WRF Webcast Selecting Cost-Effective Condition … Municipal Utilities Authority (EMUA), New Jersey...

© 2017 Water Research Foundation. ALL RIGHTS RESERVED. No part of this presentation may be copied, reproduced, or otherwise utilized without permission.

WRF Webcast

Selecting Cost-Effective Condition Assessment Technologies for High-

Consequence Water Mains

November 9, 2017

© 2017 Water Research Foundation. ALL RIGHTS RESERVED.

http://www.waterrf.org/Pages/Projects.aspx?PID=4553

Web Tool:Pipeline Inspection Decision Analyzer (PIDA)

#4553—Selecting Cost-Effective Condition Assessment Technologies for High-Consequence Water Mains



1. Framework (project objectives, definition, premise, background, etc).

2. Examples of data on costs, inspection techniques, their estimated costs, and Weibull parameters.

3. Illustrate framework tool, PIDA (Pipeline Inspection Decision Analyzer) with overview, data requirements and information that helps utilities to make decision on inspection strategies by way of detailed discussion on 1 of 15 selected case studies submitted by water utilities.

Agenda


Water Research Foundation (WaterRF)

Monroe County Water Authority (MCWA), New York

San Diego County Water Authority (SDCWA), California

Tarrant Regional Water District (TRWD), Texas

Evesham Municipal Utilities Authority (EMUA), New Jersey

Colorado Springs Utilities (CSU), Colorado

WaterOne, Kansas

City of Ottawa, Ontario

City of Calgary, Alberta

Halifax Water, Nova Scotia

Russell NDE Systems, AlbertaEchologics Engineering, Ontario_____________________________________________________________None of these analyses are possible without good data collection practices.

Acknowledgements

Technical Advisory

Chris Macey, AECOM Canada

Roy Brander, Consultant

Nathan Faber, San Diego County Water Authority

David Marshall, Tarrant Water Regional District

Dan Ellison, HDR Inc.


General objective: Investigate and quantify cost-effectiveness of inspection/condition assessment for high consequence mains.

• Strategy to determine a cost-effective course of action will include:o preventative renewal/rehabilitation of at-risk segments, selection

and implementation of the most appropriate condition assessment technique, determine expected pipe end-of-life, schedule the next pipe inspection/condition assessment.

• Compile library of parameter values

• Present case studies to demonstrate how the proposed framework could be effectively applied in various circumstances.

Objectives


Basic Premise

The main benefit of water main inspection is to identify imminent failures and convert them from catastrophic(high-cost) to manageable (low-cost).

The expected number of catastrophic failure interceptions varies over the life of the pipelines: the more deteriorated, the more potential catastrophic failures are expected.

Inspection makes sense if the cost to inspect is lower than the expected cost savings of failure interception (provided the pipeline has not reached the end of its useful life).


Basic Approach

1. Estimate pipeline deterioration rate and quantify expected number of failures as it ages.

2. For a given inspection technology, obtain cost and probability of detection of imminent failure.

3. For a given pipeline age, estimate the expected number of imminent failures that could potentially be identified and intercepted.

4. Compare the cost of inspection to the cost savings that are expected due to imminent failure interception.


Definitions (1)

• Pipeline – collection of relatively homogeneous pipe segments (bell-to-spigot).

• Pipe segment failure - occurs when a single pipe segment fails, resulting in segment renewal (replacement or rehabilitation).

• Segment time-to-failure – pipe segments comprise a statistical population assumed to have a probability distribution (Weibull) of time-to-failure.

0.00

0.20

0.40

0.60

0.80

1.00

0 50 100 150 200

Failu

re p

rob

abili

ty

Segment age

Faster deterioration

Slower deterioration

Source: Rajani, B., and Y. Kleiner. 2017. Selecting Cost-Effective Condition Assessment Technologies for High-Consequence Water Mains. Project #4553. Denver, Colo.: Water Research Foundation.



Definitions (2)

• Pipe segment (minor) repair –restores the pipe segment to as good as old (clamped small leaks, re-caulked joint leaks, etc).

• Pipe segment rehabilitation (unscheduled) - upon failure, the pipe segment can be repaired/replaced, restoring it to as good as new.

• Pipe segment rehabilitation (scheduled) - undertaken following discovery of imminent failure (interception). Pipe segment restored to as good as new.

Failure cost (consequence) includes direct, indirect and social costs:

Repair → Scheduled renewal → Unscheduled renewalMinor cost Moderate cost Significant cost


Definitions (3)

• Pipeline inspection – includes inspection planning, mobilisation, implementation and interpretation of results to identify imminent failures.

• Pipe segment imminent failure – determined by inspection (failure almost certain to occur before next inspection).

• Probability of detection (POD) - as no inspection technology is perfect, there is some likelihood that an imminent failure will not be identified.

• Probability of false positive (PFP) – probability that an inspection will erroneously identify an imminent failure.

• Validation of inspection results – a pipe segment identified as imminent failure is re-examined closely before rehabilitation/replacement is undertaken.

• Inspection cycle ─ duration between subsequent inspections. It is assumed that an inspection session can reveal with reasonable confidence imminent failures anticipated during the cycle.


Definitions (4)

Present value

of cost

Expected total costs

Cost of renewal

Minimum. cost

t = Economic useful life

Expected cost of O&M

Deferred time of renewal

• Pipeline (economic) end-of-life - when it is more economical to replace the entire pipe rather than continue to perform scheduled and unscheduled segment renewals.




Costs associated with Inspection cycle (1)

• Compute the expected number of failures.

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0.20

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0.60

0.80

1.00

0 50 100 150 200 250

Exp

ecte

d n

um

ber

of

failu

res

Pipeline age




Costs associated with Inspection cycle (2)

• Compute the expected number of failures.• Inspection will reveal a portion (POD-dependent) of existing

imminent failures.• Detected imminent failures are validated and segments are

replaced if necessary.

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0.20

0.40

0.60

0.80

1.00

0 20 40 60 80 100

Exp

ecte

d n

um

ber

of

failu

res

Pipeline age

Inspection (POD) Detected imminent failures

Undetected imminent failures




Costs associated with Inspection cycle

• Compute the expected number of failures.• Inspection will reveal a portion (POD-dependent) of existing

imminent failures.• Revealed imminent failures are validated and segments are

replaced if necessary.

Expected cost of inspection cycle of duration t years =(expected # of failures • failure cost) +(expected # of failures avoided • renewal cost) +(expected # validations • validation cost) +cost of inspection

Direct (monetary) benefit of inspection =(expected cost of failures over t years with no inspection) -

(expected cost of inspection cycle)


Inspection cost saving (example)

000

050

100

150

200

250

300

60 70 80 90 100

Expecte

d c

ost savin

gs (

000$)

Pipe age (years)

POD = 0.95POD = 0.80

POD = 0.60

POD = 0.40

POD = 0.20




Pipeline life-cycle cost (1)

-

5,000

10,000

15,000

20,000

25,000

0 20 40 60 80 100 120 140

An

nu

al (

dis

cou

nte

d)

cost

($

)

Annual failure cost if no

inspection implemented

Inspection cost

Annual failure cost

before inspection

Annual failure cost

after inspection

cycles begin

Pipe age (years)




-

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

0 20 40 60 80 100 120 140

Cu

mu

lati

ve (

dis

cou

nte

d)

cost

($

) Cumulative failure cost if no

inspection implemented

Cumulative failure cost

with inspection

Cumulative

inspection cost

Cost (discounted) of

deferred pipe

replacement

Pipeline life-cycle cost (2)

Pipe age (years)




Pipeline life-cycle cost and remaining life

-

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

0 20 40 60 80 100 120 140Cu

mu

lati

ve (d

isco

un

ted

) co

st (

$)

Pipe age (years)

Total cumulative life-cycle cost as a

function of replacement

age if no inspection

implemented

Total cumulative life-

cycle cost with 5-year

inspection cycle

Total cumulative life-

cycle cost with 10-

year inspection cycle

Begin 10-year

inspection cycle

age 58

Begin 5--year

inspection cycle

age 67

With no inspection

end-of-life at age 70




Initial Estimation of Pipeline Condition

Initial estimation is semi-informative (little or no field data):

• Expert opinion/experience.

• Inferential indicators: soil resistivity, pipe/soil corrosion potential surveys, etc.

• Similarity to other cohorts in the literature (provided in the project report).

For a given pipeline:

• Probability 5% of pipe segments will fail by age ?? years? (X5, Q2).

• Probability 15% of pipe segments will fail by age ?? years? (X15, Q3).

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0.80

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0 50 100 150 200 250


After every update re-compute pipeline remaining life.

Updating Pipe Condition (1)

Inspection provides distress indicators pointing to imminent failures.

Continual field-data about the pipeline condition are obtained from: • Actual (historical and current) failures.• Existence of imminent failures (from inspection).• Number of pipe segments survived to date.

Use a detailed Bayesian-updating process to update the time-to-failure probability distribution parameters.


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0 50 100 150 200

Failu

re p

rob

abili

ty

Segment age

Updating Pipeline Condition (2)

Example: Pipeline installed 1945, analysed in 2013, 100 segments. Semi-informative parameters determined by expert opinion.




• In 1984 a segment failed.

• In 1985 complete inspection found one imminent failure.

• In 1995 opportunistic inspection revealed imminent failure in one segment.

• In 1999 bell split (failure).

• In 2005 complete follow-up inspection revealed imminent failure in one segment.

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0 50 100 150 200

Failu

re p

rob

abili

ty

Segment age

Semi-

informative

Updated

Updating Pipeline Condition (3)




Failure Cost Data Guide

Location, location, location …Pipe size / material

Blow out

(BO)

Wire breaks

(WB)

Joint failure

(JNF)

Circular

break (CB)

Longitudinal

break (LB)

Corrosion

(COR)

JNF, WB,

BO

Gaewaski &

Blaha (2007)

Cast iron - pit

4, 6, 8 in (100, 150, 200 mm)

15, 24, 27 in (375, 600, 700 mm) $5,000

Cast iron - spun

20 in (500 mm) $99,784

Ductile iron

14 in (350 mm) $25,000

30 in (750 mm) $12,500 $937,136

Steel

24 in (600 mm) $15,000 $1,312,023

30 in (750 mm) $35,811 $937,136

48 in (1200 mm) $8,500 $1,085,255

72, 75 in (1850, 1900 mm) $62,736 $1,085,255

PCCP

24 in (600 mm) $150,000 $44,000 $1,312,023

30, 36, 42, 48 in (750, 900, 1050, 1200 mm) $937,136

36 in (900 mm) $99,250 $4,295,475

42 in (1050 mm) $12,281

48 in (1200 mm) $45,141 $86,000 $77,880 $45,000 $1,085,255

66, 69 in (1675, 1750 mm) $60,000 $2,500,500

66, 72 in (1675, 1850 mm) $41,467 $849,493 $2,500,500

Ductile iron

14 in (350 mm) $25,000

30 in (750 mm) $12,500

Steel

24 in (600 mm)

30 in (750 mm)

48 in (1200 mm) $8,500

72, 75 in (1850, 1900 mm)

PCCP

24 in (600 mm) $150,000 $44,000

30, 36, 42, 48 in (750, 900, 1050, 1200 mm)

36 in (900 mm) $99,250

42 in (1050 mm) $12,281

48 in (1200 mm) $45,141 $86,000 $77,880

66, 69 in (1675, 1750 mm) $60,000

66, 72 in (1675, 1850 mm) $41,467

72 in (1850 mm) $160,246 $252,839

90 in (2300 mm) $137,000

96 in (2450 mm) $284,649


Weibull Parameters Data Guide

Pipe material type Manuf., lining, CP, etc Pipe size Pipe vintage Utility (Region) Reference Q1 Q2 Q3

Asbestos cement (AC) n/a n/a n/a Switzerland Scholten et al. (2013) 20 60 74

Asbestos cement (AC) n/a n/a n/a Switzerland Scholten et al. (2013) 20 39 50

Cast iron (CI) Unknown type, unlined n/a 1930 - 1964 Switzerland Scholten et al. (2013) 20 59 72

Cast iron (CI) Unknown type, unlined n/a 1930 - 1964 Switzerland Scholten et al. (2013) 20 31 39

Ductile iron (DI) n/a n/a 1965 - 1980 Switzerland Scholten et al. (2013) 20 44 54

Ductile iron (DI) n/a n/a 1965 - 1980 Switzerland Scholten et al. (2013) 20 48 55

PE (Polyethylene) High density n/a n/a Switzerland Scholten et al. (2013) 20 59 72

PE (Polyethylene) High density n/a n/a Switzerland Scholten et al. (2013) 20 33 45

Prestressed concrete cylinder pipe (PCCP) ECP 51" 1962 Calleguas # 5 Romer et al. (2008) 20 43 71

Prestressed concrete cylinder pipe (PCCP) ECP 66" 1972 Muskegon County, MI Romer et al. (2008) 20 213 379

Prestressed concrete cylinder pipe (PCCP) ECP 72" 1979 Greenville, SC Romer et al. (2008) 20 33 37

Prestressed concrete cylinder pipe (PCCP) ECP 72" 1972 San Diego Co., CA Romer et al. (2008) 20 184 327

Prestressed concrete cylinder pipe (PCCP) ECP 84" 1975 Tampa, FL Romer et al. (2008) 20 145 256

Prestressed concrete cylinder pipe (PCCP) ECP 66", 69" 1960 San Diego Co., CA Romer et al. (2008) 20 210 331

Prestressed concrete cylinder pipe (PCCP) ECP 72", 84" 1972 Tarrant County, TX Romer et al. (2008) 20 436 777

Prestressed concrete cylinder pipe (PCCP) ECP 90", 108" 1988 Tarrant County, TX Romer et al. (2008) 20 249 443

Prestressed concrete cylinder pipe (PCCP) LCP 42" 1974 Howard Co., MD Romer et al. (2008) 20 95 168

Prestressed concrete cylinder pipe (PCCP) LCP 30", 36" 1975 Howard Co., MD Romer et al. (2008) 20 36 46

Prestressed concrete cylinder pipe (PCCP) LCP 42", 48" 1974 Greenville, SC Romer et al. (2008) 20 136 242

Steel (ST) Unknown type, unlined n/a n/a Switzerland Scholten et al. (2013) 20 54 66

Steel (ST) Unknown type, unlined n/a n/a Switzerland Scholten et al. (2013) 20 35 44

Pipe material type Manuf., lining, CP, etc Pipe size Pipe vintage

Asbestos cement (AC) n/a n/a n/a

Asbestos cement (AC) n/a n/a n/a

Cast iron (CI) Unknown type, unlined n/a 1930 - 1964

Cast iron (CI) Unknown type, unlined n/a 1930 - 1964

Ductile iron (DI) n/a n/a 1965 - 1980

Ductile iron (DI) n/a n/a 1965 - 1980

Q1 Q2 Q3

20 60 74

20 39 50

20 59 72

20 31 39

20 44 54

20 48 55


Inspection Technologies

Inspection Technologies CI pit CI spun DI Steel BWP PCCP RC PVC / HDPE

Visually based

Internal - Man entry and visual inspection ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

Internal - CCTV inspection ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

Electromagnetic

Magnetic flux leakage (MFL-D) ✓ ✓ ✓ ✓

Magnetic flux leakage (MFL-C) ✓ ✓ ✓ ✓

Remote field eddy current (RFEC-D) ✓ ✓ ✓ ✓

✓

Remote field eddy current (RFEC-C) ✓ ✓ ✓ ✓ ✓

✓

Broadband electromagnetic (BEM-D) ✓ ✓ ✓ ✓ ✓* ✓* ✓

Remote field transformer coupling (RFTC)

✓ ✓

Acoustical discrete time testing

Travelling or in-flow sensor ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

Drogue ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

Trunk main correlator ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

Acoustic resonance ✓ ✓ ✓ ✓

Acoustic propagation velocity ✓ ✓ ✓ ✓ ✓ ✓

Acoustical long-term monitoring

Fixed leakage monitoring systems ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓

Acoustic emissions monitoring (hydrophones, etc)

✓

Stress wave analysis (Ultrasound)

Impact echo (D) ✓ ✓ ✓ ✓

✓ ✓

Impact echo (C) ✓ ✓ ✓ ✓

✓ ✓

Guided wave (C)

✓

Phased array technology (D) ✓ ✓ ✓ ✓

Over-the-line surveys (Indirect methods)

Linear polarization resistance (LPR) soil test ✓ ✓ ✓ ✓

Pipe to soil potential survey

Pipe coating defect survey

✓ ✓

Conventional soil property testing, e.g., resistivity ✓ ✓ ✓ ✓

Hydrogen sulphide testing

✓ ✓


Inspection Technologies Capabilities

Inspection TechnologiesCast iron -

pit

Cast iron -

spun

Ductile

ironSteel

Bar-

wrappedPCCP

Reinforced

concreteHDPE

Trade (proprietary) name

for specific technologyDescription of capabilities

Probability of

detection (POD)

of imminent

failures

Probability of

false

positives

(PFP)

Typical

mobilization & de-

mobilization costs

($)

Range of inspection

costs / unit length

Visually based

Internal - Man entry and visual inspection ✓ ✓ ✓ ✓ ✓ ✓ ✓ PCWI 30kV Visual photography, coating

assessment detect longitudinal cracks

20% 0.12% $20,000 - $30,000 $12 / ft ($39 / m)

Internal - CCTV inspection ✓ ✓ ✓ ✓ Sahara, JD7 Useful for spalling of cement mortar

lining or assessing tuberculation levels.

5% 0.06% $20,000 - $30,000 $15 / ft ($49 / m)

Electromagnetic

P-Wave

Magnetic flux leakage (MFL) - discrete ✓ ✓ ✓ ✓ SmartCAT Detects pit size (external) 35% 0.60%

Magnetic flux leakage (MFL) - continuous ✓ ✓ ✓ ✓ Detailed wall thickness profile. 80% 0.60%

Remote field eddy current (RFEC) - discrete ✓ ✓ ✓ ✓ ✓ Feroscope Detailed wall thickness profile. 30% 0.30%

Remote field eddy current (RFEC) - continuous ✓ ✓ ✓ ✓ ✓ ✓ SeeSnake, HydraScan, MainscanRemaining wall thickness (% of NWT), axial position, radial position, axial length (internal)95% 1.00% $30,000 $15 / ft ($49 / m)

Broadband electromagnetic (BEM) - discrete ✓ ✓ ✓ ✓ ✓* ✓* ✓ Rocksolid HSK Measures average remaining wall thickness, coarse resolution85% 0.30% $100 / ft ($328 / m)

Remote field transformer coupling (RFTC) ✓ ✓ PipeDiver Detects wire breaks. 90% 0.06%

Acoustical Discrete Time Testing

Travelling or in-flow sensor ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ SmartBall™ Leak detection. 50% 0.30%

Drouge ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ Sahara, JD7 Leak detection. 50% 0.30%

Trunk main correlator ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ EchoShore®)-Mobile Leak detection. 50% 0.15% $15,000 $2 / ft ($7 / m)

Acoustic resonance ✓ ✓ ✓ ✓ Breivoll ART Detailed thickness profile, pipe topography and detects and distinguishes between internal and external corrosion. Also detects leakage.80% 0.30% $11-21 / ft ($35-70 / m)

Acoustic propagation velocity ✓ ✓ ✓ ✓ ✓ ✓ ePulse® Average remaining wall thickness (hoop stiffness for PCCP and Bar-wrapped).70% 0.06% $15,000 $5 / ft ($16 / m)

Acoustical Long-Term Monitoring

Fixed leakage monitoring systems ✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓ EchoShore-TX Detection of leaks as they occur. 50% 0.15% $15,000 $8 / ft ($26 / m)

Acoustic emissions monitoring (hydrophones, fiber optic) ✓ EchoShore-TX, SoundprintDetection of wire breaks as they occur. Immenent failure warning possible.90% 0.06%


pit

Cast iron -

spun

Ductile

ironSteel

Bar-

wrappedPCCP

Reinforced

concreteHDPE



Probability of

detection (POD)

of imminent

failures

Probability of

false

positives

(PFP)

Typical

mobilization & de-

mobilization costs

($)

Range of inspection

costs / unit length

Visually based



20% 0.12% $20,000 - $30,000 $12 / ft ($39 / m)



5% 0.06% $20,000 - $30,000 $15 / ft ($49 / m)

Electromagnetic

P-Wave

















Inspection Technologies Costs


pit

Cast iron -

spun

Ductile

ironSteel

Bar-

wrappedPCCP

Reinforced

concreteHDPE



Probability of

detection (POD)

of imminent

failures

Probability of

false

positives

(PFP)

Typical

mobilization & de-

mobilization costs

($)

Range of inspection

costs / unit length

Visually based



20% 0.12% $20,000 - $30,000 $12 / ft ($39 / m)



5% 0.06% $20,000 - $30,000 $15 / ft ($49 / m)

Electromagnetic

P-Wave

















pit

Cast iron -

spun

Ductile

ironSteel

Bar-

wrappedPCCP

Reinforced

concreteHDPE



Probability of

detection (POD)

of imminent

failures

Probability of

false

positives

(PFP)

Typical

mobilization & de-

mobilization costs

($)

Range of inspection

costs / unit length

Visually based



20% 0.12% $20,000 - $30,000 $12 / ft ($39 / m)



5% 0.06% $20,000 - $30,000 $15 / ft ($49 / m)

Electromagnetic

P-Wave

















Case study – Utility 1 Water District





Romer et al. (2008) Failure of PCCP – WRF (parameters re-derived from data).





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0.2

0.4

0.6

0.8

1.0

0 500 1000 1500 2000 2500 3000

Failu

re p

rob

ab

ilit

y

Segment population age (Years)

Weibull distribution

Existing: Semi-informative (prior)

Existing: Updated (based on failure data)

Replacement





Base case





Sensitivity: If inspection cost is reduced to $270K (< 25%)





Sensitivity: If failure cost is x 7 = $560K & POD is 0% (No inspection)




Context: High-consequence pipelines with high level of uncertainty and significant data gaps.

Provide Framework to consider all available information in a consistent and rational manner to:

• Facilitate building a business case for implementing inspection.

• Show when in the life of a pipeline it is cost-effective to start inspection cycles.

• Given a set of assumptions, anticipate pipeline remaining life.

• Identify candidate inspection technologies for a given. pipeline and compare them based on benefit cost ratio.

• Continually update assumptions as new field data arrive, and recalibrate results accordingly.

Concluding comments (1)


Concluding Comments (2)

• PIDA (Pipe Inspection Decision Analyzer) tool is an aid based on the developed framework to make a business case.

• Available data often imprecise and vague hence it is important to take the time to establish credible input values.

• Good practice to conduct sensitivity study for those input data or parameters where some uncertainties exist, e.g., cost of failure (location, location, location, ...), cost of inspection, probability of detection (POD), probability of false positives (PFP), etc.

• PIDA does not obviate the need for good engineering and economic judgment!


Q&A

38


Thank You

Comments or questions, please contact:

[email protected]

[email protected]

For more information visit:

www.waterrf.org

mailto:[email protected]

mailto:[email protected]

http://www.waterrf.org/

WRF Webcast Selecting Cost-Effective Condition … Municipal Utilities Authority (EMUA), New Jersey...

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