Abstract

The pipeline is an efficient tool to transmit fluid in a long distance. However, due to different reasons such as pipe aging or natural disaster, multiple leaks can occur to the broken pipeline system. Therefore, it is very crucial to find an accurate, quick, and low-cost method to detect the leakages in the pipeline. In this study, pressure distribution analysis was proposed to diagnose the location of the leakages via experimental study and Computational Fluid Dynamics (CFD) simulation. Different dimensionless variables, which are the dimensionless leak location, dimensionless leak rate, and dimensionless pressure drop, were applied in our analysis. Through the mathematical modeling which was built on the dimensionless variables, the locations of the leakages can be detected. Multiple flowrate testing was conducted to detect the locations of two leakages. The proposed method can be used to monitor the severity of the pipeline during the operation. Different from former researchers, our work combined the experimental study, CFD simulation, and dimensionless variable analysis to solve the problem of two-point leak detection. This new method can be applied to detect the leakages under different flow rates. For the detection of multiple leaks, a trial-and-error approach was investigated. When the pressure and flow rate at the inlet and outlet of the leaking pipe are known, not only does the method supply an inexpensive way to identify the leaks but also it shortens the time interval between an accident occurring and finding the leak points.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.