1. No category

Energy Pipelines CRC – Innovation Roadmap – Life Prediction and Asset Management
Match research outcomes with future requirements
Research Activities
Life prediction and asset
management
Increase understanding of requirements
Develop a solution
RP2-07A: Review of
asset management tools
used in industry today
RP2-15: Decision support system
for pipeline asset management
RP2-07D: Neural network
model for pipeline
degradation prediction
RP2-04: Identification of key
parameters in predictive
deterioration models
RP2-XX: Benchmarking
integrity management
related risks
Pipeline condition
monitoring
RP2-11: Understand
mechanisms of coating
cracking and disbondment
RP2-13: deterministic model to
predict CP / Coating failure /
localised corrosion
RP2-07C: Prototype in-situ
monitoring tool developed
to detect localised
corrosion under disbanded
coatings
Knowledge Developed
*Review of asset management tools / decision
models used by pipeline industry
*Review of existing and new pipeline health
monitoring tools available in the world market
RP2-XX: Improved
interpretation of
ILI data
Needs / Requirements
Improved asset
management software
developed and industry
training provided
Improved life prediction
models and asset
management systems
New pipeline condition
monitoring sensors
manufactured /
available to industry
Improved pipeline
conditioning monitoring
tools / sensors
RP2-14: Pipeline
condition monitoring
sensors tested in real life
pipeline applications
IP Developed
*Algorithms and a system for pipeline degradation
prediction utilising neural networks
*Decision support system for pipeline asset
management
*Pipeline condition monitoring system that can detect
localised corrosion under disbonded coatings and
under ineffective CP conditions
Identify, record and utilise/commercialise IP
© Energy Pipelines CRC 2015
Implement solution
Utilisation of IP
*Manufacturing/sell of
pipeline monitoring
sensors + associated
software and services
*Asset Management
Decision Support
software released
The first strand of research concentrates on improved asset management/decision support systems (RP2-15). Central to this system is the development of a life
prediction tool (RP2-07D ‘Pipeline Operational Life Prediction by Neural Networks’). This work should provide the decision support tools giving pipeline
operators/owners the capability to conduct option analysis to determine lowest NPV cost while retaining integrity. This will be informed by the capability to identify
confidence limits on life prediction: the time until significant repair or de-rating of the pipeline is required and the associated risk levels. The other strand of research will
complement/inform the development this asset management tool by building phenomenon-based degradation models based on experimental as well as field survey
data (RP2 07C ‘Pipeline Health Monitoring and Life Prediction’) to better inform the life prediction tool developed under RP2-07D. The primary aim of this work,
however, is to develop a pipeline condition monitoring (PCM) system by installing suitably designed sensors on real life energy pipeline sections, in particular, strategic
and ‘worst-case scenario’ pipeline sections between cathodic protection units (CPUs), non-piggable pipeline and other high risk pipeline sites (RP2-13/RP2-14). The PCM
system will provide real-time monitoring and early warning of site specific localised corrosion, cathodic protection (CP) loss, coating disbondment and degradation.
© Energy Pipelines CRC 2015