Euler-Lagrangian Simulations of Multiphase Plumes for Environmental Engineering
Ruo-Qian Wang and E Eric AdamsDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology
The present project is motivated by several issues associated with
the dumping process, and in particular the initial plume formation
phase. Through numerical simulations, we are exploring:
1) Buoyancy effects on rate of penetration and flow patterns with
plumes.
2) Distribution of the dispersed phase within the plume
3) Development of improved models describing sediment plume
behavior to guide engineering practices.
4) Providing a bridge between analytical models and experimental
results.
Fig.1 Multi-phase plumes from oil seepage and fall out (http://convergence.ucsb.edu/news/ucsb-scientists-document-fate-huge-oil-slicks-seeps-coal-oil-point)
The present study is aiming to track sediment fate in the operation of land reclamation to
minimize sand loss through suspension in the water column, i.e. turbidity, during the dumping
process. It is critical to conserve the sediment resources as well as ensure the accurate placement
of the dumped material. The reduction of turbidity will also avoid excessive environmental
impact to the surrounding ambient waters.
Multiphase buoyant intrusions are common in
natural and engineered systems and span
multiple time and length scales. Typically, the
plumes contain solid particles (e.g. volcanic
eruptions, sediment disposal in open waters),
liquid droplets (e.g. piston engine fuel
injection), bubbles (e.g. lake aeration), or their
mixtures (e.g. oil spill in oceans).
Fig.2 Sketch of dredged material dumping in open waters
I. Motivation
II. Numerical Methods
D
28.2D
30D
Free slipInflow
outflow
Grids and boundary conditions
Orifice
Governing equations
Continuous phase: Large-Eddy Simulations with the sub-grid model of Dynamic Mixed
Model, built-in filter functions, and inter-phase coupling terms.
Dispersive phase:
- Lagrangian Tracking:
- FG=gravity and buoyancy force; FS=fluid stress; FD=drag; FL=lift; FA =added mass
- Empirical coefficients:
Drag coefficient:
Lift coefficient: CL=0.05 Virtual mass Coefficient: CA=0.5
- Inter-phase coupling:
ALDSG
pFFFFF
u
dt
dmp
DALcoupling FFFF
Computing environment
The code is developed based on an open-source Computational Fluid Dynamics software
OpenFOAM
Parallel calculations are made at the High Performance Computing cluster in Nanyang
Technological University, Singapore
III. Steady State PlumesNozzle diameter
D (mm)Particle diameter
Dp (mm)Inflow Velocity
U0 (m/s)Volume Fraction
a0
5.08 500 1.66 2.4%
Centerline Characteristics
Cross-sectional Characteristics
IV. Particle Clouds
V. Conclusions and Future Plans
Comparison between simulations and experiments along the centerline
(left: volume fraction; middle: particle velocity; right: fluid velocity)*
t= 1.0 s 2.0 s 3.0 s 4.0 s
Comparison between simulations and experiments of particle cloud patterns
(upper: numerical simulations; lower: experimental photos)**
The research described in this project was funded in whole or in part by the Singapore National Research Foundation
(NRF) through the Singapore-MIT Alliance for Research and Technology (SMART) Center for Environmental
Sensing and Modeling (CENSAM).
Acknowledgement
References[1] R Parthasarathy and G Faeth, “Structure of particle-laden turbulent water jets in still water”, International Journal of Multiphase
Flow 13, 699-716 (1987).
[2] Zhao, B., Law, A. W. K., Adams, E. E., Shao, D. D., & Huang, Z. H. (2011). Effect of air release height on the formation of
sediment thermal in water. Proceedings, 34th IAHR World Congress, Brisbane, Australia.
-The present numerical method can convincingly reproduce dilute particle-laden jets.
-The reproduced dense particle cloud is comparable to the experiment.
-CFD-DEM will be used to incorporate the particle-particle collision and other sophisticated
models in order to achieve a more accurate result.
* PF refers to reference [1]
ac/a
o
wp
c/w
o
wc/w
o
z/D z/D z/D
r/z r/z r/z
a/a
c
wp/w
c
w/w
c
He
igh
t o
f th
e c
en
ter
(cm
)
Ve
locity o
f th
e c
en
ter
(cm
/s)
Ra
diu
s (
cm
)
Time (s)
Comparison between simulations and experiments of particle cloud evolution
(left: height of the cloud center; middle: settling velocity of the cloud center; right: horizontal
extent of the cloud)**
Time (s) Time (s)
** The “exp” here refers to reference [2]
Comparison between simulations and experiments along cross-sections
(left: volume fraction; middle: particle velocity; right: fluid velocity)*
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