Please use this identifier to cite or link to this item:
|Title:||Computational based analysis for leak detection in low-pressure gas pipeline network||Authors:||Khan Abdus Samad||Keywords:||DRNTU::Engineering::Electrical and electronic engineering||Issue Date:||2018||Abstract:||Oil and Gas pipeline networks are the most economical and the risk-free mode of transportation while considering energy source. Since most of the Singapore’s power is generated through natural gas, the transportation networks are very critical in terms of real-time monitoring for uninterrupted power supply thus qualified for safety, reliability and efficiency. The network can last leak-free for a long time only if properly maintained. Anomalies in low pressure pipes are difficult to detect and is still an unexplored area of research. Household users in Singapore face interrupted supply of town gas due to presence of anomalies such as leaks and water ingression in the network pipelines. During emergency, several manual measures are being taken to detect and repair the faulty pipes. However, these methods incur heavy costs, large manpower and lot of time to detect. The aim of the project is to analyze the gas flow in the distributed pipeline network during normal conditions to compare the leak conditions. Experimental data suggests that a leak causes a sudden peak in the pressure signature and constant offset in the flow parameter from its normal condition regime. In this dissertation, the effect of leak on the physical parameters of fluid flowing in the pipelines are analyzed using COMSOL Multiphysics. A physical pipeline structure, that represents the testbed network connected to an existing low-pressure town gas distribution network is modelled to perform simulation. With the understanding of the effect of leaks on parameter’s signature, a leak detection technique by software method can be implemented.||URI:||http://hdl.handle.net/10356/73140||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.