Characterization of a Bubble Curtain for PIV Measurements

Torre, Reyna Guadalupe Ramírez de la; Vargas-Ortega, D. C.; Mariana, Centeno-Sierra; Méndez-Fragoso, Ricardo; Forgach, Catalina Stern

doi:10.1007/978-3-319-11487-3_16

Cited by 3 publications

(2 citation statements)

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“…It is very challenging to maintain an acceptable concentration of particles and at the same time avoid intrusive mixing motion. The adaptation of PIV using bubbles as tracers has become popular throughout different applications [9][10][11][12][13], and tested against more common seeding methods [14]. The mentioned studies have brought to light different aspects that need to be calibrated and considered to apply these techniques outside a controlled environment.…”

Section: Introductionmentioning

confidence: 99%

Bringing optical fluid motion analysis to the field: a methodology using an open source ROV as a camera system and rising bubbles as tracers

Løken¹,

Ellevold²,

Torre³

et al. 2021

Meas. Sci. Technol.

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Detailed water kinematics are important for understanding atmosphere-ice-ocean energy transfer processes in the Arctic. There are few in situ observations of 2D velocity fields in the marginal ice zone. Particle tracking velocimetry and particle image velocimetry are well known laboratory techniques for measuring 2D velocity fields, but they usually rely on fragile equipment and pollutive plastic tracers. Therefore, in order to bring these methods to the field, we have developed a new system which combines a compact open-source remotely operated vehicle as an imaging device, and air bubbles as tracing particles. The data obtained can then be analyzed using image processing techniques tuned for field measurements in the polar regions. The properties of the generated bubbles, such as the relation between terminal velocity and diameter, have been investigated under controlled conditions. The accuracy and the spread of the velocity measurements have been quantified in a wave tank and compared with theoretical solutions. Horizontal velocity components under periodic waves were measured within the order of 10% accuracy. The deviation from theoretical solutions is attributed to the bubble inertia due to the accelerated flow. We include an example from an Arctic field expedition where the system was deployed and successfully tested from an ice floe. This work is an important milestone towards performing detailed 2D flow measurements under the ice in the Arctic, which we anticipate will help perform much needed direct observations of the dynamics happening under sea ice.

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Section: Introductionmentioning

confidence: 99%

Bringing optical fluid motion analysis to the field: a methodology using an open source ROV as a camera system and rising bubbles as tracers

Løken¹,

Ellevold²,

Torre³

et al. 2021

Meas. Sci. Technol.

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“…Another measurement technique was using the defocusing of digital particle images to calculate the velocity field from the cross-correlation of volumes from two sequential defocusing bubble images [45]. There have also been studies on the characteristics of bubbles rising in water; i.e., velocity, trajectory, oscillation frequency, size, and density [46][47][48][49].…”

Section: Introductionmentioning

confidence: 99%

On the Estimation of the Surface Elevation of Regular and Irregular Waves Using the Velocity Field of Bubbles

Vargas

Jayaratne

Mendoza

et al. 2020

JMSE

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This paper describes a new set of experiments focused on estimating time series of the free surface elevation of water (FSEW) from velocities recorded by submerged air bubbles under regular and irregular waves using a low-cost non-intrusive technique. The main purpose is to compute wave heights and periods using time series of velocities recorded at any depth. The velocities were taken from the tracking of a bubble curtain with only one high-speed digital video camera and a bubble generator. These experiments eliminate the need of intrusive instruments while the methodology can also be applied if the free surface is not visible or even if only part of the depth can be recorded. The estimation of the FSEW was successful for regular waves and reasonably accurate for irregular waves. Moreover, the algorithm to reconstruct the FSEW showed better results for larger wave amplitudes.

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