曝气生物滤池反冲洗关键因子的确定及机理浅析

通过正交试验得出以粒径为3-6mm和堆积密度为．540kg／m3的陶粒为滤料的下向流曝气生物滤池的最佳气水联合反冲洗操作参数:气反冲洗强度(Qa)为4．88L／(s·m2)、水反冲洗强度(Qw)为1．44L／(s·m2)、气预冲洗时间(Ta)为4min、气水同时反冲洗时间(Ts)为5min和单水反冲洗时间(Tw)为3min。其中水反冲洗强度有显著影响,气反冲洗强度、气水同时反冲洗时间有次要影响,气预冲洗时间、水反冲洗时间有较次影响。得到在最佳反冲洗条件下气、水在滤床中所产生速度梯度(G)分别为203．6s-1、130．2s-1。同时,分析了反冲洗后运行时水头损失和污染物去除的变化规律,并从流体力学角度初步探讨了气水联合反冲洗机理。     

石英砂均质滤料气水反冲洗强度数学模型的建立

根据石英砂均质滤料层气水反冲洗时不允许出现水力分级现象的特点 ,应用滤料层有效应力的概念和微小孔口注入液体压缩空气压力与空气流量的关系 ,推导建立了石英砂均质滤料层气水同时反冲洗时气洗强度与水洗强度关系的数学模型。     

均粒滤料过滤及气水反冲洗工艺研究

本论文在试验的基础上,通过对粒径为1.0～1.2mm的均粒滤料的过滤性能及气水反冲洗的状况进行研究,主要取得以下成果: 一、在过滤方面 1.在投加絮凝剂适当及滤前水浊度为5～10FTU的情况下,该均粒滤料滤速可达18m/h,过滤周期20～30h,过滤出水水质可控制在1.0FTU以下,滤层的截泥深度可达0.50～0.60m,滤层的厚度为1.1m,基本可满足工程要求。 2.在影响直接过滤的诸多因素中,絮凝剂的种类和投加量是最重要的因素,其次才是水力条件(如滤速)及滤层的物理参数(滤料粒径和厚度等)。 3.滤料粒径越大,周期产水量越大,截泥越深,但滤层的厚度越大。 二、在反冲洗方面 1.提出了保证气水反冲洗均匀性的措施及防止滤料流失的方法。 2.该粒径滤料的有效气水冲洗参数:先气冲1min,然后采用8～10L/(s·m~2)的水和10～14L/(s·m~2)的气同时冲4min,再以12L/(s·m~2)单水漂洗1～2min,即可使滤层含泥量控制在0.05％之内。 3.采用气水反冲洗比单独水反冲洗耗水量节约40～50％,而且滤层冲洗更干净。 同时论文中还对过滤及气水反冲洗工艺应用过程中的一些问题进行了研究,为该工艺在我国的应用提供参考。     

煤砂双层滤料滤池冲洗方式比较

本文通过中试和生产性试验，对煤砂双层滤料滤池的气水反冲洗、表面助冲和单纯水洗进行了技术经济分析。表面助冲使双层滤料滤池的煤层得到有效的冲洗，对容易积泥的煤砂混层的冲洗效果不够理想。气水反冲洗能充分清洗整个滤层，使滤池的初始过滤水头损失降低２６％，运行周期平均延长３ｈ，周期产水量增加１２７６％，生产率提高１２１％，洗水率降低５０３％。和其它两种方法相比，它的冲洗耗水量和能耗量小，表面助冲次之。气水反冲洗和单纯水洗相比可节省冲洗水、电费５４％。     

气水反冲洗滤池滤板的制作与安装

气水反冲洗滤池与水反冲洗滤池相比,有明显的优越性:过滤周期长;滤料反冲洗后清洁,不易结泥球;节省反冲洗水量等.气水反冲洗滤池能否成功,关键在于滤板的制作与安装能否满足工艺要求.一、滤板的制作滤板制作,主要可分滤板模板的制作,滤头预埋套管的固定及砼浇筑几个主要步骤.而模板制作精密,多次使用过程中不变形;滤头预埋套管固定后在砼浇筑过程中不走偏和移位,又是滤板制作的关键.     

石英砂均质滤料气水反冲洗试验研究

本文根据西安市曲江池水厂的净水工艺,对石英砂均质滤料层气水反冲洗作了试验研究.根据滤柱试验结果,提出了有效的气水反冲洗参数,即单独气冲强度为15～18L/(m~2·s),历时3min;气水混冲时,空气强度为15～18L/(m~2·s),水的强度为4L/(m~2·s),历时4min;清水漂洗强度为4L/(m~2·s),历时4min.     

本刊1996年总目次

题 名 期 页 题 名 ★城市给排水★ 气水反冲洗均质过滤特性研究 pH值碱度对脱氮除磷效果的影响及其控制方法 莫莱石一茧青石(MJ)滤料滤池在生产上的应用 石英砂均质滤料气水反冲洗试验研究 均质滤料滤池过滤理论分析 反粒度过滤反冲洗效果的探讨 暴雨选样与频率分布模型及其应用 气水反冲洗均质过滤流态分析及评价指标 污水处理设施中的脱臭技术 强化传统工艺处理微污染水源水的试验研究 富营养化湖泊水除臭试验研究 结团体流化床的运动平衡 高浊度水二级电凝聚处理工艺 镇江市金西水厂工程介绍 高压静电处理城市污水的研究 气水反冲洗承…     

气水反冲洗条件下过滤性能的研究

本研究比较了气水反冲洗条件下几种常用滤料的过滤性能,论证了气水反冲洗较单水反冲洗所具备的优越性,并对我国目前普通快滤池的改造挖潜提出了较切实可行的方案。     

氧化铁改性石英砂用于游泳池砂缸滤料过滤试验研究

对新型砂缸滤料氧化铁改性石英砂滤料(Iron Oxide Coated Sand,IOCS)进行过滤和反冲洗试验,研究其对游泳池水主要污染物的去除效果及截污性能,并与传统砂缸滤料(选原始石英砂,Raw QuartzSand,RQS)的性能进行对比研究,探寻IOCS对污染物的过滤去除效果及其再生能力。试验结果表明:IOCS滤料较RQS滤料过滤去除游泳池水中污染物的效果更佳,过滤周期更长,截污除浊能力更强。采用气水反冲洗与NaOH助脱剂组合试验的反冲洗方法,可以有效再生过滤有机物后的IOCS滤料。     

双层均质滤料过滤及气水反冲洗工艺研究

双层均质滤料过滤及气水反冲洗工艺研究硕士生：于大海导师：朱月海（同济大学环境工程学院２０００９２）本文在试验的基础上，通过对双层均质滤料（ｄ煤＝１１９～１６８ｍｍ；ｄ砂＝０５９～０８４ｍｍ）过滤性能及气水反冲洗效果的研究，取得了以下较为理想的...     

V型滤池气水反冲洗过程滤料流失影响因素分析

根据V型滤池生产运行参数和设计规范的相关规定,确定了气水同时反冲洗阶段气冲强度、水冲强度及排水槽高度的取值范围.通过模型滤柱系列对比试验,分析气冲强度、水冲强度及排水槽高度对流失滤砂质量、粒径的影响.结果显示,水冲强度是影响滤料流失的主要因素,随排水槽高度增加,跑砂量显著减少、流失滤料粒径减小.     

下向流生物滤池低温堵塞问题的分析与研究

深度处理中下向流生物滤池正常运行条件下,滤柱进水段由于污染物的降解。微生物大量积累,水头损失增长较快。尤其在低温下,由于水力条件、生物微环境、生物相改变以及微生物的自我保护,滤池更易发生气塞、堵塞,其运行周期比中温时降低近2/3,严重影响了净化效果。提出了局部反冲洗法解决膜滤池低温堵塞问题。局部反冲洗后,水头损失由60cm 降到30cm 左右。局部反冲洗在改善滤柱堵塞的同时,为自养亚硝化菌和硝化菌提供了更为稳定、适宜的微环境,使 NH_3-N 的去除率由15%增至50%以上;COD_(Cr)的去除效果因为生物活性的增加并未受到波动。局部反冲洗后,生物量和水头损失沿层积累率的最大值出现在滤柱下段。     

Short-Term Water Demand Forecast Modelling at IIT Kanpur Using Artificial Neural Networks

The efficient operation and management of an existing water supply system require short-term water demand forecasts as inputs. Conventionally, regression and time series analysis have been employed in modelling short-term water demand forecasts. The relatively new technique of artificial neural networks has been proposed as an efficient tool for modelling and forecasting in recent years. The primary objective of this study is to investigate the relatively new technique of artificial neural networks for use in forecasting short-term water demand at the Indian Institute of Technology, Kanpur. Other techniques investigated in this study include regression and time series analysis for comparison purposes. The secondary objective of this study is to investigate the validity of the following two hypotheses: 1) the short-term water demand process at the Indian Institute of Technology, Kanpur campus is a dynamic process mainly driven by the maximum air temperature and interrupted by rainfall occurrences, and 2) occurrence of rainfall is a more significant variable than the rainfall amount itself in modelling the short-term water demand forecasts. The data employed in this study consist of weekly water demand at the Indian Institute of Technology, Kanpur campus, and total weekly rainfall and weekly average maximum air temperature from the City of Kanpur, India. Six different artificial neural network models, five regression models, and two time series models have been developed and compared. The artificial neural network models consistently outperformed the regression and time series models developed in this study. An average absolute error in forecasting of 2.41% was achieved from the best artificial neural network model, which also showed the best correlation between the modelled and targeted water demands. It has been found that the water demand at the Indian Institute of Technology, Kanpur campus is better correlated with the rainfall occurrence rather than the amount of rainfall itself.     

Artificial Neural Network Models of Watershed Nutrient Loading

This paper illustrates the use of artificial neural networks (ANNs) as predictors of the nutrient load from a watershed. Accurate prediction of pollutant loadings has been recognized as important for determining effective water management strategies. This study compares Haith??s Generalized Watershed Loading Function (GWLF) and Arnold??s Soil and Water Assessment Tool (SWAT) to multilayer artificial neural networks for monthly watershed load modeling. The modeling results indicate that calibrated feed-forward ANN models provide prediction which are always essentially as accurate as those obtained with GWLF and the SWAT, and some times much more accurate. With its flexibility and computation efficiency, the ANN should be a useful tool to obtain a quick simulation assessment of nutrient loading for various management strategies.     

Applications of Artificial Neural Networks in integrated water management: fiction or future?

An Artificial Neural Network (ANN) is nowadays recognized as a very promising tool for relating input data to output data. It is said that the possibilities of artificial neural networks are unlimited. Here we focus on the potential role of neural networks in integrated water management. An Artificial Neural Network (ANN) is a mathematical methodology which describes relations between cause (input data) and effects (output data) irrespective of the process laying behind and without the need for making assumptions considering the nature of the relations. The applications are widespread and vary from optimization of measuring networks, operational water management, prediction of drinking water consumption, on-line steering of wastewater treatment plants and sewage systems, up to more specific applications such as establishing a relationship between the observed erosion of groyne field sediments and the characteristics of passing vessels on the river Rhine. Especially where processes are complex, neural networks can open new possibilities for understanding and modelling these kinds of complex processes. Besides explaining the method of ANN this paper shows different applications. Three examples have been worked out in more detail. An intelligent monitoring system is shown for the on-line prediction of water consumption, ANN are successfully used for sludge cost monitoring and optimizing wastewater treatment and the usage of ANN is shown in optimizing and monitoring water quality measuring networks. An ANN appears to be a multiuse and powerful tool for modelling complex processes.     

门限人工神经网络模型及其在洪水预报中的应用

结合门限自回归模型与人工神经网络模型的建模思想，首次提出这两种方法的耦合模型，即门限人工神经网络模型，新模型的实质是一种分段非线性化的处理方法，是对现有门限模型分段线性化的很好改进。实例计算结果说明，新模型在洪水的预报中是有效的，在各种非线性时序动态预测中具有普遍意义和广泛的实用价值。     

Fuzzy Genetic Approach for Estimating Reference Evapotranspiration of Turkey: Mediterranean Region

The applicability of fuzzy genetic (FG) approach in modeling reference evapotranspiration (ET₀) is investigated in this study. Daily solar radiation, air temperature, relative humidity and wind speed data of two stations, Isparta and Antalya, in Mediterranean region of Turkey, are used as inputs to the FG models to estimate ET₀ obtained using the FAO-56 Penman–Monteith equation. The FG estimates are compared with those of the artificial neural networks (ANN). Root mean-squared error, mean absolute error and determination coefficient statistics were used as comparison criteria for the evaluation of the models’ accuracies. It was found that the FG models generally performed better than the ANN models in modeling ET₀ of Mediterranean region of Turkey.     

坡面产流模式的神经网络模拟

坡面产流是土壤本身特性与外界影响因素相互作用的结果，它们之间具有明显的非线性输入输出关系。在分析坡面产流和神经网络模型具有某些相似的基础上，利用径流站观测资料，建立了小流域坡面产流量的三层前向网络模型（BP算法），并显示了具有较好的模拟预测效果。     

小波神经网络在水文水资源应用中的研究进展

以人工神经网络为基础的小波神经网络具有较强的逼近和容错能力、较快的收敛速度和较好的预报效果。在介绍小波神经网络模型的结构、特点基础上,着重介绍了目前关于小波神经网络在水文水资源领域的研究现状,并指出了其在理论及应用中存在的问题。     

考虑渗气渗水函数的非饱和土固结性状研究

大坝蓄水所引起的水环境变化会诱发其周边建筑物地基产生显著的沉降变形,要合理预测其沉降过程,则需研究非饱和土地基的固结性状。为此,基于混合物理论,在非饱和土的水、气两相渗流-变形耦合方程组中,采用离散线性化的方法引入了渗气渗水函数和持水曲线方程,给出了考虑渗气渗水系数比值变化的一维固结微分方程组,进而采用积分变换方法求得非饱和土层孔隙水、气压力消散及其沉降变形的解析解。最后,选取水、气相互连通的非饱和土层典型算例,通过与已有文献所述未考虑渗气渗水系数比值变化的解析解、有限差分解的计算结果对比发现:本文解析解因考虑了水、气渗流相互作用对非饱和土固结过程的影响,故其计算的孔隙水、气压力消散曲线与沉降变形曲线较已有文献解析解更接近于有限差分解的计算曲线。