Dataset Available

Dataset for: A new mechanism of sediment attachment to oil in turbulent flows: Projectile particles

Authors: Lin Zhao, Michel C. Boufadel, Joseph Katz, Gal Haspel, Kenneth Lee, Thomas King, and Brian Robinson
Published On: Oct 04 2017 15:02 UTC
DOI: https://doi.org/10.7266/N7RF5SGD
UDI: R4.x259.000:0018
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Project Information

Funded By:
Gulf of Mexico Research Initiative

Funding Cycle:
RFP-IV

Research Group:
Dispersion Research on Oil: Physics and Plankton Studies II (DROPPS II)

Point of Contact

Michel Boufadel
New Jersey Institute of Technology / Department of Civil and Environmental Engineering
michel.boufadel@njit.edu

Theme keywords

oil particle aggregation, oil spill, OPA formation, nearshore environment

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Abstract:

The dataset includes prediction of penetration depth of a thin plate of particle in oil, particle size distribution, oil droplet size distribution of oil alone and in oil particle aggregates (OPAs), and oil trapping rate by OPAs. These data have been used to generate figures in the manuscript: Zhao, L., Boufadel, M.C., Katz, J., Haspel, G., Lee, K., King, T., & Robinson, B. (2017). A new mechanism of sediment attachment to oil in turbulent flows: Projectile particles. Environ. Sci. Technol. 51(19): 11020-11028. doi:10.1021/acs.est.7b02032.

Suggested Citation:

Lin Zhao, Michel C. Boufadel, Joseph Katz, Gal Haspel, Kenneth Lee, Thomas King, and Brian Robinson. 2017. Dataset for: A new mechanism of sediment attachment to oil in turbulent flows: Projectile particles. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7RF5SGD

Publications:

Zhao, L., Boufadel, M. C., Katz, J., Haspel, G., Lee, K., King, T., & Robinson, B. (2017). A new mechanism of sediment attachment to oil in turbulent flows: Projectile particles. Environmental Science & Technology. doi:10.1021/acs.est.7b02032

Purpose:

To investigate the interaction of oil and particles in turbulent flows which represents conditions in nearshore environment, aid in the development of predictive models and remediation strategies based on the enhancement of oil-particle aggregate formation.

Data Parameters and Units:

Fig 2: Estimation of penetration depth, particle initial velocity (cm/s), penetration depth (μm), particle width (um) Fig S2: Particle size distribution, particle diameter (μm), normalized number concentration, standard deviation, cumulative volume fraction Fig S6: Droplet size distribution of the OPAs, droplet size (μm), oil-particle interaction (fraction) Fig S9: Oil trapping rate for high particle concentration, shaking time (min), percentage of oil in bottom and on the surface layer, standard deviation Fig S10: Oil trapping rate for low particle concentration, shaking time (min), percentage of oil in bottom and on the surface layer, standard deviation Fig S12: Oil droplet size distribution for oil only case, droplet diameter (μm), time (hr), standard deviation

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