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

SIMDEUM: water demand in distribution network modelling Mirjam Blokker

20 November 2009 – Colloquium TU Delft

2Watercycle Research Institute

From transport model …


… to a more detailed model …


… to an all-pipes model

5

Demand allocation: top-down or bottom-up?

00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:000

1000

2000

3000

4000

tij d

Q (

m3/h

)

Sat

Sun

Mon

Tue

Wed

Thu

Fri

0:00 6:00 12:00 18:00 24:000

1

2

3

4

5

6

Q (

m3/h

)

Tue 13 J une

Wed 14 J une

0:00 6:00 12:00 18:00 24:000

0.05

0.1

0.15

0.2

0.25

Q (

l/s)


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


Pulse Pulse IntensityIntensity

FlowFlowIntensityIntensity

TimeTime

TimeTime

),,( DIBQ

elsewhere

DTI

DIB

0

),,(

Basic principle of stochastic demand model

Source: Buchberger, 2007


SIMDEUM: parameters follow from surveys and information on appliances

0 6 12 18 240

2

4

6

time (h)

multiplier

0 6 12 18 240

0.2

0.4

0.6

0.8

1

time (h)

cdf

0 5 10 150

0.05

0.1

0.15

0.2

Ftoilet flush

cdf

0 20 400

0.02

0.04

0.06

Fkitchen tap

cdf

0 0.5 10

0.1

0.2

0.3

0.4

0.5

IPRP

(l/s)

cdf

0 0.1 0.20

2

4

6

8

10

Ikitchen tap

(l/s)

cdf

0 1 20

0.02

0.04

0.06

0.08

0.1

time (min)

Q (l/s)

0 30 60 90 1200

0.05

0.1

0.15

0.2

time (min)

Q (l/s)

0 100 2000

0.5

1

1.5

2

2.5

DPRP

(s)

cdf

0 10 20 300

0.02

0.04

0.06

0.08

0.1

Dshower

(min)

cdf

0 50 1000

0.01

0.02

0.03

Dkitchen tap

(s)

cdf

0 30 60 90 1200

0.05

0.1

0.15

0.2

time (min)

Q (l/s)

pdfArray

cdfArray

WC w/o saving

WC w/ saving

washing m achine

dishwasher

Duration

Intensity

When

PRP SIMDEUM

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


Compare: flows

43 homes

Zandvoort, 1000 homes

office


wat

er a

ge (

h)

0

2

4

6

8

10

0

2

4

6

8

10

12

14

16

wat

er a

ge (

h)

00:00 06:00 12:00 18:00 00:000

5

10

15

20

25

00:00 06:00 12:00 18:00 00:000

10

20

30

40

50

measurements

a b

c d

compare: travel timesw

ater

age

(h)

0

2

4

6

8

10

0

2

4

6

8

10

12

14

16

wat

er a

ge (

h)

00:00 06:00 12:00 18:00 00:000

5

10

15

20

25

00:00 06:00 12:00 18:00 00:000

10

20

30

40

50

ModelTD

measurements

a b

c d

wat

er a

ge (

h)

0

2

4

6

8

10

0

2

4

6

8

10

12

14

16

wat

er a

ge (

h)

00:00 06:00 12:00 18:00 00:000

5

10

15

20

25

00:00 06:00 12:00 18:00 00:000

10

20

30

40

50

ModelBU

(95% c.i.)

ModelBU

()

ModelTD

measurements

a b

c d


Practical considerations – automatic linking

data

SIMDEUM0 6 12 18 24

0

0.1

0.2

0.3

0.4

time (hr)

flow

(l/

s)

total fl ow

fl ow hot water

Censusdata

Landregister

Pipe informationsystem connections

Customerinformation


Skeletonize and aggregation


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

…


(AOC and dissolved solids)

Suspended solids

© J.H.G. Vreeburg

Regulardeposition &resuspension

Biofilmformation &sloughing

Corrosion

Precipitation &flocculation

Suspended solids

incidental

resuspension(AOC and

dissolved solids)

WQ processes in the distribution network


Suspended solids

© J.H.G. Vreeburg

Regulardeposition &resuspension

Biofilmformation &sloughing

Suspended solids

incidental

resuspension

hydraulic processes in the distribution networkparticles / wall interaction

Maximum shear stress or velocity



© J.H.G. Vreeburg

Biofilmformation

Corrosion


hydraulic processes in the distribution networkdissolved substances / wall interaction

Residual chlorine is related to• Contact time (travel time)• Temperature• Biostability (incoming water quality)




hydraulic processes in the distribution networkdissolved substances / dispersion

vmax

v

Stagnant flow, v = 0 m/sLaminar flow, vmax = 2 * vmean = 0,04 m/sTurbulent flow, vmax = 1.2 * vmean = 1,0 m/s

vmax

v


SIMDEUM: SIMulation of Demand, an End-UseModel

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


Choice in spatial and temporal aggregation influences hydraulic model results

00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:000

0.05

0.1

0.15

0.2

v [m

/s]

time step 5 min

time step 15 min

time step 1 h


00:00 06:00 12:00 18:00 00:000

1

2

3

4

5

Q [

103 m

3/h

]

Wednesday 25-J ul-2007

Thursday 26-J ul-2007

Correlation – level pumping station

0 1 2 3 4 50

1

2

3

4

5

pattern 1

patt

ern

2

R = 0.99

Auto correlation (5 min)R = 1R = 1


00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 00:000

2

4

6

Q [

m3/h

]

Tuesday 13-J un-2006

Wednesday 14-J un-2006

Correlation – level 150 homes

0 1 2 3 4 50

1

2

3

4

5

pattern 1

patt

ern

2

R = 0.68

Auto correlation (5 min)R = 0.84R = 0.80


00:00 06:00 12:00 18:00 00:000

200

400

600

800

1000

Q [

l/h]

Tue-19-Apr-2005

Wed-20-Apr-2005

0 0.2 0.4 0.6 0.8 10

0.2

0.4

0.6

0.8

1

pattern 1

patt

ern

2

R = 0.26

Auto correlation (5 min)R = 0.66R = 0.44

Correlation – level single home


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


Purmerend network

Diameter

60.00

150.00

200.00

250.00

mm

Area A (12.3 km)

Ø63 PVC 5.5% Ø90 PVC < 2.0% Ø100 AC 57.0% Ø110 PVC 8.7% Ø150 AC < 2.0% Ø160 PVC 4.8% Ø200 AC 14.0% Ø250 AC 3.8% Ø300 AC < 2.0% rest 4.7%


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


cross correlation to incoming flow

cross correlation to incoming flow

0.0-0.2

0.2-0.4

0.4-0.60.6-0.8

0.8-1.0

1. Cross correlation

BU TD=1


flow direction reversals

flow direction reversals

uni-directional flow

15%

25%35%

45%


BU TD

Q

QQFDR

=0: no reversals=1: 50% reversals


% stagnant flow

% stagnant flow

0.0-0.2

0.2-0.4

0.4-0.60.6-0.8

0.8-1.0

3.a Stagnant flow

BU TD

Mainly at connection lines


% laminar flow

% laminar flow

0.0-0.2

0.2-0.4

0.4-0.60.6-0.8

0.8-1.0

3.b Laminar flow

BU TD

Also at connection lines


% turbulent flow

% turbulent flow

0.0-0.2

0.2-0.4

0.4-0.60.6-0.8

0.8-1.0

3.c Turbulent flow

BU TD


travel time [h]

travel time [h]

0-6

6-12

12-1818-24

>24

4. Travel times

BU TD

At 0:00 h (simulation run 48 h)


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.


maximum velocity [m/s]

maximum velocity [m/s]

0

0.0-0.1

0.1-0.20.2-0.3

> 0.3

5. Max flow velocities

BU TD

0 0.05 0.1 0.15 0.2 0.25 0.30

0.05

0.1

0.15

0.2

0.25

0.3

0.35

vmax

[m/ s], standard model

v max

[m

/s],

SIM

DEU

M m

odel

connection lines

100 mm

150 mm

200 mm

300 mm

400 mm

500 mm


Quantifying effect of Bottom-Up or Top-Down demand allocation in real network

1. Cross correlation


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


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

DispersionFlow direction reversals

Maximum velocitiesNetwork fouling


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)

SIMDEUM: water demand in distribution network modelling Mirjam Blokker

20 November 2009 – Colloquium

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

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