Accurate detection of air bubbles boundaries is of crucial importance in determining the performance and in the study of various gas/liquid two-phase flow systems. The main goal of this work is edge extraction of air bubbles rising in two-phase flow in real-time. To accomplish this, a fast algorithm based on local variance is improved and accelerated on the GPU to detect bubble contour. The proposed method is robust against changes of intensity contrast of edges and capable of giving high detection responses on low contrast edges. This algorithm is performed in two steps: in the first step, the local variance of each pixel is computed based on integral image, and then the resulting contours are thinned to generate the final edge map. We have implemented our algorithm on an NVIDIA GTX 780 GPU. The parallel implementation of our algorithm gives a speedup factor equal to 17x for high resolution images (1024×1024 pixels) compared to the serial implementation. Also, quantitative and qualitative assessments of our algorithm versus the most common edge detection algorithms from the literature were performed. A remarkable performance in terms of results accuracy and computation time is achieved with our algorithm.

For the study of round jet flow at low Reynolds number, a fine analysis of instabilities is necessary. In this paper, we present a frequency analysis of temporal and spatial velocity variations in a round jet with a Reynolds number equal to 830. The data were obtained from Laser Doppler Anemometry (LDA) measurements for various downstream positions. Attention is focused on the characteristics of the instantaneous signal of the longitudinal velocity component u(t) in order to characterize the transition from laminar state to turbulent state. The spectral analysis of the LDA signals of the axial component of the exit velocities highlights the presence of a single peak of energy around a characteristic frequency f0. This frequency corresponds to the amplified mode of the instability. The jet develops a sinuous mode which is the most unstable anti-symmetric mode. The results obtained in this study concerning the sinuous mode frequency, agree well with those obtained by laser tomography technique and images analysis.

This paper reports on an experimental study of a free air jet evolving naturally and discharging from a round nozzle at a Reynolds number of 1600. By using flow visualization images and time-series analysis, the details of the flow behavior are clarified. In particular, the length of the transition zone of the jet is measured and its temporal evolution is investigated. We show that the vortex structures interact with each other, thus producing different sizes in the flow. The probability distribution and temporal evolution of the jet width at various distances from the nozzle exit are studied. The occurrence frequency of vortex rings and the Strouhal number of the jet were also determined at different positions from the nozzle exit. The results obtained are compared with those reported in the literature.

Image processing is an effective method for characterizing various two-phase gas/liquid flow systems. However, bubbly flows at a high void fraction impose significant challenges such as diverse bubble shapes and sizes, large overlapping bubble clusters occurrence, as well as out-of-focus bubbles. This study describes an efficient multi-level image processing algorithm for highly overlapping bubbles recognition. The proposed approach performs mainly in three steps: overlapping bubbles classification, contour segmentation and arcs grouping for bubble reconstruction. In the first step, we classify bubbles in the image into a solitary bubble and overlapping bubbles. The purpose of the second step is overlapping bubbles segmentation. This step is performed in two subsequent steps: at first, we classify bubble clusters into touching and communicating bubbles. Then, the boundaries of communicating bubbles are split into segments based on concave point extraction. The last step in our algorithm addresses segments grouping to merge all contour segments that belong to the same bubble and circle/ellipse fitting to reconstruct the missing part of each bubble. An application of the proposed technique to computer generated and high-speed real air bubble images is used to assess our algorithm. The developed method provides an accurate and computationally effective way for overlapping bubbles segmentation. The accuracy rate of well segmented bubbles we achieved is greater than 90 % in all cases. Moreover, a computation time equal to 12 seconds for a typical image (1 Mpx, 150 overlapping bubbles) is reached.

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