Inference Methodology for Pipeline System Integrity Management

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Sponsor: Petroleum Institute (PI) of Abu Dhabi, United Arab Emirate (UAE), In Partnership with University of Maryland, Department of Mechanical Engineering

Project Title: Inference Methodology for Pipeline System Integrity Management 

PI: Professor Ali Mosleh
Funding Level: $860,000


Project Description:
The objective of the project is to develop and demonstrate an inference methodology as part of broader objectives of a proposed project to be led by University of Maryland (UMD) to develop a systems approach to pipeline integrity and health management submitted to the Petroleum Institute (PI) of Abu Dhabi, United Arab Emirate (UAE).

The main project involves a multi-disciplinary science, engineering, and operational approach to realize a comprehensive and state-of-the-art solution to pipeline integrity. The intent is to leverage existing technologies and methods, and invent new ones as needed.  The approach is innovative and unique in its comprehensive integrative perspective, and in its focus on providing practical solutions while advancing the critical scientific and engineering foundations. The various scientific and technological challenges of proposed project will be tackled through three parallel but tightly coupled thrust areas:

Thrust Area I, Data Gathering and Monitoring Technologies
Thrust Area II, Failure Mechanism Sciences
Thrust Area III, Predictive Models and System-Level Pipeline Health Monitoring

UCLA work scope resides in Area III. The aim is to integrate the data, methods, models and technologies developed in Thrust Areas I and II into a total system health management support tool to aid in decision making and planning by the pipeline operators. This is done by developing (a) probabilistic evaluation and modeling of information from sensing, inspection and monitoring and probabilistic integration of mechanistic models and NDI for assessment of the pipe segment health (remaining life), and (b) dynamic pipeline network probabilistic health assessment model software for optimal risk-based prioritization of inspection and proactive management. Input to the proposed integrated health management system (IPHM) includes data from sensors and other inspection and monitoring methods from Thrust Area I. The output is online or offline updates on the reliability state of various segments of the pipeline system, and dynamically updated suggestions on when and where to take action (e.g., increase or decrease inspection frequency).