2009 January 10-12 1 Computational Fluid Dynamics Simulation of Open-Channel Flows Over...

2009 January 10-12 www.kostic.niu.edu

1

Computational Fluid Dynamics Computational Fluid Dynamics SimulationSimulation

of Open-Channel Flows Over Bridge-of Open-Channel Flows Over Bridge-DecksDecks

Under Various Flooding ConditionsUnder Various Flooding Conditions

The 6th WSEAS International Conference on FLUID MECHANICS The 6th WSEAS International Conference on FLUID MECHANICS ((WSEAS - FLUIDS'09WSEAS - FLUIDS'09))

Ningbo, China, January 10-12, 2009Ningbo, China, January 10-12, 2009

S. Patil, M. Kostic and P. Majumdar S. Patil, M. Kostic and P. Majumdar Department of Mechanical EngineeringDepartment of Mechanical Engineering

NORTHERN ILLINOIS UNIVERSITYNORTHERN ILLINOIS UNIVERSITY


2

Motivation: Bridges are crucial constituents of the nation’s transportation

systems Bridge construction is critical issue as it involves great amount of

money and risk Bridge structures under various flood conditions are studied for

bridge stability analysis Such analyses are carried out by scaled experiments to calculate

drag and lift coefficients on the bridge Scaled experiments are limited to few design variations and flooded

conditions due to high cost and time associated with them Advanced commercial Computational Fluid Dynamics (CFD)

software and parallel computers can be used to overcome such limitations


3

CFD is the branch of fluid mechanics which uses numerical methods to solve fluid flow problems

In spite of having simplified equations and high speed computers, CFD can achieve only approximate solutions

CFD is a versatile tool having flexibility is design with an ability to impose and simulate real time phenomena

CFD simulations if properly integrated can complement real time scaled experiments

Available CFD features and powerful parallel computers allow to study wide range of design variations and flooding conditions with different flow characteristics and different flow rates

CFD simulation is a tool for through analysis by providing better insight of what is virtually happening inside the particular design


4

Literature Review: Ramamurthy, Qu and Vo, conducted simulation of three

dimensional free surface flows using VOF method and found good agreement between simulation and experimental results

Maronnier, Picasso and Rappaz, conducted simulation of 3D and 2D free surface flows using VOF method and found close agreement between simulation and experimental results.

Harlow, and Welch, wrote Navier stokes equations in finite difference forms with fine step advancement to simulate transient viscous incompressible flow with free surface. This technique is successfully applicable to wide variety of two and three dimensional applications for free surface

Koshizuka, Tamako and Oka, presented particle method for transient incompressible viscous flow with fluid fragmentation of free surfaces. Simulation of fluid fragmentation for collapse of liquid column against an obstacle was carried. A good agreement was found between numerical simulation and experimental data


5

Objectives: The objective of the present study is to validate commercial code

STAR-CD for hydraulic research The experimental data conducted by Turner Fairbank Highway

Research Center (TFHRC) at their own laboratories will be simulated using STAR-CD

The base case of Fr = 0.22 and flooding height ratio, h*=1.5 is simulated with appropriate boundary conditions corresponding to experimental testing

The open channel turbulent flow will be simulated using two different methods

First by transient Volume of Fluid (VOF) methodology and other as a steady state closed channel flow with top surface as slip wall

Drag and lift coefficients on the bridge is calculated using six linear eddy viscosity turbulence model and simulation outcome will be compared with experimental results


6

The suitable turbulence model will be identified which predicts close to drag and lift coefficients

The parametric study will be performed for time step, mesh density and convergence criteria to identify optimum computational parameters

The suitable turbulence model will be used to simulate 13 different flooding height ratio from h*=0.3 to 3 for Fr =0.22


7

Experimental Data: Experiments are conducted for open channel turbulent flow

over six girder bridge deck for different flooding height ratios (h*) and with various flow conditions (Fr)

LBridge =0.34 m S=0.058 m

ΔWSimulation=0.00254

LFlow = 0.26 m

Flow Direction

Schematic of experimental six girder bridge deck model


8

Dimensions of experimental six girder bridge deck model

W L Flow

X

Y

Nomenclature for bridge dimensions and flooding ratios

gW

VFr avg

u

avg

gh

VFr

Theory

S

hhh bu *Flooding

Ratio

Froude Number


9

Experimental data consists of drag and lift coefficients as the function of Froude number, Fr and dimensionless flooding height ratio h*

Experimental data consists of five different sets of experiments for Froude numbers from Fr =0.12 to 0.40 and upstream average velocity 0.20 m/s to 0.65 m/s

The experiments for the Froude number, Fr=0.22 are repeated four times with an average velocity of 0.35 m/s

for h*=0.3 to 3 The lift coefficient is calculated by excluding buoyancy forces

in Y (vertical) direction


10

Drag Coefficients vs h* for Fr = 0.22

0.00

0.50

1.00

1.50

2.00

2.50

3.00

-0.10 0.40 0.90 1.40 1.90 2.40 2.90 3.40

h*

Dra

g C

oe

ffic

ien

t -

CD

12-29-06_2 01-03-07_1 01-29-07_1

01-31-07_3 AVG Drag


11

Lift Coefficient vs h* for Fr = 0.22

-2.50

-2.00

-1.50

-1.00

-0.50

0.00

0.50

-0.10 0.40 0.90 1.40 1.90 2.40 2.90 3.40

h*

Lif

t C

oe

ffic

ien

t -

CL

12-29-06_2 01-03-07_1 01-29-07_1

01-31-07_3 AVG Lift


12

Governing Equations for fluid flow:

Mass conservation equation

Momentum conservation equation

Energy conservation equation

0.

Vt

gVPDt

VD .2

dt

dEEE CVoutin


13

Dimensionless parameters for open channel flow: Reynolds Number

havgRVRe

y

b

yb

yb

p

AR Ch 2

b yRh For 2D open channel flow

,


14

Froude Number: Froude number is dimensionless number which governs

character of open channel flow

The flow is classified on Froude number

Subcritical or tranquil flow

Critical Flow

Supercritical or rapid flow

Open channel flow is dominated by inertial forces for rapid flow

and by gravity forces for tranquil flow

C

avg

gL

VFr

1Fr

1Fr

1Fr

ceGravityFor

ceInertiaForFr 2


15

Froude number is also given by

Where

gy

V

C

VFr avgavg

0

0C Wave speed (m/s)

y = Flow depth (m)


16

Force Coefficients: The component of resultant pressure and shear forces in direction of flow

is called drag force and component that acts normal to flow direction is called lift force

Drag force coefficient is

Lift force coefficient is

In the experimental testing, the drag reference area is the frontal area normal to the flow direction. The lift reference area is the bridge area

perpendicular to Y direction.

Davg

DD

AV

FC

25.0

Lavg

LL

AV

FC 25.0


17

Drag and lift reference areas for experimental data:

For drag, if ,then drag area is

if ,then drag area is

For lift, for all ,lift area is

1* h Bridgebu Lhh *)(

1* h BridgeLS *

*h BridgeFlow LL *


18

Turbulent Flow: Turbulent flow is complex phenomena dominated by rapid and

random fluctuations Turbulent flow is highly unsteady and all the formulae for the

turbulent flow are based on experiments or empirical and semi –empirical correlations

Turbulent Intensity Turbulence mixing length (m)

Turbulent kinetic energy (m2/s2)

avgV

uTI

'

5.175.0 k

Clm

225.1 TIVk avg


19

Turbulence dissipation rate (m2/s3)

Specific dissipation rate (1/s)

ml

kC 5.175.0

kC


20

Turbulence Models: Six eddy viscosity turbulence models are studied from STAR-CD

turbulence options Two major groups of turbulence models k-ε and k-ω are studied The k- ε turbulence model The k-ω turbulence models

a. Standard High Reynolds a. Standard High Reynolds

b. Renormalization Group b. Standard Low Reynolds

c. SST High Reynolds

d. SST Low Reynolds


21

The k-ε High Reynolds turbulence model: Most widely used turbulent transport model First two equation model to be used in CFD This model uses transport equations for k and ε in

conjunction with the law-of-the wall representation of the boundary layer

The k-ε RNG turbulence model: This turbulence model is obtained after modifying k-ε

standard turbulence model using normalization group method to renormalize Navier Stokes equations

This model takes into account effects of different scales of motions on turbulent diffusion


22

k-ω turbulence model: The k-ω turbulence models are obtained as an alternative to the k-ε

model which have some difficulty for near wall treatment The k-ω turbulence models

Standard k-ω model Shear stress transport (SST) model

High Reynolds Low Reynolds

High Reynolds Low Reynolds


23

SST k-ω turbulence model: SST turbulence model is obtained after combining best features of

k-ε and k-ω turbulence model SST turbulence model is the result of blending of k-ω model near

the wall and k-ε model near the wall


24

Computational Model: STAR-CD (Simulation of Turbulent flow in Arbitrary Regions

Computational Dynamics) is CFD analysis software STAR-CD is finite volume code which solves governing equations

for steady state or transient problem The first method used in STAR-CD to simulate open channel

turbulent flow is free surface method which makes use of Volume of Fluid (VOF) methodology

VOF methodology simulates air and water domain VOF methodology uses volume of fraction variable to capture air-

water interface


25

VOF technique: VOF technique is a transient scheme which captures free

surface. VOF deals with light and heavy fluids VOF is the ratio of volume of heavy fluid to the total control

volume Volume of fraction is given by

Transport equation for volume of fraction

Volume fraction of the remaining component is given by

V

Vii

0).(

ut ii

12

1

i

i


26

The properties at the free surface vary according to volume fraction of each component

2

1

.i

ii


27

Free Surface method:

Dimensions for computational model h*=1.5 generated in STAR-CD (Dimensions not to scale and in SI units)

0

Y

XZ

0.08

-1.50

-0.15

0.06

0.30

03

0.26 1.78


28

Computational Mesh:

Full computational domain with non uniform mesh and 2 cells thick in Z direction for =1.5

Y

X

Y


29

Boundary Conditions:

Bottom Wall(No Slip)

Top wall (slip)

Water Inlet

Air Inlet

Outlet

Symmetry Plane

X

Y

Z

Y

1w

0w


30

Computational parameters for VOF methodology:

Inlet velocity, U 0.35 m/s

Turbulent kinetic energy, k 0.00125 m2/s2

Turbulent Dissipation Rate, ε 0.000175 m2/s3

Solution method Transient

Solver method Algebraic Multigrid approach (AMG)

Solution algorithm SIMPLE

Relaxation factor Pressure - 0.3Momentum, Turbulence, Viscosity - 0.7

Differencing scheme MARS

Convergence Criteria 10-2

Time Step (Δt) 0.01 s


31

Water slip top wall method:

-1.5

0

0.06 Y

XZ

0.08

-0.15

03

0.26 1.78

Dimensions for computational model h*=1.5 for water slip –top-wall method (Dimensions not to scale and in SI units)


32

Boundary conditions:

Top wall (slip)

Bottom wall(No slip)

Outlet(Standard)

Symmetry Plane

X

Y

X

Y

Water Inlet

Computational domain with boundary surfaces and boundary conditions for water slip-top-wall method


33

Computational parameters for water slip-top-wall method:

U

k

Inlet velocity,

Turbulent kinetic energy,

Turbulent Dissipation Rate,

0.35 m/s

0.00125 m2/s2

0.000175 m2/s3

Solution Method Steady State

Solver Method Algebraic Multigrid approach (AMG)

Solution Algorithm SIMPLE

Relaxation factor Pressure - 0.3Momentum, turbulence, Viscosity - 0.7

Differencing scheme UD

Convergence Criteria 10-6


34

STAR-CD simulation Validation with basics of fluid mechanics :

Fully developed velocity profile for laminar pipe flow after STAR-CD simulation

Fully developed velocity profile for laminar pipe flow

-6.00E-02

-4.00E-02

-2.00E-02

0.00E+00

2.00E-02

4.00E-02

6.00E-02

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045

W Velocity (m/s)

Y C

oo

rdin

ate

(m

)

Velocity Profile for Laminar Pipe Flow Average velocity profile


35

Fully developed velocity profile for turbulent pipe flow

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0 0.05 0.1 0.15 0.2 0.25 0.3

W velocity (m/s)

Y c

oo

rdin

ate

(m

)

Velocity Profile for turbulent pipe flow Average Velocity Profile

Fully developed velocity profile for the turbulent pipe flow after STAR-CD simulation


36

Flow type WallRoughness

(m)

Theoreticalfriction factor

(Reference)

Simulation friction factor

AbsoluteDifference

PercentageDifference

Laminar Smooth 0.2844 0.2865 0.0021 0.74

Turbulent Smooth 0.0121 0.0116 0.0005 4.13

Turbulent 0.005 0.053 0.048 0.005 9.43

Turbulent 0.015 0.0872 0.0756 0.0116 13.30

Turbulent 0.075 0.2529 0.2019 0.051 20.17

Comparison between theoretical and simulated friction factor :


37

Calculation of entrance length:

DLh Re05.0Shear stress at bottom wall in flow direction

0.00E+00

2.00E-06

4.00E-06

6.00E-06

8.00E-06

1.00E-05

1.20E-05

1.40E-05

1.60E-05

1.80E-05

2.00E-05

0 20 40 60 80 100 120

X distance (m)

Wa

ll s

he

ar

str

es

s (

N/m

2)

Shear stress at bottom wall

Continued on next page

500Re mDh 2

mLh 50


38

Developement of velocity profile in laminar duct flow

0.00E+00

1.00E-01

2.00E-01

3.00E-01

4.00E-01

5.00E-01

6.00E-01

7.00E-01

8.00E-01

9.00E-01

1.00E+00

0.00E+00

1.00E-03

2.00E-03

3.00E-03

4.00E-03

5.00E-03

6.00E-03

7.00E-03

8.00E-03

9.00E-03

1.00E-02

U velocity (m/s)

Y d

ista

nce

(m

)

At 20 M At 40 M At 50 M At 60 M At 75 M At 90 M


39

Verification of power law velocity profile:Comparision for power law velocity profile from

theory and after simulation

-1.00E+00

-8.00E-01

-6.00E-01

-4.00E-01

-2.00E-01

0.00E+00

2.00E-01

4.00E-01

6.00E-01

8.00E-01

1.00E+00

0 0.2 0.4 0.6 0.8 1 1.2

U/Umax

r/R

h

Theoretical velocity profile Velocity profile from simulation


40

Comparison between Fluent and STAR-CD for same geometry:

0 0.254 0.504

0.097

1.016

0.127

0X

Y

Operating Condition Variables

Inlet Velocity U = 2 m/s

Inlet turbulence intensity 10 %

Inlet turbulence mixing length 0.1 m

Outlet gauge pressure 0 Pa

Walls No Slip

Convergence 0.001


41Comparison for velocity contours between STAR-CD and Fluent


42

Comparison for velocity vectors between STAR-CD and Fluent


43

Comparison for X velocities between Fluent and STAR-CD


44

Parameter Fluent STAR-CD(Reference Data)

Absolute Difference

Percentage Difference

ΔP STAT 1120 1161 41 3.53 %

ΔP TOT 1083 1120 37 3.30 %

Pressure difference (Pa)

3.97 %0.28-7.05-6.77CL

5.5 %0.112.001.89CD

PercentageDifference

Absolute Difference

STAR-CD(Reference

Data)

FluentForceCoefficients

Force Coefficients


45

VOF simulation of experimental data:Effect of time steps on drag coefficients

Effect of time steps for k- High Re TM on drag coefficients

2.20000

2.40000

2.60000

2.80000

3.00000

3.20000

3.40000

3.60000

-40 10 60 110 160 210 260 310

time (sec)

CD

time step 0.01 sec time step 0.05 sec time step 0.1 sec


46

Effect of time steps on lift coefficients:

Effect of time steps for k- High Re TM on lift coefficients

-1.40000

-1.20000

-1.00000

-0.80000

-0.60000

-0.40000

-0.20000

0.00000

-40 10 60 110 160 210 260 310

time (sec)

CL

time step 0.01 sec time step 0.05 sec time step 0.1 sec


47

Comparision for CD between full computational model and

computational model with decreased downstream length for k-

High Re TM for 0.05 s time step

1.00000

1.50000

2.00000

2.50000

3.00000

3.50000

4.00000

0 50 100 150 200 250

time (sec)

CD

Full Computational model Computational model with decreased downstream length

Comparision for CL between full computational domain and

computational model with decreased downstream length for k-

High Re TM for 0.05 s time step

-3.00000

-2.50000

-2.00000

-1.50000

-1.00000

-0.50000

0.00000

0.50000

1.00000

1.50000

2.00000

2.50000

0 50 100 150 200 250

time (sec)

CL

Full computational domain Computatioanl domain with decreased downstream length

Effect of decreased downstream length on force coefficients


48

Comparision for CD between full computational model and

computational model with decrease in under bridge water depth for k- High Re TM for time step 0.05 s

0.00000

2.00000

4.00000

6.00000

8.00000

10.00000

12.00000

0 50 100 150 200 250

time (step)

CD

Full Cvomputational model Compuatational model with decrease in under bridge water depth

Effect of decrease in under bridge water depth

Comparision for CL between full computational model and

computational model with decrease in under bridge water depth for k- High Re TM for time step of 0.05 s

-6.00000

-5.00000

-4.00000

-3.00000

-2.00000

-1.00000

0.00000

0 50 100 150 200 250

time (sec)

CL

Full computational model Computational model with decrease in under bridge water depth


49

Comparision between top wall as a slip and symmetry for k-

High Reynolds turbulence model

2.70000

2.95000

3.20000

3.45000

0 50 100 150 200 250 300 350

time (sec)

CD

Slip wall symmetry wall

Comparision between top wall as a slip and symmetry for k-

High Reynolds turbulence model

-1.20000

-1.00000

-0.80000

-0.60000

-0.40000

-0.20000

0.00000

0 50 100 150 200 250 300 350

time (sec)

CL

Slip wall Symmetry wall

Effect of top boundary condition at top as slip wall and symmetry


50

Free Surface Development:

Nomenclature for VOF contour plot

Free surface,

1w

0w

w Volume fraction for water

99.001.0 w


51

t=10sec t=30sec

t=50 sec

t=150 sec t=200 sec sec

t=300 sect =250 sec

t=100sec

Effect of k-ε standard turbulence model on free surface development:


52

Effect of different turbulence models on drag coefficient

-1.00000

1.00000

3.00000

5.00000

7.00000

9.00000

11.00000

13.00000

0 50 100 150 200 250 300 350

time (sec)

CD

k-epsilon High Re k-epsilon RNG k-omega STD High Re

k-omega STD Low Re k-omega SST High Re k-omega SST Low Re

Experimenal Results

Effect of different turbulence models on drag coefficients:


53

Effect of different turbulence models on lift coefficient

-2.00000

-1.80000

-1.60000

-1.40000

-1.20000

-1.00000

-0.80000

-0.60000

-0.40000

-0.20000

0.00000

0 50 100 150 200 250 300 350

Time (sec)

CL

k-epsilon High Re k-epsilon RNG k-omega STD High Re

k-omega STD Low Re k-omega SST High Re k-omega SST Low Re

Experimental Results

Effect of different turbulence models on lift coefficients:


54

TurbulenceModels

h*up h*dw h*avg CD avg CD exp CL avg CL exp

k-ε High Re 1.40 1.30 1.35 3.17 1.98 -0.83 -1.04

k-ε RNG 1.45 1.45 1.45 2.77 2.02 -1.39 -0.73

k-ω STD High Re 1.15 1.30 1.38 4.69 1.99 -0.55 -1.00

k-ω STD Low Re 1.84 1.50 1.67 10.91 1.97 -0.29 -0.60

k-ω SST High Re 1.30 1.20 1.25 3.03 1.98 -1.15 -1.10

k-ω SST Low Re 1.35 1.20 1.28 4.03 1.96 -0.91 -1.07

h*up h*dw h*avg CD avg CD exp CL avg CL exp

Count 6.00 6.00 6.00 6.00 6.00 6.00 6.00

Maximum 1.84 1.50 1.67 10.91 2.02 -0.29 -0.60

Average 1.41 1.33 1.40 4.77 1.98 -0.85 -0.92

Std. Dev. 0.23 0.13 0.15 3.09 0.02 0.40 0.21

Minimum 1.15 1.20 1.25 2.77 1.96 -1.39 -1.10

Comparison between simulation results for different turbulence model and experimental results:


55

Water slip-top-wall method:

(a) Basic Coarse mesh (b) Refined near bridge (c) Fully refined model

0 % (Ref)-1.384390 % (Ref)2.93109Fully refined

model

0.08 %-1.383280.08 %2.93367Refined near

bridge

0.54%-1.391881 % 2.96061Basic coarse

grid

% DifferenceCL% DifferenceCDMesh Density


56

0.94 %-1.378770.2 %2.9544510-4

0.0022 %-1.391850.00033 %2.9606210-5

0 % (ref)-1.391880 % (ref)2.9606110-6

% differenceCL% differenceCDConvergence

criteria

Effect of convergence criteria on final solution:


57

Comparison between VOF and Water slip-top-wall method with experimental results:

Comparision between VOF and steady state simulation for different turbulence models for base case of Fr= 0.22 and h*=1.5

0.00

2.00

4.00

6.00

8.00

10.00

12.00

k-epsilonHigh Re

k-epsilonRNG

k-omegaSTD High Re

k-omegaSTD Low Re

k-omega SSTHigh Re

k-omega SSTLow Re

Turbulence models

CD

VOF simulation Steady state simulation Experimental data

Comparision between VOF and steady state simulation for different turbulence models for base case of Fr=0.22 and h*=1.5

-1.80

-1.60

-1.40

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.00k-epsilonHigh Re

k-epsilonRNG

k-omegaSTD High Re

k-omegaSTD Low Re

k-omega SSTHigh Re

k-omega SSTLow Re

Turbulence models

CL

VOF Simulation Steady State Simulation Experimental data

`


58

Drag coefficient, CD Lift Coefficient, CL

Turbulence model VOF Exp. Water slip-top-wall

VOF Exp. Water slip-top-wall

k-ε High Re 3.17 2.02 2.96 -0.83 -0.70 -1.39

k-ε RNG 2.77 2.02 2.57 -1.39 -0.70 -1.08

k-ω STD High Re4.69 2.02 3.19 -0.55 -0.70 -1.43

k-ω STD Low Re10.91 2.02 10.59 -0.29 -0.70 -1.35

k-ω SST High Re 3.03 2.02 2.78 -1.15 -0.70 -1.26

k-ω SST Low Re 4.03 2.02 4.03 -0.91 -0.70 -1.63

The k-ε RNG predicts closet drag and lift coefficients


59

Effect of inlet turbulence on drag and lift coefficients:

Effect of inlet turbulence intensity on force coefficients when mixing length is 1 mm

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

3

0% 5% 10% 15% 20% 25% 30%

Inlet turbulence intensity

Effect of inlet turbulence intensity on drag coefficient

Effect of inlet turbulence intensity on lift coefficient

CL

CD

Effect of inlet turbulence intensity on force coefficients when mixing length is 41.5 mm

-2

-1

0

1

2

3

4

0% 5% 10% 15% 20% 25% 30%

Inlet turbulence intensity

Effect of inlet turbulence intensity on drag coefficients

Effect of inlet turbulence intensity on lift coeffcients

CD

CL


60

Fully developed velocity profile after selected runs:

Development of velocity profile for open channel flow for selected runs

-8

-6

-4

-2

0

2

4

0.2 0.22 0.24 0.26 0.28 0.3 0.32 0.34 0.36 0.38 0.4

U velocity (m/s)

Y c

oo

rdin

ate

s (

m)

1st Run 3rd Run 5th Run 9th Run 13th Run 15th Run


61

Development of turbulence kinetic energy for open channel flow for selected runs

-8

-6

-4

-2

0

2

4

0.00E+00 1.00E-04 2.00E-04 3.00E-04 4.00E-04 5.00E-04 6.00E-04 7.00E-04

Kinetic energy per unit mass (m2/s2)

Y c

oo

rdin

ate

(m

)


Fully developed turbulence kinetic energy after selected runs:


62

Fully developed turbulence dissipation rate after selected runs:

Development of turbulence dissipation rate for open channel flow for selected runs

-8

-6

-4

-2

0

2

4

0.00E+00

4.10E-04

8.20E-04

1.23E-03

1.64E-03

2.05E-03

2.46E-03

2.87E-03

3.28E-03

3.69E-03

4.10E-03

Turbulence dissipation rate (m2/s3)

Y c

oo

rdin

ate

(m)



63

h * CFDSimulation

Experimental(Reference)

Absolute Difference


0.289 1.63 1.92 0.29 15.10

0.493 1.78 1.21 0.57 47.10

0.68 1.92 1.57 0.35 22.29

0.972 2.29 1.37 0.92 67.15

1.281 2.68 1.98 0.7 35.35

1.500 2.66 2.02 0.64 31.68

1.709 2.62 1.95 0.67 34.35

2.015 2.51 1.89 0.62 32.80

2.309 2.39 1.82 0.57 31.31

2.517 2.33 1.79 0.54 30.16

2.706 2.28 1.73 0.55 31.79

3.008 2.19 1.71 0.48 28.07

3.097 2.17 1.69 0.48 28.40

Comparison between CFD simulations and experimental data for Fr=0.22 for drag coefficients:


64

h * CFD Simulation

Experimental(Reference)

Absolute Difference


0.289 -0.42 -1.70 1.28 75.29

0.493 -0.77 -1.28 0.51 39.84

0.68 -1.00 -1.76 0.76 43.18

0.972 -1.44 -1.75 0.31 17.71

1.281 -1.53 -1.13 0.40 35.40

1.500 -1.01 -0.70 0.31 44.29

1.709 -0.81 -0.53 0.28 52.83

2.015 -0.46 -0.29 0.17 58.62

2.309 -0.10 -0.14 0.04 28.57

2.517 -0.12 -0.04 0.08 233.33

2.706 -0.05 0.03 0.08 275.00

3.008 -0.06 0.06 0.13 201.59

3.097 -0.10 0.10 0.19 198.97

Comparison between CFD simulation and experimental data for Fr=0.22 for lift coefficients:


65

Comparision between CFD simulations and experimental results for drag coefficients for case of Fr=0.22

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0 0.5 1 1.5 2 2.5 3 3.5

h*

CD

CFD simulation Experimental results


66

Comparision between CFD simulation and experimental results for lift coefficients for case of Fr=0.22

-2.00

-1.50

-1.00

-0.50

0.00

0.50

0 0.5 1 1.5 2 2.5 3 3.5

h*

CL

CFD Simulation Experimental results


67

Conclusion: CFD simulations by STAR-CD for Fr=0.22 case , predicts more drag than

experimental drag except for h*=0.289 The percentage difference if the experimental data is taken as reference, is

maximum of 67% for h*=0.972 and minimum of 15% for h* =0.289 For lift predictions, for cases of h*<1, CFD simulations predict more lift

than experimental . For h*>1, CFD simulations predict lower lift than experimental


68

Recommendations for future work: VOF simulations are run for convergence criterion of 0.01.

VOF should be run for more convergence criterion and that is only available with large computing power.

VOF simulations should be run for lower time step than 0.01 sec and for longer simulation time up to 500 sec.

In this study only linear eddy viscosity turbulence models are used. The effect of Large Eddy Simulation, Reynolds stress models and non linear eddy viscosity turbulence models should be tested on force coefficients


69

Acknowledgments:

The authors like to acknowledge support by Dean Promod Vohra, College of Engineering and Engineering Technology of Northern Illinois University (NIU), and Dr. David P. Weber of Argonne National Laboratory (ANL); and especially the contributions by Dr. Tanju Sofu, and Dr. Steven A. Lottes of ANL, as well as financial support by U.S. Department of Transportation (USDOT) and computational support by ANL’s Transportation Research and Analysis Computing Center (TRACC).


70

QUESTIONS ???

More information at:More information at:www.kostic.niu.edu

http://www.kostic.niu.edu/

Date post:	26-Dec-2015
Category:	Documents
Upload:	aubrie-nash
View:	213 times
Download:	0 times

2009 January 10-12 1 Computational Fluid Dynamics Simulation of Open-Channel Flows Over...

Documents