Summary:
UCLA researchers in the B. John Garrick Institute for Risk Sciences have developed a user-friendly software that utilizes real-time data and comprehensive failure models to help natural gas operators optimize mitigation actions to enhance the structural reliability and safety of a pipeline system.
Background:
There is over 2.6 million miles of pipelines moving gas and oil throughout the United States, and many more miles of pipelines are used to transport water and sewage. The average annual cost of pipeline incidents was more than $522 million over the past 20 years. The lack of a comprehensive and accessible set of system-level integrity management tools for operators is the primary reason behind recurrent pipeline failures. To save the pipelines from the detrimental failures and expensive downtimes, a program that manages methods and activities for evaluating the health state of pipelines and scheduling inspection and maintenance is required. The current pipeline integrity methods consist of 3 main steps: damage identification, defect prediction, and mitigation suggestions. The current health monitoring techniques can detect defects efficiently, but the implementation of these methods is complicated, time consuming and costly. To address the costs issues related to data gathering, the industry has been relying on presumed probability of certain type of failure mode to quantify the health state of the system and predict its failure path. However, the complex operating conditions often lead to coexistence of multiple types of failure causes, and the models that simply accounts for only one type of failure is insufficient. Consequently, these model-based solutions are not comprehensive and cannot reflect the dynamic and stochastic nature of the pipeline failures. The current mitigation plans’ optimization step also presents a major limitation: there is not a user-friendly software tool that help the operators make timely decisions to prevent failures. Therefore, there is a need for an advanced pipeline system integrity management (PSIM) solution that integrates the gathered data, failure mechanism models, and optimal mitigation suggestions together to help the pipeline operator take effective actions after assessing the possible threats to a system.
Innovation:
Professor Mosleh and his research team have developed an advanced yet user-friendly software to address the safety challenges presenting in the pipeline industries. The innovation is a comprehensive assessing tool with a system-level prognosis and health monitoring (PHM) capabilities for PSIM, and it serves as a “one-stop-shop” for the pipeline operators to inspect and analyze the health state of the pipelines and have optimized mitigation suggestions accordingly. To account for all possible deterioration mechanisms in the convoluted situations, both real-time and historical data are fed into the comprehensive models to perform a system-level failure analysis. Compared to the traditional pipeline integrity management solution, this innovation considers dynamic and time-dependent mitigation actions to the pipeline operators. The information of optimized sensor placement and updated inspection/maintenance schedule is passed back to the predicting model as the field data to constantly optimize the mitigation plans to avoid or reduce the likelihood of pipeline failure at a lower cost. Furthermore, due to its ease of integration with different types of pipeline systems and versatility of proposed data analytics techniques, this PSIM solution as a whole can be easily adapted with other types of pipeline systems that are used for large-scale infrastructure.
Potential Applications:
• Provides comprehensive safety solutions for energy-related pipelines
• Health state monitoring of pipes used for infrastructure systems (water and wastewater, etc.)
• Long-haul fiber optic communication systems monitoring (terrestrial and submarine)
• Freight carriers monitoring (trucks and container ships)
Advantages:
• Advanced yet user-friendly software
• Real-time information accessing and analyzing capabilities
• Takes account of all possible failure modes of the pipeline
• System-level dynamic diagnosis of the pipelines
• Provides customized and cost-effective mitigation plans
• Facilitates risk-informed decisions on sensor placement and maintenance scheduling
Development to Date:
Code was first published in 2020.
Related Papers:
Chalgham, Wadie, Keo-Yuan Wu, and Ali Mosleh. "System-level prognosis and health monitoring modeling framework and software implementation for gas pipeline system integrity management." Journal of Natural Gas Science and Engineering 84 (2020): 103671. https://doi.org/10.1016/j.jngse.2020.103671
Reference: UCLA Case No. 2022-279