EXPLORATION OF SCOUR CHARACTERISTICS AROUND SPUR DIKE...

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

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mailto:[email protected]


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


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)


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.


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)


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]


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


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)


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)


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)


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)


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)


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 [-]

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