exploration of scour characteristics around spur dike...
TRANSCRIPT
International Water Technology Journal, IWTJ Vol. 6 –No.2, June 2016
130
EXPLORATION OF SCOUR CHARACTERISTICS AROUND SPUR DIKE
IN A STRAIGHT WIDE CHANNEL
Elsaiad A.A.1 and
Elnikhely E.A.
*2
Professor of hydraulics1, Water and Water Str. Eng. Dep., Faculty of Engineering, Zagazig
University, Zagazig, Egypt, E-mail: [email protected]
Lecturer2, Water and Water Str. Eng. Dep., Faculty of Engineering, Zagazig University, Zagazig,
Egypt, *Corresponding author E-mail: [email protected]
ABSTRACT
Investigation of scour and determination of hole of scoring around spur dike are among the
most important issues for channel protections. Laboratory experiments were carried out in a straight
rectangular flume with a non-submerged spur dike. The effect of spur dike angled at 90ο, 55
ο, 40
ο and
25ο was studied. Experiments were also conducted for different spur dike nose angle with various
Froude number. The experimental results of the model indicated that the relative maximum depth of
scour is highly dependent on the spur dike inclination angle with channel wall and the nose angle of
spur dike. The relative maximum scour depth decreased by 55% for decreasing the inclination angle of
spur dike from 90ο to 25
ο and by about 45% for decreasing the nose angle from 90
ο to 40
ο. The
greatest hole dimensions of scour was associated with 90ο nose angle of spur dike. Furthermore, the
90 degree spur dike was modeled using SSIIM numerical model. The numerical model was based on
the finite-volume method to solve the non-transient Navier-Stocks equations and a bed load
conservation equation. The numerical results were compared with the experimental results to verify
the numerical model. Moreover, Empirical equations are obtained by using linear regression analysis
for estimating the maximum value of relative scour depth. The predicted results agreed with the
experimental results.
Keywords: Experimental, Spur dike, Scour, Froude number, SSIIM. Received 16 March 2016.Accepted 16, May 2016
1 INTRODUCTION
A spur dike can be defined as an elongated structure having one end on bank and the other end
projecting into the current. Spur dikes have been widely used to redirect the flow in channels and protect
eroding stream banks. The problem of scour around any obstruction placed in an alluvial channel is of great
importance to hydraulic engineers, because an accurate estimation of local scour beside these structures is
very important for safe and economic design of their foundations. Gill (1972) by changing the radius of curve,
the flow depth and the diameter of particles in the direct and bent channels, showed that the distance between
dikes depends on the radius of the curve. Zaghloal (1983) conducted experimental investigations to study the
effects of upstream flow conditions, sediment characteristics, and spur-dike's geometry on the maximum scour
depth and scour pattern around a spur-dike. Suzuki et al. (1987) conducted experiments on characteristics of
the movable channel bed around a series of spur dikes and found that the bed form around a non-submerged
spur dike has a significant impact on the relative distance between the spur dikes and their lengths.
Kuhnle et al. (2002) investigated the local scour associated with angled spur dikes to downstream
channel side wall. The model of spur dikes with two contraction ratios and three angles 45, 90 and 135 were
tested to predict the depth and volume of the scour hole associated with a spur dike. Nagy (2004) studied
maximum depth of local scour near emerged vertical – wall spur dike. An equation for estimating the
maximum scour depth ratio was derived. Ezzeldin et al. (2007) investigated local scour around spur dikes
installed as a training structure on straight channel. Equations to estimate scour depth and scour hole length
upstream and downstream the spur dike were proposed. Ghodsian and Vaghefi (2009) presented the results
of an experimental study on scour and flow fields around a T-shaped spur dike in a 90o bend and found that
International Water Technology Journal, IWTJ Vol. 6 –No.2, June 2016
131
the amount of scour at the upstream of spur dike is much more compared to the downstream of spur dike. Naji
Abhari et al. (2010) reviewed the numerical simulation of flow patterns in a 90o bend using the SSIIM model
and concluded that this model has the ability to calculate the flow pattern in a 90o bend. T-shape spur dike in a
180 degree channel bend was studied by Masjedi et al. (2010). Tests were conducted using one spur dike
with 110 mm length in position of 60 under four flow conditions to study the effects of various flow
intensities. It was found that the depth of scour increased as time increased, Masjedi et al. (2010). Masjedi
and Foroushani (2012) studied the effect of different shape of single spur dike in river bend on local scour. It
was found that, the least erosion of the around in the near bank resion was associated with the spur dikes with
oblong shape. For different sets of dikes arrangements, the local scour magnitude for permeable dikes was
reduced significantly compared to that of impermeable ones, Osman and Saeed (2012).
The time evolution of scour around spur dike for several duration was investigated by Shafaie et al.
(2008). An equation shown the relation between scour depth and time of scour was derived. The turbulence
intensity distribution around spur dikes with different structures under the same flow condition was studied by
Zhang et al. (2012). It can be calculated that the turbulence intensity in the arc-like spur dike and fan-like are
relatively weaker than that of the hook-like spur dike, and the strongest turbulence intensity occurs around the
trapezoidal spur dike. Downstream of the spur dike, the concentration fluctuation became intensive with the
increase of spur dike angle, Chen and Jiang (2010). Flow and scour patterns resulted from the installation of
two T-shaped spur dikes were evaluated in a 90ο bend under clear water conditions. The submerged and
nonsubmerged spur dikes were modeled numerically at different locations in the bend. In the submerged
mode, the maximum scour depth decreased to 22% compared to the non-submerged mode one, Vaghefi et al.
(2015). The turbulent flow in the local scour hole around a single non-submerged spur dyke was investigated
with both experimental and numerical methods Zhang et al. (2009). It was found that the simulation results
are reasonably consistent with those of the experimental measurements.
Karami et al. (2012) investigated scour phenomenon around a series of impermeable, nonsubmerged
spur dikes with both experimental and numerical methods. A comparison between experimental and
numerical results was carried out to verify the CFD model. Li et al. (2013) used FLOW-3D software to
simulate the three-dimensional flow and local scour around a non-submerged spur dike. Ali et al. (2012)
studied the time development of the scour hole around the spur dike plates. It was observed that, with
increasing time development the greatest hole of the scour was associated with 75 degree spur dike. Vaghefi
et al. (2014) used a numerical study around a T-shaped spur dike in a 90ο bend, it was concluded that by
increasing the submersion of the spur dike, the flow changes into up flow behind the wing. Vaghefi et al.
(2014) studied the effect of submergence ratio of a T-shaped spur dike on the water surface profile in a 90ο
bend, using the SSIIM model. They concluded that the SSIIM numerical could accurately simulate the flow
pattern and scour in a 90ο bend.
Lodhi et al. (2016) investigated the influence of cohesion on scour depth around submerged spur dike
founded in the mixtures of cohesive sediment consisting of clay–gravel and clay–sand–gravel. The process,
geometry and scour depth around submerged spur dike in cohesive sediments were significantly affected by
clay percentage and unconfined compressive strength of cohesive sediment mixtures. The principle objective
of this study is to carry out experimental tests to investigate the local scour phenomenon and the relation
between the dimensions of the scour hole that takes place beside the spur dike, and between the flow
parameters, the angle of inclination, and the spur dike nose angle. The 90ο spur dike was modeled numerically
using SSIIM model. Regression analysis was used to predict some formulas between the relative maximum
scour depth against other parameters involved in the phenomena.
2 EXPERIMENTAL SETUP
Layout of experimental set up is illustrated in Fig. (1). Experiments were conducted in a straight
rectangular flume of 0.4 m wide, 0.20 m deep and 4.0 m length, as shown in Fig. (1) and Fig. (2a). The
laboratory flume was made from a self-colored, glass reinforced plastic mounding. The discharges were
measured using a pre-calibrated orifice meter fixed in the main flow line. The tailgate was fixed at the end of
the experimental part of the flume; it was used to adjust the tail water depth at the downstream side. The water
International Water Technology Journal, IWTJ Vol. 6 –No.2, June 2016
132
depths were measured by means of point gauges. The model sand is non uniform (uniformity coefficient
=D60/D10 =1.52<6.0) with D50=1.78mm, and geometric mean standard deviation =D85/D15 =1.54. The model of
spur dike was built from wood with length L=10 cm, height h= 15 cm, and 1.5 cm thickness. The water
surface levels were measured along the center line of the flume at the upstream and downstream of the spur
dike model. Water surface levels and scour dimensions were measured around the spur dike by using an
ordinary point gauge (of 0.1 mm accuracy) which was mounted on a carriage.
The experimental program is summarized as in tables (1), it is including two stages. Stage I explores
the effect of spur dike alignment angle. This stage includes four different angles θ =90ο, 55
ο, 40
ο and 25
ο,
while the nose angle was fixed α=90ο
see Fig. (1). Stage II explores the second group of models were aligned
perpendicular, i.e. θ=90ο, and the nose was sloped with angles α=90
ο, 70
ο, 55
ο and 40
ο, as shown in Fig. (2b).
The total number of Experiments is 90.
Figure 1. Schematic diagram of the experimental model
Figure 2. a) The flume used. b) The tested models α=90 ο, 70
ο, 55
ο and 40
ο
Table 1. Scheme of experimental work stages.
Model Description
1 θ =90
ο, 55
ο, 40
ο and 25
ο
for α=90 ο
2 θ =90
ο
for α=90 ο
, 70 ο,55
ο, and 40
ο
3 DIMENSIONAL ANALYSIS
A dimensional analysis is used to correlate the different variables affecting the local scour at spur
dike. The different variables affecting the local scour at spur dikes (hs) are expressed as:
ℎ𝑠
𝑦= 𝑓 𝜆,
𝐿𝑢𝑠
𝑦,𝐿𝑑𝑠
𝑦,𝑤
𝑦, 𝜃, 𝛼 (1)
(a) (b)
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133
which: hs
y = the relative maximum scour depth; is the kinetic energy factor λ = 𝐹𝑛
2 ; Fn = Froude number;
𝐿𝑢𝑠
𝑦= the relative length of scour upstream the spur dike;
Lds
y = the relative length of scour downstream the
spur dike; w
y = the relative width of scour hole; y = the water depth ; θ = the angle of spur dike junction with
channel side; and α = angle of spur dike nose.
3 THE NUMERICAL MODEL
SSIIM is an abbreviation for simulation of sediment movements in water intakes with multiblock
option empirical equations. The SSIIM program solves the Navier-Stokes equations with the k − ε on a three
dimensional and general non-orthogonal grids. These equations are discredited with a control volume
approach. An implicit solver is used, producing the velocity field in geometry. The velocities are used when
solving the convection-diffusion equations for different sediment sizes. The Navier-Stokes equations for non-
compressible and constant density flow can be modeled as:
∂U i
∂t+ Uj
∂U i
∂xj=
1
ρ
∂
∂xj −pδij − ρuiuj (2)
where, Ui = the local velocity, xj = space dimension, p = pressre, δij = kronecker delta, ρ = fluid density
and ui = the average velocity.
The first term on the left side of the Equation (2) indicates the time variations, the second term is the
convective term. The first term on the right-hand side is the pressure term and the second term on the right
side of the equation is the Reynolds stress. This equation is solved using finite discontinuing volume method.
A control-volume approach is used for discretization of the equations. The Reynolds stress is evaluated using
turbulence model k − ε .
−uiuj = υT ∂u i
∂xj+
∂u j
∂xi -
2
3 kδij (3)
The first term on the right – hand side of the Equation (3) is the diffusive term in The Navier-Stokes
equations.The influence of rough boundaries on fluid dynamics is modeled through the inclusion of the wall
law as given as follows:
U
U∗=
1
Kln 30z Ks (4)
where, ks equals to the roughness height, which calculated using Van Rijns (1987), K is von Karmen
constant, U is the mean velocity, U∗is the shear velocity and z is the height above the bed.
4 MODEL GEOMETRY AND PROPERTIES
A structured grid mesh on the x-y-z plane was generated. An uneven distribution of grid lines in both
horizontal and vertical directions was chosen in order to keep the total number of cells in an acceptable range
and to get valuable results in the area. The spur dike was generated by specifying its ordinates, and then the
grid interpolated using the elliptic grid generation method. However, the spur dike was generated by blocking
the area of spur dike, Fig.(3) shows the grid mesh generation around spur dike.
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134
Figure 3. Mesh generation around spur dike
5 MODEL VERIFICATION
Figure (4) shows experimental results of maximum scour depth as a ratio of the tail water depth, (hs/y)
Experimental, versus the numerical values, (hs/y) SSIIM, predicted by the 3D numerical model for the case of
spur dike angled at 90o. It is noticeable that there were well agreement between the experimental and
numerical values of maximum scour depth with an average correlation coefficient of 97%. Figure (5) shows
also a comparison between the present experimental results and the experimental results of Ezzeldin et al
(2007). It is observed that very close values of scour depth were obtained.
Figure 4. Simulated versus experimental for (hs/y) for 90
o spur dike
Figure 5. Agreement of Ezzeldin et al (2007) results with the experimental measurements
for 90o spur dike
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 0.2 0.4 0.6 0.8 1 1.2 1.4
hs/
y Ex
per
imen
tal
hs/y (SSIIM data)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18
hs/
y
λ
Recent data
Ezzeldin et al (2007)
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135
Figures (6) to (8) show the contour maps of scour holes for the case of spur dike angled at 90o. It
can be concluded that the hole geometry has the approximate form of an inverted frustum cone with its
vertex representing the point of maximum depth of scour which is almost occurs near the groin tip. The
base of scour hole is circular with its center on the extent of the spur longitudinal centerline. The horizontal
velocity distribution over the mobile bed by distance 0.1% of water depth for 90o spur dike is shown in
Fig.(9). It can be seen that, there is a large vortex around the spur dike due to the presence of spur dike, the
velocity increased rapidly with the decrease of the channel wide. At downstream of the spur dike, the
velocity recovers gradually; the water flow goes towards the side of the flume and forms a wake zone with
low speed behind the dike.
Figure 6. Scour hole contour map [θ= 90o, Fn=0.247]
Figure 7. Scour hole contour map [θ= 90o, Fn=0.262]
Figure 8. Scour hole contour map [θ= 90
o, Fn=0.322]
International Water Technology Journal, IWTJ Vol. 6 –No.2, June 2016
136
Figure 9. Horizontal velocity distribution over the mobile bed by distance 0.1% of water depth
for [θ= 90o, Fn=0.322]
6 ANALYSIS
A long experiment was conducted at the position of θ = 90o, α=90
ο for a spur dike, to estimate the
ultimate scour depth. Fig. 10 shows the relation between hs/hst and T/To where:
hst: The ultimate scour depth,
T: Time of scour, and
To: The ultimate scour time (150 min.).
It is noticed that, the scour depth hs reaches to 0.95% hst at T/To=0.85, this means that the stability of
scour depth occurs at time T= To=120 min.
Figure 10. The relation between T/To and hs/hst
7.1. Effect of Spur Dike Alignment Angle
Spur dike may be positioned facing upstream (repelling groin), normal to flow (deflecting groin) or
facing downstream (attracting groin). Each orientation to the flow affects the river current in a different way.
The present study is limited on the cases of deflecting and attracting groins. The angle tested in this research
was 90ο, 55
ο, 40
ο and 25
ο. The relationships between 𝜆 and the different scour parameters including hs/y,
Lus/y, Lds/y and w/y are presented, for different spur dike alignment angles, see Figs. (11a, 11b, 11c and 11d),
respectively. Generally, it can be noticed that all scour parameters increases as 𝜆 increases. In addition, scour
parameters hs/y and w/y are minified to the minimal limit in case of spur dike alignment angle, θ = 25o. The
relative scour depth hs/y decreases by about 55% for θ = 25o compared to the case of θ = 90
o. This may be
referred to that the angle affects on flow velocity where the velocity of flow changed to facing flow, angle 90o
repelling flow strongly than another and become smooth gradually as decreasing θ from 90o to 25
o . It is
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 1.2
hs/
hst
T/To
International Water Technology Journal, IWTJ Vol. 6 –No.2, June 2016
137
noticed that, the relative scour length Lus/y decreasing by about 40% by decreasing the angle θ from 90o to
40o. It can be seen that for the case of θ = 25
o the upstream scour length disappears and the scour hole is
totally exist in the downstream side of spur dike as shown in Fig. (11b). In contrast, the relative scour length
Lds/y decreasing by about 60% for the case of θ = 90o
(i.e. spur dike alignment doesn’t show a significant
effects on scour hole length downstream the spur dike), spur dike angled at 25o gives the longer downstream
scour hole length. The relative scour width w/y reduces by about 38% for θ = 25o compared to θ = 90
o. From
previous figures the case of θ = 25o gives the best performance in bank protection.
7.2. Effect of Spur Dike Nose Angle
Figs. (12a, 12b, 12c, 12d) show the relationships between 𝜆 and the different scour parameters
including hs/y, Lus/y, Lds/y and w/y for different spur dike nose angles of α=90ο, 70
ο, 55
ο, and 40
ο. It is
obvious that all scour parameters increase as 𝜆 increases. Spur dike nose angle of α=40 ο
gives the minimum
values of hs/y by about 45%, meaning that the nose angle α=40ο is the best angle which causes minimum
scour depth. It was investigated that, the relative scour length of hole in the upstream Lus/y reached to its
minimum value in case of α=40ο , it reduces the relative upstream scour length Lus/y, by about 50% compared
to the case of α=90ο. However, α=90
ο causes the maximum reduction of the relative scour length in the
downstream Lds/y by about 30%. The maximum reduction of scour hole width w/y was found at α=40ο by
about 24%. It is noticed that the spur dike nose angle α has a significant effect on the different scour
parameters.
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18
hs/
y
𝜆
θ=90
θ=55
θ=40
θ=25
0
0.5
1
1.5
2
2.5
0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18
Lus/
y
𝜆
θ=90
θ=55
θ=40
(a)
(b)
International Water Technology Journal, IWTJ Vol. 6 –No.2, June 2016
138
Figure 11. Relations between 𝜆 and the different scour parameters for different spur dike alignment
angle θ and constant α=90 o.
0
2
4
6
8
10
12
0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18
Lds/
y
𝜆
θ=90
θ=55
θ=40
θ=25
0
1
2
3
4
5
6
7
8
0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18
w/y
𝜆
θ=90
θ=55
θ=40
θ=25
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16
hs/
y
𝜆
α=90
α=70
α=55
α=40
(c)
(d)
(a)
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139
7 STATISTICAL REGRESSION
Based on the experimental measurements, statistical equations were proposed to predict the relative
scour depth. Depending on the regression tasks and statistical analysis and using the regression tool, the
statistical equation (1) was built to predict the studied parameters.
8456.07145.0405.14 ky
hs (5)
(6)
0
0.5
1
1.5
2
2.5
3
3.5
4
0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16
Lus/
Y
𝜆
α=90
α=70
α=55
α=40
0
1
2
3
4
5
6
7
0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16
Lds/
y
𝜆
α=90
α=70
α=55
α=40
0
1
2
3
4
5
6
7
8
9
0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16
w/y
𝜆
α=90
α=70
α=55
α=40
7011.0869.0064.8 ky
hs
Figure 12. Relations between 𝜆 and the different scour parameters for different
spur dike nose angle α and constant θ = 90o
(b)
(c)
(d)
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140
where:
kθ: alignment coefficient = θ/90.
kα: nose angle coefficient = α/90.
These equations are valid within the following ranges of the involved parameters: hs/y [0.15-1.3], λ [0.03-
0.166], 𝑘𝜃 [0.5-1.0] and 𝑘𝛼 [0.5-1.0]. Figs. (13a, 13b) shows the calculated values of the investigated
parameters against the measured ones for eqns. 5 and 6, respectively.
Generally, it can be observed that, there is an acceptable agreement between the measured data and
the predicted ones. The results showed well agreement between the experimental and predicted values of hs/y
(R2 = 0.94, 0.86). The residuals of the previous equation are plotted versus the predicted values as shown in
Figs. (14a, 14b). R2 between residuals and predicted values are 1.06E
-23&7.25E
-20.
Figure 13. Comparison between experimental results and statistical
model Eqns. (5) & (6) results.
0
0.2
0.4
0.6
0.8
1
1.2
0 0.2 0.4 0.6 0.8 1 1.2
hs/
y (m
easu
red
)
hs/y (predicted)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
hs/
y (m
eas
ure
d)
hs/y (Predicted)
(a)
(b)
International Water Technology Journal, IWTJ Vol. 6 –No.2, June 2016
141
Figure 14. Variations of residuals for different data sets with predicted data
Eqns. (5) & (6)
8 CONCLUSION
The results of several long duration scour laboratory experiments around spur dike are presented in
this work to investigate the characteristics of scour hole around a single spur dike installed in a straight flume.
The analysis of the results shows the following conclusions:-
All of scour parameters increase with the increase of the kinetic flow factor 𝜆 with a linear trend.
The spur dike oriented at angle 25 o
showed a good performance in reducing the scour depth and in bank
protection.
Decreasing the spur dike alignment angle from 90 ο to 40
ο reduces the relative upstream scour length Lus/y
by about 40%.
Spur dike angled at 25 o gives the longer downstream scour hole length.
The relative scour dimensions decreases by decreasing the spur dike nose angle from 90 ο
to 40 ο by ratios
45% for depth, 50% for upstream length, and 24% for width of scour hole.
In addition, the simulated results show the ability of SSIIM for modeling the local scouring around spur
dike with an average correlation coefficient of 98%.
The results of the proposed statistical equations are compared to the experimental measurements and an
acceptable agreement has been found
-0.2
-0.1
0
0.1
0.2
0.3
0 0.5 1 1.5
Res
idu
als
Predicted
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0 0.5 1 1.5 2Re
sid
ual
s
Predicted
(a)
(b)
International Water Technology Journal, IWTJ Vol. 6 –No.2, June 2016
142
NOTATIONS
Fn :Froude number [-]
hs : maximum scour depth [L]
hst: The ultimate scour depth [L]
Lus :Scour hole length upstream the spur dike. [L]
Lds :Scour hole length downstream the spur dike. [L]
T : Time of scour [T]
To: The ultimate scour time [T]
w : width of scour hole [L]
y : water depth [L]
θ : angle of spur dike junction with channel side [-]
α : angle of spur dike nose [-]
𝜆: Kinetic flow factor [-]
REFERENCES
Ali, R.; Alireza, J. & Rashid S. (2012) Investigation on Scour Hole Around Spur Dike in a 180 Degree
FlumeBend. World Applied Sciences Journal, 19(7), pp.924-928.
Chen, L.P. & Jiang, J.C. (2010) Experiments and numerical simulations on transport of dissolved
pollutants around spur dike. Journal of Water Science and Engineering, 3(3), pp.341-353.
Ezzeldin, M.M.; Saafan, T.A.; Rageh, O.S. & Nejm, L.M. (2007) Local scour around spur dikes.
11th International Water Technology Conference, IWTC11, Sharm El-Sheikh, Egypt, pp.779-795.
Ghodsian, M. & Vaghefi, M. (2009) Experimental study on scour and flow field in a scour hole around a
T-shape spur dike in a 90 degree bend. International Journal of Sediment Research, 24(2), pp.145–158.
Gill, M.A. (1972) Erosion of sand beds around spur dikes. Journal Hydraulics Division, 98(9), pp.91-98.
Karami, H.; Basser, H.; Ardeshir, A. & Hosseini, S.H. (2012) Verification of numerical study of scour around
spur dikes using experimental data. Water and Environmental Journal, 28(1), pp.124-134.
Kuhnle, R.A.; Alonso, C.V. & Douglas, S.F. (2002) Local scour associated with angled spur dikes.
Journal of hydraulic engineering, 128(12), pp.1087-1093
Li, G.; Lang, L. & Ning, J. (2013) 3D Numerical Simulation of Flow and Local Scour around a Spur
Dike. IAHR World Congress, pp.1-9.
Lodhi, A.S.; Jain, R.K. & Sharma, P.K. (2016) Influence of cohesion on scour around submerged dike
founded in clay–sand–gravel mixtures. ISH Journal of hydraulic engineering, 22(1), pp.70-87.
Masjedi, A.; Bejestan, M.S. & Moradi, A. (2010) Experimental study on the time development of local
scour at a spur dike in a 180o flume bend. Journal of food, Agriculture & environment, 8(2), pp.904-907.
Masjedi, A.; Dehkordi, V.; Alinejadi, M. & Taeedi, A. (2010) Experimental study on scour depth around
a T-shape spur dike in a 180 degree bend. World Applied Sciences Journal, 10(10), pp.1146-1152.
Masjedi, A. & Foroushani, E. (2012) Reduction of local scour by shape of single spur dike in river bend.
9th ISE, Vienna.
Nagy, H.M. (2004) Maximum depth of local scour near emerged vertical-wall spur dike. Alexandria
Engineering Journal, Faculty of Engineering, Alexandria University, Egypt, 43(6), pp.819-829.
International Water Technology Journal, IWTJ Vol. 6 –No.2, June 2016
143
Naji, A.M.; Ghodsian, M.; Vaghefi, M. & Panahpur, N. (2010) Experimental and numerical simulation of
flow in a 90 degree bend Flow. Measurement and Instrumentation, 21(3), pp.292-298.
Osman, M.A. & Saeed, H.N. (2012) Local scour depth at the nose of permeable and impermeable spur
dykes University of Khartoum Engineering Journal, 2(1), pp.1-9.
Shafaie, A. & Ardeshir, A. (2008) Length and orientation of minor spur in the sand bed. Proceedings of
the 4th IASME/WSEAS Int. Conference on water resources, hydraulics & hydrology, pp.46-52.
Suzuki, K.; Michiue, M. & Hinokidani, O. (1987) Local bed form around a series of spur dikes in alluvial
channel. In Proceedings of the 22nd
Congress, IAHR, Lausanne, Switzerland, pp.317-321.
Vaghefi, M.; Safarpoor, Y. & Hashemi, S.S.H. (2014) Effect of T-shape spur dike submergence ratio on
the water surface profile in 90 degree channel bend with SSIIM numerical model. International journal of
advanced engineering and applied research, 7(4), pp.1–6.
Vaghefi, M.; Shakerdargah, M. & Akbari, M. (2014) Numerical study on the effect of ratio among
various of submersion on three-dimensional Velocity Components around T-shaped Spur Dike Located in a
90 degree bend. International Journal Scientific Engineering and Technology, 3(5), pp.675-679.
Vaghefi, M.; Safapoor, Y. & Hashemi, S.S. (2015) Effects of distance between the T-shaped spur dikes
on flow and scour patterns in 90o bend using the SSIIM model. Ain Shams Engineering Journal,
http://dx.doi.org/10.1016/j.asej.2015.11.008.
Zaghloul, N.A. (1983) Local scour around spur-dikes. Journal of Hydrology, 60(1-4), pp.123-140.
Zhang, H.; Nakagawa, H.; Kawaike, Y.B. & Baba, Y. (2009) Experimental and simulation of turbulent
flow in local scour around a spur dyke. International Journal of Sediment Research, 24(1), pp.33-45.
Zhang, X.; Wang, P. & Yang, C. (2012) Experimental Study on Flow Turbulence Distribution around a
Spur Dike with Different Structure. International Conference on Modern Hydraulic Engineering, Science
Direct, 28, pp.772-775.