The objective of this study was to comprehensively examine the pulsatile flow behavior within an elastic tube using experimental and theoretical approaches. This work is an extension of our earlier report [Roknujjaman et al., Phys. Fluids, 34, 123612 (2022)]. In this paper, we adapted a quasi-one-dimensional model to elucidate the wave propagation and pulse attenuation phenomena in an elastic tube and compared with experimental findings. According to our investigation, the key findings were as follows: the experimental and predicted flow wave propagation trend agreed well. Additionally, because of the silicon tubes greater deformation than the urethane tubes, the pulsation was decreased farther in the silicon tubes than in the urethane ones. Furthermore, because of the reflected wave near the tube exit, the pulsations amplitude significantly increased, but it did not enlarge when the resistance was installed at the exit. Finally, we infer that the quasi-one-dimensional model is a better fit for experimental results compared to the two-dimensional model.

Various transient test-based techniques have been developed for detecting leaks in pipeline systems, and most of these depend on a signal that is reflected by the leak. In field pipes, this signal is easily disturbed by high frequency noise, which can prevent detection. This paper presents a leak detection method using transient pressure damping by energy dissipation from the leak, which is minimally affected by the noise. The numerical simulation confirms that the method can be applied within the range of practical pipe scales, provided that the flow rate is reduced by restricting the valve. The model is verified, and leak location is estimated within an error of <6% of the total length despite the noise from the loops. This method offers a simple and easy means to detect leaks without numerical simulation, although it is limited to single pipeline systems.

For decades, leak detection methods utilizing pressure variations (transient test-based technique: TTBT) have been recognized as convenient and accurate for pipeline leak detection. However, their effectiveness in long-distance complex structured field pipelines has not been fully demonstrated, presenting significant challenges for practical implementation. This study, for the first time, tested the effectiveness of inverse transient analysis (ITA), a type of TTBT, on detecting a single-point leak in the Ogura irrigation pipeline system in Sado, Niigata, Japan. The system spans approximately 18 km and features several branches and diameter changes. We proposed a new ITA method using the transient model and the comprehensive learning particle swarm optimization (CLPSO) as the optimization technique. In the verification experiments, pressure variations were induced by closing the downstream valve under two different initial downstream flow rates (approximately 0.032 and 0.093 m³/s) in scenarios without a leak, with a leak near the downstream end of the main pipeline, and with a leak on the branch pipeline. The calibration of the transient model with the wave speed distribution as parameters was conducted prior to leak detection, demonstrating pre-estimation of this wave speed distribution is essential for accurate leak detection. The application of the proposed ITA for measured pressure variations resulted in averaged estimated leak location errors along the total length of the pipeline system with the standard deviations as follows: 0.217 ± 0.038% near the downstream end of the main pipeline for a 0.032 m³/s downstream flow, 0.978 ± 0.456% for a 0.093 m³/s flow, 1.843 ± 1.815% on the branch pipeline for a 0.032 m³/s flow, and 0.880 ± 0.560% for a 0.093 m³/s flow. In cases of the leak near the downstream end of the main pipeline, smaller steady flow rate resulted in smaller variability and higher accuracy in the estimated leak location. Conversely, for the leak in the branch pipeline, larger steady flow rate was better for the estimated leak position. This suggests that the optimal steady flow rate for accurate leak detection varies depending on the leak location. The leak sizes can be expressed as ratios of the estimated leakage discharges to the actual average irrigation water flow rate, resulting in values ranging from 4.86% to 8.58%. From these results, the proposed leak detection method is expected to contribute to reducing the effort and cost for irrigation engineers to narrow down potential leak areas in pipeline systems.

The sedimentation of flocs in aquatic environments is a fundamental phenomenon that has not yet been fully elucidated. This study quantitatively examines sedimentation behavior, particularly focusing on sedimentation turbulence, in a two-dimensional system between flat plates, utilizing image analysis. Experiments were conducted in a rectangular container with montmorillonite suspensions coagulated in a sodium chloride solution. The settling motion of flocs was visualized using a green laser from above and captured horizontally with a digital camera. The study employed Particle Image Velocimetry (PIV) to analyze the velocity field in floc sedimentation, using the flocs as tracers to calculate the mean velocity at the sediment–supernatant interface. The results showed that the mean PIV value is affected by rising particles caused by sedimentation turbulence, indicating that PIV analysis of flow fields using flocs as tracers is reliable. The maximum settling velocity was found to increase with the initial interface height and the thickness of the container. The study further notes that flow velocity fluctuations increase during rapid sedimentation, marked by repeated collisions, separation, and the flocculation of variably sized flocs, offering a clear explanation of sedimentation turbulence. Additionally, Fourier analysis of vertical spectra in the container reflects the formation and collapse of flocs.