SMaRT-Online WDN : Online Security Management and Reliability Toolkit for Water Distribution Networks
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1 SMaRT-Online WDN : Online Security Management and Reliability Toolkit for Water Distribution Networks Thomas Bernard, Mathias Braun, Fraunhofer Institute IOSB Olivier Piller, Denis Gilbert, IRSTEA Jochen Deuerlein, 3S Consult GmbH Andreas Korth, Reik Nitsche, DVGW-Technologiezentrum Wasser Marie Maurel, Veolia Environnement Anne-Claire Sandraz, Veolia Eau d Ile de France Fereshte Sedehizade, Berliner Wasserbetriebe Jean-Marc Weber, Communauté Urbaine de Strasbourg ISCRAM, Baden-Baden, Germany, May 14, 2013 SMaRT-OnlineWDN.eu
2 Online Monitoring of Drinking Water Networks 2 Water supply networks are constantly exposed to deliberate or accidental contamination. An online security management system should support the water supplier in planning countermeasures effectively and in short time: Where is the source of the contamination? What impact will the contamination have on the water distribution network? Which measures are needed to contain the harm?
3 Decision Support Tasks of 3
4 German-French Project 4 Project Partners Water Utilities Berliner Wasserbetriebe Communauté Urbaine de Strasbourg Veolia Eau d Ile-de-France Sponsored by Industry 3S Consult GmbH (Germany) Research Institutes IRSTEA (France) DVGW-Technologiezentrum Wasser (Germany) Fraunhofer Institute IOSB (Germany) Veolia Environment (France)
5 Overview 5 System architecture Optimal Sensor Placement Alarm Generation Module Online Simulation Model Online Source Identification Risk Analysis and Impact Assessment Real and Test Networks
6 System architecture of 6
7 Optimal Sensor Placement 7 Software tool for optimal placement of sensors in the drinking water network
8 Optimal Sensor Placement 8 Multi-Objective Optimization Problem Priorization of the partly conflicting performance criteria by water utilities
9 Alarm Generation Module 9 Aim: Detection of contaminations from various sensor information without false alarm
10 Alarm Generation Module 10 Training from historical data (method: PCA) Software modul with GUI developed Oxygene Conductivity Redox ph Turbidity
11 Online Simulation Model 11 State estimation Look-ahead-Simulations as decision support tool for planning of counter measures
12 Online Simulation Model 12 Berlin (östliche Hochstadt) After aggregation (no house connection pipes): -59,158 nodes -63,824 pipes (length ~ 1,960 km) -52,811 demands (~ 4,400 m³/h / 38,544,000 m³/a) Stations: - 1 water treatment plant - 2 transfer points - 1 booster pumping station - 3 valves with connections to other network parts - 5 online measuring devices - 38 measuring devices, that are not online
13 Transport Model at Junctions and Crossings 13 In most simulation software simplified assumptions regarding mixing at crossings and T-junctions are implemented (e.g. complete mixing, Bulk advective mixing) Especially for laminar flow (slow velocities) mixing is not perfect! Approach: Extract more accurate mixing models from 2D-/3D CFD simulations
14 Transport Model Result for T-Junction 14 For v rel ~ 0.25 and ~0.75 no ideal mixing!
15 Online Source Identification 15 Information about Contamination Source Prediction of dissemination
16 Risk Analysis and Impact Assessment 16 Real impacts and perceived ones are performed for the three aspects of sustainability: - environmental - social - economical, combined with technical innovation Feed back RISK ASSESSMENT Likelihood VS Vulnerability VS Consequences RISK MANAGEMENT: MITIGATION AND COMMUNICATION Scenarios and actions for risk management Cost-Benefit analysis of risk management actions VS Risk aversion
17 Real Networks investigated in the Project 17 Berlin Strasbourg Paris
18 Test Network at Berliner Wasserbetriebe 18
19 Test Network at TZW Dresden 19
20 20 Thanks for your Attention!
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