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.     

Sex‐specific and dose‐response relationships of urinary cobalt and molybdenum levels with glucose levels and insulin resistance in U.S. adults

Growing studies have linked metal exposure to diabetes risk. However, these studies had inconsistent results. We used a multiple linear regression model to investigate the sex-specific and dose-response associations between urinary metals (cobalt (Co) and molybdenum (Mo)) and diabetes-related indicators (fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), homeostasis model assessment for insulin resistance (HOMA-IR), and insulin) in a cross-sectional study based on the United States National Health and Nutrition Examination Survey. The urinary metal concentrations of 1423 eligible individuals were stratified on the basis of the quartile distribution. Our results showed that the urinary Co level in males at the fourth quartile (Q4) was strongly correlated with increased FPG (β = 0.61, 95% CI: 0.17–1.04), HbA1c (β = 0.31, 95% CI: 0.09–0.54), insulin (β = 8.18, 95% CI: 2.84–13.52), and HOMA–IR (β = 3.42, 95% CI: 1.40–5.44) when compared with first quartile (Q1). High urinary Mo levels (Q4 vs. Q1) were associated with elevated FPG (β = 0.46, 95% CI: 0.17–0.75) and HbA1c (β = 0.27, 95% CI: 0.11–0.42) in the overall population. Positive linear dose-response associations were observed between urinary Co and insulin (P_nonlinear = 0.513) and HOMA–IR (P_nonlinear = 0.736) in males, as well as a positive linear dose-response relationship between urinary Mo and FPG (P_nonlinear = 0.826) and HbA1c (P_nonlinear = 0.376) in the overall population. Significant sex-specific and dose-response relationships were observed between urinary metals (Co and Mo) and diabetes-related indicators, and the potential mechanisms should be further investigated.     

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     

Adaptive management: Promises and pitfalls

Proponents of the scientific adaptive management approach argue that it increases knowledge acquisition rates, enhances information flow among policy actors, and provides opportunities for creating shared understandings. However, evidence from efforts to implement the approach in New Brunswick, British Columbia, Canada, and the Columbia River Basin indicates that these promises have not been met. The data show that scientific adaptive management relies excessively on the use of linear systems models, discounts nonscientific forms of knowledge, and pays inadequate attention to policy processes that promote the development of shared understandings among diverse stakeholders. To be effective, new adaptive management efforts will need to incorporate knowledge from multiple sources, make use of multiple systems models, and support new forms of cooperation among stakeholders.     

建筑火灾区域模拟竖孔流动的计算

本文根据建筑火灾双层区域模拟思想，给出其常微分控制方程组，并分析了其压力求解方法，然后，运用伯努力利方程推导了相邻房间通过矩形竖孔（门或窗）的质量流率计算公式，还讨论了竖孔流动中性面产生条件。在此基础上，结合一两房间、两孔建筑中烟气运动实例，运用Ｃ．Ｗ．Ｇｅａｒ刚性稳定算法对火灾发展及烟气流动过程进行了数值模拟；给出各竖孔中性面位置、数量和各主环境之间通过竖孔的质量流率；还给出各房间气体平均温升、     

IMPLICATIONS OF ON‐GROUND NITROGEN LOADING AND SOIL TRANSFORMATIONS ON GROUND WATER QUALITY MANAGEMENT1

ABSTRACT: This paper presents a modeling approach based on a geographic information system (GIS) to estimate the variability of on‐ground nitrogen loading and the corresponding nitrate leaching to ground water. The methodology integrates all point and nonpoint sources of nitrogen, the national land cover database, soil nitrogen transformations, and the uncertainty of key soil and land use‐related parameters to predict the nitrate mass leaching to ground water. The analysis considered 21 different land use classes with information derived from nitrogen sources such as fertilizer and dairy manure applications, dairy lagoons, septic systems, and dry and wet depositions. Simulations were performed at a temporal resolution of one month to capture seasonal trends. The model was applied to a large aquifer of 376 square miles in Washington State that serves more than 100,000 residents with drinking water. The results showed that dairy manure is the main source of nitrogen in the area followed by fertilizers. It was also seen that nitrate leaching is controlled by the recharge rate, and there can be a substantial buildup of soil nitrogen over long periods of time. Uncertainty analysis showed that denitrification rate is the most influential parameter on nitrate leaching. The results showed that combining management alternatives is a successful strategy, especially with the use of nitrification inhibitors. Also, change in the land use pattern has a noticeable impact on nitrate leaching.     

SIMULATING THE IMPACT OF DRAINAGE DESIGN IN A COLD CLIMATE WITH ADAPT1

ABSTRACT: Surface and subsurface drainage make crop production economically viable in much of southern Minnesota because drainage allows timely field operations and protects field crops from extended periods of flooded soil conditions. However, subsurface drainage has been shown to increase nitrate/nitrogen losses to receiving waters. When engaging in drainage activities, farmers are increasingly being asked to consider, apart from the economic profit, the environmental impact of drainage. The Agricultural Drainage and Pesticide Transport model (ADAPT) was used in this study to evaluate the impact of subsurface drainage design on the soil water balance over a two‐year period during which observed drainage discharge data were available. Twelve modeling scenarios incorporated four drainage coefficients (DC), 0.64 cm/d, 0.95 cm/d, 1.27 cm/d, and 1.91 cm/d, and three drain depths, 0.84 m, 1.15 m, and 1.45 m. The baseline condition corresponded to the drainage system specifications at the field site: a drain depth and spacing of 1.45 m and 28 m, respectively (DC of 0.64 cm/d). The results of the two‐year simulation suggested that for a given drainage coefficient, soils with the shallower drains (but equal DC) generally have less subsurface drainage and can produce more runoff (but reduced total discharge) and evapotranspiration. The results also suggested that it may be possible to design for both water/nitrate/nitrogen reduction and crop water needs.     

TEMPORAL CHANGES IN THE YADKIN RIVER FLOW VERSUS SUSPENDED SEDIMENT CONCENTRATION RELATIONSHIP1

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.