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Investigation of flow over spillway modeling and comparison between experimental data and CFD analysis


Abstract and Figures

As a part of design process for hydro-electric generating stations, hydraulic engineers typically conduct some form of model testing. The desired outcome from the testing can vary considerably depending on the specific situation, but often characteristics such as velocity patterns, discharge rating curves, water surface profiles, and pressures at various locations are measured. Due to recent advances in computational power and numerical techniques, it is now also possible to obtain much of this information through numerical modeling. In this paper, hydraulic characteristics of Kavsak Dam and Hydroelectric Power Plant (HEPP), which are under construction and built for producing energy in Turkey, were investigated experimentally by physical model studies. The 1/50-scaled physical model was used in conducting experiments. Flow depth, discharge and pressure data were recorded for different flow conditions. Serious modification was made on the original project with the experimental study. In order to evaluate the capability of the computational fluid dynamics on modeling spillway flow a comparative study was made by using results obtained from physical modeling and Computational Fluid Dynamics (CFD) simulation. A commercially available CFD program, which solves the Reynolds-averaged Navier-Stokes (RANS) equations, was used to model the numerical model setup by defining cells where the flow is partially or completely restricted in the computational space. Discharge rating curves, velocity patterns and pressures were used to compare the results of the physical model and the numerical model. It was shown that there is reasonably good agreement between the physical and numerical models in flow characteristics.
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KSCE Journal of Civil Engineering (0000) 00(0):1-10
Copyright 2016 Korean Society of Civil Engineers
DOI 10.1007/s12205-016-1257-z
pISSN 1226-7988, eISSN 1976-3808
Water Engineering
Investigation of Flow Over Spillway Modeling and Comparison
between Experimental Data and CFD Analysis
Serife Yurdagul Kumcu*
Received May 14, 2014/Revised 1st: August 13, 2015, 2nd: January 26, 2016/Accepted April 24, 2016/Published Online June 24, 2016
As a part of design process for hydro-electric generating stations, hydraulic engineers typically conduct some form of model
testing. The desired outcome from the testing can vary considerably depending on the specific situation, but often characteristics such
as velocity patterns, discharge rating curves, water surface profiles, and pressures at various locations are measured. Due to recent
advances in computational power and numerical techniques, it is now also possible to obtain much of this information through
numerical modeling. In this paper, hydraulic characteristics of Kavsak Dam and Hydroelectric Power Plant (HEPP), which are under
construction and built for producing energy in Turkey, were investigated experimentally by physical model studies. The 1/50-scaled
physical model was used in conducting experiments. Flow depth, discharge and pressure data were recorded for different flow
conditions. Serious modification was made on the original project with the experimental study. In order to evaluate the capability of
the computational fluid dynamics on modeling spillway flow a comparative study was made by using results obtained from physical
modeling and Computational Fluid Dynamics (CFD) simulation. A commercially available CFD program, which solves the
Reynolds-averaged Navier-Stokes (RANS) equations, was used to model the numerical model setup by defining cells where the flow
is partially or completely restricted in the computational space. Discharge rating curves, velocity patterns and pressures were used to
compare the results of the physical model and the numerical model. It was shown that there is reasonably good agreement between
the physical and numerical models in flow characteristics.
Keywords: dam structures, spilllway modeling, CFD anaysis, numerical model, physical model
1. Introduction
Hydraulic design of a spillway and a stilling basin has been
one of the most studied subjects in hydraulic engineering.
Properly designed approach flow conditions, spillways and
stilling basins will be able to pass flood flows efficiently and
safely to downstream of dams. Physical scale modeling has been
used in the design and investigation of hydraulic structures for
over 100 years. A hydraulic model is still a precision device for
the experimental investigation of flow over a spillway structure,
which can give reliable information only if it is designed correctly
(Willey et al., 2012).
With increasing computer processing capacity, numerical
simulations for hydrodynamic processes become attractive,
including flow over spillways. A comparison of these numerical
results with experimental or prototype data is still required for
calibration and validation. Computational Fluid Dynamics (CFD) is
a branch of numerical modeling that has been developed for
solving problems involving fluid flow. This includes applications
involving fluid-solid interaction, such as the flow of water in a
river or over and around hydraulics structures. There is therefore
considerable interest on the part of hydraulic engineers into the
applicability of CFD to model fluid flow. The majority of available
literature on applying CFD to spillway modeling came from studies
using Flow-3D, which solves the Reynolds-averaged Navier-
Stokes (RANS) equations (Ho et al., 2003; Savage et al., 2001;
Kim, 2010; Chanel, 2008). To track the free water surface (air/
water interface) as it moves in time and space, the program
implements a sophisticated algorithm called the Volume-of-Fluid
(VOF) method. The VOF method tracks the amount of fluid in
each computational cell. Cells range from completely empty to
completely full and the volume changes as flow moves in or out
from neighboring cells. Flow-3D also uses a Fractional Area/
Volume Obstacle Representation (FAVOR) method to define
obstacles (Hirt and Sicilian, 1985). This method allows Flow-3D to
use fully structured computational grids that are much easier to
generate than the deformed grids used by most other CFD
programs. Teklemariam et al. (2001) prepared a report outlining the
use of Flow-3D and it discusses how Flow-3D was successful in
matching the physical model test results for discharge as well as
flow patterns and velocities in modeling (Flow-3D User’s manual,
2012). The report also introduced the ability of Flow-3D to provide
discharge measurements that were very close to empirical
estimates. Teklemariam et al. (2008) discuss the great potential for
*Assistant Professor, Civil Engineering Dept., Necmettin Erbakan University, Konya, Turkey (Corresponding Author, E-mail:
Serife Yurdagul Kumcu
2KSCE Journal of Civil Engineering
the use of CFD for the assessment of a design, as well as screening
and optimizing of hydraulic structures and cofferdam layouts. They
conclude that CFD has been successful in optimizing the final
conceptual configuration for the hydraulics design of the project,
but recommend that physical modeling still be used as a final
This paper provides experimental studies performed on Kav ak
Dam and analyses the stability of spillway design by using
FLOW-3D model. It compares the hydraulic model tests with
FLOW-3D simulation results and gives information on how
accurately a commercially available Computational Fluid Dynamic
(CFD) model can predict the spillway discharge capacity and
pressure distribution along the spillway bottom surface.
2. Physical Model
A 1/50-scaled undistorted physical model of the Kavsak Dam
spillway and stilling basin was built and tested at the Hydraulic
Model Laboratory of State Hydraulic Works of Turkey (DSI).
The model was constructed of plexiglas and was fabricated to
conform to the distinctive shape of an ogee crest. The spillway
has 45.8 m in width and 57 m long with a bottom slope of 125%.
The length of the stilling basin is about 90 m. During model tests,
flow velocities were measured with an ultrasonic flow meter.
Pressures on the spillway were measured using a piezometers
Table 1. Upstream and Downstream Operating Conditions of the
Kavsak Dam
Run Upstream reservoir
elevation (m)
Downstream tailwater
elevation (m)
1 306.55 168.00
2 311.35 174.50
3 314.00 178.90
4 316.50 182.55
Fig. 1. (a) Original Project Design and Final Project Design after Experimental Investigations and Flow Measurement Sections at the
Approach, (b) Top View Experimentally Modified Approach in the Laboratory, (c) Side View of the Experimentally Modified Approach
in the Laboratory
Investigation of Flow Over Spillway Modeling and Comparison between Experimental Data and CFD Analysis
Vol. 00, No. 0 / 000 0000 3
board reading provided the average pressure reading at each
pressure tap location. Both the upstream reservoir lake level and
downstream tailwater elevations were measured using piezometers.
A control valve was used to set the flow in the physical model.
The model was operated at four different upstream reservoir
elevations as given in Table 1. The 3rd and 4th runs in Table 1
belong to corresponding Q1000 and Q10000 discharge values of the
project. The downstream tailwater elevations was adjusted by
another control gate located far downstream of the model
(Kumcu, 2010).
3. Approach Flow Conditions
In order to obtain uniform flow conditions and decreasing the
energy losses through the approach, velocity must be less than 5
m/s ( entürk, 1994). As the flow velocities are high and flow is
vortex flow, the streamlines are separated in front of the gate
piers and the flow is not uniform. In order to obtain uniform flow
conditions some modifications were made in the reservoir
topography. The piers were extended into the dam reservoir and
their shapes were changed to pass the flow safely. As the piers
behave as a console they are also extended longitudinally in
vertical direction up to mixing with the dam body (290 m above
the talweg) for stability issues. Flow measurement sections and
modifications which were done after experimental investigations
are given in Fig. 1. Flow velocity measurements belonging to
original project and experimentally modificated project are given
in Fig. 2. It is clear from the Fig. 2 that, approach flow velocities
are decreasing after doing modifications. In the theoretical study
of the project, the discharge capacity of the spillway was
computed considering that all gates would be completely open
for all reservoir water levels. Discharge rating curve varies withS
Fig. 2. Flow Velocity Measurements at the Approach Belonging to Theoretical Project Design and the Design which is Observed after the
Experimental Modifications
Serife Yurdagul Kumcu
4KSCE Journal of Civil Engineering
the water level over the crest. As the spillway rating curve is an
important parameter to show the consistency and accuracy of the
model application to prototype, the spillway rating curves obtained
from the theoretical and experimental studies are compared with
each other. According to Savage and Johnson (2001) the theoretical
flow discharge through a spillway can be expressed by:
where Q denotes the flow discharge, C discharge coefficient, L
the spillway crest length or width and H upstream head measured
from the crest to the unaffected upstream water stage. The
discharge coefficient, C is not constant. It is influenced by a
variety of factors including the depth of approach, relation of the
actual crest shape to the ideal nappe shape, upstream face slope,
downstream apron interference, and downstream submergence
(Design of small dams, 1977). Each of the conditions has ranges
and design curves that describe the effect of the parameters
mentioned. The theoretical flow discharges were calculated for
various water depths to obtain the rating curve over the spillway
by using Eq. (2). Experimental measurements were also gained
by using gauging of water depths for a given discharge. Comparison
of theoretical discharge measurements with experimental study
is shown in Fig. 3. It was seen in Fig. 3 that, although both values
are very close to each other, when the discharge capacity is
higher than Q= 3000 m3/s. For a given discharge, the flow can
pass over the spillway with lower flow depths than the
theoretical calculations, so it is in the safe side.
4. Pressure and Velocity Measurements on Spill-
Cavitation depends on the pressure and speed of flow, which is
shown by the Cavitation number. Office of the United States
claims an paper under the title “Cavitation on spillways and
chutes” (1990), presented the Cavitation Number as follows:
where; σ is the dimensionless cavitation number; P is the
absolute pressure (N/m2); Pu is the vapor pressure of the fluid (N/
m2); r is the flow density (kg/m3) and U is mean flow velocity
(m/s). If the flow pressure drops below the vapor pressure the
water begins to vaporize, just like if it was boiling (Wagner,
1967). As the bubbles can't escape they will implode. The
pressures fluctuations associated with bubble collapse produce
noise and vibrations and, eventually can lead to the structure
failure (Vischer and Hager, 1997). Cavitation can cause damage
in a very short time (Falvey, 1990). The cavitation number at
which cavitation starts is here referred as the critical cavitation
number (Kokpinar and Gogus, 2002). According to Erfanian-
Azmoudeh and Kamanbedast (1990) the critical cavitation
number is σ = 0.25, and cavitation will occur if σ< 0.25.
In order to investigate the flow characteristics and to calculate
the cavitation numbers; flow depths, the pressures and flow rates
were measured at Km: 22.5, 30.5 and 43.0 (Spillway crest is
Km: 0 + 000.00) for the reservoir discharge capacities of Q = 500
m3/s, 1000 m3/s, 2500 m3/s, 3856 m3/s and 5053 m3/s considering
that for spillway gates are fully open. Flow depths were measured
directly, and pressures were measured by using manometers. The
details of the experimental study and the calculations are given in
the report of Hydraulic Model Studies of Kavsak Dam and HPP
(Kumcu, 2010).
In the original design case, when the flow discharge is 3856
m3/s and 5053 m3/s, some negative pressures were attended
along the spillway and cavitation numbers are calculated. These
results indicate that the velocities were very high and the
pressure variations strongly affect the flow in this area. Flow
characteristics which were observed at these points presented in
Table 2. It is clearly seen that, cavitation numbers are under the
critical cavitation number, σ= 0.25 at Km: 0+043.00 for
Q = 3856 m3/s and 5053 m3/s. Therefore the cavitation risk is
real. Protection of the surface from cavitation erosion is usually
Fig. 3. Rating Curves of Theoretical Project Design and the Design
which is Observed after the Experimental Modifications
Table 2. Flow Characteristics Along the Spillway from the Physical
Distance from
Spillway crest
U ave
1 0+022.50 500 20.67 0.413
2 0+030.50 500 15.04 0.923
3 0+043.00 500 15.47 0.870
1 0+022.50 1000 18.21 0.544
2 0+030.50 1000 18.38 0.632
3 0+043.00 1000 20.51 0.509
1 0+022.50 2500 19.14 0.493
2 0+030.50 2500 20.40 0.549
3 0+043.00 2500 26.26 0.329
1 0+022.50 3856 20.30 0.429
2 0+030.50 3856 20.17 0.583
3 0+043.00 3856 27.78 0.218
1 0+022.50 5053 20.33 0.415
2 0+030.50 5053 21.72 0.517
3 0+043.00 5053 29.20 0.212
Investigation of Flow Over Spillway Modeling and Comparison between Experimental Data and CFD Analysis
Vol. 00, No. 0 / 000 0000 5
achieved by introducing air next to the flow structure surface.
Aeration devices are designed to introduce artificially air within
the flow upstream of the first location where cavitation damage
might occur. Aerators are designed to deflect high velocity flow
away from the chute surface. The water taking off from the
deflector behaves as a free jet with a large amount of interfacial
aeration. This is made by means of aeration devices located on
the bottom and sometimes on the sidewalls of the structure
(Chanson, 2002). If the gate piers are not going on longitudinally
along the spillway and the spillway is steep and short, aeration
slot located at the downstream end of the gate piers is used for
aeration (Chanson, 2005). In this design tip of the gate piers also
increases. In order to prevent cavitation, aerators were fixed at
the downstream end of the gate piers. In order to increase the
amount of air introduced by aerators the deflectors were placed
in front of the aerators (Demiröz, 1986). The plan view of
experimental arrangement of aerators and the damps is shown in
the Fig. 4.
It can be clearly seen from Fig. 5 that, aerators and deflector
are working very efficient, and face of the spillway has been
aerated enough by aerators.
5. Numerical Simulation
After serious modification are made on the original project, a
comparative study was made for flow over a spillway structure
using results obtained from 1/50 scaled physical modeling with
full scaled (prototyped) Computational Fluid Dynamics (CFD)
simulation. The commercially-available CFD package FLOW-
3D Version 10.0 was used in the simulation of the flow field. The
CFD package applies finite-volume method to solve the RANS
One of the main characteristics of turbulent flow is fluctuating
velocity fields. These fluctuations cause mixing of transported
quantities like momentum, energy and species concentration and
thereby also fluctuations in the transported quantities. Because of
the small scales and high frequencies of the fluctuations they are
too computationally expensive to simulate directly in practical
engineering situations. Instead, the instantaneous governing
equations are time-averaged to remove the small scales and the
result is a set of less expensive equations containing additional
Fig. 4. Plan View and Section View of the Aerator and Damp
Fig. 5. Aerators and Damps: (a) Shape of the Aerators and Deflectors (Chanson, 2005), (b) Application of the Aerators and Deflectors in
the Experimental Study
Serife Yurdagul Kumcu
6KSCE Journal of Civil Engineering
unknown variables. These unknown (turbulence) variables are
determined in terms of modeled variables in turbulence models.
This process of time-averaging is called Reynolds averaging.
When this is done the solution variables in the instantaneous
Navier-Stokes equations are decomposed into the mean (time-
averaged) and fluctuation components (Reynolds decomposition,
Margeirsson, 2007). For the velocity components:
where and are the mean and fluctuating velocity components
respectively. Scalar variables are decomposed in a similar way.
When expressions of this form for the flow variables are substituted
into the instantaneous continuity and momentum equations and a
time (ensemble) average is taken the Reynolds-averaged Navier-
Stokes (RANS) equations are yielded. They can be written as;
Here the overbar on the mean velocity has been dropped. The
velocities and other solution variables now represent time-
averaged values instead of instantaneous values. The additional
terms that have appeared are called Reynolds stresses
and must be modeled in order to close Eq. (5). Because
turbulence is the main cause of entrainment, a turbulence-
transport model must be used in connection with the air-
entrainment model and the traditional k-epsilon (ε) turbulence
model be employed in the present study. It is one of the two-
equation models which are considered the simplest of the so
called complete models of turbulence. Ever since it was proposed
in 1972 its popularity in industrial flow simulations has been
explained by its robustness, economy and reasonable accuracy
for a wide range of turbulent flows. The details of the k-ε model
can be found in Kim (2007). Free surfaces are modeled with the
Volume of Fluid (VOF) technique, which was first reported in
Nichols and Hirt (1975), and more completely in Hirt and
Nichols (1981). Trademarked as TruVOF, this technique is one of
the defining features of the program and provides three important
functions for free surface flow: location and orientation of free
surfaces within computational cells, tracking of free surface
motion through cells, and a boundary condition applied at the
free surface interface.
The location of the flow obstacles is evaluated by the program
implementing a cell porosity technique called the fractional area/
volume obstacle representation of FAVOR method (Hirt, 1992).
The free surface was computed using a modified volume-of-fluid
method (Hirt and Nichols, 1981). For each cell, the program
calculates average values for the flow parameters (pressures and
velocities) at discrete times using staggered grid technique
(Versteeg and Malalasekera, 1996). On the Cartesian coordinate
system (x, y, z), governing equations for analysis of incompressible
three dimensional flow are given below by Kim et al. (2010):
Where, are velocity components in the coordinate
directions , are fractional areas open to flow
in the coordinate directions of , ρ is density and RSOR is a
density source term.
where, VF is a fractional volume open to flow, p is pressure,
are body accelaration in the coordinate direction
, and are viscous accelerations in the coordinate
direction .
The VOF method is based on the assumption that the two
fluids are not interpenetrating. Each phase (fluid) is given a
variable that accounts for how much percentage of each
computational cell is occupied by the phase. This variable is
called a volume fraction of the phase. The volume fractions of all
phases sum up to unity in each computational cell. The fields for
all variables and properties are shared by the phases and represent
volume-averaged values. Variables and properties represent either
only one phase or a mixture of phases in a given cell depending
on the volume fractions of the phases in the cell. If is
equal to 1, the control volume will be full of fluid, and F is equal
to 0, no fluid will exist in a control volume. Furthermore, in the
case of a free water surface, F is shown to have the value
between 0 and 1. Applying function F to Eq. (6) governing
equation becomes:
FLOW-3D version V10.0 was used to simulate flow over the
Kavsak Dam along with the renormalized group turbulence
model. A rectangular grid was defined in the computation
domain shown in Fig. 6. Total number of grid cells was
approximately 6.24E+06 in which only 4.36E+06 of them were
active. The corresponding uniform mesh size used in meshing
was x = y = z = 0.5 m with rectangular grid system and 40-hr
elapsed computational duration. There were many tests have
been conducted to validate the usefulness of the air-entrainment
model. In each one, after finding the mesh size for each case, the
air entrainment rate coefficient was selected as Cai r = 0.5. Souders
and Hirt (2004) also indicated that, the value of air entrainment
coefficient, Cair, is expected to be less than unity because only a
portion of the raised disturbance volume is occupied by air. Cair =
0.5 assumes on average that air will be trapped over about half
------ ui
---- ρui
------ ρuiuj
------ uui
------ ρuiuj
----- uAx
----- vAy
----- wAz
()+++ RSOR
----- 1
----- vAy
----- wAz
xyz,,() fxfyfz
------ 1
----- FuAx
----- FvAy
Investigation of Flow Over Spillway Modeling and Comparison between Experimental Data and CFD Analysis
Vol. 00, No. 0 / 000 0000 7
the surface area. Usta E. (2014) selected air entrainment rate
coefficient 0.5 as the value which is suitable for most cases
recommended by Flow 3D User Manuel, 2012.
To simulate given flow, it is important that the boundary
conditions accurately represent what is physically occurring.
Because the flow is defined in Cartesian coordinates, there are
six different boundaries on the computational mesh domain. The
boundary conditions on the mesh were set as follows: sidewalls
y- common no slip, non-porous/wall; top z-pressure boundary
with gauge pressure equal to zero (atmospheric); bottom z-no
slip/wall; left x-local stagnation pressure based on upstream total
head H over the spillway crest with a hydrostatic pressure
distribution; and right x-local static pressure based on downstream
tailwater elevation with a hydrostatic pressure distribution. 50 m
upstream and 200 m downstream of the spillway crest were used
as the boundary conditions of left x and right x, respectively.
In running the FLOW-3D CFD software, computation modules
of viscosity and turbulence, gravity, air-entrainment, and density
evaluation were activated for all cases studied. Since there are no
prototype data available for comparison to the CFD solution, the
data from the physical model have been scaled to prototype
6. Discussion and Results
The main purpose of this part of the studies to compare results
from a physical model with that of a CFD model for flow over an
ogee crest spillway and through stilling basin. The flow rates
over the spillway crest and free surface elevations, depth-
averaged velocity distributions, and the pressures acting on the
crest and on the stilling basin are used to compare the differences
between the physical model and the CFD model. The existing
Kavsak Dam physical model data have been used as a baseline
of this comparison (Kumcu, 2010).
Table 2 shows the physical model measured flow rates (QPM)
and the numerically calculated flow rates from the CFD model
(QCFD). The results have been normalized to allow a comparison
in their simplest form in Fig. 4. The 10000 years return period
parameters, (H0)10000 = 16.46 m and Q10000 = 5053 m3/s, from
physical model are used as the basis. In Fig. 7 the static head
above crest, H0, is normalized by the (H0)10000 and shown in the
abscissa. The discharge Q is normalized by Q10000 and shown on
the ordinate. Using the physical model and its discharge as
observed standard, the relative percent difference in discharge is
calculated in Table 3. The relative percent difference at a given
(H0)/(H0)10000 is defined as (QCFD - QPM)/QPM x100 and shows that
the CFD model agrees within 3.2% in average with the physical
The data for Q10000 = 5053 m3/s in the physical model was used
for the comparison of free surface elevation between the physical
model and the CFD model as seen in Fig. 8. Since similar results
Table 3. Comparison of Observed Flow Rate Versus Computed
Flow Rate (prototype scale)
1 1000 1034 3.4
2 2500 2415 3.4
3 3856 4001 3.7
4 5053 5170 2.3
Fig. 6. (a) Solid Model, (b) Solid Model with Mesh of the Kavsak
Dam Spillway used in the CFD Simulations (final design)
Fig. 7. Comparison between the Physical Model (PM) and the
Numerical Model (CFD) Predictions for Flow Rates Over
Fig. 8. Comparison of Free Surface Elevations between Physical
Model and CFD Model for Q= 5053 m3/s
Serife Yurdagul Kumcu
8KSCE Journal of Civil Engineering
were obtained, other simulation plots and comparison with
physical model data will not be given here. In the comparison,
free surface data is plotted in elevation where the crest is at 300
m above the sea level. As seen in the figure, the majority of the
points overlap exceptionally well, while only the hydraulic jump
roller region on the profile seems to exhibit any notable error.
This is due to the difficulties of both CFD modeling and
measurement in physical model in accounting effects of strong
turbulence at the hydraulic jump region and flow aeration with
related consequences on bulking of flow depth.
Figures 9 shows 2D view of depth-averaged velocity contours
obtained from the CFD model for the flow rate of Q = 5053 m3/s.
Since most of the free surface elevation data of physical model
overlaps the CFD model data, the depth-averaged velocity
values of both models also show similarities. The maximum
value of depth-averaged velocity was found as approxiamtely 32
m/sec which creates a potential risk for cavitation damage.
The distiribution of air antrainment rate obtained from the
CFD model data along with the flow over spillway and through
stilling basin for the flow rate of Q = 5053 m3/s was given in
Fig. 9. CFD Solution of 2D Depth-averaged Velocity Distribution
Along the Spillway Structure for Q10000 = 5053 m3/s (velocity
values are in m/s)
Fig. 10. 2D-CFD Solution of Volume Fraction of Entrained Air Con-
tours Along the Spillway Structure for Q10000 = 5053 m3/s
Fig. 11. Comparison of CFD and Physical Model Pressures for: (a) Q = 1000 m3/s, (b) Q = 2500 m3/s, (c) Q = 3856 m3/s, (d) Q = 5053 m3/s
Investigation of Flow Over Spillway Modeling and Comparison between Experimental Data and CFD Analysis
Vol. 00, No. 0 / 000 0000 9
Figure 10. According to the Fig. 7, the bottom surface of the
spillway downstrean of the aerator structure, where potentially
under the risk of cavitation damage, is sufficiently aerated. Since
the value of 1-3% of air concentration can be generally accepted
as a critical value for the prevention of cavitation damage, CFD
results promise always more than 10% of air conenration value.
With the horizontal distance starting from the crest axis the
bottom pressure distributions (in Pascal) along the spillway and
stilling basin have been shown on Figs. 8 to provide a comparison
of spillway and stilling basin average pressures for four different
flow rate conditions on the physical model as; Q = 1000 m3/s,
2500 m3/s, 3856 m3/s, and 5053 m3/s. Pressures from the CFD
model compared quite favorably with the scaled physical model
data with the exception of pressure data obtained around baffle
blocks located at the longitudinal distances of 50.5 m and 86 m
from the spillway crest. On prototype scale, the maximum
absolute pressure difference was predicted at the longitudinal
distance of 86 m from the crest as H = 19.2 m for Q10000 = 5053
m3/s. The possible source of error was considered from the
selection of uniform mesh size as x = y = z = 0.5 m
throughout the computation domain. For a finer meshing with
nested mesh blocks (e.g. x = y = z = 0.25 m or finer) better
predictions around baffle blocks could be expected from the
CFD model that will be part of the another subsequent research
The data presented in Fig. 11 demonstrates that CFD modeling
is capable of reasonably predicting pressures on spillways and
stilling basins. The concern of modeling supercritical flow
transitioning to subcritical flow has been still a difficult problem
to solve, however numerical advances are rapidly reducing the
inherent difficulties of this problem (Savage and Johnson, 2006).
7. Conclusions
In this study, 1/50-scaled physical model was conducted in
order to investigate flow conditions and rating curves for full
openings of the radial gates of the spillway and flow over the
spillway for the operating conditions in the Kavsak Dam. A
series of experiments are tested in the State Hydraulic Works
Hydraulic Laboratory. Some modifications were done to obtain
uniform flow conditions and decreasing the energy losses
through the approach. Cavitation risk was tested flow along the
spillway. Aerators and damps are added as there was cavitation
risk. After observing final design for the approach flow
conditions and spillway, an attempt was made to simulate flow
over a spillway structure using commercially available CFD
software. Obtained results from the full-scaled (prototyped) CFD
model was compared to existing physical model data of the
Kavsak Dam and HEPP.
The flow rate results show that the CFD model provided a
reasonable solution. The average relative percent difference
between the CFD model and the physical model was obtained as
The CFD results obtained for free surface elevation and depth-
averaged velocity fit generally the physical model data, whereas
some difficulties observed at the flow transition from supercritical
to subcritical through the hydraulic jump region mainly due to
effects of high turbulence and flow bulking.
Although numerical methods offer a potential to provide
solutions with increasing accuracy, physical model studies are
still considered as the basis from which all other solution
methods used.
Bureau of Reclamation (1977). Design of small dams, U.S. Government
Printing Office, Washington, D.C., U.S.
Bureau of Reclamation (1990). Cavitation in chute and spillways,
Engineering Monograph, No.42, U.S.
Chanel, P. G. (2008). An evaluation of computational fluid dynamics for
spillway modeling, MSc Thesis, University of Manitoba Winnipeg,
Manitoba, Canada.
Chanson, H. (2002). The hydraulics of stepped chutes and spillways,
Balkema, Lisse, The Netherlands.
Chanson, H. and Gonzalez, C. A. (2005). “Physical modeling and scale
effects of air-water flows on stepped spillways.” Journal of Zhejiang
University Science, Vol. 6A, No. 3, pp. 243-250.
Demiroz, E. (1986). “Specifications of aeration structures which are
added to the spillways.” DSI Report, HI-754, DSI-TAKK Publications,
Ankara, Turkey.
Erfanain-Azmoudeh, M. H. and Kamanbedast, A. A. (2013). “Determine
the appropriate location of aerator system on gotvandoliadam's
spillway using Flow 3D.” American-Eurasian J. Agric. & Environ.
Sci., Vol. 13, No. 3, pp. 378-383, DOI: 10.5829/idosi.aejaes.2013.
13.03. 458.
Falvey, H. T. (1990). Cavitation in chutes and spillways, Engineering
Monograph 42 Water Resources Technical Publication US Printing
Office, Bureau of Reclamation, Denver.
Flow-3D User ’s Manual (2012). Flow science, Inc., Santa Fe, N.M.
Hirt, C. W. (1992). “Volume-fraction techniques: Powerful tools for flow
modeling.” Flow Science Report, No. FSI-92-00-02, Flow Science,
Inc., Santa Fe, N.M.
Hirt C. W. and Nichols B. D. (1981). “Volume of Fluid (VOF) method
for the dynamics of free boundaries.” Jornal of Computational
Physics, Vol. 39, pp. 201-225, DOI: 10.1016/0021-9991(81)90145-5.
Hirt, C. W. and Sicilian, J. M. (1985). “A Porosity technique for the
definition of obstacles in rectangular cell meshes.” Proceedings of
the 4th International Conference on Ship Hydro-dynamics, 24-27
September 1985, National Academic of Sciences, Washington DC.
Ho, D., Boyes, K., Donohoo, S., and Cooper, B. (2003). “Numerical
flow analysis for spillways.” 43rd ANCOLD Conference, Hobart,
Tas m a nia .
Johnson, M. C. and Savage, B. M. (2006). “Physical and numerical
comparison of flow over ogee spillway in the presence of tailwater.”
Journal of Hydraulic Engineering, Vol. 132, No. 12, pp. 1353-135,
DOI: 10.1061/(ASCE)0733-9429.
Kim, S. D., Lee, H. J., and An, S. D. (2010). “Improvement of hydraulic
stability for spillway using CFD model.” Int. Journal of the Physical
Sciences, Vol. 5, No. 6, pp. 774-780.
Kokpinar, M. A. and Gogus, M. (2002). “High speed jet flows over
spillway aerators.” Canadian Journal of Civil Engineering, Vol. 29,
No. 6, pp. 885-898, DOI: 10.1139/l02-088.
Kumcu, S. Y. (2010). Hydraulic model studies of Kavsak Dam and
HEPP, DSI Report, HI-1005, DSI-TAKK Publications, Ankara,
Serife Yurdagul Kumcu
10 KSCE Journal of Civil Engineering
Margeirsson, B. (2007). Computational modeling of flow over a spillway,
MSc Thesis, Chalmers University of Technology, Gothenburg, Sweden.
Nichols, B. D. and Hirt, C. W. (1975). “Methods for calculating multi-
dimensional, transient free surface flows past bodies.” Proc. First
Intern. Conf. Num., Ship Hydrodynamics, Gaithersburg, ML.
Savage, B. M. and Johnson, M. C. (2001). “Flow over ogee spillway:
Physical and numerical model case study.” Journal of Hydraulic
Engineering, ASCE, Vol. 127, No. 8, pp. 640-649, DOI: 10.1061/
Souders, D. T. and Hirt, C. W. (2004). “Modeling entrainment of air at
turbulent free surfaces.” Critical Transitions in Water and Environmental
resources Management, pp. 1-10.
entürk, F. (1994). Hydraulics of dams and reservoirs, Water Resources
Publication Colorado, USA.
Teklemariam, E., Korbaylo, B, Groeneveld, J., Sydor, K., and Fuchs, D.
(2001). Optimization of hydraulic design using computational fluid
dynamics, Waterpower XII, Salt Lake City, Utah.
Teklemariam, E., Shumilak, B., Sydor, K., Murray, D., Fuchs, D., and
Holder, G. (2008). “An integral approach using both physical and
computational modeling can be beneficial in addressing the full
range of hydraulic design issues.” CDA Annual Conference,
Winnipeg, Canada.
Usta, E. (2014). Numerical investigation of hydraulic characteristics of
Laleli Dam spillway and comparison with physical model study,
Master Thesis, Middle East Technical University, Ankara, Turkey.
Versteeg, H. K. and Malalasekera, W. (1996). An introduction to
computational fluid dynamics, Longman Scientific and Technical,
Longman Group Limited, Harlow, England.
Vischer, D. L. and Hager, W. H. (1997). Dam hydraulics, J. Wiley &
Sons Ltd., England.
Wagner, W. E. (1967). “Glen Canyon diversion tunnel outlets.” J.
Hydraulic Division, ASCE, Vol. 93, No. HY6, pp. 113-134.
Willey, J., Ewing, T., Wark, B., and Lesleighter, E. (2012). Comple-
mentary use of physical and numerical modeling techniques in
spillway design refinement, Commission Internationale Des Grands
Barrages, Kyoto, June 2012.
... The review concludes that CFD modelling is a cheaper way to obtain a rating curve. The application of CFD models for rating curve investigation is cover by various publications [18]- [20]. In contrast, the physical models are still more reliable in identifying complicated and unexpected problems (especially unsteady flow patterns). ...
... Numerous works published in professional journals [16], [20], [23], [24] and experience from our applied research show that the rating curve determined by the CFD model corresponds with the values measured on the physical model. The relative percent difference between values from CFD and physical model is below 5 %. ...
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Discharge measurement is the base of proper water management. The effective design and operation of hydraulic structures under both normal and extreme flow conditions depend on the quality of hydrological data. Understanding the water system requires consistent and long-term measurement. Despite that, the gauging station network is sparse, and its numbers are declining worldwide. This article aims to draw attention to the possibility of accurate flow measurement using existing hydraulic structures. Flow over a hydraulic structure profile is a physically well-defined phenomenon as the construction shape is fixed and simple compared to river profiles. The discharge can be derived from rating curves, turbine characteristics, and several easily measured variables. That allows continuous discharge measurement. The accuracy is compared with the gauging station on the river. Suitable technical solutions for ensuring and monitoring ecological flow are discussed.
... This multiphase model was applied for this simulation because, contingent on the volume fractions of relative phases in the cell, some variables and components in a given cell reflect group of individual phases or a mixture of phases. Topological changes are automatically taken into account by the level-set concept in VOF [19,20]. Furthermore, because water surface is the point of contact between air and water, implementing boundary conditions here on surface has been disregarded. ...
By recording parameters such as velocity and volume fraction by contour plots or plane, a CFD model enables to analyse flow patterns in the model, such as free-surface vortices A free-surface vortex, a common problem may indeed be observed in a variety of submerged water intakes, notably shallow basins and low head intakes. These FSVs are likely to form an air-core vortex, eventually entrapping detritus and air pockets in the water intake system and causing further vibration and damage to the downstream turbine. When paired with a high velocity, the formation of vortices in the system been known to produce hydraulic transients, which cause unwanted operation or pressure changes. The model of the 1:100 scale dam reservoir was generated, computationally meshed, and modelled in FLUENT under ANSYS 2019 R3 at two different water levels to observe the FSV formations. To mitigate those FSV formations, anti-vortex plates with two distinct plates—square and wedge—were used. From the findings square plates outperform wedge plates because square it lowers the speed of a fast-flowing fluid and reduces it into a laminar flow rather of a turbulent flow, which benefits vortex class deterioration. Data from the simulation and experimental shows a strong agreement in terms of velocity at outlet 1 from both water levels with relative errors of 3.0% and 14.1% respectively
... BC Hydro has been using FLOW-3D to investigate a wide range of challenging hydraulics problems for different types of water conveyance structures, leading to a greatly improved understanding of flow patterns and performance (BC Hydro 2022). Numerical results including velocity, flow depth, and pressure simulated by Flow 3D software are well matched with observation ones (Parsaie et al. , 2016Kumcu 2017). However, the improvement of the confidence in the numerical model results is not able to use for which constructions are lacking measured data on prototype model (BC Hydro 2022). ...
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Hydraulic safety assessments on existingconveyance structurers, such as spillway and outlet work, are urgent tasks in water resources management. 3D numerical model has been considered an efficient tool to evaluate hydraulics characteristics of the flow over these works. Flow 3D model involvingturbulence and air entrainment modules is used to assess flow rate, velocity, pressure, and air entrainment rate alongTa Trach spillway (Thua Thien Hue, Vietnam). Computed discharges released fromspillway and bottomoutlet are well matched with analytical results. Besides, two standards of concrete erosion are used to assess hydraulic safety level under different workingconditions. In the group of extreme cases includingInflow design flood (IDF) and Exceeded flood (EF) cases, spillway is more likely to damage fromcavitation than the culvert with the cavitation indexrangingfrom0.45 to 1.0. While groups of control gate of spillway and culvert are likely to suffer fromabrasion when the high-speed flow appears. The concrete grade of the bottomof culvert is not guaranteed when velocity in culvert is greater than threshold value of 9 m/s, which may cause the surface damage of the construction
... The application of CFD modeling for hydraulic analysis of spillway flows and performance evaluation of aerators is quite recent (Aydin 2018;Gadge et al. , 2019Gurav 2015;Jothiprakash et al. 2015;. Some other researchers like Bennett et al., (2018), Kumcu, (2017), and Yang et al., (2019 have also used CFD models to analyze the flows of different spillway projects. Another branch of CFD, i.e., particle methods in specific SPH (Shadloo et al. 2016;Ye et al. 2019;Luo et al. 2021), is also being applied for simulation of spillway flows (Saunders et al. 2014;Gu et al. 2017;Moreira et al. 2019Moreira et al. , 2020. ...
Submerged spillways with large capacity outlets are generally provided below the dam crest to perform the dual functions of flood disposal and sediment flushing. Flood water passing through these spillways exhibits turbulent behavior. Moreover; hydraulic analysis of such turbulent flows is a challenging task. Therefore, the present study aims to use numerical simulations to examine the hydraulic behavior of submerged spillways constructed at Mangla Dam, Pakistan. Besides, the hydraulic performance of aerator was also evaluated at different operating conditions. Computational fluid dynamics code FLOW 3D was used to numerically model the flows of Mangla Spillway. Reynolds-averaged Navier–Stokes equations are used in FLOW 3D to numerically model the turbulent flows. The study results indicated that the developed model can simulate the submerged spillway flows as it computed the flow parameters with an acceptable error of up to 6%. Moreover, air concentration computed by model near spillway chute bed was 3% which raised to more than 6% after the installation of ramp on aerator which showed that developed model is also capable of evaluating the performance of submerged spillway aerator.
Plunge pools are an economical means for discharging energy flows downstream of dams. However, the high energy discharge usually falls down from a considerable height, which leads to the phenomenon of erosion. The understanding of this risk is of paramount importance. In this study, a numerical modeling using a coupled SPH-FEM-DEM method was developed to simulate the hydraulic behavior of a physical model Ski-Jump Spillway. Several examples of validation demonstrate the precision of developed models.
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This article presents a three-dimensional CFD model and OpenCV code by comparing the flow over the spillway with the experimental data for use in spillway studies. A 1/200-scale experimental model of a real dam spillway was created according to Froude similarity. In the experimental studies, velocity and water depth were measured in four different sections determined in the spillway model. A three-dimensional ANSYS Fluent model of the spillway was created and the simulations of the flows occurring during the flood were obtained. In the numerical model, the two-phase VOF model and k-epsilon turbulence model are used. As a result of the numerical analysis, velocity, depth, pressure, and cavitation index values were examined. The velocity and depth values obtained with models were compared and a good agreement was found between the results. In addition, in this study, a different technique based on image processing is developed to calculate water velocity and depth. A floating object was placed in the spillway channel during the experiment and the movement of the object on the water was recorded with cameras placed at different angles. By using the object tracking method, which is an image processing technique, the position of the floating object was determined in each video frame in the video recordings. Based on this position, the velocity of the floating object and its perpendicular distance to the bottom of the channel was determined. Thus, an OpenCV-Python code has been developed that determines the velocity and water depth of the floating object depending on its position. The floating object velocity values obtained by the algorithm were compared with the velocity values measured during the experimental model, and new velocity correction coefficients were obtained for the chute spillways.
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The AlAdhaim Dam is located 133 kilometers northeast of Baghdad. It is a multipurpose dam and joints the Iraqi dam system in 2000. It has a storage capacity of 1.5 billion m3. The dam has an ogee spillway with a length of 562 m, a crest level of 131.5 m.a.m.s.l. and a maximum discharge capacity of 1150 m3/s at its maximum storage height of 143 m.a.m.s.l. This research aimed to investigate the hydrodynamics performance of the spillway and the stilling basin of AlAdhiam Dam by using numerical simulation models under gated situations. It was suggested to modify the dam capacity by increasing the dam's storage capacity by installing gates on the crest of the dam spillway. The FLUENT program was used to simulate the flow over the spillway. The free surface was calculated using the volume of fluid (VOF) method. To deal with turbulence, the SST k-ω turbulence model was used. The study showed that the spillway is capable of carrying the designed flood discharge and the modified conditions with negative pressure behind the gate and at some points along the spillway. Hydraulic jumps occur at various distances throughout the plunge pool depending on the incoming velocity in the flip bucket.
In this study, the FLOW 3D computational fluid dynamics (CFD) software was used to estimate the performance of the United States Bureau of Reclamation (USBR) type II and USBR type III stilling basins as energy dissipation options for the Mirani Dam spillway, Pakistan. The 3D Reynolds-averaged Navier–Stokes equations were solved, which included sub-grid models for air entrainment, density evaluation, and drift–flux, to capture free-surface flow over the spillway. Five models were considered in this research. The first model has a USBR type II stilling basin with a length of 39.5 m. The second model has a USBR type II stilling basin with a length of 44.2 m. The 3rd and 4th models have a USBR type II stilling basin with a length of 48.8 m and a 39.5 m USBR type III stilling basin, respectively. The fifth model is identical to the fourth, but the friction and chute block heights have been increased by 0.3 m. To set up the best FLOW 3D model conditions, mesh sensitivity analysis was performed, which yielded a minimum error at a mesh size of 0.9 m. Three sets of boundary conditions were tested and the set that gave the minimum error was employed. Numerical validation was done by comparing the physical model energy dissipation of USBR type II (L = 48.8 m), USBR type III (L =35.5 m), and USBR type III with 0.3-m increments in blocks (L = 35.5 m). The statistical analysis gave an average error of 2.5% and a RMSE (root mean square error) index of less than 3%. Based on hydraulics and economic analysis, the 4th model was found to be an optimized energy dissipator. The maximum difference between the physical and numerical models in terms of percentage energy absorbed was found to be less than 5%.
In this study, the vortex formed on the upstream of the frontal water intake structure in a dam lake was investigated by numerical modeling. Using the computational fluid dynamics method, vortex formation for different water levels was examined numerically. The purpose of this study is to prevent the formation of vortex, which can cause serious damage to the hydraulic structure. The water intake structure examined in the study has three units and rectangular shapes. The geometrical areas of each unit in the water intake structure are equal. The discharge and the distance between the side curtain walls were kept constant. The pressure at the inlet of the water intake structure has been changed depending on the height of the water level. The model scale of the water intake is 1/40. Froude model affinity was used as the model scale. In the numerical study, air intakes to the extent of serious damage to the structure and vortex formations have been observed. Visual simulations and analysis results of numerical models prepared and analyzed in FLOW-3D were examined in FlowSight. The first numerical models are based on examining the vortexes in the water intake structure, and the later numerical models are on the structures that prevent the vortexes in the water intake structure. Vortex formation in hydraulic structures is an undesirable physical phenomenon. Especially in dams with hydroelectric power plants, it causes serious damage to energy efficiency loss, water intake structure, shortening the service life of turbines and energy tunnels. Due to these problems, different anti-vortex structures were tested on the numerical model by CFD method in order to eliminate or reduce the negative forces from vortexes. Structures that block the tested vortex may allow to increase the operating water level in the dam reservoir. A new water intake structure model has been created for the solution of this hydraulic problem, which may cause great danger. Thanks to the new models created, it has been observed that air intake and vortex formations occur in a way that will cause less damage to the hydraulic structure in question.
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A study was completed to compare how parameters over a standard ogee-crested spillway using a physical model, numerical model, and existing literature. The physical model was constructed of Plexiglas and placed in a test flume. Pressure taps were installed along the entire length of the spillway. Discharge and pressure data were recorded for 10 different flow conditions. A commercially available computational fluid dynamics (CFD) program, which solves the Reynolds-averaged Navier-Stokes equations, was used to model the physical model setup. Data interpolated from U.S. Bureau of Reclamation and U.S. Army Corps of Engineers design nomographs provided discharge and pressure data from the literature. Nondimensional discharge curves are used to compare the results from the different methods. Pressures are compared at low, mid, and high flow conditions. It is shown that there:is reasonably good agreement between the physical and numerical models for both pressures and discharges. The availability and power of existing numerical methods provides engineers with another tool in the design and analysis of ogee spillways.
Hydraulic model test was used to analyze the rapidly varied flow on the spillway. But, it has some shortcomings such as error of scale effect and expensive costs. Recently, through the development of three dimensional computational fluid dynamics (CFD), rapidly varied flow and turbulence can be simulated. In this study, the applicability of CFD model to simulate flow on the spillway was reviewed. The Karian dam in Indonesia was selected as the study area. The FLOW-3d model, which is well known to simulate a flow having a free surface, was used to analyze flow. The flow stability in approach channel was investigated with the initial plan design, and the results showed that the flow in approach channel is unstable in the initial plan design. To improve flow stability in the spillway, therefore, the revised plan design was formulated. The appropriateness of the revised design was examined by a numerical modeling. The results showed that the flow in spillway is stable in the revised design.
Data obtained from two physical models were compared to the results obtained from numerical model investigations of two ogee-crested spillways. In 2001, Savage and Johnson investigated ogee-crested spillways without the effect of tailwater; the present study includes the influence of tailwater on the spillway. The comparison showed that numerical modeling can accurately predict the rate of flow over the spillway and the pressure distribution on the spillway. The results of this study provide users of numerical models performance information that can be used to aid them in determining which tool to use to effectively analyze dams and their associated spillways.
Overview In free-surface flows the turbulence in the liquid may be sufficient to disturb the surface to the point of entraining air into the flow. This process is important, for example, in water treatment where air is needed to sustain microorganisms for water purification and in rivers and streams for sustaining a healthy fish population. Air entrainment is typically engineered into spillways downstream of hydropower plants to reduce the possibility of cavitation damage at the base of the spillway. Other situations where air entrainment is undesirable are in the sprue and runner systems used by metal casters, and in the filling of liquid containers used for consumer products. The importance of being able to predict the amount and distribution of entrained air at a free liquid surface has led to the development of a unique model that can be easily inserted into FLOW-3D ® as a user customization. The model has two options. One option, to be used when the volume fraction of entrained air is relatively low, uses a scalar variable to record the air volume fraction. This model is passive in that it does not alter the dynamics of the flow. A second air-entrainment model, option two, is based on a variable density formulation. This model includes the "bulking" of fluid volume by the addition of air and the buoyancy effects associated with entrained air. However, this dynamically coupled model cannot be used in connection with heat transport and natural (thermal) convection.
Several methods have been previously used to approximate free boundaries in finite-difference numerical simulations. A simple, but powerful, method is described that is based on the concept of a fractional volume of fluid (VOF). This method is shown to be more flexible and efficient than other methods for treating complicated free boundary configurations. To illustrate the method, a description is given for an incompressible hydrodynamics code, SOLA-VOF, that uses the VOF technique to track free fluid surfaces.
This paper discusses numerical methods for caluclating multi-dimensional, transient, free surface flows interacting with general curved boundaries. To effectively model a free surface, three problems must be resolved: the surface must be numerically defined, a presciption must be provided to advance it in time, and appropriate boundary conditions must be applied at the location of the surface. The schemes chosen to meet these conditions must be compatible. (from paper)