Session: 16-01-01: Government Agency Student Poster Competition

Paper Number: 150379

150379 - From Pipeline Failure Incidents to Actionable Insights: Simulating Failure Propagation Using Saint® 

Low carbon emissions, abundance, and versatility underscore consuming natural gas as one of the most significant energy sources. Although natural gas transportation through complex pipeline networks makes its delivery economical and safe, it poses a serious hazard due to imminent pipeline failure incidents. These invaluable infrastructures are always susceptible to failure, thus creating a challenge for all stakeholders. Pipeline failure incidents may occur and propagate to a larger scale, endangering human lives, resulting in substantial monetary losses, and causing immense environmental disasters. Identifying the pipeline failures and analyzing their effects on the entire network is crucial to restrain its propagation to the affected area only.

The proposed failure propagation model utilizes incident data from the Pipeline and Hazardous Materials Safety Administration (PHMSA) database. The model is developed in three steps; in the first step, ArcGIS pro® software is utilized to see the spread of failure incidents in the United States (U.S.). In the second step, Scenario Analysis Interface for Energy Systems (SAInt®) software is employed to simulate the propagation of failure incidents in the entire network. The last step compares simulation results with historical incident data to validate the model's accuracy.

The adopted methodology involves collecting and preprocessing pipeline failure incident data acquired from the PHMSA website. The processed data is plotted using ArcGIS pro® software to locate hotspots and identify the severely affected areas. New York County is selected for analysis because it has experienced fourteen failure incidents in the past ten years. The proposed model utilized control points and junctions as nodes, and edges signify the pipeline segments. Externals used for the network include control valves, underground gas storage (UGS) facilities, gas compressor stations, and liquified natural gas (LNG) terminals. The fourteen failure incidents are depicted by employing control valves at failure locations, simulating the gas pressure reduction during pipeline failure. The model is inputted into SAInt® for simulation, allowing dynamic network analysis under several failure scenarios. A transient hydraulic model is developed to simulate the network's dynamic behavior of the natural gas flow. Upon failure at any point, the model adjusts the flow and pressure of natural gas in the entire network, identifying how failure propagates. The simulation outcomes are analyzed by observing flow adjustments to understand the natural gas dynamic behavior during failure incidents and identify critical nodes and segments that require extensive monitoring. The last step compares simulation results with historical incident data to validate the model's accuracy. This comparative analysis ensures the model reflects real-world conditions and can reliably predict future failure propagation of similar incidents.

The findings of this study can significantly impact pipeline management strategies by highlighting the network's vital points and providing valuable information for improving safety measures and emergency response plans. This proactive approach prevents failures before they occur, reducing downtime and enhancing overall gas pipeline reliability. This study lays the groundwork for future research and development of more sophisticated failure propagation models. Future studies may utilize more response variables and real-time data to improve the predictive capabilities of these models by building on the methodologies and findings presented here.

Presenting Author: Yasir Mahmood North Dakota State Univeristy

Presenting Author Biography: Yasir Mahmood is a second-year PhD student and graduate research assistant at North Dakota State University (NDSU). He specializes in transportation engineering under the supervision of Prof. Dr. Ying Huang. His research focuses on pipeline failure prediction and propagation models of natural gas and hazardous materials. Yasir's work is supported by a grant from the National Science Foundation (NSF), EPSCoR RII Track-2 Program, through NSF award # OIA-2119691.

Authors:

Yasir Mahmood North Dakota State Univeristy
Ying Huang North Dakota State University