Speed excursion simulation of PIG using improved friction models

This study proposes two novel friction models of pipeline inspection gauges (PIGs) to simulate and predict speed excursions in long pipeline system pigging operations. Speed excursion of PIG indicates its sudden acceleration mainly caused by gas compressibility and frictional variation in low-pressure and low-flowrate gas pipelines. The first friction model adopts a dynamic friction table coupled with an exponential friction model to simulate the speed excursion caused by variations in friction. The second friction model utilizes a linear equation for friction variation caused by changes in wall thickness and pipe bends, then weight parameters are applied to determine the influence of each factor. These two friction models are tuning models based on field data to simulate speed excursions caused by frictional variation, which can be strategically selected according to the purpose of the simulation. In the numerical model, the transient gas flow equations are solved by the method of characteristics (MOC), and then the Runge-Kuta method is used to solve the dynamic equation of the PIGs. Simulation results applying the proposed friction models are compared to the field pigging data for three different routes operated by the Korea Gas Corporation (KOGAS), and the obtained simulation results are in good agreement with the field pigging data. The first model, tuned friction model, was able to simulate the average pigging velocity and speed excursions of the total distance ratio with high accuracy. The second proposed model, weighted friction model, was slightly less accurate than the first friction model, however it was able to predict the average pigging velocity and speed excursions under different operating conditions. These results mean that the speed excursion can be simulated and predicted with high accuracy using the proposed friction models through the tuning process. Therefore, these two novel friction models would provide insights for the operators to simulate and predict the unstable movement of the PIGs in their pipeline networks.

Automated summary

This study introduces two novel friction models for pipeline inspection gauges (PIGs) to simulate and predict speed excursions in pipeline operations. These friction models, based on field data tuning, accurately predict speed excursions and offer valuable insights for operators to understand and predict unstable PIG movement in pipeline networks.