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ORIGINAL PAPER

Flow simulation along a seal: the impact

of an external device

Anja A. H. Hazekamp & Roy Mayer & Nynke Osinga

Received: 3 April 2009 / Revised: 4 June 2009 / Accepted: 9 June 2009 /
Published online: 30 June 2009

# Springer-Verlag 2009

Abstract An increasing number of marine mammal studies

on physiology, behaviour and ecology rely on data, which

have been collected from back-mounted devices, such as

bio-logging tags and satellite transmitters. However, external

devices may influence an animal’s hydrodynamics,

behaviour and energy expenditure and, therefore, can

impede the individual animal. To investigate the influence

of external devices on seals, the water flow along a grey

seal was simulated using computational fluid dynamics

calculations. The simulations revealed several changes in

forces and moments and thus balance, due to this device.

The investigated satellite transmitter creates an average

12% increase of the drag coefficient. Additionally, there are

significant relative transmitter-induced increases in pitching

moment (32%) and lift (240%). The simulations also

showed that the transmitter generates areas of decreased

wall shear stress on the seal’s back. The results of this study

demonstrate that external devices can change the hydrodynamics

of the seal, which is expected to alter the seal’s

physiology and behaviour and its use of the ecosystem.

Long-term attachment may have adverse effects on the

animal’s welfare. It is important to take these effects into

consideration when studying tagged seals; otherwise, the

value of the data obtained will be poor. Therefore,

interpretations and extrapolations regarding ‘natural behaviour’

of animals in their ‘natural environment’ should only

be made with great caution.

Keywords Computational fluid dynamics (CFD) .

Telemetry . Animal welfare . Satellite transmitter .

Grey seal (Halichoerus grypus)

Abbreviations

CFD Computational fluid dynamics

Cd Drag coefficient

Cl Lift coefficient

Cm Pitching moment coefficient

D Drag force (N)

L Lift force (N)

M Pitching moment

ρ Fluid density (kg m−3)

U Swimming speed (m s−1)

A Frontal projection area (cm2)

α Pitch angle (°)

Ν Kinematic viscosity (m2 s−1)

WSS Wall shear stress (N m2)

Introduction

Throughout the past few decades, a variety of telemetry

devices, such as bio-logging tags (e.g. Block 2005;

Kooyman 2004; Naito 2004; Ponganis 2007) and satellite

transmitters (e.g. Culik and Luna-Jorquera 1997;

Matthiopoulos et al. 2004; Myers et al. 2006), have been

used on various animal species to investigate a wide range

of ecological and conservation questions. These include

systems to study physiology (such as body temperature),

behaviour (such as diving and foraging behaviour) and use

Eur J Wildl Res (2010) 56:131–140

DOI 10.1007/s10344-009-0293-0

Communicated by F.-J. Kaup

A. A. H. Hazekamp : N. Osinga (*)

Seal Rehabilitation and Research Centre (SRRC),

Hoofdstraat 94a,

9968AG Pieterburen, The Netherlands

e-mail: nynke@zeehondencreche.nl

R. Mayer

FlowMotion Germany,

Weenermoorer Strasse 193,

26826 Weener, Germany

of the ecosystem (such as seasonal and diurnal migrations).

In particular, these telemetry instruments have been used to

obtain information on animals, such as diving birds and

marine mammals, which have a wide range and are difficult

to observe because they spend a considerable amount of

time under water.

To date, biological telemetry studies have been carried

out on various species of the marine environment, such as

cetaceans (e.g. Gifford et al. 2007; Read and Westgate

1997), seals (e.g. Call et al. 2007; Matthiopoulos et al.

2004), marine turtles (e.g. Lohmann et al. 2008; Watson

and Granger 1998), penguins (e.g. Clarke and Kerry 1994;

Ponganis et al. 2004; Ropert-Coudert et al. 2001), other

diving birds (e.g. Benvenuti and Dall'Antonia 2004;

Paredes et al. 2005; Whidden et al. 2007), fish (e.g. Gifford

et al. 2007; Koed and Thorstad 2001) and even jellyfish

(Hays et al. 2008). More recently, marine mammals have

also been used solely as instrument to transport physical

telemetry devices to gain information on physical environmental

parameters, for instance salinity and water temperature

(Fedak 2004; Hooker and Boyd 2003).

To contribute successfully to new insights on animal

physiology, behaviour and ecology, telemetry studies

require instrumentation that does not alter the animal’s

behaviour, either in time (e.g. time spent foraging) or in

space (e.g. foraging locations, diving depths). However,

attaching external devices to or even implanting devices in

animals may influence their hydrodynamics or physiology

and alter behaviour and energy expenditure (Bannasch et al.

1994; Croll et al. 1991; Wilson et al. 1986). A wide range

of hydrodynamical and behavioural effects of carrying

devices have been documented, for example in diving birds

(Hamel et al. 2004; Igual et al. 2005; Paredes et al. 2005;

Whidden et al. 2007), penguins (Culik et al. 1994; Taylor

et al. 2001; Wilson et al. 1986, 2004) and fish (Koed and

Thorstad 2001; Thorstad et al. 2001). In the long term, the

hydrodynamic effects of external devices may have serious

consequences for the animal’s welfare.

Seals have a highly streamlined body, which is a prime

example of convergent evolution in their design to

minimise drag for locomotion in the water (Howell 1930).

The effect of animal-carried systems is particularly important

in marine animals (e.g. Bannasch et al. 1994; Culik et

al. 1994; Watson and Granger 1998) because the drag

caused by moving non-streamlined units through the dense

medium, i.e. water, may lead to substantial increases in

energy expenditure.

There are several methods that can be used to explore the

issue of how external devices influence diving animals. In

some studies, the behaviour of animals with an external

device was observed in captivity (Healy et al. 2004; Petrie

and Rogers 1996; Simeone et al. 2002; Stewart et al. 1989).

Captive studies are, however, of limited value given that

most animals in captivity do not usually exhibit normal

diving and foraging behaviour. The consequences of a

reduction in the ability to forage may not be significant in

laboratory animals, but could prove to be severely

debilitating or even fatal for free-ranging wild animals

(Hawkins 2004). In some studies, the behaviour of freeranging

animals with and without devices has been

compared (Croll et al. 1991; Whidden et al. 2007;

McMahon et al. 2008). The most common approach to

study the hydrodynamic effects of external devices on

swimming animals is to experimentally investigate the

generated forces on models. There are a few methods by

which models can be studied: water tunnels, wind tunnels

and flow simulations. All these methods share the same

disadvantage, namely the modelled animal has a rigid

body and it is not a deforming swimming animal. Most

of the studies with models have been performed in wind

tunnels because of the ease of measuring the forces on

the model in a steady flow compared to water tunnels

and towing tanks. However, when conducting tests in air

instead of water, it is necessary to compensate the

different viscosities of air and water with the flow

velocity (Reynolds analogy). This means that the

velocity in the wind tunnel needs to be about 11 times

greater than the investigated swimming speed in water to

achieve a comparable flow situation (5 ms−1 swimming

speed leads to 55 ms−1 wind tunnel velocity). Water

tunnel tests are usually too small to investigate a seal

model on a real scale. Akin to the viscosity of different

fluids, the scale of the model can be compensated by flow

velocity. Here, the smaller the model is, the larger the

velocity has to be (again Reynolds analogy).

Although external devices may have various impacts

on the seals, as lined out above, our study focused

specifically on the issue of hydrodynamics. In the

present study, we chose to use a flow simulation model

on a real scale as well as the characteristics of water,

using computational fluid dynamics (CFD). The CFD

models were introduced in the 1990s to study insects and

birds during flight (Liu 2002). If the simulations are

performed with care, an equivalent or even greater

accuracy to the wind tunnel test can be achieved. In

addition, flow simulation using CFD can generate a large

quantity of data and is very time- and cost-effective.

The aims of the present study were:

1. To identify and describe the effects of an externally

attached satellite transmitter on velocity distribution,

drag, lift, pitching moment, static pressure and wall

shear stress at different swimming speeds of a grey seal

2. To describe the effects of transmitter-induced changes

in the hydrodynamics on the physiology, behaviour,

ecology and welfare of seals

132 Eur J Wildl Res (2010) 56:131–140

Materials and methods

Computational fluid dynamics

To address the issue of how a transmitter influences seals, the

water flow along a grey seal (Halichoerus grypus Fabricius,

1791) with and without a transmitter was simulated using

CFD calculations. CFD methodology consists of a mathematical

model applied to the fluid flow. It is based on the

numerical solution of partial differential equations expressing

local balances of mass, momentum and energy, which may

eventually couple to transport equations of non-reactive or

reactive flows for given operating conditions. To do so, we

used the FLUENTTM software, which has been developed

for simulation, visualisation and prediction of fluid flow and

heat and mass transfer.

With a system of equations representing turbulent

models, it is not feasible to predict details of an unsteady

flow like the flow around structures, not even when

including a low Reynolds number (Re). To overcome this

problem, we used the standard k-epsilon (κ-ε) model in the

FLUENTTM software.

Model

A model of a seal in the steady gliding position, with minimal

fluid dynamical drag, was set. The three-dimensional geometrical

model of the grey seal created for the simulation was

based on post mortem measurements, photographs and

observations of swimming grey seals.

The model was designed without complex details such as

front flippers and eyes. The three-dimensional model of the

device was based on a commonly used Argos Satellite Relay

Data Logger. The location of this satellite transmitter was

dorsal, close to the head, which is the most frequently used

place to attach these transmitters on seals. A ‘best case

scenario’ was simulated, in which the effect of the device on

the fluid dynamical drag should be as little as possible (Fig. 1).

A three-dimensional computational calculation domain

was used, consisting of about one million grid cells, most of

them close to both the surface of the seal and the transmitter

to achieve maximum accuracy (Fig. 2).

For this simulation, the following values and settings

were used:

Fluid mechanical settings:

Fluid: seawater

Kinematic viscosity: ν=1.06×10−6m2s−1

Density: ρ=1,028 kg m−3

Computer settings:

Mesh: three-dimensional, 1×106 grid cells

Turbulence model: k-epsilon (κ-ε) model

Seal model:

Frontal cross-sectional area A, 800 cm2

Pitch angles α, 0°

Hydrodynamics

Flow velocity, forces and moments

The water flow was simulated, and then distribution

velocity, the different forces and moments acting on the

seal with and without a transmitter were investigated. The

forces and moments have been computed for a swimming

seal, for each swimming velocity between 1 and 5 ms−1,

which is within the normal range (Gallon et al. 2007;

Orthmann 2000; Thompson and Fedak 1993). The drag, lift

Fig. 1 Three-dimensional geometrical model of seal in steady gliding

situation

Fig. 2 Three-dimensional mesh

Eur J Wildl Res (2010) 56:131–140 133

and pitching moment have been calculated and will be

described as dimensionless coefficients (Fig. 3).

The drag coefficient, lift coefficient (Cl) and the pitching

moment coefficient (Cm) were computed using the following

equations:

Cd ¼ D_ð0:5 _ r _ U2 _ AÞ

Cl ¼ L_ð0:5 _ r _ U2 _ AÞ

Cm ¼ M_ð0:5 _ r _ U2 _ A _ LÞ

U ¼ 1 _5 ms_1

where D is the drag force, L is the lift force, M is the pitching

moment, ρ is the fluid density, U is the swimming speed and

A is the projection surface of the model (this is the area of the

seal perpendicular to the direction of the fluid motion).

The centre of gravity of the seal is assumed to be found

at maximum girth.

Static pressure

The static pressure is the pressure at a nominated point on

the seal model moving with the water. The changes in

static pressure, which are due to the transmitter, were

simulated.

Wall shear stress

A viscous fluid-like water moving along a solid body will

incur a shear stress along the surface. At the surface,

the velocity of the fluid is zero, but at some height from

the surface, the flow speed increases asymptotically to the

outer flow velocity. The region between these two points

is called the boundary layer. The tangential frictional force

along the surface is called wall shear stress. The integral

of this wall shear stress along the entire surface of the

body determines its friction drag, which limits its gliding

speed and length and therefore its energy consumption.

The wall shear stress was calculated for a seal with and

without a device.

Results

The CFD simulation identifies several effects of the

external device on the hydrodynamics of the seal, including

velocity distribution, drag, lift, pitching moment, static

pressure and wall shear stress.

Velocity

The simulation of the velocity magnitude reveals that a seal

without a device is a highly streamlined object, where no

flow separation or backflow occurs. Figure 4a shows the

velocity vectors 1 cm from the object’s surface coloured by

velocity magnitude (metre per second). A seal object with a

device shows a decrease in average velocity magnitude on

the back of the seal (Fig. 4b). In addition, vortices and

backflow can be found near the device.

Forces and moments

With flow simulation using CFD, it was not only possible

to determine the drag, but also to calculate lift force and

pitching moment. The results revealed several changes in

forces and moments due to the device (Table 1).

The investigated satellite transmitter created an average

increase of the drag coefficient of 12% (Fig. 5). The

simulated drag coefficient varied between 0.08 and 0.1.

The absolute values for the lift force are rather small

compared to the drag force; the lift was about 6% of the

drag for a seal without an external device. We found that

the transmitter created a significant average increase in the

coefficient of the lift force of 240% (Fig. 6). There was a

remarkable and sudden increment between a swimming

speed of 2 and 3 ms−1.

The pitching moment of the swimming seal was

determined and revealed a significant average transmitterinduced

increase of 32% in the pitching moment coefficient

(Fig. 7).

Static pressure

The simulation showed that the transmitter changes the

distribution of the static pressure slightly, but only in the

vicinity of the transmitter and near the nose of the seal

model. Large values for the static pressure could be

found at the front face of the transmitter, whereas the

pressure distribution along the seal did not change

Fig. 3 Lift, drag and pitching moment significantly.

134 Eur J Wildl Res (2010) 56:131–140

Wall shear stress

The simulation demonstrated that the transmitter generates

areas of decreased wall shear stress on the seal’s back (Fig. 8).

Discussion

Hydrodynamics

The CFD simulation demonstrates that there are several

ways in which the transmitter affects the hydrodynamics of

the seal: velocity distribution, drag, lift, pitching moment,

static pressure and wall shear stress change. Below, the

effects of externally attached devices will be discussed.

The CFD simulation reveals that there is a change in

flow velocity along the seal. The identified vortices and

backflow around the transmitter may interfere with the

seal’s whiskers and thus its search for prey.

The simulated drag coefficient varies between 0.08 and

0.1. The transmitter-induced drag increase of 12% corresponds

with values found in the literature based on model

studies for external devices on highly streamlined marine

mammals and diving birds with back-mounted devices

(0.07–0.14; Bannasch et al. 1994; Orthmann 2000; Stelle

et al. 2000). The highest values for the static pressure could

Fig. 4 a Velocity vectors (seal

without transmitter). b Velocity

vectors (seal with transmitter)

Eur J Wildl Res (2010) 56:131–140 135

be found at the frontal section of the transmitter. This pressure

drag from the frontal region of the transmitter contributes to

the increase in the total drag of 12%. The pressure drag of the

transmitter may lead to lesions such as necrosis and

inflammatory lesions in the tissues underneath the device.

Next to the increase in drag, two additional forces were

identified by the CFD simulation. We found that the

transmitter also creates a significant average increase in

the coefficient of the lift force of 240%. While diving, the

increase in lift creates an upward force. If sufficiently large,

this may consequently affect diving depth and duration. It

may take the animal a certain period of time to learn how to

adjust to the extra energy expenditure and changes in

hydrodynamics. The sudden increment of the lift force,

which was revealed between a swimming speed of 2 and

3 ms−1, requires the animal to deal with a changing lift

factor. Furthermore, we found that there is a significant

increase of 32% of the average transmitter-induced pitching

moment coefficient. The animal is exposed to a force,

which induces a momentum around its lateral axis. If

sufficiently large, the seal may subsequently become

hydrodynamically unstable. That means that, when the seal

starts to pitch up, the angle of ‘flow’ attack increases. This

further increases the lift force and the pitching moment,

which further and even faster increases the angle of attack,

and so forth. All the compensating activities will again lead

to an increase in drag and energy expenditure.

The simulation demonstrated that the transmitter generates

areas of decreased wall shear stress on the seal’s

back. Necropsy on a grey seal, which had been fitted with a

transmitter and washed up dead on the Dutch coast, showed

fouling on the satellite transmitter attached to the seal

(SRRC marine mammal database 2006). Algae was found

growing in the fur of the seal’s back and around its neck.

When compared to the areas of decreased wall shear stress

in the model, it revealed that the areas match perfectly. The

areas of high wall shear stress on top of the transmitter also

correspond with areas where no fouling was present. It may

therefore be concluded that fouling adheres to the seal in

areas with low wall shear stress induced by the transmitter.

There is a close relationship between the wall shear stress

and the heat transfer from the seal’s body to the surround-

Table 1 Results for drag coefficient, lift coefficient (Cl) and pitching
moment coefficient (Cm) for a swimming seal with and without a

transmitter at different swimming velocities (metre per second)

Swimming speed (ms−1) 1 2 3 4 5

Cd1 (with transmitter) 0.119 0.109 0.101 0.094 0.091

Cd2 (without transmitter) 0.108 0.098 0.090 0.083 0.080

Cd1–Cd2 (%) 0.011 (10.2%) 0.011 (11.2%) 0.011 (12.2%) 0.011 (13.3%)
0.011 (13.8%)

Cl1 (with transmitter) 0.016 0.016 0.019 0.019 0.018

Cl2 (without transmitter) 0.007 0.006 0.005 0.005 0.004

Cl1–Cl2 (%) 0.009 (128.6%) 0.010 (166.7%) 0.014 (280.0%) 0.014
(280.0%) 0.014 (350.0%)

Cm1 (with transmitter) −0.0077 −0.0071 −0.0062 −0.0063 −0.0065

Cm2 (without transmitter) −0.0093 −0.0098 −0.0101 −0.0102
−0.0103

Cm1–Cm2 (%) 0.0016 (17.2%) 0.0027 (27.6%) 0.0039 (38.6%) 0.0039
(38.2%) 0.0038 (36.9%)

Fig. 5 Drag coefficient for a

swimming seal with and without

a transmitter at different

swimming velocities

136 Eur J Wildl Res (2010) 56:131–140

ing water. In areas of decreased wall shear stress, the heat

transfer is lower. Therefore, the energy balance and body

temperature regulation of the seal might be influenced by

the transmitter. A disturbance in the warmth regulation and

energy balance of the seal may have serious consequences

for the animal, especially when its overall condition is poor.

Modelling with CFD demonstrates the significant impact

of external devices on the hydrodynamics of seals. The

altered hydrodynamics will inevitably have effects on the

free-living behaviour of seals; however, it is difficult to

quantify these effects. The performance of equipped seals

has not yet been compared with that of unequipped seals.

Potential impacts include, amongst other things, changes in

maximum swimming velocity, time spent foraging, weight

gain, reproductive success, etc. Eventually, the use of

external devices may have serious consequences for the

welfare of the individual animal. Further research is

required to understand how altered hydrodynamics relates

to the performance of free-living seals.

The effects of external devices are most likely to be

severe when (1) animals are small, (2) devices are large, (3)

animals are pursuit predators for which speed is important

and (4) deployments are long. We expect that applying the

same size transmitter on a smaller species, such as harbour

seals, will induce more significant changes in hydrodynamics.

The use of smaller instrumentation may reduce the

deleterious effects of external devices. Due to advances in

microelectronics, it is possible to produce smaller and

lighter devices with improved hydrodynamic characteristics.

It is essential to minimise drag by reducing the frontal

area of the device and streamlining its shape. The development

and use of short deployment devices should be

considered, like those already applied for turtles (Houghton

et al. 2002) and cetaceans (Aguilar Soto et al. 2008).

Next to effects on hydrodynamics, external devices may

have other consequences. The procedure of attachment of

the devices, which may involve stress during capturing, the

use of anaesthetics or sedatives or the physical obstruction

due to the device itself, may impede the individual animal’s

welfare. Furthermore, bio-fouling seems to be a problem in

some of the tagged animals. In the aforementioned case,

green algae, mussels and seaweed were observed within

Fig. 6 Lift coefficient for a

swimming seal with and without

a transmitter at different

swimming velocities

Fig. 7 Pitching moment coefficient

for a swimming seal with

and without a transmitter at

different swimming velocities

Eur J Wildl Res (2010) 56:131–140 137

4 months after the attachment of the device (SRRC 2006).

Fouling on transmitters has been described for tagged fish

(Dicken et al. 2006; Thorstad et al. 2001) and marine turtles

(Hays et al. 2007). Fouling increases the drag and decreases

the swimming performance, but is seldom taken into account

when estimating negative effects from devices on animals.

Biased results

The successive steps required to obtain telemetry data, from

the sampling program to the final analyses of the data, have

a subjective element. Predictions on population distribution

are being increasingly based on telemetry studies, which

focus on a few individual animals. Results are then

extrapolated to the level of the population. Aarts et al.

(2008) question the sampling error in telemetry-based

population level inferences. They argue that sampling error

in telemetry studies is usually large because, due to

logistical constraints, only a small sample of animals are

tagged and because sampling effort between tagged

individuals is almost never balanced. The principle of

telemetry studies implies that the tagged animals behave

normally and that the instrumentation used does not alter

the behaviour of the animals studied. However, various

Fig. 8 a Wall shear stress

(seal without transmitter).

b Wall shear stress

(seal with transmitter)

138 Eur J Wildl Res (2010) 56:131–140

studies demonstrated that attaching or even implanting

telemetry devices to animals have an impact on physiology

or behaviour, and this can be significant (Bannasch et al.

1994; Croll et al. 1991; Culik and Wilson 1991; Ropert-

Coudert et al. 2000; Whidden et al. 2007). These effects

should not be neglected when analysing data retrieved from

these devices; otherwise, the value of the information

obtained from the devices will be poor. The subjective

assessment that an animal is performing ‘normally’ is

probably one of the weakest links in the chain of events

from telemetry device designing, testing and implementation,

to analysis and interpretation of results (Ropert-

Coudert and Wilson 2004). Only 10% of marked animal

studies published in major journals in 1995 mentioned that

tag impact had been considered (Murray and Fuller 2000).

Therefore, interpretations and extrapolations regarding

‘natural behaviour’ of animals in their ‘natural environment’,

such as estimated population size, rates of survival,

diving and foraging behaviour, should be made with great

caution.

The simulation

In this study, we chose a model of a seal in the steady

gliding position, with minimal fluid dynamical drag. The

three-dimensional seal model used in this study was based

on data of a grey seal. A ‘best case scenario’ was used, in

which the transmitter is situated exactly in the middle of the

seal’s back and is not rotated. We assume that in practice

this is more difficult to achieve, resulting in somewhat more

serious transmitter-induced effects on the animal. The

model was based on a seal without complex details such

as front flippers, eyes and whiskers. The absolute

transmitter-induced changes in hydrodynamics may therefore

be slightly different. The model can be improved by

adding more details in future studies. It would also be

useful to assess device impacts in relation to natural

variation in hydrodynamics in seals, e.g. fat versus thin

individuals. The additional effects of different levels of biofouling

need to be investigated as well.

Conclusion

The tracking of marine mammals can provide useful

information for conservation such as identifying important

conservation areas. However, the ethical implications of

device effects need to be balanced against the benefits for

species conservation. We recommend that before using

external devices on (streamlined) aquatic animals, the

effects of the device should be calculated using CFD

models. Since species and device characteristics will

determine the severity of the impact of the devices, this

should be done on a ‘case-by-case’ level. The calculated

effects render it possible to determine the level of altered

hydrodynamic forces. The calculated effects can be used to

assess the impact on animal welfare and adjust the data

collected from the transmitter. Improving the hydrodynamic

design of external devices will benefit the research results

while minimising the impact on the welfare of the

individual animals.

Acknowledgements We thank Dr. Pieter ‘t Hart for many useful

discussions and valuable comments to previous versions of the

manuscript. We thank Dr. Joanna M. Swabe for editing and improving

the manuscript. We are grateful for the volunteers of the stranding

network (EHBZ) of the SRRC, who always are available to help sick

and wounded marine mammals. Their observations of animals with

externally attached telemetry devices were very helpful. We thank

IMARES B.V. for providing the dummy of the Argos Satellite Relay

Data Logger (SMRU), which was used in this study.

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