Gas Pipeline Leak Detection by Integrating Dynamic Modeling and Machine Learning Under the Transient State
This study focused on developing machine learning models to detect leak size and location in transient state conditions. The model was designed for an onshore methane–hydrogen blending gas pipeline in Canada. Base case simulations revealed significant effects on mass flow and pressure due to leaks,...
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          | Main Authors: | Juhyun Kim, Sunlee Han, Daehee Kim, Youngsoo Lee | 
|---|---|
| Format: | Article | 
| Language: | English | 
| Published: | MDPI AG
    
        2024-11-01 | 
| Series: | Energies | 
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/17/21/5517 | 
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