Leak Detection Through Transient Flow Simulation in Blended Hydrogen Transportation Systems

Abstract Leaks in fluid transportation pipelines cause major safety and system integrity issues. It is well-understood that such leaks get amplified when hydrogen is blended into natural gas transportation pipelines due to hydrogen embrittlement. Therefore, this study presents a leak detection model using transient flow simulations to predict leaks in such systems. The results aim to improve leak detection accuracy and reliability. The approach focuses on studying flow dynamics in transportation pipelines with leaks. To achieve this, a transient flow simulator is used to model the flow through a pipeline, where the flow through a leak is treated as flow through a restriction. Cases are simulated with hydrogen blended into natural gas at molar concentrations of 0%, 10%, and 30%. Furthermore, the system’s behavior is analyzed under varying leak sizes, while pressure trend data are collected at multiple points to track fluctuations. Additionally, temperature, mass flow losses, and critical velocity through the leak are evaluated. The physical phenomena of the leak's effects are explained for a better understanding and to improve pipeline leak detection accuracy. The properties of the three tested fluids are compared, and the variations in fluid properties are described, such as an inverse relationship between the hydrogen concentration and density. The effect of the leak is strongly influenced by the speed of sound, which limits mass losses in the system. Then, critical velocity is an essential parameter to monitor. While minor leaks below a certain threshold are minimally affected by hydrogen concentration, larger leaks result in greater mass losses. Furthermore, increasing the hydrogen concentration results in a lower critical mass flow through the leak and limits the losses for these cases. In addition, increasing the hydrogen amount lowers the Joule-Thomson coefficient and reduces the cooling effect exhibited in the pipeline due to the leak. Analyzing the pressure trends at multiple locations along the pipe helps the early identification of the leak, so these data trends can be used to place the sensors directly upstream and downstream of the leak. Predicting leaks in pipelines transporting natural gas mixed with hydrogen introduces different insights due to hydrogen's unique properties. These properties require new models for leak detection, pipeline material selection, and flow management. This research will provide valuable information on how hydrogen impacts pipeline integrity, detection system sensitivity, leak propagation, and environmental risks. The results enable more effective risk assessment, operational strategies, and maintenance in hydrogen-natural gas systems, supporting the shift to hydrogen-blended energy networks.