TY - JOUR
T1 - Dispersion of Oil Droplets in Rivers
AU - Cui, Fangda
AU - Behzad, Hamed
AU - Geng, Xiaolong
AU - Zhao, Lin
AU - Lee, Kenneth
AU - Boufadel, Michel C.
N1 - Funding Information:
This research was supported by a grant from the Multi-Partner Research Initiative under Grant No. MECTS-#3939073-v1-OFSCP. However, no official endorsement should be implied by these entities. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the National Science Foundation (NSF) Grant No. TG-BCS190002. Specifically, we used the Bridges computer cluster, which is an NSF-funded system at the Pittsburgh Supercomputing Center (PSC).
Publisher Copyright:
© 2021 American Society of Civil Engineers.
PY - 2021/3/1
Y1 - 2021/3/1
N2 - The dispersion of oil droplets in rivers was numerically investigated for uniform flow in a hypothetical wide river with a depth of 3.0 m. The river hydrodynamics profile was used in conjunction with the VDROP model to produce the oil droplet size distribution (DSD), whereas the NEMO3D model was used to track the movement of the oil droplets. Results suggest that the gradient of eddy diffusivity significantly affected the upward-normal (i.e., quasi-vertical) transport of the droplets, and caused them to mix rapidly through the depth. We also found that an increase in buoyancy resulted in a decrease in the streamwise variance and spreading coefficient. Oil droplets broke up due to the relatively large energy dissipation rates in the river at approximately 1.0 m below the surface and deeper. The droplet breakup varies DSD in the river water column, which may subsequently affect other chemo-physical processes (e.g., oil-particle aggregation). The breakup efficiency is affected by a system-dependent parameter Kb, which reflects the uncertainty of a system. The steady-state DSD was bimodal for the case Kb=0.05, whereas it was unimodal for larger Kb values (i.e., Kb=1.0 and 0.25), respectively. More small-sized droplets were generated and persisted in the deep-water column with larger Kb values. The droplet breakup also enhanced the streamwise spreading of the plume. The effect of droplet entrainment on oil dispersion was studied by assuming constant entrainment probabilities of surface oil droplets. The oil DSD varied with different droplet entrainment probabilities, and the number of oil droplets generated in the water column decreased significantly with a decrease in the entrainment probability of the oil droplets.
AB - The dispersion of oil droplets in rivers was numerically investigated for uniform flow in a hypothetical wide river with a depth of 3.0 m. The river hydrodynamics profile was used in conjunction with the VDROP model to produce the oil droplet size distribution (DSD), whereas the NEMO3D model was used to track the movement of the oil droplets. Results suggest that the gradient of eddy diffusivity significantly affected the upward-normal (i.e., quasi-vertical) transport of the droplets, and caused them to mix rapidly through the depth. We also found that an increase in buoyancy resulted in a decrease in the streamwise variance and spreading coefficient. Oil droplets broke up due to the relatively large energy dissipation rates in the river at approximately 1.0 m below the surface and deeper. The droplet breakup varies DSD in the river water column, which may subsequently affect other chemo-physical processes (e.g., oil-particle aggregation). The breakup efficiency is affected by a system-dependent parameter Kb, which reflects the uncertainty of a system. The steady-state DSD was bimodal for the case Kb=0.05, whereas it was unimodal for larger Kb values (i.e., Kb=1.0 and 0.25), respectively. More small-sized droplets were generated and persisted in the deep-water column with larger Kb values. The droplet breakup also enhanced the streamwise spreading of the plume. The effect of droplet entrainment on oil dispersion was studied by assuming constant entrainment probabilities of surface oil droplets. The oil DSD varied with different droplet entrainment probabilities, and the number of oil droplets generated in the water column decreased significantly with a decrease in the entrainment probability of the oil droplets.
KW - Entrainment probability
KW - Lagrangian particle tracking
KW - Oil dispersion
KW - Population balance model
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U2 - 10.1061/(ASCE)HY.1943-7900.0001858
DO - 10.1061/(ASCE)HY.1943-7900.0001858
M3 - Article
AN - SCOPUS:85099404663
SN - 0733-9429
VL - 147
JO - Journal of Hydraulic Engineering
JF - Journal of Hydraulic Engineering
IS - 3
M1 - 04021004-1
ER -