权值中的应用   总被引:8,自引:1,他引:8  
应用模糊集值统计的理论 ,对煤矿安全评价中具有随机性和模糊性的指标进行数学分析 ,进一步改进了其权值的确定方法 ,使其更加符合实际情况 ,并对由此得出的权值进行了可靠性分析。通过实例表明 ,该方法克服了经典统计法的不足 ,提高了煤矿安全评价的实用性和科学性  相似文献   
7.
ABSTRACT: Dynamic linear models (DLM) and seasonal trend decomposition (STL) using local regression, or LOESS, were used to analyze the 50‐year time series of suspended sediment concentrations for the Yadkin River, measured at the U.S. Geological Survey station at Yadkin College, North Carolina. A DLM with constant trend, seasonality, and a log10 streamflow regressor provided the best model to predict monthly mean log10 suspended sediment concentrations, based on the forecast log likelihood. Using DLM, there was evidence (odds approximately 69:1) that the log10 streamflow versus log10 suspended sediment concentration relationship has changed, with an approximate 20 percent increase in the log10 streamflow coefficient over the period 1981 to 1996. However, sediment concentrations in the Yadkin River have decreased during the decade of the 1990s, which has been accompanied by a concomitant increase in streamflow variability. Although STL has been shown to be a versatile trend analysis technique, DLM is shown to be more suitable for discovery and inference of structural changes (trends) in the model coefficient describing the relationship between flow and sediment concentration.  相似文献   
8.
李海云  梁籍  郭逍宇 《环境工程学报》2017,11(12):6309-6320
运用聚类分析、判别分析和主成分/因子分析方法来研究潮白河流域再生水补水河段地下水水质的时空变异情况。对地下水进行剖面分析(剖面A为平行于水流场方向,剖面B垂直于水流场方向)。地下水研究结果表明除NO3-、NH4+和Mn2+外,其余指标均达到地表水Ⅱ类标准。剖面A的季节判别中由于淋溶作用筛选出pH和TDS,正确率为77.5%,说明研究区在近岸区。同时,剖面B的季节变异由于远离河岸的土壤蓄水层中氧化还原作用使得Fe3+、Mn2+、Na+、NO2-、CODMn和TP被判别出,正确率为74.4%。此外,由于非冻土期土壤蓄水层中频繁的淋溶作用和活跃的生化反应识别出CODMn、HCO3-、NO2-、pH、SO42-、Cl-、Na+和Ba2+表征了非冻土期剖面A的空间变异,而判别正确率为100%的F-、Na+和HCO3-则表征了冻土期剖面A的空间变异。冻土期剖面B的TDS和TP以及非冻土期剖面B的TN和K+的判别正确率均为100%。再生水对近岸带的影响较远岸带显著。该分析结论可归因于再生水的污染、土壤蓄水层矿物盐岩溶解污染、工农业废水排放的点源污染和降水及流域水土流失所造成的非点源污染的综合作用。  相似文献   
9.
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.  相似文献   
10.
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.  相似文献   
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