ASDL 연구팀, Gas Science and Engineering 학술지 논문 게재
ASDL 연구팀에서 Gas Science and Engineering 학술지에 투고한 논문이 2025년 2월자로 게재되었습니다. 축하합니다!
Title: Digital twin model of in-line inspection systems for low-pressure, low-flow natural gas pipelines
Author: Kwanghyun Yoo, Dae-Kwang Kim, Jae-Jun Kim, Seung-Ung Yang, Hui-Ryoung Yoo, HongSeok Song, Seungjoon Jang, Chongam Kim, Yutaek Seo, Dong-Kyu Kim
Journal: Gas Science and Engineering, 134, 205518. (February 2025)
Doi: https://doi.org/10.1016/j.jgsce.2024.205518
Abstract:
In-line inspection (ILI) of natural gas pipelines is currently performed by an intelligent pipeline inspection gauge (PIG) using the differential pressure of the fluid in pipelines. The ILI robotic system is driven by the pressure difference between the front and rear parts of the robot, and the sensor system collects data about pipeline integrity. Regarding “low-pressure, low-flow” natural gas pipelines, ILI is challenging because of the high speed of the PIG, which is referred to as the “speed excursion.” The PIG’s speed excursion signifies the abrupt acceleration mostly induced by the gas compressibility and the friction differences of each pipe element. When the robot encounters a friction-change section, it moves at a high speed because of the friction drop. This paper proposes a digital twin model of the ILI robotic system for natural gas pipelines, for which a previously developed simulation algorithm for the dynamic behavior of the ILI robotic system is used. The validation of the digital twin model for the two types of ILI systems is discussed. Four error metrics were used to validate the accuracy of the behavior prediction using the digital twin model. Thus, the dynamic behavior of the ILI robotic system can be predicted under various boundary conditions, such as low-pressure and low-flow pipelines, using our proposed digital twin model.
Title: Digital twin model of in-line inspection systems for low-pressure, low-flow natural gas pipelines
Author: Kwanghyun Yoo, Dae-Kwang Kim, Jae-Jun Kim, Seung-Ung Yang, Hui-Ryoung Yoo, HongSeok Song, Seungjoon Jang, Chongam Kim, Yutaek Seo, Dong-Kyu Kim
Journal: Gas Science and Engineering, 134, 205518. (February 2025)
Doi: https://doi.org/10.1016/j.jgsce.2024.205518
Abstract:
In-line inspection (ILI) of natural gas pipelines is currently performed by an intelligent pipeline inspection gauge (PIG) using the differential pressure of the fluid in pipelines. The ILI robotic system is driven by the pressure difference between the front and rear parts of the robot, and the sensor system collects data about pipeline integrity. Regarding “low-pressure, low-flow” natural gas pipelines, ILI is challenging because of the high speed of the PIG, which is referred to as the “speed excursion.” The PIG’s speed excursion signifies the abrupt acceleration mostly induced by the gas compressibility and the friction differences of each pipe element. When the robot encounters a friction-change section, it moves at a high speed because of the friction drop. This paper proposes a digital twin model of the ILI robotic system for natural gas pipelines, for which a previously developed simulation algorithm for the dynamic behavior of the ILI robotic system is used. The validation of the digital twin model for the two types of ILI systems is discussed. Four error metrics were used to validate the accuracy of the behavior prediction using the digital twin model. Thus, the dynamic behavior of the ILI robotic system can be predicted under various boundary conditions, such as low-pressure and low-flow pipelines, using our proposed digital twin model.
