csiro manufacturing science and technology
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Manufacturing & Infrastructure Technology
The Evaluation of Pipe Performance and
Durability
Stewart BurnCSIROUrban Water InfrastructureContact [email protected]
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)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
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
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
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
0
2
4
6
8
10
12
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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 )
0
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 - [email protected]
AwwaRf – Jian Zhang WERF – Roy Ramani CARE-S - Sveinung Saegrov http://www.csiro.au http://www.cmit.csiro.au/
research/urbanwater/mouws/