Date:12/5/2017
Title:Condition Assessment & Pipe Failure Prediction Project: Condition Assessment for Failure Prediction
Description:
‚ÄčThis is the second in a series of three webcasts presenting the results of Advanced Condition Assessment and Failure Prediction Technologies for Optimal Management of Critical Water Supply Pipes (project #4326). This webcast conveyed the research work carried out on the suitability of a selection of direct Condition Assessment (CA) techniques in failure prediction of critical cast iron (CI) mains. Four technologies were covered: Magnetic Flux Leakage (MFL), Pulsed Eddy Currents (PEC), Remote Field Eddy Currents (RFEC), and acoustic wave propagation. The role of verification as employed in the project was also discussed, as well as the part that water utilities can play in this process within their own operational procedures for CA. A quick overview was provided on further side trials carried out with additional direct CA techniques recently developed and thus with less market uptake, including pressure wave propagation and Magnetoelastic sensing. The second part of the webcast focused on the quantitative assessment of failure of corroded cast iron pipes. Introducing a tool for failure prediction, it showed how CI pipes could be analyzed for failure deterministically if condition assessment has been performed. While parametric studies could be undertaken with this tool, it does not account for significant uncertainties that may be present with input variables. To cater to this, an advanced feature of the tool for probabilistic failure prediction will be introduced with examples. The potential use of the tool without condition assessment for preliminary desktop analysis and with condition assessment for more updated analysis was outlined. Research partners on this project include Water Research Foundation, Sydney Water, Hunter Water Corporation, City West Water, Melbourne Water, South East Water Limited, Water Corporation of West Australia, South Australia Water, and UKWIR.
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Long Description:
Presented by Jaime Valls Miro, Associate Professor, University of Technology Sydney; and Jayantha Kodikara, Professor, Monash University
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