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SIMDEUM: water demand in distribution network modelling Mirjam Blokker 20 November 2009 – ColloquiumTU Delft.

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Presentation on theme: "SIMDEUM: water demand in distribution network modelling Mirjam Blokker 20 November 2009 – ColloquiumTU Delft."— Presentation transcript:

1 SIMDEUM: water demand in distribution network modelling Mirjam Blokker 20 November 2009 – ColloquiumTU Delft

2 2 Watercycle Research Institute From transport model …

3 3 Watercycle Research Institute … to a more detailed model …

4 4 Watercycle Research Institute … to an all-pipes model

5 5 Demand allocation: top-down or bottom-up?

6 6 Watercycle Research Institute Is a bottom-up demand allocation the future? Practical considerations Is it necessary for specific purposes? Hydraulics influence WQ processes Choice in spatial and temporal aggregation influences hydraulic model results Effect of Bottom-Up or Top-Down demand allocation in real network

7 7 Watercycle Research Institute Pulse Intensity Flow Intensity Time Time Basic principle of stochastic demand model Source: Buchberger, 2007

8 8 Watercycle Research Institute SIMDEUM: parameters follow from surveys and information on appliances How often did you flush the toilet? How long did you take a shower for? When did you get up, leave the house, go to bed? Siemens typical patterns  I D No flow measurements

9 9 Watercycle Research Institute Compare: flows 43 homes Zandvoort, 1000 homes office

10 10 Watercycle Research Institute compare: travel times

11 11 Watercycle Research Institute Practical considerations – automatic linking data SIMDEUM Census data Land register Pipe information system connections Customer information

12 12 Watercycle Research Institute Skeletonize and aggregation

13 13 Watercycle Research Institute Hydraulics influence water quality processes High flows can re-suspend particles or slough biofilm Dissolved substances move with the water; may also disperse in case of laminar flows Non-conservative substances (chlorine) decrease under influence of contact time and e.g. temperature …

14 14 Watercycle Research Institute (AOC and dissolved solids) Suspended solids © J.H.G. Vreeburg Regular deposition & resuspension Biofilm formation & sloughing Corrosion Precipitation & flocculation Suspended solids incidental resuspension (AOC and dissolved solids) WQ processes in the distribution network

15 15 Watercycle Research Institute Suspended solids © J.H.G. Vreeburg Regular deposition & resuspension Biofilm formation & sloughing Suspended solids incidental resuspension hydraulic processes in the distribution network particles / wall interaction Maximum shear stress or velocity

16 16 Watercycle Research Institute (AOC and dissolved solids) © J.H.G. Vreeburg Biofilm formation Corrosion (AOC and dissolved solids) hydraulic processes in the distribution network dissolved substances / wall interaction Residual chlorine is related to Contact time (travel time) Temperature Biostability (incoming water quality)

17 17 Watercycle Research Institute (AOC and dissolved solids) hydraulic processes in the distribution network dissolved substances / dispersion v max v Stagnant flow, v = 0 m/s Laminar flow, v max = 2 * v mean = 0,04 m/s Turbulent flow, v max = 1.2 * v mean = 1,0 m/s v max v

18 18 Watercycle Research Institute SIMDEUM: SIMulation of Demand, an End-Use Model SIMDEUM was developed and validated with flows and travel times Conclusion: SIMDEUM generates realistic demand patterns, and thus a proper BU model can be constructed. Next step: Determine difference between current (TD) method and new (BU) method

19 19 Watercycle Research Institute Choice in spatial and temporal aggregation influences hydraulic model results

20 20 Watercycle Research Institute Correlation – level pumping station R = 0.99 Auto correlation (5 min) R = 1

21 21 Watercycle Research Institute Correlation – level 150 homes R = 0.68 Auto correlation (5 min) R = 0.84 R = 0.80

22 22 Watercycle Research Institute R = 0.26 Auto correlation (5 min) R = 0.66 R = 0.44 Correlation – level single home

23 23 Watercycle Research Institute Effect of Bottom-Up or Top-Down demand allocation in real network (Purmerend) Two network models: BU: model + SIMDEUM demand patterns Each connection has unique demand pattern Time step is 0.01 h (36 s) TD: model + sum demand pattern Sum pattern is the total flow of BU model Time step is 5 min

24 24 Watercycle Research Institute Purmerend network

25 25 Watercycle Research Institute Effect of Bottom-Up or Top-Down demand allocation in real network (Purmerend) 1.Cross correlation with respect to incoming flow 2.Flow direction reversals 3.Flow regime: stagnant, laminar, turbulent flow 4.Travel time 5.Maximum velocity

26 26 Watercycle Research Institute 1. Cross correlation BU TD=1

27 27 Watercycle Research Institute 2. Flow direction reversals BU TD =0: no reversals =1: 50% reversals

28 28 Watercycle Research Institute 3.a Stagnant flow BU TD Mainly at connection lines

29 29 Watercycle Research Institute 3.b Laminar flow BU TD Also at connection lines

30 30 Watercycle Research Institute 3.c Turbulent flow BU TD

31 31 Watercycle Research Institute 4. Travel times BU TD At 0:00 h (simulation run 48 h)

32 32 Watercycle Research Institute Travel times, average or accounting? …the longer water is in contact with the fabric of the distribution system, the higher the propensity for water quality problems to occur, and it is feasible that a small volume of poor quality water could conceivably harbor enough bacteria to cause failed regulatory samples and pose a public health risk.

33 33 Watercycle Research Institute 5. Max flow velocities BU TD

34 34 Watercycle Research Institute Quantifying effect of Bottom-Up or Top-Down demand allocation in real network 1.Cross correlation 2.Flow direction reversals 3.Flow regime: a.Stagnant flow b.Laminar flow c.Turbulent flow 4.Travel time 5.Maximum velocity 1.Large effect on diameter < 200 mm 2.Large effect 3. a.Effect in branch ends b.Effect in branch ends c.Limited effect 4.Limited effect on average travel times, more effect on variation 5.Effect especially noticeable on smaller pipe diameters and in branch ends

35 35 Watercycle Research Institute When is a BU model required? Tracing contaminants: when is the water save again, including for customers at the outskirts of the network? Id. for residual chlorine Hydraulics and water quality in branched networks Dispersion Flow direction reversals Maximum velocities Network fouling

36 36 Watercycle Research Institute Is a bottom-up demand allocation the future? Practical considerations Yes – automatic demand generation and allocation Possibly followed by skeletonization / aggregation step Is it necessary for specific WQ purposes? Self-cleaning network design: yes, in simplified form (uni-directional only) Tracing dissolved substances: yes in the outskirts (dispersion, flow direction reversals); yes in case maximum travel time is important (non-conservative substances)

37 SIMDEUM: water demand in distribution network modelling Mirjam Blokker 20 November 2009 – Colloquium

38 38 Watercycle Research Institute WQ in DWDS contamination propagation corrosion sedimentation and re-suspension coagulation, flocculation, precipitation disinfectant decay DBP formation bacterial re-growth Biofilm formation nitrification taste and odour Advection flows dispersion mixing at junctions inertia compressibility water / pipe Reaction initial WQ residence time / contact time temperature shear stress interaction with wall or other processes Water demand model temporal scale spatial scale stochastic / deterministic Accuracy auto (temporal) correlation cross (spatial) correlation probability of stagnation probability of laminar flow probability of turbulent flow Field data flow measurements tracer test monitoring WQ process water-use related surveys

39 39 Watercycle Research Institute WQ – an ADR model Advection Dispersion Reaction The concentration (C) of a dissolved or particulate substance changes through the network by (plug) flow, through dispersion (esp. laminar flow) and reaction (with pipe wall or other substances)

40 40 Watercycle Research Institute Water demand influences water quality Water demand determines flow, which influences Advection (plug flow, flow direction reversal) Dispersion (flow regime: stagnant / laminar / turbulent) Reaction Contact time (travel time) Temperature (travel time, flow velocity) Wall interaction (flow regime) Shear stress (maximum velocity) …?


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