A New Alarm Generation Concept For Water Distribution Networks Based On Machine Learning Algorithms

Water Distribution Networks (WDNs) are critical infrastructures that are exposed to deliberate or accidental chemical, biological or radioactive contamination. A monitoring system capable of protecting a WDN against contamination events in real time is a big challenge needed to be accomplished. Powerful online sensor systems are currently developed and the prototypes are able to detect a small change in water quality. Consequently, the main objective of the project SMaRT-OnlineWDN is the development of an online security management toolkit for WDNs that is based on sensor measurements of water quality as well as water quantity. A new approach for the fast and reliable detection of abnormal events in the WDNs by an alarm generation module is presented in this paper. Although in the past several approaches have been investigated and implemented (e.g. CANARI of EPA), so far these alarm generation concepts haven\u27t been widely applied in real WDNs. Two reasons for that are: (1) The parameterization of existing alarm generation software products is too complex and time consuming, (2) a lot of abnormalities in the data appear due to special operational actions (e.g. sensor calibrations, flushing of pipes, rapid changes of water quality due to mixing of different water resources). To cope with this difficulties, in our approach the alarm generation module is trained both by historical data and in online mod using OPC technologies. Multi-variate statistical methods which need only a few parameters (e.g. Principal Component) are used. A fingerprint database is built up by the water utility experts and it is used to label known events. Results based on real WDN data of Berlin, Strasbourg and Paris are presented

SMaRT-OnlineWDN: A Franco-German Project For The Online Security Management Of Water Distribution Networks

Water Distribution Networks (WDNs) are critical infrastructures that are exposed to deliberate or accidental chemical, biological or radioactive contamination which need to be detected in due time. However, until now, no monitoring system is capable of protecting a WDN in real time. Powerful online sensor systems are currently developed and the prototypes are able to detect a small change in water quality. In the immediate future, water service utilities will install their networks with water quantity and water quality sensors. For taking appropriate decisions and countermeasures, WDN operators will need to dispose of: 1) a fast and reliable detection of abnormal events in the WDNs; 2) reliable online models both for the hydraulics and water quality predictions; 3) methods for contaminant source identification backtracking from the data history. Actually, in general none of these issues (1) – (3) are available at the water suppliers. Consequently, the main objective of the project SMaRT-OnlineWDN is the development of an online security management toolkit for WDNs that is based on sensor measurements of water quality as well as water quantity. Its main innovations are the detection of abnormal events with a binary classifier of high accuracy and the generation of real-time, reliable (i) flow and pressure predictions, (ii) water quality indicator predictions of the whole water network. Detailed information regarding contamination sources (localization and intensity) will be explored by means of the online running model, which is automatically calibrated to the measured sensor data. Its field of application ranges from the detection of deliberate contamination including source identification and decision support for effective countermeasures to improved operation and control of a WDN under normal and abnormal conditions (dual benefit).In this project, the technical research work is completed with a sociological, economical and management analysis

SMaRT-OnlineWDN D4.2 : Investigation sur les mécanismes des phénomènes spécifiés

The main objective of the SMaRT-OnlineWDN project is the development of an online security management toolkit for water distribution networks that is based on sensor measurements of water quality as well as water quantity. Pseudo-real time modelling of water quantity and water quality variables is the cornerstone of the project. Existing transport model tools are not adapted for online modelling and ignore some important phenomena that may be dominant when looking at the network in greater detail with an observation time of several minutes. The aim of this deliverable is to report investigations by the SMaRT-OnlineWDN partners regarding processes of contaminant mixing at junctions and transport in pipes. Firstly, investigations at the Berliner Wasserbetriebe (BWB) are presented (section 1). The test field is a simple loop with old cast iron pipes representative of old pipes in the BWB network. Chemicals can be injected into the pipe by a pump and three multi-parameter sensors, located at different distances, measure hydraulic and quality parameters (flow, pressure, conductivity pH-value, oxygen,…) during the flow. This network was calibrated for the roughness and the effective diameter of pipes which is reported here. Experiments with salt and its transport under different regimes was also studied. So the transport phenomena like advection, dispersion and absorption can be studied. Next, a statistic and hydraulic analysis of the Tee and cross-junctions is achieved on the two networks in France (Strasbourg CUS) and Vedif network (demand area of Villejuif) ) (section 2). It was found that there are a lot of cases where double tee-junctions are present with a distance inter-tee inferior to 10 diameters which may favour imperfect mixing. A hydraulic analysis was also performed which ensures that every hydraulic regime is well represented. For example, for a double-tee junction with equal 100mm diameter 40% of the Reynolds cases are for laminar flow and 80% are under 10,000. For higher diameters the statistics fall to 20% for laminar flow and 60% under 10,000. The results of this analysis serve to design the new test rig built in Dresden by TZW and supply CFD cases for the numerical simulation. Finally, in section 3, the new test rig at TZW (Dresden) and all the investigations that were necessary to know which product to inject, the injection system and the experimental setup are presented. First investigations at TZW have been performed applying several colour tracers with different densities under laminar and turbulent flow conditions The experiments were conducted in a straight pipe with velocities in a range of 0.004m/s to 0.5 m/s. The main results under laminar flow conditions are: 1) Dispersion is the main process for spreading and mixing, 2) The behaviour (moving up or down) of the tracer depends particularly on the density of the injected liquid, 3) An injected liquid with a higher or lower density than the water moves at the pipe wall with a lower velocity than the water body

SMaRT-OnlineWDN deliverable 4.3&4: Adaptation of transport equations and CFD Simulation of the transport phenomena and comparison with measured data

The main objective of the SMaRT-OnlineWDN project is the development of an online security management toolkit for water distribution networks that is based on sensor measurements of water quality as well as water quantity. Pseudo-real time modelling of water quantity and water quality variables is the cornerstone of the project. Existing transport model tools are not adapted for online modelling and ignore some important phenomena that may be dominant when lookingat the network in greater detail with an observation time of several minutes. The aim of this deliverable is to report investigations by the SMaRT-OnlineWDN partners about processes of contaminant mixing a T-junctions and transport in pipes

SMaRT-OnlineWDN deliverable 4.1 : Spécification des phénomènes qui doivent être modélisés

The main objective of the SMaRT-OnlineWDN project is the development of an online security management toolkit for water distribution networks that is based on sensor measurements of water quality as well as water quantity. Pseudo-real time modelling of water quantity and water quality variables are the cornerstone of the project. Existing transport model tools are not adapted for online modelling and ignore some important phenomena that may be dominant when looking at the network in greater detail with an observation time of several minutes. The aim of this deliverable is to define which phenomena should be considered in the online models. Firstly, existing models are described and the way water distribution networks are represented by graphs. Then, important phenomena that are missing are presented. The results are based on a bibliography study and the experience of the partners. Finally, a summary of conclusions is given. In summary, it is important to consider: 1)Inertia terms to make slow transient predictions of the hydraulic state. The velocity output will be slow-varying; 2)The hydrodynamic dispersion and possibly the molecular diffusion to improve the transport along a pipe and at junctions; 3)The imperfect mixing at Tee and Cross junctions depending on velocity inlets; 4)The diameter reduction and the wall roughness; It is proposed to calibrate these parameters on a regular basis (annual); 5)One chemical substance. It was also decided not to develop the model for 6)Pathogens; 7)Behaviour of multi-species; 8)Sedimentation. These are outside the scope of the project

SMaRT-OnlineWDN deliverable 4.1 : Spécification des phénomènes qui doivent être modélisés

The main objective of the SMaRT-OnlineWDN project is the development of an online security management toolkit for water distribution networks that is based on sensor measurements of water quality as well as water quantity. Pseudo-real time modelling of water quantity and water quality variables are the cornerstone of the project. Existing transport model tools are not adapted for online modelling and ignore some important phenomena that may be dominant when looking at the network in greater detail with an observation time of several minutes. The aim of this deliverable is to define which phenomena should be considered in the online models. Firstly, existing models are described and the way water distribution networks are represented by graphs. Then, important phenomena that are missing are presented. The results are based on a bibliography study and the experience of the partners. Finally, a summary of conclusions is given. In summary, it is important to consider: 1)Inertia terms to make slow transient predictions of the hydraulic state. The velocity output will be slow-varying; 2)The hydrodynamic dispersion and possibly the molecular diffusion to improve the transport along a pipe and at junctions; 3)The imperfect mixing at Tee and Cross junctions depending on velocity inlets; 4)The diameter reduction and the wall roughness; It is proposed to calibrate these parameters on a regular basis (annual); 5)One chemical substance. It was also decided not to develop the model for 6)Pathogens; 7)Behaviour of multi-species; 8)Sedimentation. These are outside the scope of the project

SMaRT-OnlineWDN D5.6 : Test et optimisation du modèle de simulation temps réel sur un réseau miniaturisé de distribution d'eau

For the performance of WP 5 and also WP 6 the Dresden test network was used. The communication between the different software packages via OPC was checked as well as the performance and functionality of different algorithms and models including the alarm generation module, transport and source identification calculations

SMaRT-OnlineWDN : Un Projet franco-allemand pour la gestion réel de la sécurité des réseaux de distribution d'eau

International audienceThe SMaRT-OnlineWDN project ́s main objective is to develop an early warning system and a decision support toolkit for emergencies and the deliberate contamination of water distribution networks. There are four parts in this Project. One is to find an optimal sensor network as a combination of different sensor types e.g.: quality and hydraulic sensors and an optimal sensor placement. Another one is developing an online running model, which is automatically calibrated to the measured sensor data and simulates the current hydraulic status of the WDN. The third part is developing a model with more accurate transport and mixing mechanisms. Once a contamination event has been detected, the source identification tool will locate the contamination source by using the inverse transport model. Then, the spread of contamination is found out by simulating the future hydraulic status and using a forecast on water demand. For validating the models, the methods and the data acquisition, experiments are done at a real world test track. The fourth part of the project is a Risk analysis by studying the likelihood and impacts of deliberate contamination and how to behave in this case and also how to inform customers. The decision support toolkit is completed by combining all parts together

Maternal control of early mouse development

The hiatus between oocyte and embryonic gene transcription dictates a role for stored maternal factors in early mammalian development. Encoded by maternal-effect genes, these factors accumulate during oogenesis and enable the activation of the embryonic genome, the subsequent cleavage stages of embryogenesis and the initial establishment of embryonic cell lineages. Recent studies in mice have yielded new findings on the role of maternally provided proteins and multi-component complexes in preimplantation development. Nevertheless, significant gaps remain in our mechanistic understanding of the networks that regulate early mammalian embryogenesis, which provide an impetus and opportunities for future investigations