WIT Press


STUDY ON PINHOLE LEAKS IN GAS PIPELINES: CFD SIMULATION AND ITS VALIDATION

Price

Free (open access)

Volume

132

Pages

12

Page Range

129 - 140

Published

2021

Paper DOI

10.2495/MPF210111

Copyright

Author(s)

BURAK AYYILDIZ, MUHAMMAD AZIZUR RAHMAN, ADOLFO DELGADO, IBRAHIM HASSAN, HAZEM NOUNOU, RASHID HASSAN, MOHAMED NOUNOU

Abstract

In the present study, the computational fluid dynamics (CFD) simulations of pinhole leaks (1.27–3.3 mm) in a low-pressure, up to 2.5 bars, air pipeline which has 16 mm (0.62 inch) inner diameter has been performed by using a 3D transient DES (detachable eddy simulation) model of a commercial CFD code, ANSYS Fluent R3. Also, a laboratory-scale experimental setup is established with a 5 m long pipe with inner diameter (ID) = 16 mm. In steady operational stages, mass balance method is used to calculate the leakage mass flow rate in the experimental setup. In addition, pressure point analysis (PPA) with two dynamic and one differential pressure gauges is used to detect chronic/small leaks at transient stages. This method is cost effective and easy to maintain compared to expensive acoustic leak detection systems. The numerical results were validated against the experimental data. The simulations values of leakage mass flow rate are slightly higher (~10%) than the experiments but overall the simulation results are in good agreement with experiment. The proposed model simulates the flow leakage, pressure distribution and velocity profile around the defined size of the leakage. Transient simulation is performed to use power spectral density (PSD) and Fast Fourier transformation (FFT) of the acoustic pressure variation to predict acoustic oscillations and turbulent behavior of the flow field around the leakage location. These results could help advance current understandings of several leak detection systems that will reduce the false alarms of the leakage monitoring systems.

Keywords

CFD simulation, chronic leak detection, gas pipeline leakage, dynamic pressure wave monitoring