wrf webcast condition assessment pipe failure prediction project corrosion new field data and...

Download WRF Webcast Condition Assessment  Pipe Failure Prediction Project Corrosion   new field data and supporting theory/models: •37 detailed corrosion analyses ... Corrosion of Cast Iron Pipes ... for steels and cast iron pipes buried in

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

    WRF Webcast

    Condition Assessment & Pipe Failure Prediction Project

    Corrosion and Failure Prediction

    November 30, 2017

  • 2017 Water Research Foundation. ALL RIGHTS RESERVED.

    Advanced Condition Assessment and Failure Prediction Technologies for

    Optimal Management of Critical Pipes (#4326)

    Partnership project funded by Sydney Water, WRF, Hunter Water Corporation, City West Water, Melbourne Water, South East Water Limited, Water Corporation of West Australia, South Australia Water, and UKWIR.

    $6M+ of committed funding spread over 5 years, plus over $16M of committed cost-share and in-kind support.

  • 2017 Water Research Foundation. ALL RIGHTS RESERVED.

    http://www.waterrf.org/Pages/Projects.aspx?PID=4326

    Research Team:

    Monash University

    University of Technology Sydney

    The University of Newcastle

    WRF Technical Advisory Committee:

    David Hughes

    Jeff Leighton

    http://www.waterrf.org/Pages/Projects.aspx?PID=4326

  • 2017 Water Research Foundation. ALL RIGHTS RESERVED.

    Activities

    Activity 1: How, when and where will pipes fail within the entire network?

    Activity 2: How do we assess the condition of the pipe cost effectively?

    Activity 3: How do we calculate pipe deterioration rates accurately with respect to the pipe environment?

    Activity 4: What is the time-dependent probability of

    failure along the pipeline?

  • 2017 Water Research Foundation. ALL RIGHTS RESERVED.

    Reasons to Listen to These Webcasts

    Much new field data and supporting theory/models:

    37 detailed corrosion analyses from field pipe

    Finite element modeling of pipes

    Traffic loading tests

    Pressure loading tests

    Condition assessment testing with ground-truthing of the results on field pipe

    Key Outcomes: Large patch corrosion leads to catastrophic failure

    Pipes leak before they break

    Manage internal pressure to extend pipe life

    Monash Tool developed - a model for corrosion progression, failure prediction

  • 2017 Water Research Foundation. ALL RIGHTS RESERVED.

    Critical Pipe Webcast Series

    1st webcast

    Corrosion and Failure

    Prediction

    November 30, 2017

    2nd webcast

    Condition Assessment for Failure Prediction

    December 5, 2017

    3rd webcast

    Key Outcomes and Sydney Water Case

    Study

    January 11, 2018

  • 2017 Water Research Foundation. ALL RIGHTS RESERVED.

    Todays presenters

    Robert E. Melchers, Professor of Civil Engineering at The University of Newcastle, Australia

    Jayantha Kodikara, Professor of Civil Engineering at Monash University, Australia

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

    Predicting Long-Term ExternalCorrosion of Cast Iron Pipes

    Rob MelchersThe University of Newcastle,

    Australia

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    9

    Outline

    Aims & background

    Factors for corrosion of ferrous metals in soils

    Development of corrosion of cast iron in soils with time

    Practical observations

    Corrosion between first leak and eventual pipe fracture

    Drivers for CI pipe corrosion

    Take-home messages

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    10

    Aims:

    Cast iron pipes

    internally cement-lined

    In practice need to know amount of

    corrosion of pipe now and the future rate

    Approach:

    Model to predict development of external

    corrosion as a function of time and soil

    environment

    Model based on science

    Considering also field practices

    Pit depth = main interest

    Calibrate model to actual field data

    time

    corrosion

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    11

    Background 1

    Severe corrosion observed sometimes for steels and cast iron pipes

    buried in soils

    Field observations back to 1930s

    Various German and UK studies - reviewed elsewhere

    Numerous model and theoretical studies . (Cole and Marney 2012)

    Also major field experiments:

    US NBS (Romanoff 1957) up to 17 years

    New Zealand study (Penhale 1984) - up to 20 years

    Swedish study (Norin and Vinka 2004) 4 years

    Canada (NRC, Kleiner et al. 2013) exhumed pipes, limited soil data

    Currently no satisfactory model for prediction

    i.e. with acceptable margin of error (see Ricker 2010)

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    12

    Background 2

    Most field studies of very limited extent

    New Zealand study up to 20 years, but few observations in between

    US NBS study (Romanoff 1957)

    pieces of cast iron, small scale model pipes, not operational pipes

    considered: soil air pore space, specific gravity, shrinkage, internal

    drainage, moisture content, soil resistivity, annual precipitation

    soil pH, Na+K, Ca, Mg, CO3, HCO2, Cl-, SO4

    -

    Did not measure: free water at pipe, organic carbon, nitrates (DIN) .

    Did not report burial processes, backfill properties .

    Still the most comprehensive data source.

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    13

    US-NBS study 120+ soils US-wide, many irons and steels, up to 17 years exposure,

    many soil parameters measured a truly major, costly exercise.

    Sources: Romanoff 1957 Ricker 2010

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    14

    Background 3 Tomashev (1966): expect similarities with atmospheric corrosion

    - wetter longer => more corrosion

    Gupta & Gupta (1974): wetness of metal surface soil moisture

    von Wolzogen Khur & van der Vlugt (1934): microbiologically

    influenced corrosion (MIC) in soil corrosion

    Melchers & Jeffrey (2013) importance of nutrients for MIC

    Heyn & Braun (1908), Brasher (1967), Mercer & Lumbard (1995):

    - dilute salt solutions have no significant influence on corrosion

    in (near-) stagnant conditions

    - soil moisture is almost stagnant -> soil chemistry little relevance

    Backfill is contact with pipe: usually the native soil profile

    Corrosion under non-uniform deposits / metal contact can be severe

    Different interpretations to earlier efforts new issues

    Most data in the literature is insufficient.

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    15

    Our study: Develop prediction model for amount of corrosion and future rate

    Based on sound theory + calibrated to data from real pipes

    Developed a new soil data collection protocol with Hunter Water,

    Sydney Water

    Exhumed some 37 pipes

    Pipe surfaces digitally scanned

    Data interpreted (see publications)

    Soil data collected and correlated

    Outcomes:

    First-pass model developed .

    New insights from discussions with field staff, from data

    interpretations, cross-disciplinary ideas .

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    16

    Modelling approach

    Corrosion development = bi-modal trend

    Steels, cast iron, aluminium alloys, copper alloys

    in a wide variety of exposure conditions (see Corrn Sci, Corr J, etc.)

    including soils (see Aust Corr confs 2014-2016)

    Long-term trend linear but not through origin

    Calibrate: using field data from present project ( + Romanoff )

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    Observations:

    Figure 2. Observed corrosion penetrations p0 versus exposure period t.

    These are all clay soils light to heavy

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    First cut interpretations

    Figure 2. Observed corrosion penetrations p0 versus exposure period t.

    wet

    wetwetwet

    poor

    backfill

    Rocks

    in fill

    These are all clay soils light to heavy

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    19

    Time of wetness in soils

    Corrosion can occur only when metal is sufficiently wet

    Sands, loams: borrow time of wetness concept - atmospheric corrosion

    Effective wet time: Gupta & Gupta (1979):

    Low moisture content (mc) => no corrosion (moisture held in soil)

    Sharp rise in corrosion as soil mc reaches

    65% water holding capacity

    Subsequent drop = lack of O2 in

    tests - ignore - long-term corrosion

    requires little O2.

    Clays: usually wet at depth

    Currently: expts for Gupta effect

    Appears similar to loams

    Effect: substitute effective time of wetness for real time .

  • The University of Newcastle, Australia - Centre for Infrastructure Performance and Reliability

    Mean trend an

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