Development and laboratory assessment of a subsea particle image velocimetry system for bubble and turbulence measurements in marine seeps

Abstract We present the development and laboratory evaluation of RPiPIV, an underwater particle image velocimetry (PIV) system controlled by a Raspberry Pi. Designed specifically to measure bubble characteristics and bubble‐induced flow in natural hydrocarbon seeps, RPiPIV comprises three primary pressure enclosures, housing a consumer‐grade laser for particle illumination, a Gig‐E camera for image capture, a Raspberry Pi for system control, and essential supporting electronics for voltage conversion, battery management, and remote connection. Operating on 24–36 V DC power, the RPiPIV system can be deployed tethered onto a remotely operated vehicle or self‐contained for extended duration measurements. Comparing the RPiPIV and a laboratory high‐speed camera system, we conducted assessments of bubble imaging in a bubble stream and PIV measurements in a water jet, bubble‐chain flow, and single‐orifice bubble plume. Laboratory assessments revealed that bubble diameter estimates differed by approximately 5%. In PIV measurements, mean axial velocities exhibited differences of approximately 5%, while turbulent normal and shear stresses showed variances within 10–30%. Dissipation rates of turbulence kinetic energy differed by approximately 60%. These findings underscore the system's potential for reliably quantifying complex multiphase flow characteristics in deep‐sea environments.

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Publication Details

Journal
Limnology and Oceanography Methods
Published
2025-02-01
DOI
https://doi.org/10.1002/lom3.10670
Citations
1
Primary Topic
Fluid Dynamics and Mixing
Type
article
Field-Weighted Citation Impact
0.67

Funders

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article

Development and laboratory assessment of a subsea particle image velocimetry system for bubble and turbulence measurements in marine seeps

Binbin Wang, X. Ying, Mustahsin Reasad
1 citations
Limnology and Oceanography Methods
Fluid Dynamics and Mixing
0.67
article

Development and laboratory assessment of a subsea particle image velocimetry system for bubble and turbulence measurements in marine seeps

Binbin Wang, X. Ying, Mustahsin Reasad
article en
1 citations

Abstract

Abstract We present the development and laboratory evaluation of RPiPIV, an underwater particle image velocimetry (PIV) system controlled by a Raspberry Pi. Designed specifically to measure bubble characteristics and bubble‐induced flow in natural hydrocarbon seeps, RPiPIV comprises three primary pressure enclosures, housing a consumer‐grade laser for particle illumination, a Gig‐E camera for image capture, a Raspberry Pi for system control, and essential supporting electronics for voltage conversion, battery management, and remote connection. Operating on 24–36 V DC power, the RPiPIV system can be deployed tethered onto a remotely operated vehicle or self‐contained for extended duration measurements. Comparing the RPiPIV and a laboratory high‐speed camera system, we conducted assessments of bubble imaging in a bubble stream and PIV measurements in a water jet, bubble‐chain flow, and single‐orifice bubble plume. Laboratory assessments revealed that bubble diameter estimates differed by approximately 5%. In PIV measurements, mean axial velocities exhibited differences of approximately 5%, while turbulent normal and shear stresses showed variances within 10–30%. Dissipation rates of turbulence kinetic energy differed by approximately 60%. These findings underscore the system's potential for reliably quantifying complex multiphase flow characteristics in deep‐sea environments.

Limnology and Oceanography MethodsVol. 23(3)
Missouri Heart Center (US), University of Missouri (US)
National Science Foundation, Office of Naval Research
Life below water
Openalex Percentile: Top 35%
Fluid Dynamics and Mixing
0.67
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Development and laboratory assessment of a subsea particle image velocimetry system for bubble and turbulence measurements in marine seeps — Binbin Wang, X. Ying, et al. · Limnology and Oceanography Methods (2025) | TGRS Research Map | TGRS