Evaluation of wastewater characterization methods.

Wastewater contains various organic components with different physical and biochemical characteristics. ASM No. 1 distinguishes two categories of biodegradable organic matter in wastewater, rapidly and slowly biodegradable. In general there are two methods for wastewater characterization: based on filtration in combination with a long-term BOD test or based on a respirogram. By comparing both approaches, we showed that in wastewater three categories of organic compounds with different biodegradation rates can be distinguished. These categories are referred to as readily biodegradable, rapidly hydrolysable and slowly hydrolysable organic matter. The total biodegradable COD can be found from a long-term BOD-test combined with a curve-fit and the readily biodegradable and rapidly hydrolysable from a respirogram. The slowly hydrolysable is the difference between total biodegradable COD and the sum of readily biodegradable and rapidly hydrolysable COD. Simulation with characterization based on filtration for a pre-anoxic reactor with a certain N-removal compared with the N-removal of the same plant with wastewater according to the modified characterization shows different results of each wastewater, especially with regard to the effluent nitrate concentration.     

Application of remote monitoring and automatic control system using neural network for small wastewater treatment plants in Korea.

For this study, an automatic control system has been developed by using a neural network and internet-based remote monitoring system for efficient operation of plants that have a serious variance of influent loading and have difficulties in appropriate maintenance, just like small wastewater treatment plants in Korea. In the control algorithm, ORP was used as the main sensor for control. At the point where the ORP value was judged to reach the "nitrate knee" of denitrification and phosphorus release, ORP indicated the state of lower saturation read by the neural network and then changed the operating condition from the reduction state to the oxidation state. For example, if ORP indicates the state of higher saturation at the point of "nitrogen breakpoint" or "ammonia valley" of nitrification, the neural network reads it and cuts off the oxygen supply and mixing. The dORP data have been used as one of the main input for the neural network. After the operation of lab-scale cyclic aeration process using an automatic control system, it has been found that regardless of loading variance, more than 95% of organic matters and more than 60% of nitrogen and phosphorus have been removed. Assuming that an internet-connected computer and a basic web browser are available, this study has developed a remote monitoring system that can monitor the operating status of small plants or any troubles with them.     

Biological treatability of raw and ozonated synthetic penicillin formulation effluent.

Chemical pre-treatment of synthetic Procaine Penicillin G (PPG) effluent with ozone (applied dose = 1440 mg/h; treatment duration = 60 min) at pH = 7 was investigated. Successive biological treatability studies were performed with raw, ozonated penicillin formulation effluent and synthetic readily biodegradable substrate as simulated domestic wastewater. The PPG effluent additions were adjusted to constitute approximately 30% of the total COD in the reactor. Ozonation of PPG effluent resulted in practically complete removal of the parent pollutant accompanied by 40% COD abatement. Speaking for the raw PPG effluent, prolonged acclimation periods were necessary to obtain significant COD removal efficiencies. Batch activated sludge treatment experiments and respirometric studies have demonstrated that the selection of true retention time is extremely crucial for having high amount of slowly hydrolysable substrate or complex wastewater, like pharmaceutical effluent. The effect of ozonation time on biological treatability performance of PPG has been evaluated in the study. Pre-ozonation of PPG effluent did not improve its ultimate biodegradability.     

滑坡体力学参数反分析研究

除室内试验和现场试验之外,反演分析是一种可以利用现有变形监测数据获取滑坡体等效力学参数的方法.以清江杨家槽滑坡体为例进行研究,提出了将均匀设计、遗传算法与BP神经网络结合起来应用于滑坡体反分析的新方法.先将具有很好全局寻优能力的改进遗传算法作为BP神经网络的学习算法,形成遗传神经网络;然后利用均匀设计方法设计网络学习样本,训练遗传神经网络映射滑坡体变形与滑坡体力学参数的非线性关系;最后将实测位移值作为网络输入,网络输出即为参数的反演值.该方法克服了优化反分析方法反演时间过长,解不易收敛等缺陷,实现了多参数的同时反演.通过对反分析结果进行检验与评价,证明其结果符合实际工程要求.     

基于EEMD-GA-BP模型的大坝变形监测数据预测

针对大坝自动监测数据序列存在的不稳定性和测值漂移问题,提出了基于集合经验模态分解(EEMD)和遗传(GA)BP神经网络的大坝变形监测数据预测方法。采用EEMD技术提取反映大坝真实变形的低频信号,剔除自动监测系统数据中存在的噪声和野值,利用遗传算法优化的BP神经网络对真实信号进行学习与外推,据此构建EEMD-GA-BP模型。利用本文模型计算得到大坝变形的预测值,将其与实测变形值进行对比,并根据残差大小比较了本文方法与其它方法的预测效果。算例表明,本文提出的组合模型能有效地提高大坝变形预测精度。     

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.     

SBR工艺动力学研究与工程应用

棉浆粕废水组分较为复杂,治理具有一定的技术难度,采用两相厌氧、序批式活性污泥法和物化处理组合工艺取得了较好的效果。生产运行结果表明:SBR工艺对COD,BOD的去除效率分别达到40％～57％和55％～70％。在水温自然变化情况下,测定了好氧SBR单元的生化动力学参数,并与已有文献报道的纸浆和造纸废水的测定结果进行了比较,表明棉浆粕废水经两相厌氧处理后的出水更易于生化处理,但仍属较难好氧生化处理废水。     

基于模糊神经网络和遗传算法的大坝安全监控模型

应用监控模型来监控大坝的工作性态是一条有效途径 ,但由于大坝工作条件复杂 ,影响因素繁多 ,为以精确的数学模型进行描述带来了很大的困难 ,而应采用从定性到定量的综合集成的方法 ,将专家知识、监测数据和各种信息与计算机软硬件技术结合起来 ,把坝工理论和坝工专家的经验结合起来对其进行研究。文中应用模糊神经网络和遗传算法等人工智能技术 ,依据专家的经验确定隶属函数 ,从而建立模糊神经网络预报模型 ,根据专家对实际情况的正确分析 ,对预报结果进行修正 ,达到进一步提高预报精度的目的     

水质自动监测系统的组成及控制原理

广东省马口水文站应用的水质自动监测系统(WQMS)是一套以在线自动分析仪、可编程控制器PLC为核心,运用现代传感器技术、自动测量技术、自动控制技术、计算机应用技术以及相关的专用分析软件和通信网络所组成的综合性监测系统.该系统可以实现水质的实时连续监测和远程控制,达到及时掌握主要流域重点断面水体的水质状况、预警预报重大或流域性水质污染事故、解决跨行政区域的水污染事故纠纷、监测总量控制制度落实情况.     

Performance evaluation of physicochemical processes for biologically pre-treated livestock wastewater.

The use of a combination of biological and physicochemical methods is a promising technique to reduce highly concentrated pollutants in livestock wastewater: firstly, biodegradable organic matters, nitrogen and a part of phosphorus should be removed in a biological treatment process and then residual non-biodegradable organic matters, color and phosphorus be eliminated by physicochemical methods. In this study, therefore, the integrations of chemical coagulation, activated carbon adsorption, Fenton oxidation and ozonation were evaluated to provide an appropriate post-treatment process for biologically pre-treated livestock wastewater. With applying a single method such as coagulation and Fenton oxidation, a yellowish brown color and COD still remained. According to the experimental result, the quality of treated wastewater including color was enough to be discharged after chemical coagulation followed by ozonation or Fenton oxidation process. Among these, ozonation was the most effective technology for decolorization. Neither simple biological nor physicochemical process provides an adequate treatability for the sufficient depletion of organics and decolorization when treating livestock wastewater. Considering only the removal efficiency, the integration of Fenton oxidation and ozonation would be an efficient alternative as a post-treatment.     

An intelligent singular value diagnostic method for concrete dam deformation monitoring

Extracting implicit anomaly information through deformation monitoring data mining is highly significant to determining dam safety status.As an intelligent singular value diagnostic method for concrete dam deformation monitoring,shallow neural network models result in local optima and overfitting,and require manual feature extraction.To obtain an intelligent singular value diagnosis model that can be used for dam safety monitoring,a convolutional neural network(CNN)model that has advantages of deep learning(DL),such as automatic feature extraction,good model fitting,and strong generalizability,was trained in this study.An engineering example shows that the predicted result of the intelligent singular value diagnostic method based on CNN is highly compatible with the confusion matrix,with a precision of 92.41%,receiver operating characteristic(ROC) coordinates of(0.03,0.97),an area-under-curve(AUC) value of 0.99,and an F1-score of 0.91.Moreover,the performance of the CNN model is better than those of models based on decision tree(DT) and k-nearest neighbor(KNN) methods.Therefore,the intelligent singular value diagnostic method based on CNN is simple to operate,highly intelligent,and highly reliable,and it has a high potential for application in engineering.     

基于BP神经网络的温榆河水质参数反演模型研究

为进一步提高内陆水体水质参数遥感反演的准确性,北京市温榆河被选为研究对象,研究选取ETM＋数据和准同步实测水质指标（浊度、BOD;）数据,建立了多个隐含层数目为1的BP神经网络模型,并选出分别针对浊度和BOD5的最佳神经网络模型,利用ETM＋影像的波段组合值反演了浊度和BOD,浓度值。最后将其反演结果与常规多元线性回归模型的反演结果进行精度比较。结果表明：温榆河的水质参数遥感反演为非线性问题,使用BP神经网络方法进行浊度与BOD,两种水质参数反演的结果优于线性回归方法的反演结果。     

Reuse of a dyehouse effluent after being treated with the combined catalytic wet peroxide oxidation process and the aerated constructed wetland.

A catalytic wet peroxide oxidation process was combined with the aerated constructed wetland in order to treat the raw dyehouse wastewater to in acceptable level for reuse as washing process water. More than 90% of BOD and CODs could be removed with the wet peroxide oxidation reactor and the remaining pollutants in the treated water were transformed into biodegradable ones which could have been successfully treated at the following aerated constructed wetland. The highest values of BOD5, CODMn, CODCr, SS and T-N in the treated water were 1.6, 1.8, 2.1, 0.5 and 12.8 mg/L, respectively. These values were low enough for the treated water to be reused at the washing process.     

Development of a new process for treatment of a pharmaceutical wastewater

In this study a process for biological treatment of toxic wastewater from a pharmaceutical company was developed. By simulations on a laboratory scale, the contribution of organic material and toxicity in wastewater from different sources was determined and the degradability of specific compounds were studied. The information obtained from these tests was used to improve the treatability of the wastewater at the sources. As an example a persistent organic phosphorous compound could be degraded after pre-treatment with chemical hydrolysis. By further simulations on a laboratory scale it was possible to screen through a large number of process configurations to determine the best working biological treatment A combination of fungal and bacterial treatment was found to remove toxicity from the wastewater more than a conventional bacterial treatment. The results from the laboratory studies were confirmed in pilot tests. A full scale treatment plant, which design is based on the results from these studies are presently under construction.     

Comparison of the nutrient removal efficiency of onsite wastewater treatments systems: applications of conventional sand filters and sequencing batch reactors (SBR).

When domestic wastewater was treated with different onsite applications of buried sand filters and sequencing batch reactors, good organic matter removal was common and effluent BOD7 concentrations from 5 to 20 mg/l were easily achievable. For total nitrogen, effluent concentrations were usually between 20 and 80 mg/l. Good phosphorus removal, even using special adsorption or precipitation materials, was difficult to achieve and large variations occurred. The median effluent concentration of total phosphorus in the most successful sand filter application was less than 0.1 mg/l and other sand filters and SBRs had the median concentrations varying from 1.7 to 6.7 mg/l. These results are based on one year in situ monitoring of 2 conventional buried sand filters, 6 sand filter applications with special phosphorus adsorbing media within the filter bed, 5 sand filters with separate tertiary phosphorus filtration and 11 small SBRs of three different types. The study was carried out in southern Finland during 2003-05. The whole project included monitoring of more than 60 plants of 20 different treatment types or methods, used in normal conditions to treat domestic wastewater. Evaluation of the different systems was made by comparing the measured effluent concentrations. In addition the effluent concentrations were compared to the discharge limits calculated according to the new Finnish regulation.     

北京市水体水质自动监测与评价系统建设

北京市水体水质自动监测与评价系统以现代水质监测技术、数据库技术、地理信息技术和网络技术为载体,通过建立水质自动连续监测站、网络综合数据库、评价分析软件、预测模型、网络发布系统,来记录、查询、评价各类水体水环境监测结果,根据其变化情况分析水质变化规律,预测其趋势,并直观地反映在图形上,为上级领导部门决策提供可靠依据.     

Multi-component kinetics of activated sludge treatment of bleached kraft mill effluent.

This study investigated the discrepancies between the BOD removal rates measured during short term assays and those measured during continuous activated sludge treatment of bleached kraft mill effluent (BKME). A combination of batch tests and fed batch tests with oxygen uptake rate (OUR), chemical oxygen demand (COD), biochemical oxygen demand (BOD), and mixed liquor volatile suspended solids (MLVSS) measurements were used to characterize the degradation rates for the activated sludge treatment of BKME and to divide the soluble readily biodegradable substrate into two to five separate fractions based on biodegradation rates. The removal rates varied by over an order of magnitude between the most readily degradable substrates (1 x 10(-3) mg COD/mg MLVSS minute), and the more slowly degradable substrates (2 x 10(-5) mg COD/mg MLVSS minute). If the readily biodegradable fraction of BKME was modeled as one substrate, initial rate kinetic measurements from batch tests were heavily influenced by the fractions with the greatest degradation rates, while any remaining BOD in the treated effluent was predominantly from the slowly degradable fraction, giving inconsistent results. Taking the multi-component nature of the wastewater into account, batch test results can be used to predict fed-batch and continuous activated sludge reactor performance.     

新型在线泥沙粒度与含沙量测控系统设计

为了实现河工模型试验中泥沙粒度级配的在线实时测量与含沙量控制,设计了新型在线泥沙粒度与含沙量自动测量控制系统。采用了在线湿法超声波粒度分析仪（OUPS）,并结合新型潜水排污泵等先进辅助设备,构成了两种泥沙自动控制系统,即“OPUS及循环管道含沙量自动控制系统”和“OPUS及螺杆泵含沙量自动控制系统”。简要介绍了在线超声波粒度分析仪的测量原理与性能,以及自动测量控制系统的测控原理与设计要点,为河工模型提供了先进的泥沙颗粒分析与含沙量自动量测控制试验平台。     

Photocatalytical polishing of paper-mill effluents.

Photocatalytic oxidation (PCO) is a promising technology for purification of biological pretreated wastewater or destruction of non-biodegradable compounds. For this reason PCO has been investigated as a last step of purification of biologically pre-treated paper-mill effluents. The influence of the parameters pH, TiO2-modification, TiO2-concentration, catalyst re-use, concentration of substances to be oxidised (wastewater quality) has been determined. The TOC of the biologically pretreated wasterwater was up to 55 mg L(-1). This wastewater was treated with a previously presented aerated cascade photoreactor which was modified for batch experiments. A high specific oxidation rate of up to 0.76 g TOC m(-2) h(-1) as well as a complete TOC mineralization has been achieved after the optimisation of the process parameters. The complete destruction of recalcitrant compounds will offer the opportunity to reuse the wastewater in the production process. The increase of the BOD5/TOC ratio after a short irradiation period indicates the transformation of recalcitrant organic compounds to better biodegradable intermediates. The use of PCO as a pre-treatment step for the enhancement of the biodegradability of wastewater, containing recalcitrant or inhibitory compounds is an alternative to a long and energy-intensive total pollutant mineralization.