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The practical uses of PODDS
Practical uses of PODDS
Neil CroxtonPrincipal Modelling Engineer
Civil EngineeringUnited Utilities
The practical uses of PODDS
Prediction Of Discolourationin Distribution Systems
Agenda
• Overview of the discolouration problem
• introduction to PODDS• project• Theory• modelling
• practical uses
Background
Preston
Liverpool
Crewe
Manchester
Carlisle
Crewe
Carlisle
ManchesterLiverpool
PrestonPreston
Liverpool
Crewe
Manchester
Carlisle
Crewe
Carlisle
ManchesterLiverpool
Preston
• 5,400 square miles• a population of over 7 million• Over 2,500 district metered areas• 455 service reservoirs• 626 pumping stations• 127 water treatment works• treating 2,000 million litres of water daily• 1,444 kilometres of aqueduct• 40,000 kilometres of water main
The discolouration problem
2008 ~ 2,000 complaints2009 ~12,000 complaints2010 ~10,000 complaints2011 ~ 4,000 complaints
Water, usually supplied like this
sometimes like this…
The discolouration problem
Discolouration - where from and why?
• corrosion products / biofilms• historical output from treatment works• complex water chemistry• poor cleaningWhy?• bursts• operational changes• operator error• increased demand• illegal use
1 NTU1 NTU 4 NTU4 NTU
90 NTU90 NTU 190 NTU190 NTU
40 NTU40 NTUTurbidity – what does it look like?
1. a research project undertaken by Sheffield University
2. a theory of how discolouration happens
3. a predictive software tool
PODDS – 3 aspects to consider
• a research project undertaken by Sheffield University
• supported by some UK water companies
• a theory of how discolouration happens• principal proponents: Prof Joby Boxall & Dr Stewart Husband
• the aim is to predict where discolouration is likely to occur -how much? when?
PODDS – the research project
PODDS – the theory
= discolouration= discolouration
normal flow
increase to well above normal flow
giving > 0.7 ms-1
increase to well above normal flow
giving > 0.7 ms-1
TRADITIONAL sediment theory
= discolouration= discolouration
normal flownormal flow
ANY value above normal flowANY value above normal flow
the PODDS theory
• discolouration arises due to the erosion of layers of cohesive “sticky” material that builds up on the pipe walls
• Layers get used to the normal daily flow
• anything above this “conditioned” flow erodes the layers, causing discolouration
PODDS – the theory
“conditioned” flow; no l removed
No discolouration on 1st dayal shears ayers
pipe is NOT conditioned to 2nd day higher flow; discolouration occurs
peak flow 1st dayflow broadly similar overprevious few months
peak flow 2nd day
pipe wall
build-upof material
flow through pipe
PODDS theory – in motion
• EPANET based– public-domain open-source software
• simple or complex models
• hand-built or exported from other software
• Currently building up a set of field test based turbidity parameters
• searching for the ideal set based on pipe characteristics
PODDS – the software
all mains modelall mains model
Calibrating the PODDS model
simple modelsimple model
sourcesource
demanddemand
flow
Imposing the flow and monitoring the turbidity
portable self-contained turbidity monitoring
equipment x2
portable self-contained turbidity monitoring
equipment x2
turbidity – 2 daysturbidity – 2 days
Model Calibration to WQ data
modelled turbiditymodelled turbidity
imposed flow to create
turbidity response
imposed flow to create
turbidity response
measured turbiditymeasured turbidity
flow - 2 daysflow - 2 days
PODDS Model parameters altered so that model = reality
(most influential being the value which represents the rate at which material is mobilised)
PODDS Model parameters altered so that model = reality
(most influential being the value which represents the rate at which material is mobilised)
Practical uses of PODDS
some examples…
EPAnet400 l/s400 l/s
+50 l/s+50 l/s
+50 l/s+50 l/s
+50 l/s+50 l/s
+50 l/s+50 l/s
movement of turbidity across the network
EPAnet
09:00
normal flownormal flow
EPAnet
10:00
+50 l/s for 30 mins+50 l/s for 30 mins
+30NTU+30NTU15NTU15NTU
2NTU2NTU5NTU5NTU
EPAnet
11:00
back to normal flowback to normal flow
5NTU5NTU2NTU2NTU
EPAnet
12:00
5NTU5NTU2NTU2NTU
EPAnet
13:00
5NTU5NTU
2NTU2NTU
EPAnet
14:00
5NTU5NTU
2NTU2NTU
EPAnet
15:00
5NTU5NTU
2NTU2NTU
EPAnet
16:00
5NTU5NTU
2NTU2NTU
EPAnet
20:00
5NTU5NTU
2NTU2NTU
EPAnet
24:00
5NTU5NTU
2NTU2NTU
EPAnet
28:00
5NTU5NTU
EPAnet
31:30
back to normal turbidity levels>20 hours after 30 min flow eventback to normal turbidity levels>20 hours after 30 min flow event
one more to construct
Uses of PODDS – priority ranking
0
4
8
12
16
20
24
0% 10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
mod
elle
d Tu
rbid
ity (N
TU)
extra Flow (%)
Ranking of trunk mains using potential to cause discoloured water- modelled Turbidity (NTU) against increase in Flow (%) -
pipe 1
pipe 2
pipe 3
pipe 4
pipe 5
pipe 6
4 NTUnetworkPCVfailure
4 NTUnetworkPCVfailure
PIPE 610% increase in flow = 4NTUHIGH RISK
PIPE 610% increase in flow = 4NTUHIGH RISK PIPE 1
>100% increase in flow = <4NTULOWER RISK
PIPE 1>100% increase in flow = <4NTULOWER RISK
Uses of PODDS – priority ranking
Uses of PODDS – reducing the risk
1. Allows flow increase while maintaining a low turbidity response2. Facilitates gradual removal of deposits, effectively “cleaning” or reducing the
risk of future discolouration – increases the headroom.
• to compare the potential discolouration risk• to determine where the greatest investment need is required.• cost savings by avoiding or deferring mains replacement
• operational charts used to gradually increase flow• operational charts used to lower the risk of discolouration
• “cleaning” the pipes while maintaining the flow
• PODDS theory in a wider sense is being used regularly in the design of engineering solutions.
• mitigating risk in operational changes and enabling works
• large-scale cleaning of small diameter plastic mains• using “conditioning” flow to design robust flushing schedules
Uses of PODDS - summary
Summary
• the discolouration problem
• introduction to PODDS • project• theory• modelling
– field trials– calibration
• practical uses – priority ranking, getting the best use out of our finances– lowering the risk– regular use of PODDS concepts in engineering design
Neil Croxton, Principal Modelling Engineer,Clean Water Network Modelling
Engineeringand Capital Delivery United Utilities
Thanks, any questions?
Uses of PODDS – operational chartsChanging flows in large diameter mains
data lines produced by running scenario versions of the PODDS model with different initial conditioning flows e.g. 100, 150, 200 etc