Aquacultural Engineering 67 (2015) 24–31
Contents lists available at ScienceDirect
Aquacultural Engineering
journal homepage: www.elsevier.com/locate/aqua-online
Experimental study on flow velocity and mooring loads for multiple
net cages in steady current
Yun-Peng Zhao a,∗ , Chun-Wei Bi a,∗ , Chang-Ping Chen b , Yu-Cheng Li a , Guo-Hai Dong a
a
b
State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China
Civil Engineering, Dalian Ocean University, Dalian 116023, China
a r t i c l e
i n f o
Article history:
Received 14 February 2015
Received in revised form 7 May 2015
Accepted 18 May 2015
Available online 28 May 2015
Keywords:
Net cage
Multi-cage system
Hydrodynamic characteristics
Flow-velocity reduction
a b s t r a c t
To enable the optimum design and evaluation of fish farm and mooring performance in the energetic
open ocean, a series of physical model experiments were conducted to investigate the hydrodynamic
characteristics of a large fish farm containing 1 up to 8 net pens with the model scale of 1:40. In the physical
model experiments, the main mooring line tension and flow-velocity magnitude were measured when
current flowed through the multiple net cages. According to the experimental data, the upstream anchor
lines of the cage will endure most of the current load acting on the multi-cage system. When the net cages
are arranged in double columns, the tension force in the upstream anchor lines increases with increasing
number of net cage. But this phenomenon is not obvious when the net cages are arranged in single column.
There exists obvious flow-velocity reduction inside net cages of the multi-cage configurations; however,
there is no statistical difference in flow velocity over varied configurations with different number of
net cage. The appropriate multi-cage system in engineering practices should be determined through
considering both the mooring line force and the flow-velocity distribution.
© 2015 Elsevier B.V. All rights reserved.
1. Introduction
Marine aquaculture is expanding all over the world, and the net
cage is becoming prevalent in the aquaculture industry. Large fish
farms that include multiple-cages are becoming common in the
aquaculture industry. In addition, the new mooring system allows
auxiliary equipment, such as feeding platforms (Rice et al., 2003;
Fullerton et al., 2004), to be installed at the site. The intent is to
approach commercial level operations so that proper economic
and environmental assessments can be initiated. In the meantime,
increased activity is expected to force a move to less sheltered sites
where loads in the mooring lines and flow field inside and around
the cage are expected to become more important. From the engineering perspective, multi-cage systems need to be designed to
cost-effectively withstand extreme conditions while providing a
suitable growing environment. The study on open ocean fish cage
and mooring system dynamics has focused primarily upon either
the oscillatory response of components to waves or the steady drag
of these structures to ocean currents (Kristiansen and Faltinsen,
2014; Kim et al., 2014).
∗ Corresponding authors. fax: +86 0411 84708526.
E-mail addresses: Ypzhao@dlut.edu.cn (Y.-P. Zhao), bicw@mail.dlut.edu.cn
(C.-W. Bi).
http://dx.doi.org/10.1016/j.aquaeng.2015.05.005
0144-8609/© 2015 Elsevier B.V. All rights reserved.
As to the multi-cage system in the open ocean, the fluid will flow
through the adjacent side and bottom areas as it moves toward the
sea cage. The motion of the flow is a rather complicated process. The
fishing net is a kind of small-scale flexible structure. The interaction
between the fishing net and the fluid is very complicated. Though
the hydrodynamics of the fishing net have been studied extensively,
the behaviors of fluid flowing around fishing net and the velocity
reduction downstream from a fishing net are still a problem to be
solved.
Techniques used to investigate these mechanisms have typically included the use of scaled physical and numerical models, and
where possible, field measurements. In the past decades, a number
of studies have been carried out to investigate dynamic loads acting on the net-cage system. To our knowledge, Kawakami (1964)
proposed relative reliable semi-empirical formula to calculate the
drag force acting on net. Aarsnes et al. (1990) further divided the
external forces on net cage into drag force and lift force, considering the angle between normal direction of plane net and current
velocity. Their work has laid a foundation for further study of the
dynamic characteristics of net cage. Colbourne and Allen (2001)
surveyed the motion and load responses of gravity cage with field
test, and compared the results of field test and physical model
test. Li et al. (2006a,b) investigated the dynamic behavior of gravity cage with numerical and physical model tests, and obtained a
promising result. Lee et al. (2008) proposed a mathematical model
Y.-P. Zhao et al. / Aquacultural Engineering 67 (2015) 24–31
for analyzing the performance of a fish-cage system influenced by
currents and waves. DeCew et al. (2010) investigated the submergence behavior of a fish cage in a single-point mooring system
under currents by a numerical model. Tsukrov et al. (2011) investigated the normal drag coefficients of copper alloy netting used
in marine aquaculture. Xu et al. (2012) studied numerically the
hydrodynamic behavior of multiple net cages in waves. Kristiansen
and Faltinsen (2014) investigated the mooring loads on an aquaculture net cage in current and waves by dedicated model tests and
numerical simulations.
Both from an engineering perspective and from an ecological
perspective, the flow field of open-ocean aquaculture net-cages
must be considered under the effect of steady ocean currents.
Aarsnes et al. (1990) carried out a series of tests to study the velocity
distribution within net cage systems, and velocity reduction formulae for the net cages were developed. Fredriksson (2001) studied
the flow velocity in an open ocean cage with field measurements,
and an approximate 10% velocity reduction was found. Lader et al.
(2003) conducted a series of experiments to investigate the forces
and geometry of a net cage in uniform flow, and an average of 20%
velocity reduction was measured inside the cage. Johansson et al.
(2007) performed field measurements at four farms in Norway,
and major current reduction was measured in the current passing
through the cages. The measured current reduction was between
33% and 64%. Gansel et al. (2011) conducted laboratory tests and
field measurements to study the effects of biofouling and fish
behavior on the flow field inside and around stocked salmon fish
cages. Recently, Bi et al. (2014) developed a numerical strategy to
study the flow inside and around flexible fish cages by combining
the porous-media fluid model and the lumped-mass mechanical
model based on their previous study of Zhao et al. (2013). Cornejo
et al. (2014) developed a numerical model to describe the flow
velocity downstream of the salmon farm on an incident current
with constant and semidiurnal variability. Rasmussen et al. (2015)
conducted full-scale measurements to visualize the flow field in
the wake of the salmon farm over the duration of two days in an
oscillating tidal current.
Herein, a series of physical experiments is conducted to
investigate the hydrodynamic characteristics of a large fish
farm containing 1 up to 8 net pens. In the physical model
experiments, the main mooring line tension and flow-velocity
distribution are measured under different multi-cage configurations in currents. The objective of this paper is to describe the
dynamics of the multi-grid mooring system and the flow-velocity
reduction of multiple cages. Understanding the hydrodynamic
behavior would enable the multi-cage system to be used more
effectively.
This paper is organized as follows. In Section 2, a description
of the physical model is introduced. Section 3 contains the results
of the physical model experiments, which include two parts: Part
1 presents the mooring line tension of five different multi-cage
configurations; and Part 2 presents the flow-velocity reduction
inside the net cages. Finally, in Section 4, the conclusions are
presented.
Fig. 1. The schedule of net cages in experiments.
2.1. Facilities and instruments
The experiments were conducted in a wave-current basin (56 m
long, 34 m wide and 1 m deep) at the State Key Laboratory of Coastal
and Offshore Engineering, Dalian University of Technology, China
(see Fig. 1). The basin was equipped with current-producing system, acoustic Doppler velocimeter (ADV), data acquisition system,
a tension sensor for measuring the forces under water and computers.
2.2. Net-cage model
A model in scale 1:40 was used to represent a fish cage with a
circumference of 50 m and net depth of 10 m. Circular polyethylene
net cages with a circumference of 40–120 m and a depth of 6–30 m
are most common in China today. The net cages are often arranged
in mooring grids in single or double columns with typically space
between them greater than 20 m. At most sites, the mooring grid is
oriented perpendicular to the dominant current direction to maximize water flow, oxygen supply and the removal of wastes from the
net cages. As a result, the forces on the system and the net deformation have increased. According to the prototype dimensions of the
gravity cage and the experimental conditions; the model scale of
the experiments is set as 1:40. The net cage structures are modeled
according to geometric and gravity similarities (see Table 1). In
addition, elastic similarity should be considered when referring to
the mooring line. The net system is modeled according to extended
gravity simulation criteria that has been discussed and validated
by Li et al. (2005).
Table 1
Specifications of the prototype and model of the gravity cage.
Component
Parameter
Prototype
Model
Floating collar
Outer circle diameter
Inner circle diameter
Pipe diameter
Density
Material
16.92 m
15.92 m
250 mm
11.35 kg/m
HDPE
0.423 m
0.398 m
6.25 mm
7.1 g/m
PVC
Cylindrical net
Height
Mesh size
Twine diameter
Material
10 m
40 mm
2.35 mm
PE
0.25 m
23.4 mm
0.72 mm
PE
Sinker
Unit mass
Number of pieces
34.3 kg
10
0.54 g
10
Buoy
Diameter
Geometric shape
1.2 m
Sphere
38 mm
Sphere
Mooring line
Twine diameter
Density
Material
40 mm
953 kg/m3
PE
0.72 mm
953 kg/m3
PE
2. Experimental setup
To enable the optimum design and evaluation of fish cage
and mooring performance in the energetic open ocean, a series
of physical model experiments was conducted to investigate the
hydrodynamic characteristics of a large fish farm. In the physical model experiments, the main mooring line tension was
measured under different multi-cage configurations in currents.
Flow-velocity magnitude inside and downstream from the net cage
was also measured.
25
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Y.-P. Zhao et al. / Aquacultural Engineering 67 (2015) 24–31
Fig. 2. The single cage grid mooring system (unit: m).
The net-cage model consists of a floating collar, a cylindrical
net and ten sinkers attached to the bottom of the net. The net is
mounted with diamond meshes as same as the prototype. The total
number of the meshes in the circumferential direction is 92 and in
the depth direction is 12. The specifications of the net-cage model
are presented in Table 1.
corresponding to the prototype velocities of 0.7 m/s and 0.9 m/s.
Current measurements were made using ADV with a specified accuracy of 1 mm/s. The sampling rate was 50 Hz. The measurements
were run three times to assess the repeatability of the measurements. Each measurement of current was conducted over a period
of 30 s. The mean velocity at a measurement point is the averaged
value of the three measurements.
2.3. Model arrangement
The physical model experimental setup, taking a single cage as
an example, is shown in Fig. 2. The grid mooring system consists
of three types of mooring lines, which are bridle lines, grid lines
and anchor lines. The square-mooring grid is located 0.1 m below
the water surface and there is a buoy at each corner. The configuration of the cage system is maintained using these buoys with no
pre-tension in the mooring line. The tension in the mooring line is
measured using a tension sensor mounted on the anchor line. The
flow velocities inside and downstream from the net cages are also
measured. Fig. 3 shows the general setting of gauging points for
each net cage. Sketch of five multi-cage configurations are shown
in Fig. 4.
The coordinate system for the model is a right-handed, 3D Cartesian coordinate system. In the coordinate system, x is positive
toward the flow direction, y is perpendicular to the flow direction
on the horizontal plane and z is negative toward the direction of
the acceleration of gravity.
2.4. Current conditions
The hydrodynamic characteristics of net cages were investigated at the prototype water depth of 20 m. According to the model
scale of the laboratory experiment, the experimental water depth
was 0.5 m. The velocity of incidence flow is measured by a gauging
point in front of the heading net cage (about 1.2 m). The designed
velocity of incidence flow is set as 0.111 m/s and 0.142 m/s,
Fig. 3. The sketch of gauging points inside and around a net cage (unit: m).
Y.-P. Zhao et al. / Aquacultural Engineering 67 (2015) 24–31
27
Fig. 4. Sketch of five multi-cage configurations.
3. Results and discussion
The multi-cage configuration was anchored to the bottom of the
wave-current basin with the mooring grid system. At the end of
the anchor lines, load cells were positioned to measure the anchor
forces. ADV velocity instrument was used to measure the flow field
in the net cylinders when current flow through the net cages. There
are five different kinds of net-cage arrangements (configurations
A–E) when 2 up to 8 net pens are contained.
3.1. Mooring line tension
The anchor line tension is a key parameter of common concerns.
Herein, the tension in the anchor lines of the single cage system
and the five multi-cage configurations are analyzed to obtain the
loads distribution throughout the net cage system. In this section,
all quantities are provided in prototype scale, which equal the corresponding model-scale force divided by the third power of model
scale 1/40.
3.1.1. Mooring line tension of the single cage
Considering the symmetry of the cage system, we focused on
the anchor lines deployed at one side of the cage and the anchor
lines are numbered as Fig. 5. The tension in each anchor line is the
Fig. 5. Sketch of the single cage model with numbered anchor lines.
Table 2
The tension in the anchor lines in two current cases (unit: kN).
u (m/s)
0.7
0.9
Anchor line no.
1
2
3
4
8.93
12.4
6.39
7.72
4.83
5.75
0.09
0.31
average value of the two anchor lines in the symmetric position.
Table 2 shows the average values of tension in the anchor lines of
the single cage system in two current cases.
As shown in Table 2, the tension in the anchor line 1 is larger
than that in other anchor lines and the anchor line 3 loads slight
tension. It is apparent that the anchor lines upstream of the net
cage are most loaded. The side anchor lines endure certain external
forces which is smaller than that in upstream corner anchor lines.
The tension in the anchor lines on the lee-side is slight. Therefore,
in a current, the external forces on each cage mainly contain two
parts: one is transferred to upstream corner anchor line (anchor
line 1); the other is transferred to the side anchor line (anchor
line 2).
In the laboratory experiment, the setback of the cage system
is not noticeable which is difficult to be measured. Alternatively,
the deformation of the cage system corresponding to prototype
velocity of 0.7 m/s is calculated using the lumped-mass method
(Zhao et al., 2007; Xu et al., 2012) (see Fig. 6). As a result, the calculated setback of the mooring grid is approximately 5% of the cage
diameter. There is no pre-tension in the cage system; however, line
4 in the single cage model does not go slack in the two current
cases. The tension force in line 4 under the 0.9 m/s current is larger
than that under the 0.7 m/s current, although the tension forces
are quite small. This is probably due to the fact that incidence flow
makes the floating collar pitch in a small angle, thus the downstream lines are tensioned. In addition, larger velocity intuitively
creates larger pitch angle which leads to more tension force in
line 4.
The tension in each anchor line increases with increasing current velocity and it presents the similar trend under different
current cases. For simplicity, the anchor line tensions of each
cage configuration are analyzed when u0 = 0.7 m/s in the following
section.
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Y.-P. Zhao et al. / Aquacultural Engineering 67 (2015) 24–31
Fig. 6. The setback of the cage system corresponding to prototype velocity of 0.7 m/s
calculated using the lumped-mass method. The blue dashed line describes the original position of the cage system and the red solid line describes the deformed system.
(For interpretation of the references to color in figure legend, the reader is referred
to the web version of the article.)
3.1.2. Mooring line tension of multi-cage configuration
As shown in Fig. 7, the anchor lines upstream of the multi-cage
configurations endure great force and the tension in side anchor
lines is smaller than that in upstream anchor lines. It is indicated
that the anchor lines upstream of the cages endure most of the
external forces acting on the multi-cage system. However, there is
no significant difference in the tension in side anchor lines among
the five configurations.
For configurations A and E, the tension forces in the anchor line
upstream of the two configurations are almost equal (see Fig. 7).
The forces are 24.32 kN and 24.0 kN, respectively. It illustrates that
the increase in the number of net cage has little effect on the tension
in the anchor lines upstream of the net-cage system when the net
cages are laid out in single column. For configurations B–D, net
cages are laid out in double columns. The maximum tension force
in the anchor lines upstream of the configurations increases with
increasing number of net cage (see Fig. 7). The forces are 15.36 kN
for configuration B, 18.88 kN for configuration C and 24.64 kN for
configuration D. The comparison shows that the tension force in
the upstream anchor lines is not proportional to the number of
net cage. Despite the number of net cage multiplied, the tension
force only increased by 22.9% and 30.5% for configurations C and D
respectively. It is considered that most of the increased loads are
distributed to the side anchor lines.
For multi-cage configurations contain the same number of net
cages, the arrangement type of the net cages will affect the distribution of the load in anchor lines. Taking as example for configurations
C and E, four cages are arranged in double columns and single column respectively. The maximum tension force in the anchor line
is 18.88 kN for configuration C and 24.00 kN for configuration E.
According to the experimental results, the anchor lines upstream
of configuration E endure greater force than that of configuration
C. It can be interpreted that configuration C can distribute the total
force of the multi-cage system to each anchor line better than configuration E. The tension force in the anchor lines decreases with the
net cages arranged in double columns. Similar phenomenon occurs
in the tension in each anchor line when comparing configurations
A and B.
3.1.3. Practical implication
In this study, the material of mooring line is polyethylene (PE)
for both scale and prototype model. Increment in both tension
force and amount of mooring line will intuitively lead to increased
costs. Compared with single-column configuration, double-column
one can effectively reduce the number of mooring line with no
significant increment in tension force. Therefore, double-column
Fig. 7. The tension in the anchor lines of each multi-cage configuration (unit: kN). The maximum tension forces are highlighted in bold.
Y.-P. Zhao et al. / Aquacultural Engineering 67 (2015) 24–31
29
Table 3
The flow-velocity reduction factor inside and downstream from the single cage.
Incidence velocity u0 (m/s)
Velocity inside u1 (m/s)
Velocity downstream u2 (m/s)
Reduction factor u1 /u0
Reduction factor u2 /u0
0.1350
0.1543
0.1205
0.1342
0.0913
0.1052
0.89
0.87
0.68
0.68
Fig. 8. The flow-velocity reduction factor inside the cage.
configuration is considered as more cost effective. Other than the
tension-force difference, the 2 × 4 configuration (configuration D)
is recommended over the five configurations from a perspective of
economizing cost.
3.2. Flow velocity reduction
3.2.1. Flow through single gravity cage
As there is no significant difference between the values of five
measurement points inside the net cage, their averaged value is
considered as the flow velocity in cage denoted by u1 . The value
of the gauging point downstream from the net cage is considered
as the flow velocity downstream from cage denoted by u2 . The
corresponding flow-velocity-reduction factor can be obtained by
comparing with the incidence velocity u0 . The flow velocities and
the flow-velocity-reduction factors inside and downstream from
the single cage in two current cases are presented in Table 3.
There exists an obvious flow-velocity reduction inside the cage
while there is a larger velocity reduction downstream from the cage
(see Table 3). It is indicated that the incidence flow can be attenuated when passing the fishing net and the reduction in flow velocity
increases with increasing number of fishing net. As the free stream
flows through two nets before reaching the gauging point downstream from the net cage, the flow-velocity reduction is larger than
that inside the net cage which is attenuated only by the upstream
net.
3.2.2. Flow through multi-cage configuration
The flow-velocity-reduction factors present the similar trend
under different current cases inside and downstream from the
net cage. For flow through multi-cage configurations, the flowvelocity-reduction factor inside the cage is the average value of
the reduction factors inside the same cage in the two current cases.
Considering the symmetry of the cage system in double columns,
we focused on the reduction factor inside the net cages deployed
at one side of the cage system. The reduction factor is the average
value of the two cages in the symmetric position.
Obvious flow-velocity reduction exists inside net cages of
the multi-cage configurations, and the flow-velocity reduction
increases with increasing cage number (see Fig. 8). The net cages
influence the flow-velocity distribution inside themselves and also
have noticeable influence on the flow field inside the net cages
around them.
Comparing the experimental results of configurations A and E,
the flow-velocity-reduction trends of the two configurations are
consistent and there is no statistically difference (see Fig. 9). It illustrates that the increment in the number of downstream cage has no
noticeable effect on increasing the flow-velocity reduction inside
the net cages. In configurations B–D, net cages are laid out in double
Fig. 9. Comparisons of the flow-velocity reduction factor inside the net cages
between configurations A and E.
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Y.-P. Zhao et al. / Aquacultural Engineering 67 (2015) 24–31
significant. What is more, this phenomenon becomes more noticeable for the downstream net cage where the interaction between
the paratactic net cages in different columns is considered reaches
the maximum performance.
In engineering practices, water motion helps to maintain the
water quality in a net cage and that sufficient water exchange is
important for the health and growth of the caged fish. From this perspective, the 2 × 1 configuration (configuration B) is recommended
for less reduction in flow velocity inside the net cage.
The experimental data have been compared with the numerical results of Bi et al. (2014) and the results of Løland’s formula
(Løland, 1991; Aarsnes et al., 1990) (see Fig. 11). Løland combined
theoretical work with experimental work to derive formulas for
flow-velocity reduction of the cage nets:
u = u0
nc
ri
(1)
i=1
where ri is given by
Fig. 10. Comparisons of the flow-velocity reduction factor inside the net cages
among configurations B–D.
columns and the number of the net cage doubles. Similarly, there
is no significant difference in flow-velocity reduction between the
three configurations (see Fig. 10).
For fish farms containing the same number of net cages, the
arrangement of the net cage can influence the flow-velocity distribution. In configuration B, the two net cages influence the
flow-velocity distribution inside each other. As a result, the flowvelocity-reduction factor in configuration B is a little greater than
that of the upstream net cage in configuration A, although it is not
statistically significant. Similar phenomenon occurs when comparing configurations E and C.
Due to the water blockage of the fishing net, the flow velocity increases at the flanks of the net cage. Therefore, the net cages
deployed in double columns have less reduction in flow velocity
inside than the net cages in single column. Fig. 11 shows the comparisons of flow-velocity-reduction factor between configurations
D and E. The flow-velocity-reduction factor inside the net cage
of configuration D is consistently greater than that of the corresponding net cage of configuration E, although it is not statistically
Fig. 11. Flow-velocity reduction factor inside the net cages from configurations D
and E (present study), the numerical results of Bi et al. (2014) and the results of
Løland’s formula (Løland, 1991).
ri = 1.0 − 0.46Cd
(2)
where ri is the flow velocity reduction factor, nc is the number of
upstream crossings of other plane nets before the current hits the
actual plane net, and Cd is the drag coefficient of the net calculated
using empirical formulas proposed by Balash et al. (2009):
cyl
Cd = Cd (8.03Sn2 − 0.74Sn + 0.12)
cyl
(3)
−2/3
.
where Cd = 1 + 10Ren
The comparison shows that the present results are in good
agreement with the numerical results of Bi et al. (2014). However,
Løland’s formula seems to overestimate the flow velocity inside
downstream cages. This discrepancy is attributed to the difference
in the deformation of fishing net. Løland’s formula may apply to net
cages with limited deformation as it shows good agreement with
the numerical results of net cages with no deformation (Zhao et al.,
2013).
4. Conclusions
According to the experimental results, the following conclusions
can be drawn:
• The upstream anchor lines endure most of the external forces acting on the multi-cage system. The tension force in the upstream
anchor lines increases with increasing number of net cage for
double-column configurations while the increment in net cage
has no noticeable effect on the line tension. For configurations
consisting of the same number of net cage, the tension in each
anchor line of the double-column configuration is smaller than
that of single-column one. Increment in both tension force and
amount of mooring line will intuitively lead to increased costs.
Other than the tension-force difference, the 2 × 4 configuration
is recommended from a perspective of economizing cost.
• Obvious flow-velocity reduction exists inside net cages of
the multi-cage configurations and the flow-velocity reduction
increases with increasing cage number. However, there is no
statistical difference in flow velocity for varied configurations.
In general, the net cages arranged in double columns have less
reduction in inside than the net cages in single column. From the
perspective of water exchange, the 2 × 1 configuration is recommended.
• The experimental results provide the basis for the optimum
design of a fish farm. In engineering practices, the appropriate
multi-cage system should be determined through considering
both the mooring line force and the flow-velocity distribution.
Y.-P. Zhao et al. / Aquacultural Engineering 67 (2015) 24–31
Acknowledgments
This work was financially supported by the National Natural Science Foundation (NSFC) Projects Nos. 51239002 and 51221961,
Cultivation Plan for Young Agriculture Science and Technology
Innovation Talents of Liaoning Province (No. 2014008).
References
Aarsnes, J.V., Rudi, H., Løland, G., 1990. Current forces on cage, net deflection. In:
Engineering for Offshore Fish Farming. Thomas Telford, London, pp. 137–152.
Balash, C., Colbourne, B., Bose, N., Raman-Nair, W., 2009. Aquaculture net drag
force and added mass. Aquac. Eng. 41 (1), 14–21.
Bi, C.W., Zhao, Y.P., Dong, G.H., Zheng, Y.N., Gui, F.K., 2014. A numerical analysis on
the hydrodynamic characteristics of net cages using coupled fluid–structure
interaction model. Aquac. Eng. 19 (2014), 1–12.
Cornejo, P., Sepúlveda, H.H., Gutiérrez, M.H., Olivares, G., 2014. Numerical studies
on the hydrodynamic effects of a salmon farm in an idealized environment.
Aquaculture 430 (2014), 195–206.
Colbourne, D.B., Allen, J.H., 2001. Observations on motions and loads in
aquaculture cages from full scale and model measurements. Aquac. Eng. 24 (2),
129–148.
DeCew, J., Tsukrov, I., Risso, A., Swift, M.R., Celikkol, B., 2010. Modeling of dynamic
behavior of a single-point moored submersible fish cage under currents.
Aquac. Eng. 43 (2), 38–45.
Fredriksson, D.W., (Ph.D. dissertation) 2001. Open Ocean Fish Cage and Mooring
System Dynamics. University of New Hampshire, Durham, NH, USA.
Fullerton, B., Swift, M.R., Boduch, S., Eroshkin, O., Rice, G., 2004. Design and analysis
of an automated feed buoy for submerged cages. Aquac. Eng. 32 (1), 95–111.
Gansel, L., Rackebrandt, S., Oppedal, F., McClimans, T., 2011. Flow fields inside
stocked fish cage and the near environment. In: Proceeding of 30th
International Conference on Offshore Mechanics and Arctic Engineering,
Rotterdam, Netherlands, OMAE2011-50205.
Johansson, D., Juell, J.E., Oppedal, F., Stiansen, J.E., Ruohonen, K., 2007. The
influence of the pycnocline and cage resistance on current flow, oxygen flux
and swimming behaviour of Atlantic salmon (Salmo salar L) in production
cages. Aquaculture 265 (1), 271–287.
Kristiansen, T., Faltinsen, O.M., 2014. Experimental and numerical study of an
aquaculture net cage with floater in waves and current. J. Fluids Struct., http://
dx.doi.org/10.1016/j.jfluidstructs.2014.08.015
31
Kim, T., Lee, J., Fredriksson, D.W., DeCew, J., Drach, A., Moon, K., 2014. Engineering
analysis of a submersible abalone aquaculture cage system for deployment in
exposed marine environments. Aquac. Eng. 63 (2014), 72–88.
Kawakami, T., 1964. The theory of designing and testing fishing nets in model.
Modern Fishing Gear of the World, vol. 2. Fishing News (Books), London, pp.
471–482.
Lader, P.F., Enerhaug, B., Fredheim, A., Krokstad, J., 2003. Modeling of 3D Net
Structures Exposed to Waves and Current. SINTEF Fisheries and Aquaculture,
Trondheim, Norway.
Lee, C.W., Kim, Y.B., Lee, G.H., Choe, M.Y., Lee, M.K., Koo, K.Y., 2008. Dynamic
simulation of a fish cage system subjected to currents and waves. Ocean Eng.
35 (14–15), 1521–1532.
Li, Y.C., Gui, F.K., Zhang, H.H., Guan, C.T., 2005. Simulation criteria of fishing nets in
aquiculture sea cage experiments. J. Fish. Sci. China 12 (2), 179–187 (in
Chinese).
Li, Y.C., Zhao, Y.P., Gui, F.K., Teng, B., 2006a. Numerical simulation of the
hydrodynamic behavior of submerged plane nets in current. Ocean Eng. 33
(17–18), 2352–2368.
Li, Y.C., Zhao, Y.P., Gui, F.K., Teng, B., 2006b. Numerical simulation of the influences
of sinker weight on the deformation and load of net of gravity sea cage in
uniform flow. Acta Oceanol. Sin. 25 (3), 125–137.
Løland, G., (Ph.D. dissertation) 1991. Current Force on Flow through Fish Farms.
Norwegian Institute of Technology, Trondheim, Norway.
Rasmussen, H.W., Patursson, Ø., Simonsen, K., 2015. Visualisation of the wake
behind fish farming sea cages. Aquac. Eng. 64 (2015), 25–31.
Rice, G.A., Chambers, M.D., Stommel, M., Eroshkin, O., 2003. The design,
construction and testing of the University of New Hampshire Feed Buoy. In:
Open Ocean Aquaculture: From Research to Commercial Reality, Baton Rouge,
Louisiana., pp. 197–203.
Tsukrov, I., Drach, A., DeCew, J., Swift, M.R., Celikkol, B., 2011. Characterization of
geometry and normal drag coefficients of copper nets. Ocean Eng. 38 (17–18),
1979–1988.
Xu, T.J., Dong, G.H., Zhao, Y.P., Li, Y.C., Gui, F.K., 2012. Numerical investigation of the
hydrodynamic behaviors of multiple net cages in waves. Aquac. Eng. 48 (2012),
6–18.
Zhao, Y.P., Bi, C.W., Dong, G.H., Gui, F.K., Cui, Y., Xu, T.J., 2013. Numerical simulation
of the flow field inside and around gravity cages. Aquac. Eng. 52 (2013),
1–13.
Zhao, Y.P., Li, Y.C., Dong, G.H., Gui, F.K., Teng, B., 2007. Numerical simulation of the
effects of structure size ratio and mesh type on three-dimensional deformation
of the fishing-net gravity cage in current. Aquac. Eng. 36 (3),
285–301.