CFD Modelling of River Flow

8/12/2019 CFD Modelling of River Flow

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CFD Modell ing of River F low

By

Dr. D.R. Kaushal

Associate ProfessorDepartment of Civil Engineering

IIT Delhi


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CFD Modeling of multiphase flows

CFD modeling consists of:

1. Division of the domain into discrete control volumes usingGAMBIT

2. Integration of the governing equations on the individual CV toconstruct algebraic equations for the discrete dependent variablesusing FLUENT

3. Linearization of the discretized equations and solution of theresultant equation system to yield updated values of the dependent

variables using FLUENT


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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 foreach 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)


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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 throughhorizontal 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.)


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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 exchangemomentum, 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.


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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


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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)


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RNG based k turbulence model

Force balance on the particle in x- direction


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Sewer/canal sediment management by Invert Trap


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Experimental Study on Invert Trap


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Experimental Setup contd..Pictorial View of Experimental Set-Up

Collecting Tank

Channel

Sediment injector

Pump

Invert Trap

Inlet Tan

Regulator

Re-circulatingPipe

Experimental Set-Up at Simulation Laboratory, Civil Engineering Department, IIT Delhi

Video Clip
http://f/Experiment%20Video/MOV00079.MPGhttp://f/Experiment%20Video/MOV00079.MPG


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Invert Trap Configurations


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Variation of retention ratio with slot size


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Three-dimensional geometry for Configuration 5 used in CFD

computations


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Grid Generation using GAMBIT

Cross-sectional mesh used in CFD


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Zones Cell depth Cell

length

Number

of Mesh

cells

Channel

(upstream ofinvert trap)

3mm 5 mm 70,000

Invert Trap 1 mm 3 mm 20,000

Channel

(downstream of

invert trap)

3mm 5 mm 40,000

Details of 3D mesh generated using GAMBIT software


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CFD based velocity contours in m/s at flow rate of 9.95 l/s


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Fluid velocity vectors in m/s for slot size of 15 cm at flow rate of 9.95 l/s


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CFD based particle trajectories at flow rate of 9.95 l/s


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CFD-based retention ratio for Sand1 particles for different slot sizes for

Configuration4


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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 Argentina 312 1997Iron Concentrate China 105 1997


Coal USA 1675 1979

Coal USA 440 1970


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Experimental Set-Up at Fluid Mechanics Laboratory, IIT Delhi

Slurry pipeline transportation system


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CFD based pressure drop profile in slurry pipe bend


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CFD based concentration profiles profile in slurry pipe bend


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CFD simulation of hydraulic jump


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CFD simulation of drop structure


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CFD simulation of drop gated spillway


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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.


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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


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CFD based deposition pattern in meandering river


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END...

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CFD Modelling of River Flow