CFD Modelling of River Flow
By
Dr. D.R. Kaushal
Associate Professor
Department of Civil Engineering
IIT Delhi
CFD Modeling of multiphase flows
CFD modeling consists of:
1.
Division of the domain into discrete control volumes using
GAMBIT
2.
Integration of the governing equations on the individual CV to
construct algebraic equations for the discrete dependent variables
using FLUENT
3.
Linearization of the discretized equations and solution of the
resultant equation system to yield updated values of the dependent
variables using FLUENT
Modeling multiphase flows using CFD
1. The Eulerian Model (Euler-Euler Approach)
The Eulerian model is the most complex of the multiphase
models.
It solves a set of momentum and continuity equations for
each phase.
Coupling is achieved through the pressure and interphase
exchange coefficients.
Kaushal, D.R., Thinglas, T. and Tomita, Y., CFD modeling for pipeline flow of fine
particles at high concentration, Int. J. of Multiphase Flow, Under Review, 2011.
(slurry flow of glass beads with mean diameter of 125mm for velocity up to 5m/s at
volumetric concentrations of 30%, 40% and 50% for each velocity)
Modeling multiphase flows using CFD
2. The Mixture Model (Euler-Euler Approach)
The mixture model is designed for two or more phases (fluid or
particulate).
As in the Eulerian model, the phases are treated as interpenetrating
continua.
The mixture model solves for the mixture momentum equation and
prescribes relative velocities to describe the dispersed phases, hence
applicable for medium concentrations up to 20% by volume.
1. Kaushal, D.R., Kumar, A. and Tomita, Y., Flow of mono-dispersed particles through
horizontal bend, Int. J. of Multiphase Flow, Under Review, 2011.
2. Kaushal, D.R., Kumar, A. and Tomita, Y., Flow of bi-modal particles through
horizontal bend, Int. J. of Multiphase Flow, Under Review, 2011.
(slurry flow of silica sand with mean diameter of 450 mm for velocity up to 3.6 m/s at
volumetric concentrations of 4%, 9% and 17% for each velocity. Fly ash is added in
different proportions for bi-modal slurry flow study.)
Modeling multiphase flows using CFD
3. The Discrete Phase Model (Euler-Lagrange Approach)
The fluid phase is treated as a continuum by solving the time-averaged
Navier-Stokes equations.
Dispersed phase is solved by tracking a large number of particles
through the calculated flow field. The dispersed phase can exchange
momentum, mass, and energy with the fluid phase.
A fundamental assumption made in this model is that the dispersed
second phase occupies a low volume fraction (up to 10% by volume).
The particle trajectories are computed individually at specified intervals
during the fluid phase calculation.
Kaushal, D.R., Thinglas, T. and Tomita, Y., Experimental Investigation on Optimization
of Invert Trap Configuration for Solid Management, Powder Technology, Accepted.
Modeling multiphase flows using CFD
4. The Volume of Fluid (VOF) model
The VOF model can model two or more immiscible fluids
The VOF formulation relies on the fact that two or more fluids (or
phases) are not interpenetrating
 VOF solves single set of momentum equations
 VOF tracks the volume fraction of each of the fluids throughout the
domain
VOF is widely used for open channel flows
Governing Equations of Discrete Phase Model (DPM)
Reynolds-averaged Navier-Stokes equations representing transport
equations for the mean flow velocities
Source term in the momentum equation due to presence of the particulate
phase and for each cell C
Boussinesq hypothesis, relating the Reynolds stresses with the mean velocity
gradients (Hinze, 1975)
RNG based k   turbulence model
Force balance on the particle in x- direction
Sewer/canal sediment management by Invert Trap
Experimental Study on Invert Trap
Experimental Setup contd..
Pictorial View of Experimental Set-Up
Sediment injector
Channel
Inlet Tank
Invert Trap
Collecting Tank
Regulator
Pump
Re-circulating
Pipe
Video Clip
Experimental Set-Up at Simulation Laboratory, Civil Engineering Department, IIT Delhi
Invert Trap Configurations
Variation of retention ratio with slot size
Three-dimensional geometry for Configuration 5 used in CFD
computations
Grid Generation using GAMBIT
Cross-sectional mesh used in CFD
Details of 3D mesh generated using GAMBIT software
Zones
Cell depth
Cell
length
Channel
(upstream of
invert trap)
Invert Trap
3mm
5 mm
Number
of Mesh
cells
70,000
1 mm
3 mm
20,000
3mm
5 mm
40,000
Channel
(downstream of
invert trap)
CFD based velocity contours in m/s at flow rate of 9.95 l/s
Fluid velocity vectors in m/s for slot size of 15 cm at flow rate of 9.95 l/s
CFD based particle trajectories at flow rate of 9.95 l/s
CFD-based retention ratio for Sand1 particles for different slot sizes for
Configuration4
 List of Selected Long-Distance Slurry Pipelines
Product
Project Location
Length
Year of
(Km)
Operation
Iron Concentrate
India (BRPL Orissa)
220
2009
Iron Ore tailings
India (BRPL Orissa)
18
2009
Bauxite Ore
Brazil
244
2007
Iron Concentrate
Brazil
400
2007
Iron Concentrate
China
177
2007
Iron Concentrate
India (Essar Steel)
268
2005
Copper Concentrate
Chile
103
2004
Copper/Zinc Concentrate Peru
302
2001
Copper Concentrate
Chile
203
1998
Copper Concentrate
Argentina
312
1997
Iron Concentrate
China
105
1997
Copper Concentrate
Chile
167
1990
Coal
USA
1675
1979
Coal
USA
440
1970
Slurry pipeline transportation system
Experimental Set-Up at Fluid Mechanics Laboratory, IIT Delhi
CFD based pressure drop profile in slurry pipe bend
CFD based concentration profiles profile in slurry pipe bend
CFD simulation of hydraulic jump
CFD simulation of drop structure
CFD simulation of drop gated spillway
CFD simulation of cantilever outfall
CFD simulation of Ganga river
 The hydraulic characteristics of natural river flood plains are not well
understood at present. This is due to the problems encountered in
monitoring spatially distributed patterns of flow depths, velocity,
turbulence characteristics etc.
 For designing the flood protection strategies, it is very important for
river engineers to accurately predict water levels that may be expected due
to any flood discharge.
 One of the consequences resulting from the more recently recognized
hazards of climate change is the potential to increase the levels and
occurrence of flooding worldwide.
 Meandering channel flows being highly complicated are a matter of
recent and continued research.
 3D geometry is developed using (x,y,z) coordinates obtained from
DEM

CFD based simulations are done on the basis of discharge data

Based on CFD analysis, meandering patterns are obtained
 CFD results will be studied to suggest flood protection strategies and
preventive measures for protecting banks from erosion
CFD based deposition pattern in meandering river
END…..….