截流式合流制排水管网设计新思路

提出了一种以溢流井为分界线,将截流式合流制排水管网分解为一系列小型完全合流制排水管网的设计新思路,并以管网关联矩阵和节点连接特性矩阵为基础,以节点平衡原理和节点递归算法为核心,实现完全合流制排水管网的流量计算和水力计算.该方法能有效减小管网计算模型的规模,降低程序设计难度,提高程序的实用性.     

Dynamic optimisation of WWTP inflow to reduce total emission.

A prerequisite for an integrated control of sewer and wastewater treatment plant (WWTP) is a capacity driven inflow control to WWTP. This requires reliable information about the current status of WWTP operation and its behaviour on varying hydraulic, COD and nutrient loads. So far most of the proposed control strategies are based on hypothetical modelling studies. In this paper the behaviour of three large WWTPs on increased storm water loads is analysed based on online measurements of several years. In all cases the main limiting factors for an increase of load were the sedimentation processes in the secondary clarifier and the nitrification capacity. In one case study predictive control strategies have been developed observing these processes which are backboned by effluent control. Tests using an integrated model of sewer and WWTP demonstrate that inflow control on emission load varies significantly with rain intensity.     

Soft sensing of water depth in combined sewers using LSTM neural networks with missing observations

Information and communication technologies combined with in-situ sensors are increasingly being used in the management of urban drainage systems. The large amount of data collected in these systems can be used to train a data-driven soft sensor, which can supplement the physical sensor. Artificial Neural Networks have long been used for time series forecasting given their ability to recognize patterns in the data. Long Short-Term Memory (LSTM) neural networks are equipped with memory gates to help them learn time dependencies in a data series and have been proven to outperform other type of networks in predicting water levels in urban drainage systems. When used for soft sensing, neural networks typically receive antecedent observations as input, as these are good predictors of the current value. However, the antecedent observations may be missing due to transmission errors or deemed anomalous due to errors that are not easily explained. This study quantifies and compares the predictive accuracy of LSTM networks in scenarios of limited or missing antecedent observations. We applied these scenarios to an 11-month observation series from a combined sewer overflow chamber in Copenhagen, Denmark. We observed that i) LSTM predictions generally displayed large variability across training runs, which may be reduced by improving the selection of hyperparameters (non-trainable parameters); ii) when the most recent observations were known, adding information on the past did not improve the prediction accuracy; iii) when gaps were introduced in the antecedent water depth observations, LSTM networks were capable of compensating for the missing information with the other available input features (time of the day and rainfall intensity); iv) LSTM networks trained without antecedent water depth observations yielded larger prediction errors, but still comparable with other scenarios and captured both dry and wet weather behaviors. Therefore, we concluded that LSTM neural network may be trained to act as soft sensors in urban drainage systems even when observations from the physical sensors are missing.     

Reducing the total discharge from a large WWTP by separate treatment of primary effluent overflow.

At many large wastewater treatment plants (WWTPs) the increased hydraulic load, caused by combined sewer systems during storm events, results in primary effluent overflow when the capacity of further treatment is exceeded. Due to stringent effluent standards, regulating the total discharge from the WWTPs, the Rya WWTP in G?teborg and the Sj?lunda WWTP in Malm? will have to reduce the impact of primary effluent overflow. Separate, high rate, precipitation processes operated only during high flow conditions have been investigated in pilot units at the two WWTPs. Precipitation in existing primary settlers operated at a surface loading of 3.75 m/h removed phosphorus to 0.35 mg/l. The Actiflo process was also shown to remove suspended solids and phosphorus well. BOD was reduced by 50-60%. With such processes the overall effluent concentrations from the plants can be reduced significantly. Key upgrading features are small footprints, short start up time and high efficiency.     

图神经网络驱动的流域洪水预报技术

本研究提出了一个图指导的时空关联预报模型（GSCPM，graph-guided spatiotemporal correlation prediction model），针对性地解决流域洪水预报中的时空关系建模和滞后影响问题。该模型通过多个长短期记忆网络（LSTM）编码每个监测点历史属性的时间关联特征，随后利用图卷积神经网络（GCN）挖掘监测点间的地理空间依赖。此外，提出了雨量滞后特征、泄洪量滞后特征和上游水位滞后特征用以挖掘变量滞后效应。本文在现实流域数据集上进行了广泛的实验，通过跟LSTM、RNN 等模型的比较，证明了GSCPM 模型的优越性，适合在流域洪水预报中推广使用。     

Potentials of real time control, stormwater infiltration and urine separation to minimize river impacts: dynamic long term simulation of sewer network, pumping stations, pressure pipes and waste water treatment plant.

River Panke (Berlin, Germany) suffers from hydraulic peak loads and pollutant loads from separate sewers and combined sewer overflows (CSOs). Pumping the wastewater through long pressure pipes causes extreme peak loads to the wastewater treatment plant (WWTP) during stormwater events. In order to find a good solution, it is essential not to decide on one approach at the beginning, but to evaluate a number of different approaches. For this reason, an integrated simulation study is carried out, assessing the potentials of real time control (RTC), stormwater infiltration, storage and urine separation. Criteria for the assessment are derived and multi-criteria analysis is applied. Despite spatial limitations, infiltration has the highest potential and is very effective with respect to both overflows and the WWTP. Due to a high percentage of separate systems, urine separation has a similar potential and causes the strongest benefits at the WWTP. Unconventional control strategies can lead to significant improvement (comparable to infiltrating the water from approximately 10% of the sealed area).     

Integrated modelling of sewer system and wastewater treatment plant for investigating the impacts of chemical dosing in sewers

Chemicals are often dosed to control the production and accumulation of hydrogen sulfide in sewers. The biological and/or chemical actions of these chemicals have profound impacts on the composition of wastewater entering a WWTP, thereby affecting its performance. In this paper, an integrated modelling methodology for simultaneously investigating the effects of dosing of chemicals in sewer network and N and P removal at the downstream WWTP is reported. The sewer system is modelled using a sewer model (SeweX), and the WWTP is modelled using ASM2d model with some modifications. The importance of integrated modelling in sewer management is also demonstrated.     

Monitoring in inline storage sewers for stormwater treatment to determine efficiencies.

A special structure of combined sewer overflow tanks is the inline storage sewer with downstream discharge (SKU). This layout has the advantage that besides the sewer system, no other structures are required for storm water treatment. Consequently only very little space is required and compared to combined sewer overflow tanks, there is an enormous potential in reducing costs during construction. To investigate the efficiency of an inline storage sewer, a monitoring station was established in Dortmund-Scharnhorst, Germany. The monitoring station was in operation for a period of 2.5 years. Within this period water samples were taken during a total of 20 discharge events. Besides the complete hydraulic data collection, seven water samplers took more than 5,000 water samples during dry and wet weather. This adds up to a total of more than 20,000 individual lab analyses. The average of the total efficiency for the SKU-West is 86%. 29% of this efficiency can be attributed to the throttle flow. The remaining 57% can be divided into a part of 48% that can be attributed to the process storage and 9% that can be attributed to sedimentation and erosion process.     

Lake Level Prediction using Feed Forward and Recurrent Neural Networks

The protection of high quality fresh water in times of global climate changes is of tremendous importance since it is the key factor of local demographic and economic development. One such fresh water source is Vrana Lake, located on the completely karstified Island of Cres in Croatia. Over the last few decades a severe and dangerous decrease of the lake level has been documented. In order to develop a reliable lake level prediction, the application of the artificial neural networks (ANN) was used for the first time. The paper proposes time-series forecasting models based on the monthly measurements of the lake level during the last 38 years, capable to predict 6 or 12 months ahead. In order to gain the best possible model performance, the forecasting models were built using two types of ANN: the Long-Short Term Memory (LSTM) recurrent neural network (RNN), and the feed forward neural network (FFNN). Instead of classic lagged data set, the proposed models were trained with the set of sequences with different length created from the time series data. The models were trained with the same set of the training parameters in order to establish the same conditions for the performance analysis. Based on root mean squared error (RMSE) and correlation coefficient (R) the performance analysis shown that both model types can achieve satisfactory results. The analysis also revealed that regardless of the model types, they outperform classic ANN models based on datasets with fixed number of features and one month the prediction period. Analysis also revealed that the proposed models outperform classic time series forecasting models based on ARIMA and other similar methods .

     

A CFD Modeling Approach for Municipal Sewer System Design Optimization to Minimize Emissions into Receiving Water Body

The design of the urban sewage system is site specific, and it makes the use of three-dimensional (3D) model an alternative to a field study or a laboratory experiment. However, the use of 3D computational fluid dynamics (CFD) in the study of the urban sewage system has been generally limited to the study of a single structural component with simplified assumptions. In this study, the 3D model that adopted the renormalized group (RNG) k-ε turbulence model, the volume of fluid (VOF) free water surface model and the particle tracking approach was verified comparing the predicted flow field data with the measurements in laboratory scale experiments. Then, the model was applied to optimize the design of the combined sewer system (CSS) in the city of Edmonton with multiple hydraulic structures. Considering the details of predicted flow characteristics and the behaviors of the suspended solids, the final design was chosen and implemented to reduce the water pollution induced by the direct combined sewer overflow (CSO) discharge to the receiving water body. It is shown that the proposed 3D CFD modeling approach is a cost-effective tool to design the municipal sewer system.     

An integrated approach for improving the wastewater discharge and treatment systems

Since treatment plants have been built all over Germany during the last decades, the water quality of receiving streams has been improved remarkably. But there are still a lot of quality problems left, which are caused e.g. by combined sewer overflows (CSO), treatment plant effluents or rainwater discharges from separate sewer systems. At present different efforts are undertaken to control sewer systems in order to improve the operation of urban drainage systems or more generally, design processes. The Emschergenossenschaft and Lippeverband (EG/LV) are carrying out research studies, which are focusing on a minimization of total emissions from sewer systems both from wastewater treatment plant (WWTP) effluents and from CSO. They consider dynamic interactions between rainfall, resultant wastewater, combined sewers, WWTP and receiving streams. Therefore, in an advanced wastewater treatment, a model-based improvement of WWTP operation becomes more and more essential, and consequently a highly qualified operational staff is needed. Some aspects of the current research studies are presented in this report. The need and the use of an integrated approach to combine existing model components in order to optimize dynamic management of combined sewer systems (CSS) with a benefit for nature are outlined.     

明满流过渡及跨临界流一维数值模拟

介绍了跨临界流及明满流在国外的研究进展,采用普雷斯曼格式辅以删减对流加速度项法和Preissmann狭缝法建立了一套能够处理缓流、急流、跨临界流和明满流的数学模型。为了验证所建模型的可行性,计算了多个具有解析解或试验结果的算例,结果表明吻合程度良好。     

枚举法和动态规划法在污水管网布置优化中的应用

用VB语言编写污水管网布置优化计算程序,从污水有向网络图出发,以污水管网系统费用最低为优化目标,并结合图论理论知识,应用枚举法将污水管网的所有可能的布置形式全部列出,同时利用水力参数优化计算,进行动态规划剪枝,选出污水管网最优的布置形式及其相应的最优水力参数.     

The hydraulic capacity of deteriorating sewer systems.

Sewer and wastewater systems suffer from insufficient capacity, construction flaws and pipe deterioration. Consequences are structural failures, local floods, surface erosion and pollution of receiving waters bodies. European cities spend in the order of five billion Euro per year for wastewater network rehabilitation. This amount is estimated to increase due to network ageing. The project CARE-S (Computer Aided RE-habilitation of Sewer Networks) deals with sewer and storm water networks. The final project goal is to develop integrated software, which provides the most cost-efficient system of maintenance, repair and rehabilitation of sewer networks. Decisions on investments in rehabilitation often have to be made with uncertain information about the structural condition and the hydraulic performance of a sewer system. Because of this, decision-making involves considerable risks. This paper presents the results of research focused on the study of hydraulic effects caused by failures due to temporal decline of sewer systems. Hydraulic simulations are usually carried out by running commercial models that apply, as input, default values of parameters that strongly influence results. Using CCTV inspections information as dataset to catalogue principal types of failures affecting pipes, a 3D model was used to evaluate their hydraulic consequences. The translation of failures effects in parameters values producing the same hydraulic conditions caused by failures was carried out through the comparison of laboratory experiences and 3D simulations results. Those parameters could be the input of 1D commercial models instead of the default values commonly inserted.     

Interaction between the treatment plant and the sewer system in Halmstad: Integrated upgrading based on real time control

In Halmstad, Sweden great efforts have been made during the 1990's to improve the functionality and to reduce the environmental impact of the sewer system and the wastewater treatment plant The investment and rehabilitation program includes to a great extent an effective use of existing resources. The wastewater treatment plant is reconstructed to meet increased nutrient removal demands. A five year rehabilitation plan for the sewer system is under completion, where the measures mainly are motivated by the aim to reduce the combined sewer overflow volumes and to minimize the risk of local flooding. It was soon realized that an integrated use of storage volumes at the wastewater treatment plant and within the sewer system could improve the general conditions for the treatment at the plant. To implement this strategy a real time control system was introduced by installing controllable weirs and flow control devices in the main sewer. The article describes the background of the sewerage master plan, how the upgrading work has been carried out by means of simulations and measurement, gives examples of some expected potential benefits, and outlines plans for the future.     

Optimisation and control of the inflow to a wastewater treatment plant using integrated modelling tools

The present paper describes the Heisingborg Pilot Project, a part of the Technology Validation Project: “Integrated Wastewater” (TVP) under the EU Innovation Programme. The objective of the Heisingborg Pilot Project is to demonstrate implementation of integrated tools for the simulation of the sewer system and the wastewater treatment plant (WWTP), both in the analyses and the operational phases. The paper deals with the programme for investigating the impact of real time control (RTC) on the performance of the sewer system and wastewater treatment plant As the project still is in a very early phase, this paper focuses on the modelling of the transport of pollutants and the evaluation of the effect on the sediment deposition pattern from the implementation of real time control in the sewer system.     

基于WD-COA-LSTM模型的月降水量预测

为进一步提高月降水量预测精度,提出了基于小波分解（WD）和郊狼优化（COA）算法的长短期记忆神经网络（LSTM）降水量预测模型（WD-COA-LSTM）。首先用小波分解对时间序列进行预处理,消除序列的非平稳性,得到1个低频序列和3个高频序列;然后通过郊狼优化算法对神经网络（LSTM）模型进行参数优化;最后将各子序列预测值叠加得到月降水量预测值。将提出的模型应用于洛阳市栾川县白土镇和洛宁县故县镇两个雨量站的月降水量预测中,并与LSTM、COA-LSTM、WD-LSTM模型预测结果进行对比。结果表明：提出的WD-COA-LSTM模型的预测精度最高,说明小波分解和郊狼优化算法能有效加强LSTM模型预测的精度和泛化能力,为月降水量的预测提供了一种新的途径。     

基于JPWSPC水动力模型的优化引水量计算分析

为提高水系河网水动力模拟的稳定性和计算效率,采用了汊点水位预测校正法(JPWSPC)处理缓流河网汊点和结构物连接处的回水效应,综合工程因素,建立了工程实例的河网一维水动力模型,计算分析了不同引水(分水)方案下河道水位过程和水力停留时间的变化。结果表明:在蓄水建筑物调蓄条件下,不同引水流量对河道水面面积和景观效果区别不大,河道的水力停留时间则与过流流量密切相关。通过优化调整引水量及河道分流比的模拟计算,为保证水资源高效利用、降低引水经济成本提供技术依据。     

Development and commissioning of decision support tools for sewerage management.

Managing sewerage systems is a highly complex task due to the dynamic nature of the facilities. Their performance strongly depends on the know-how applied by the operators. In order to define optimal operational settings, two decision support tools based on mathematical models have been developed. Moreover, easy-to-use interfaces have been created as well, aiding operators who presumably do not have the necessary skills to use modelling software. The two developed programs simulate the behaviour of both wastewater treatment plants (WWTP) and sewer network systems, respectively. They have essentially the same structure, including raw data management and statistical analysis, a simulation layer using the application programming interface of the applied software and a layer responsible for the representation of the obtained results. Four user modes are provided in the two software including the simulation of historical data using the applied and novel operational settings, as well as modes concerning prediction of possible operation periods and updates. Concerning the WWTP software, it was successfully installed in Nantes (France) in June 2004. Moreover, the one managing sewer networks has been deployed in Saint-Malo (France) in January 2005. This paper presents the structure of the developed software and the first results obtained during the commissioning phase.     

大型水利水电工程施工水力控制及灾害预测关键技术

针对我国西部山区大型梯级水利水电工程施工面临复杂环境下的导截流标准及风险控制、陡坡隧洞导流安全水力控制、深厚覆盖层河床安全经济截流水力控制、导截流过程灾害预测控制等新问题,经过长达28 a的系统研究,解决了大型梯级水利水电工程施工导截流水力控制和灾害减免的相关技术难题。包括:①构建了多梯级同建条件下施工导流系统风险评估模型和基于水文实时监测预报的截流标准决策模型,提出了满足安全性、经济性要求的标准优选方法,修订了施工导流设计规范;②揭示了陡坡隧洞易发生明满交替流等不良水力特性的成因及机制,提出了进口隔流浮堤消涡、锐缘进口减免明满交替流、出口压坡增压等复合式水力控制技术,保障了隧洞运行安全,提出的钢筋笼柔性毯和过水围堰分级整流防护新技术,解决了大流量、深厚覆盖层条件下度汛安全难题;③提出了考虑水深、流速分布、河床糙度、绕流系数影响的天然截流块体稳定实用计算公式以及六面体钢筋石笼人工截流块体稳定计算公式,计算精度更接近实际;④发明了内附透水反滤土工膜的四面体钢筋笼和圆柱线体新型截流材料;⑤提出了“水下宽戗堤” 新技术,减轻了截流难度;⑥首次提出了高陡岸坡滑坡涌浪过程中第二次涌浪为首浪的论点,建立了首浪高度实用计算公式、涌浪产生与传播预测模型;⑦提出了土石围堰溃决过程与洪水演进高分辨率模拟技术。这些关键技术对于推动相关学科发展、加快水利水电行业科技进步起到了巨大作用。