Manufacturing & Infrastructure Technology

The Evaluation of Pipe Performance and

Durability

Stewart BurnCSIROUrban Water InfrastructureContact Stewart.Burn@csiro.au

Research Activity

CSIRO – 6500 scientists across Australia 20+ working specifically on asset

management of water systems Water - PARMS Sewers - CARE-S

Benefits from our Research Improved Asset Management – Risk Based

System Reduced Failures Appropriate service at optimal cost Some return from our investment to invest in

further

Asset Management Components

Asset management strategies

We consider the key Components of an Asset management strategy include

A Risk based methodology based on Whole Life Costing methodologies to

measure consequences Models for predicting pipe failure

Statistical Models Physical/Probabilistic Models

Asset management strategies

PVC Average failure rates (US/Canada)

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East Bay Ottawa Epcor Calgary NRC data

Ave

rage

failu

re ra

te (p

er 1

00km

/per

yea

r)

0

2

4

6

8

10

12

14

CityWest

Hunter YarraValley

Ipswich SouthEast

Gosford Sydney

Ave

rage

failu

re ra

te (p

er 1

00 k

m/p

er y

ear)

US/Canada

PVC Average failure rates (Australia)

Age (years)

Failu

re ra

te (/

00km

/yr)

0 50 100 150

510

5010

050

0

SxOtherSx48

Sx56Sx79

Sx92

Statistical models

Standard failure curves developed for particular material, diameter, length, pressure, soil environment

7 Australian water authorities assessed with 50 years plus of data, 17 UK authorities now being assessed - UKWIR

Statistical Models Need tuning to each authority

Currently seeing if generic curves exist

Developing Physical/Probabilistic Models in conjunction with AwwaRf

PVC pipes – CSIRO/AwwaRF

Physical/probabilistic model predicts fracture failures in the field

Linear Elastic Fracture Mechanics theory used to predict time to brittle fracture from pipe wall defects

Uncertainty in model variables accounted for using Monte Carlo simulations

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1

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1.8

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0 5 10 15 20 25 30 35 40Age (years)

Ave

rage

failu

reR

ate

(per

100

km

/per

yea

r)

UKWIR database: 100 mm PVC-UModel: PVC-U Ca/Zn (AUS) DN 100 mm, Class 1.2 MPa, p = 0.70 MPaModel: PVC-U Ca/Zn (AUS) DN 100 mm, Class 1.2 MPa, p = 0.75 MPa

Polyethylene (PE) pipes – CSIRO/AwwaRF

Increased ductility of current PE materials renders conventional linear elastic fracture mechanics theory invalid

The historical development of different PE grades adds further complication

Physical/Probabilistic failure model in progress and is supported by statistical models based on recorded failure data

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0 5 10 15 20 25 30 35 40 45Age (years)

Ave

rage

failu

reR

ate

(per

100

km

/per

yea

r)2nd generation

PE

2nd & 3rd generation PE

1st generation PE

Asbestos Cement pipes - CSIRO

Physical/Probabilistic model predicts degradation and loss of strength in the field

Failure predicted to occur under critical combined internal pressure and external loading

Uncertainty in key variables accounted for by Monte Carlo simulation methods

10

15

20

25

30

35

500 550 600 650Chainage (metres)

Exp

ecte

d fa

ilure

tim

e (y

ears

)Predicted failure time

Actual 1st failure occurred 21 years after installation

Cast Iron pipes – CSIRO Physical/Probabilistic model predicts corrosion

penetration through pipe wall Failure predicted to occur under combined internal

pressure and external loading at critical corrosion pit depth

Uncertainty in key variables accounted for by Monte Carlo simulation methods

Large volumes of historical failure data also allows statistical models to be developed

0

50

100

150

200

25 30 35 40 45 50

Years since installation

Failu

res p

er 1

00km

per

yea

r

StatisticalPhysical prob.

Ductile Iron pipes – NRC/CSIRO/AwwaRF

AwwaRf project in progress in collaboration with National Research Council, Canada

Will develop service life prediction models for Ductile Iron pipe

In-situ monitoring of corrosion damage in relation to soil electrochemical properties

Statistical methods used to extrapolate measured corrosion damage to longer lengths of pipeline

Physical/Probabilistic model to predict corrosion failure in different soil environments

Cement Mortar Lining (CML) CSIRO/AwwaRF

AwwaRf project in preparation to address the long term performance of Cement Mortar Linings in Cast and Ductile Iron pipes

Industry and literature surveys to identify field failure modes in CML

Quantify the interactions between water quality parameters and CML failure

Develop accelerated test methods for modelling CML degradation

Physical/Probabilistic model to predict failure under different operating conditions and water quality conditions

Condition Assessment – Pro-Active assets

Failure models can be calibrated using non-destructive condition assessment techniques

Electromagnetic tools available to measure corrosion pit depth in metallic pipes

Research effort towards the development of condition assessment tools for non-metallics (cement, plastics)

0 2 5 0 5 0 0 7 5 0 1 0 0 0 1 2 5 0 1 5 00 1 7 5 0 2 0 00 2 2 50L o n gitu d in a l D ista nc e (m m )

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25 0

50 0

75 0

1 00 0

1 25 0

1 50 0

1 75 0

2 00 0

Circ

umfer

entia

l Dist

ance

(mm)

2

3

4

5

6

7 > 7

< 2

3

5

6

4

C a lib r a te dE q uiva len t T h ic k n e ss

(m m )

Sewer Deterioration Models

Deterioration models developed in EU CARE-S project with 15 partners

Models developed for Structural Collapse In/Ex Filtration Blockages

Siltation Root intrusion

More Information

CSIRO - Stewart.Burn@csiro.au

AwwaRf – Jian Zhang WERF – Roy Ramani CARE-S - Sveinung Saegrov http://www.csiro.au http://www.cmit.csiro.au/

research/urbanwater/mouws/