design and wind tunnel testing of

a size sampling in-situ net system

(ssisnetJ

Robert Paul Mitchke

«*^.

^J^
^

TtifrVz

NAVAL POSTGRADUATE SCHOOL

Monterey, California

THESIS

DESIGN AND WIND TUNNEL TESTING OF

A SIZE SAMPLING IN-SITU NET SYSTEM
(SSISNET)

by

Robert Paul Mitchke

September 1976

Thesis Advisor

E. D. Traganza

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Design and Wind Tunnel Testing of
a Size Sampling in- situ Net System

(SSISNET)

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Master's Thesis;
September 1976

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Robert Paul Mitchke

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Naval Postgraduate School
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A number of plankton sampling devices have been designed
and tested and their physical properties (filtration, effi-
ciency, filtration pressure drop, net filtration ratio and
mesh approach speed) have been calculated and compared. The
data necessary to make these calculations were collected by
mounting 1/4 scale sampler models in a wind tunnel, the wind
speed having been adjusted to that corresponding to a water

FORM
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(Page 1)

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speed of 40 m/min; wind speeds were measured at the samplers'
mouths by a remote controlled hot-wire anemometer. Photo-
graphs were taken of the flow patterns through the use of a
flow visualization system comprised of a liquid aerosol gen-
erator and tunnel injection system. A study of the photo-
graphs and the reduced data resulted in the discovery of an
optimum design for a plankton collection system that is com-
posed of a mouth reduction nose cone and two nets in series
housed in a cylindrical casing.

DD Form 1473

1 Jan 73

~, N 0102-014-6601 2 SECURITY CLASSIFICATION OF THIS PAGEr***" Dalm Enfrtd)

Design and Wind Tunnel Testing of

a Size Sampling i n - s i t u Net System
(SSISNET]

by

Robert Paul Mitchke
Lieutenant, United States Navy
B.S., University of Houston, 1967

Submitted in partial fulfillment of the
requirements for the degree of

MASTER OF SCIENCE IN OCEANOGRAPHY

from the

NAVAL POSTGRADUATE SCHOOL
September 1976

MbMb

ABSTRACT

A number of plankton sampling devices have been designed
and tested and their physical properties (filtration, effi-
ciency, filtration pressure drop, net filtration ratio and
mesh approach speed) have been calculated and compared. The
data necessary to make these calculations were collected by
mounting 1/4 scale sampler models in a wind tunnel, the wind
speed having been adjusted to that corresponding to a water
speed of 40 m/min; wind speeds were measured at the samplers'
mouths by a remote controlled hot-wire anemometer. Photo-
graphs were taken of the flow patterns through the use of a
flow visualization system comprised of a liquid aerosol gen-
erator and tunnel injection system. A study of the photo-
graphs and the reduced data resulted in the discovery of an
optimum design for a plankton collection system that is com-
posed of a mouth reduction nose cone and two nets in series
housed in a cylindrical casing.

TABLE OF CONTENTS

I. INTRODUCTION - - - - 10

II. THEORETICAL BACKGROUND -------------12

A. FILTRATION PERFORMANCE 12

B. FLOW PATTERNS ------- 16

III. METHODS --------- 22

A. WIND TUNNEL TESTING --- 22

B. FLOW SPEED MEASUREMENTS 27

IV. TESTS 60

V. RESULTS ----- - 66

VI. DISCUSSION -- _-- 68

APPENDIX ------- 70

REFERENCES ----------------------92

INITIAL DISTRIBUTION LIST - 93

LIST OF FIGURES

1. Generalized geometry of a plankton net

with a mouth reduction nose cone ---------14

2. The accelerations ahead of plankton nets ----- 18

3. Streamlines ahead of nets ------------19

4. Probable flow pattern associated with some

basic forms of plankton sampler ---------21

5. Mouth reduction nose cone models 1, 2 and 3 - - - 41

6. Sampler model A: simple conical net -------42

7. Sampler model B: simple conical net -------43

8. Sampler model C: nose cone model 2

andconical net - - - - - - - - - - - - - - - - - 44

9. Sampler model D: nose cone model 2

and conical net - - - - - - - - - - - - - - - - - 45

10. Sampler model E: nose cone model 2,

conical net and casing - - - - - - - - - - - - - - 46

11. Sampler model F: nose cone model 2,

conical net and casing - - - - - - - - - - - - - - 47

12. Sampler model G: nose cone model 2,

conical net and casing --------------48

13. SSISNET sampler model H: two conical

nets and casing - - - - - - - - - - - - - - - - - 49

14. SSISNET sampler model I: nose cone

model 1, two conical nets and casing -------50

15. SSISNET sampler model J: nose cone model 1,

two conical nets and casing - - - - - - - - - - - 51

16. SSISNET sampler model K: nose cone model 2,

two conical nets and casing - - - - - - - - - - - 52

17. SSISNET sampler model L: nose cone model 3,

two conical nets and casing - - - - - - - - - - - 53

18. SSISNET sampler model M: nose cone model 2,

two conical nets and casing - - - - - - - - - - - 54

19. SSISNET sampler model N: nose cone model 1,

two conical nets and casing - - - - - - - - - - - 55

20. SSISNET sampler model 0: nose cone model 1,
590 ym conical net (one-third mesh area

clogged), 103 ym conical net and casing - - - - - 56

21. SSISNET sampler model P: nose cone model 1,
590 ym conical net (one-third mesh area

clogged), 103 ym conical net and casing ----- 57

22. SSISNET sampler model Q: 590 ym conical net
(one-third mesh area clogged), 103 ym conical

net and casing - - - - - - - - - - - - - - - - - - 58

23. SSISNET sampler model R: 590 ym conical net
(one-third mesh area clogged), 103 ym conical

net and casing - - - - - - - - - - - - - - - - - - 59

24. Pressure drop (AP) vs. mesh approach speed

(v) for each sampling system prototype ------ 64

LIST OF PLATES

1. Low speedwind tunnel - - - - - - - - - - - - - - - 2 3

2. Liquid aerosol generator and

tunnel injection system -------------- 25

3. Remote controlled hot-wire anemometer probe - - - - 28

4. Servo-transl ater unit used to remotely

position hot-wire anemometer probe -------- 29

5. X-Y plotter and power supply ----------- 30

6. Mouth reduction nose cone model 1--------- 31

7. Mouth reduction nose cone model 2 - - - - - - - - - 32

3. Mouth reduction nose cone model 3--------- 33

9. Sampler model A: simple conical net ------- 34

10. Sampler model C------------------ 35

11. Sampler model H------------------ 36

12. Sampler model J------------------ 37

13. Sampler model K------------------ 38

14. Sampler model L------------------ 39

ACKNOWLEDGEMENTS

The author wishes to express his appreciation to Dr.
Eugene D. Traganza, the advisor, for allowing the author to
participate in his project: Investigation of Biochemical
Relationships for Determining Concentrations of Zooplankton
Biomass and Its Correlation with Chemical and Acoustical
Properties of the Ocean, sponsored by the Office of Naval
Research, Code 482, Arlington, Virginia; for his perceptive
guidance and suggestions; for his encouragement and exper-
ienced insight in the final preparation of the manuscript.

A sincere debt of gratitude is owed to Dr. T. Sarpkaya
and Dr. T. M. Houlihan of the Department of Mechanical Engi-
neering who so willingly donated their equipment, time,
talent, suggestions and encouragement to this project.

A special acknowledgement is due the Mechanical Engineer'
ing Department laboratory personnel, whose technical assist-
ance was priceless: Mr. Tom Christian, Mr. Kenneth
Mothersell and Mr. James Selby.

The author is especially grateful to his family for
their understanding, patience and support and for the many
sacrifices they made while the research was being conducted
and the manuscript prepared and completed.

I. INTRODUCTION

According to Aron (1965): "Problems associated with varia-
tion of time and space among pelagic organisms are already
difficult enough to evaluate without imposing additional com-
plexity through the inadequate understanding of the sampling
tools." Plankton sampling by nets began about 150 years ago
and in these early stages of collection one haul produced such
a wealth of unknown organisms that a lifetime of work was in-
volved in their description. Thus, it is not surprising that
the concentration of effort was studying plankton rather than
understanding the intrinsic details of the plankton sampler.
Tranter (1968) states that when it became apparent that plank-
ton "had such significance in the productivity of the sea and
the food chains therein, pi anktol ogi s ts wanted to know how to
relate the number of organisms found to the volume of water
filtered, their distribution in depth, space and time, and
their daily, seasonal and annual variations. Development of
the gear was gradual to begin with but its tempo increased,
partly because of the increased realization of the importance
of quantitative work, and partly because of the increase in
the number of people studying the subject. The desire for so
much comprehensive quantitative knowledge brought with it a
host of sampling problems": escapement, avoidance, speed of
tow, volume of water filtered, mesh size, drag and clogging.
These problems have recently become more comprehensible with

10

the use of underwater diving and photography and wind and
water test tunnels, along with the assistance of experts in
hydrodynamics and engineering. Although these factors are
giving the evolution of plankton sampling a new impetus,
Tranter (1968) states that there has been a lack of experi-
ments conducted to study the hydrodynamics associated with
most contemporary samplers. Furthermore, a search of the
literature published on the subject subsequent to 1968 has
discovered no further attempts to empirically obtain this
hydrodynamic data.

The foregoing clearly indicates the desirability and
necessity for empirical flow pattern data characteristic of
various sampler designs. And more specifically, as Tranter
(1968) remarks, as far as encased plankton samplers are con-
cerned there is insufficient data and information available
for making any predictions or conclusions about their perform-
ance in relation to other sampler designs.

Consequently the subject of this investigation has been
to study the relative entrance flow patterns associated with
encased samplers, in particular a type that includes a mouth
reduction nose cone and two nets in series housed in a
cylindrical casing. This sampler type can aptly be termed
as a "size sampling in-situ net" (SSISNET) system. An
analysis of the flow patterns produced by several SSISNETS of
different design has resulted in the discovery of an optimum
combination of sampler parameters that can be used in the
ultimate construction of a single SISSNET system.

li

II. THEORETICAL BACKGROUND

A. FILTRATION PERFORMANCE

Four physical properties associated with plankton net fil-
tration that are of significant consequence when sampling
plankton are (Tranter, 1968):

(1) filtration efficiency

(2) filtration pressure drop

(3) net filtration ratio

(4) mesh approach speed

Filtration efficiency (F) primarily affects the volume of
water filtered, but also has an influence on plankton escape-
ment and avoidance, both of which increase as F decreases.
Filtration efficiency is defined by Tranter (1968) as the
ratio of the volume of water filtered by a plankton sampler
to the volume swept by the sampler mouth. That is,

F =

W

A-D

(1)

where W is the volume of water filtered, A is the area of
the sampler mouth and D is the distance traveled. The rela
tion may also be expressed as,

F =

A

V

V'
V

(2)

where V is the tow speed and V is the mean speed of the flow
through the mouth of the sampler.

12

Filtration pressure drop ( A P ) influences the ultimate con
dition of the catch; it is determined by the speed at which
the water approaches the net gauze (approach speed). Accord-
ing to Tranter (1968)

1 2

AP = K • j pv

(3)

where v is mesh approach speed, p is sea water density; K (re

si stance coefficient) is a function of the gauze porosity (6)

and Reynolds number (Re) and has been shown by Wieghardt
(1953) to be:

K i izl . 6 Re"1/3

(4)

Reynolds number is given by the equation

Re = -

(5)

where d is the diameter of the gauze strands, k is the kine-
matic viscosity of the water. The porosity is the open area
fraction of the gauze comprising the filtering surface and
is calculated from the equation:

_2

3 =

(d+m)

(6)

where m is the mesh width and d is the diameter of the strands
in the meshwork. The effective Reynolds number becomes Re
cos 8 when the flow strikes the gauze at the angle 8 to the

13

normal, thus the maximum possible values of filtration pres-
sure are obtainable by setting 9=0.

If a mouth reduction nose cone is added to a conical net,
as in Figure 1, the filtration efficiency increases. The nose
cone also has the effect of creating a low pressure area which

Mouth area /!« * R?

Anglo of
expansion

Surface area a =» r (K+i) s

-Nose cone

Net

-*-k Bucket 7

Figure 1. Generalized geometry of a plankton net
with a mouth reduction nose cone
(From Tranter and Heron, 1967).

draws a column of water wider than the reduced mouth through
the sampler (Figure 4c). The angle of expansion and the
length of the nose cone are critical because they actually
control the filtration efficiency, which depends upon the mean
flow velocity through mouth and the mouth area. Reduction
cones are most efficient when their angle of expansion (a)
is less than 3 1/2° (Pankhurst and Holder, 1952), and their
length is greater than the diameter of the net mouth. In-
crease of length is restricted by physical practicality and
by the reduction of the mouth area, which would decrease the
vol ume accepted .

14

Another important limitation on dimensions is a result

of the filtration efficiency decreasing sharply when the net

a

side angle (9) is reduced below 75° or the ratio — rises

a

above approximately 0.2 (Tranter and Heron, 1967; Smith et al.,
1965). This ratio can be calculated from

mouth area A ttR
porous area a ttRs

= cos

(7)

where R is the mouth radius and s is net slant length.

A factor closely related to this area ratio is the net
filtration ratio (FR) and is given by

FR -f

(8)

where B is the net porosity. As the length of the net de-
creases the filtration ratio decreases; this condition pro-
motes clogging which, in turn, reduces the filtration effi-
ciency. Therefore the net must be long enough to minimize
clogging; however it also has to be restricted to that length
which is physically manageable.

The mesh approach speed (v) is a parameter that can be
obtained from the equation (Tranter, 1968)

v = v

F'$

(9)

and then used to calculate the filtration pressure drop by
equation (3). This approach speed alone does not cause
damage to organisms; but it is primarily the associated

15

pressure drop across the net that would be responsible for
any damage. It is also likely that this pressure drop in-
fluences the selectivity or organisms by the meshes (Vannucci,
1968). That is, a high AP could cause organisms to be pulled
through the mesh, distorting any selectivity data. Because
AP varies as the square of the approach speed (equation (3)),
small changes in this speed will lead to relatively large
changes in AP. Therefore approach speed should be restricted
to an optimum value, one that would create a AP large enough
to insure a continuous fluid flow, but not great enough to
be destructive to the organisms.

B. FLOW PATTERNS

The interaction between a plankton net and the water
through which it is towed produces for each type of sampler
a unique flow pattern which is closely related to its filtra-
tion performance. This interaction significantly affects the
entire sampling process because of the many other factors in-
volved. For example, an approaching net causes disturbances
that may result in avoidance by motile zooplankton; the volume
of water filtered is directly related to the shape of the net;
and clogging of the net can seriously reduce filtration. The
following discussion will closely examine these and other
water-net interactions with a description of the various flow
patterns produced.

"The pressures on both sides of the gauze are equal for a
stationary net; however, for a moving net the inside pressure
is higher than that on the outside and the resulting flow

16

pattern is dependent upon the distribution of these pressures"
(Tranter, 1968). Also Tranter (1968) states that the conical
net has the most evenly distributed pressures, thereby result-
ing in a uniform flow rate over the entire filtering area of
the net which is important when attempting to maximize filtra-
tion efficiency.

The entrance area of the net displays flow patterns that
are influenced both by the resistance of the net and by tow-
ing structures ahead or near the mouth. Most of the disturb-
ances created ahead of the net by the tow cable and bridle
can be alleviated by towing with the cable attached to the
top of the forward section of the sampler casing or by attach-
ing the cable to the rear of the casing and sampling during a
guided vertical fall. Upstream accelerations caused by
various towing appratus are shown in Figure 2. This disturb-
ance, coupled with any upstream pressure variation when nets
are attached, can have a severe adverse impact upon results
of collection efforts due to the belief that plankton sense
and move away from foreign objects (Tranter, 1968).

"The sampler mouth, or at least the shape of its mouth,
can play-an important role in reducing or even alleviating up-
stream disturbances that may cause avoidance by plankton"
(Tranter, 1968). It has been shown by Tranter (1968) that
the addition of a mouth-reduction cone increases filtration
efficiency by creating a low pressure area which results in
a larger cross-section of the water column being drawn into
the net. Figure 3 is a comparison of streamline patterns

17

4

17

\

o

1

27

*' \

o

IS

10

29

49 \

N
\

47 \

o

1]

54

33

32

\
44 /

o

9

30

43

/

24

4S

•

o

1

29
IS

49 /

/
/
/

•

©

<

•

**

•

14 (

a

"^ IS

o

^3

3 O

o

o

0^^ o

o

0

o

o

o *«*„ o

•

©

o

s

0

•

*' O

II

•«

It

12

12

IO

JO

1

20

16

o

t

o

s

a

o

4

*»I2

Figure 2 . The accelerations (cm/sec) ahead of plankton nets.

a. Linear accelerations ahead of a non-filtering cone 1 m
in diameter without a bridle preceding the entrance. The
tow speed is 11 cm/sec (44 m/min).

b. Linear accelerations ahead of
lead line. The tow speed is 129

c. Linear accelerations ahead of
and lead line. The tow speed is
( from Tranter, 1 968) .

a ring with bridle and
cm/sec ( 77 m/mi n ) .
a plankton net ring, bridle
129 cm/ sec (77 m/min).

18

©

Figure 3. Streamlines ahead of nets
10 percent of the water entering a

a . A coni ca 1 net
presented to it.

b. A conical net
presented to it.

c. A conical net

ing 125
1968) .

percent

which

whi ch

, with
of the

Each streamline
ci rcul ar net.

of the

encl oses

is accepting 75 percent
is accepting 95 percent

water
of the water

a mouth-reduction cone, which is accept-
water presented to it (from Tranter,

19

associated with conical nets with and without a reduction
cone. The advantage gained in filtration efficiency through
the use of the mouth reduction cone can be seen by examining
that figure and noting the increase in percentage of water
accepted when using the cone with the net.

Tranter (1968) also offered a series of figures depict-
ing probable flow patterns associated with some basic forms
of plankton samplers. These are shown in Figure 4; however,
they are based on theory rather than actual observance.
Plankton sampler type f was selected for study in this thesis
because it would allow stacking different size nets within
the casing for separating plankton by size. This type sam-
pler also has the filtration control advantages of a mouth
reduction nose cone.

20

©

©

©

©

©

©

Figure 4. Probable flow pattern associated with some basic
forms of plankton sampler.

a. Simple conical net (F < 1).

b. Conical net with porous collar (F * 1).

c. Conical net with nonporous mouth-reducing cone (F > 1)

d. Conical net with nonporous mouth-reducing cone (F = 1)

e. Conical net with nonporous casing (F < 1).

f. Conical net with nonporous casing and nonporous mouth-
reducing cone (F = 1). (from Tranter, 1968)

21

III. METHODS

A. WIND TUNNEL TESTING

One method of measuring the hydrodynami c characteristics
of plankton nets is to construct scale models and to test
them in wind or water tunnels. The wind tunnels are partic-
ularly suited for this purpose becasue of ease of experimenta-
tion, flow visualization, and measurement of the forces acting
on the nets. It is for this reason that it was decided to
carry out a series of experiments in the low speed wind tunnel
of the Mechanical Engineering Department of the Naval Post-
graduate School (Plate 1).

The tunnel is of open circuit design with its intake in-
side the building and exhausting outside. The test section
is 51 cm by 71 cm at the center and is 2.4 meters long. The
prime mover is a six blade axial fan, located at the down-
stream end, and driven by a variable speed 75 horsepower elec-
tric motor. The wind speed is continuously variable from
548 m/min to 5486 m/min when the test section is clean, and
from about 914 to 4572 m/min (equivalent to 15 and 75 m/min
water speed) when the model is installed. The freestream
turbulence intensity is controlled at the plenum entrance,
followed by up to five interchangeable graded screens and an
area contraction ratio of ten to one.

The tunnel was equipped with a flow visualization system
comprised of a liquid aerosol generator and injection system

22

O)

c
c

+->

T3
0)
O)
Q.
CO

+->

3&&s&^:- •*■ •

23

(Plate 2). The flow of the aerosol particles in front of and
around the models have been used to study the flow patterns.
This will be described in greater detail later.

Evidently, model tests in general and the use of different
fluids (e.g. air and water) for the model and prototype re-
quire the establishment of model laws in order to be able to
correctly interpret the results and to transfer them from one
model to another. Fundamentals of fluid mechanics show that
(see for example Streeter, 1958) complete similarity requires
geometric, kinematic and dynamic similarity of the models.
In other words, for the present investigation, this requires
that the model and the prototype be geometrically similar
and that the model and prototype Reynolds numbers and Mach
numbers be identical. It is assumed that there are no free
surface effects and the Froude number is excluded from further
consideration. Reynolds similarity establishes the correct
ratio of the inertial forces to viscous forces in the model
and prototype at the corresponding points. Mach similarity,
on the other hand, brings into the tests the possible effects
of the fluid compressibility and expresses the ratio of the
inertial forces to elastic forces. In the present study, the
compressibilities of the fluids involved, that is of air and
water, are quite negligible. Air shows compressibility
effects for body speeds corresponding to Mach numbers of
about 0.4 or greater. Water shows compressibility effects for
speeds of sound in water or close to it. This, in fact, corre^
sponds to a sound speed of about 4000 feet/sec. Cavitation

24

n»:><*x- "'■*■■»" gr7.yyTvr.ii;;*'1 *m v~j^k~*

9.

Plate 2. Liquid aerosol generator and tunnel injection
system.

25

and other effects take place long before the compressibility
effects come into the picture in collecting plankton (if the
collector were ever to travel at such high speeds). Further
discussion of the compressibility effects is meaningless and
the Mach similarity need not be considered.

According to Reynolds similarity, Streeter (1958) used
the equation

UaDa

V D.

w

= Reynolds number

(10)

in which U and V are wind and water speeds relative to the

collector, D the diameter, and v the kinematic viscosity of

- 7 2
the fluid (v . = 9000 X 10 m /min at room temperature and
air

-7 2
v . = 575 X 10 m /min at 20°C temperature). The indices

"a" and "w" denote "air" and "water" respectively to indicate

the Reynolds numbers for the model and prototype media.

Solving for the speed of air in the wind tunnel, one has:

D

w

(11)

w

The characteristic dimension is taken as the inlet diameter

of the collector without a nose cone, for the prototype D =

r w

31.6 cm, and for the model D^ = 7.9 cm, for a model scale of

a

1/4. The Reynolds numbers and the corresponding wind and
water speeds for the model and prototype respectively are
given in Table I.

26

TABLE I. Various wind tunnel air speeds (Ua) and the corre
sponding water speeds (V) required to match the
Reynolds numbers.

Ua
wind speed (m/min)

Reynolds number
(dimensionless)

V
water speed (m/min)

1560
• 1870
2190
2505
2815
3130
3440
3760
4070 •
4380

137400
164900
192400
219700
247300
275000
302300
330000
357300
385000

25
30
35
40
45
50
55
60
65
70

B. FLOW SPEED MEASUREMENTS

The desired model combination of nets, reduction cone and
casing was assembled and mounted in the test section of the
wind tunnel. The air speed was adjusted to that corresponding
the water speed. Photographs were taken of the flow stream
lines, i.e. aerosol particles (Plates 6 through 14).

A remote controlled hot-wire anemometer was used to mea-
sure voltages at various points in front of the different
models (Plates 3 and 4). These voltages were recorded on an

X-Y plotter (Plate 5), then converted to wind speeds (U) with

a

the following equation, which is derived from the standard

calibration procedure of a hot-wire anemometer probe:

2 2

Ua1/2 * — H" H2)

27

2
I

+->

o

c
o

to

o

Q.

+->

o

E:

to

c

*

s- a;

-M O

03 S-

i— Q.

to

c s-

03 <D

S- 4->

+J CD

o o

> E

5- O)

<U c

go ra

O)

29

Q.
Ol

ZS

to

s-

OJ

s
o

CL

-a

E
rT3

i-
0)

4->
O

i—
CL

>-

X

LO
<T3

30

^jg^jggjBstawfiBj^MMjjH

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where E is the voltage recorded on the X-Y plotter, E is
the voltage registered by the anemometer at zero wind speed
and y is the anemometer probe characteristic impedance. In
the case of one probe E was found to be 5.4 volts and y to
be 0.79. A second probe had an E of 3.27 and a y of 0.5.
The wind speeds were then converted into corresponding water
speeds (V) through the use of Table I. The voltage profile
data and corresponding water speeds were tabulated for each
system model in the Appendix. The water speed data were
used in equation (2) to obtain the filtration efficiency and
in equation (9) for mesh approach speed calculations, which
in turn was used in equation (3) to obtain filtration pres-
sure drop values. These results are tabulated for all models
and are listed on the corresponding drawings (Figures 5
through 23). A comparison of the values were made for the
purpose of choosing the model that had optimum characteristics

40

2505 M/MIN WIND SPEED, EQUIVALENT

TO 40 M/MIN WATER SPEED

MEAN SPEED THROUGH MOUTH (mTn)
FILTRATION EFFICIENCY

Ji5,4_

Ul

MEAN SPEED THROUGH MOUTH ("min) 4 7.6
FILTRATION EFFICIENCY LIS.

MEAN SPEED THROUGH MOUTH (mTn")__A^x5_
FILTRATION EFFICIENCY L_Q9_

Figure 5. Mouth reduction nose cone models 1, 2 and 3.

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59

IV. TESTS

The effects of filtration efficiency, filtration pressure
drop, net filtration ratio and mesh approach speed were in-
vestigated by varying the following sampler model parameters:

casing length

mouth reduction nose cone length and angle

speed of tow

number of nets

net mesh size

length of nets

clogging of nets
Each wind tunnel test, model description and corresponding
figures and plates are listed below (data tabulated on figures
are based upon prototype dimensions and water speed equiva-
lences; the X-Y coordinate system is reference for the hot-
wire anemometer probe positions):

1. Nose cone model 1 of 7.6 cm length and 3 1/2° angle
(Figure 5 and Plate 6)

2. Nose cone model 2 of 13.5 cm length and 3 1/3° angle
(Figure 5 and Plate 7)

3. Nose cone model 3 of 12.6 cm length and 6° angle
(Figure 5 and Plate 8)

4. Sampler model A: 15.2 cm, 590 ym simple conical net
(Figure 6 )

60

5. Sampler model B: 48.0 cm, 590 ym simple conical net
(Figure 7 and Plate 9)

6. Sampler model C: nose cone model 2 with 22.9 cm, 590 ym
conical net attached (Figure 8 and Plate 10)

7. Sampler model D: nose cone model 2 with 30.5 cm, 590 ym
conical net attached (Figure 9)

8. Sampler model E: nose cone model 2 with 22.9 cm, 590 ym
conical net and 38.1 cm casing attached (Figure 10)

9. Sampler model F: nose cone model 2 with 30.5 cm, 590 ym
conical net and 38.1 cm casing attached (Figure 11)

10. Sampler model G: nose cone model 2 with 38.1 cm, 590 ym
conical net and 38.1 cm casing attached (Figure 12)

11. Sampler model H: 72.4 cm casing with a 22.9 cm, 590 ym
conical net and a 38.1 cm, 103 ym conical net attached
(Figure 13 and Plate 1 1 )

12. Sampler model I: nose cone model 1 with a 22.9 cm, 590 ym
conical net, a 38.1 cm, 103 ym conical net and a 72.4 cm
casing attached (Figure 14)

13. Sampler model J: nose cone model 1 with a 22.9 cm, 590 ym
conical net, a 38.1 cm, 103 ym conical net and a 68.9 cm
casing attached (Figure 15 and Plate 12)*

14. Sampler model K: nose cone model 2 with a 22.9 cm, 590 ym
conical net, a 38.1 cm, 103 ym conical net and a 68.9 cm
casing attached (Figure 16 and Plate 13)

15. Sampler model L: nose cone model 3 with a 22.9 cm, 590 ym
conical net, a 38.1 cm, 103 ym conical net and a 68.9 cm
casing attached (Figure 17 and Plate 14)

61

16. Sampler model M: nose cone model 2 with two 22.9 cm,
590 ym conical nets and a 38.1 cm casing attached
(Figure 18)

17. Sampler model N: nose cone model 1 with a 22.9 cm,
590 ym conical net, a 38.1 cm, 103 ym conical net and
a 38.1 cm casing attached (Figure 19)

18. Sampler model 0: nose cone model 1 with a 22.9 cm,

590 ym conical net (one-third mesh area clogged between
mouth and apex), a 38.1 cm, 103 ym conical net and a
38.1 cm casing attached (Figure 20)

19. Sampler model P: nose cone model 1 with a 22.9 cm,

590 ym conical net (one-third mesh area clogged at apex),
a 38.1 cm, 103 ym conical net and a 38.1 cm casing
attached ( Fi gure 21 )

20. Sampler model Q: 38.1 cm casing with a 22.9 cm, 590 ym
conical net (one-third mesh area clogged between mouth
and apex), a 38.1 cm, 103 ym conical net attached
(Figure 22)

21. Sampler model R: 38.1 cm casing with a 22.9 cm, 590 ym
conical net (one-third mesh area clogged at apex), a
38.1 cm, 103 ym conical net attached (Figure 23)

62

Figure 24 is a plot of all different sampler prototypes
(vice models) with different combinations of mesh approach
speed and pressure drop; the curve demonstrates that a
slight increase in approach speed corresponds to a wery
drastic increase in pressure drop across the net. This large
pressure variable is highly undesirable since the objective
is to collect organisms that will be preserved by the sampler
rather than possibly destroyed due to high pressure differen-
tial across the net.

The sampler prototypes at the lower end of the curve are
those that were clogged (0, P, Q, R), illustrating the degra-
dation in a system's performance as a result. Prototype H
is a system with two nets and casing and has low speeds,
pressure drop and filtration efficiency (0.37). Prototypes
I, J and N are identical with the exception that the casing
lengths are 2.9 m , 2.76 m and 1.52 m respectively, a factor
that has no observed effect on any of the parameters; these
three systems, however, utilized nose cone 1, which proves
to be responsible for those systems ' low filtration efficien-
cies (each were 0.52). A and B are simple conical nets of
length 1.93 m and 0.60 m respectively. Prototypes E, F and
G are all systems with reduction cone, casing and only one
net (an undesirable feature).

Prototypes K, L and M are all systems with reduction cone
casing, and two nets; system K has the highest filtration
efficiency (0.74) and it is located at a point just before
the curve extends into the region of higher pressure drops.

63

3 4 5 6 7 8
v, Mesh approach speed (m/min)

10

Figure 24.

Pressure drop (AP) vs. mesh approach speed
(v) for each sampling system prototype.

64

The two remaining systems (C and D) are those of a reduction
cone and net assembly, which have extremely high approach
speed and pressure drops.

Prototype K is clearly the optimum system. It has a
relatively high filtration efficiency, low approach speed
and pressure drop. Its casing houses two nets, both of which
have area ratios below 0.2. The total length of the system
can be varied by reducing the casing length provided the nets
remain protected.

65

V. RESULTS

1. Figure 5 shows that the mouth reduction nose cone model 2
has a higher filtration efficiency than models 1 and 3.

2. Figures 6 and 7 show that an increase in the net length
increases filtration ratio, and filtration efficiency but
reduces the pressure drop across the net.

3. Figures 8 and 9 show that increasing net length when a
nose cone is attached results in an increase in filtra-
tion ratio, no change in filtration efficiency and a de-
crease in pressure drop.

4. The reduction cones and net assemblies shown in Figures
10 and 11 have higher filtration efficiencies than the
corresponding reduction cone, net and casing assemblies
shown in Figures 11 and 12. However, the addition of the
casing results in a much lower pressure drop.

5. The model shown in Figure 10 has a greater filtration
efficiency than those shown in Figures 11 and 12; however
clogging rapidly diminishes the filtration efficiencies
of nets with lower filtration ratios.

6. The model shown in Figure 18 has a lower filtration effi-
ciency than tnat shown in Figure 10 due to the additional
net; however the pressure drop is reduced.

7. The net and casing assembly shown in Figure 13 has a lower
filtration efficiency than the same assembly with a mouth
reduction nose cone attached as shown in Figure 14.

66

10

11

Figures 15, 16 and 17 show that the net and casing
assembly with the reduction cone model 2 attached has
a higher filtration efficiency than with either cone
model 1 or 3 attached.

Figure 15 shows that an increase in tow speed increases
filtration efficiency; however the increase is not a
proportional one. An increase in tow speed from 23.7
m/min to 59.6 m/min resulted in an increase of filtra-
tion efficiency of only .09.

Figures 15 and 19 show that decreasing the model casing
length from 68.9 cm to 38.1 cm has no effect on filtra-
tion efficiency.

A comparison of Figures 20, 21, 22 and 23 with Figure
19 shows that net clogging results in a lower filtration
efficiency. Furthermore, if clogging is concentrated
at the apex of the nets the result is a lower filtration
efficiency than if the same percentage of clogging
occurred nearer the mouth of the nets.

67

VI. DISCUSSION

A plankton collection device has been designed and
tested that is a combination of relatively optimum physical

characteristics, including a high filtration efficiency

_ 3
(0.74), a low filtration pressure drop (6.41 X 10 nt),

high net filtration ratios (3.18 and 5.40) and a low maxi-
mum mesh approach speed (3.63 m/min).

The research was initiated by investigating these physi-
cal properties associated with the basic conical plankton
net and was completed with the study of complex sampling
systems. A simple conical net has a filtration efficiency
less than 1.0; however with the attachment of a mouth reduc-
tion nose cone this figure was increased to greater than 1.0.
The nose cone model that was found to result in the highest
filtration efficiency was one of 13.5 cm in length with an
angle of expansion of 3 1/3°. According to Pankhurst and
Holder (1952) the best results are obtained by using a cone
with an angle less than 3 1/2°.

The length of the nose cone, nets and casing were re-
stricted so the scaled-up prototype would be of suitable
size. Tranter (1968) points out that the filtration effi-
ciency of a net decreases rapidly beyond an area ratio (A/a)
of 0.2, which converts into a net minimum side length (for
the model) of 19.5 cm or 78 cm for the prototype. Increas-
ing the net length beyond this value increases the filtration

68

efficiency and reduces clogging; however, physical restraints
have to be imposed due to handling, stowage and weight prob-
lems. In the optimum model net, side lengths of 22.9 cm and
38.1 cm were used for the 590 pm and 103 urn nets respectively.
So that a size sampling i_n situ net (SSISNET) system could be
realized, two nets had to be utilized in series. The mesh
size of the front net would be such that all larger plankton
would be collected there but the desired sized plankton would
pass through and be collected by the rear net for removal and
analysis. No more than two nets were tested because the
system becomes cumbersome; a system that utilizes more than
two nets increases resistance to flow (back pressure) and
thus leads to a reduction in filtration efficiency.

Aside from the fact that a casing was needed to house the
two nets, the casing was found to have several desirable
effects on the overall performance of the system, although it
did cause a reduction in filtration efficiency. The casing
protects the catch and nets and minimizes turbulence; it
lends hydrodynamic stability to the system, a factor that
could perhaps be further conveniently improved with the addi-
tion of fins. The casing also causes a lower pressure drop
across the nets. Thus, sampler model K, the encased net sys-
tem shown in Figure 16 was chosen because it had the most
desirable combination of characteristics, i.e. a high filtra-
tion efficiency (0.74), high filtration ratios (3.18 and 5.40),
and a mesh approach speed that results in a low pressure
differential across the nets (6.41X 10 nt).

69

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REFERENCES

1. Aron, W., E. H. Ahlstrom, B. Bary, A.W.H. Be, and W. D.
Clarke, "Towing Characteristics of Plankton Sampling
Gear," Limnology and Oceanography, v. 10 (3), 333-340,
1965.

2. Neumann, G. and W. J. Pierson, Principles of Physical
Oceanography , Prentice-Hall, 1966.

3. Pankhurst, R. C. and D. W. Holder, Wind Tunnel Technique,
London, Pitman, 1952.

4. Pope, A. and J. J. Harper, Low Speed Wind Tunnel Testing,
John Wiley and Sons, Inc., 1-4, 1966.

5. Smith, P. E. and R. I. Clutter, "Hydrodynamics of Flow
and Collection in Plankton Nets", Ocean Science and
Ocean Engineering, n. 1, 515 (abstract) , 1965.

6. Streeter, V. L., Fluid Mechanics , McGraw-Hill Book Co.,
Inc. , 8-9, 1960.

7. Tranter, D. J., "A Formula' for the Filtration Coefficient
of a Plankton Net", Australian Journal of Marine and
Freshwater Research, v. 18, 113-121, 1967.

8. Tranter, D. J. and A. C. Heron, "Experiments on Filtra-
tion in Plankton Nets", Australian Journal of Marine and
Freshwater Research, v. 18, 89-111, 1967.

9. Tranter, D. J. and P. E. Smith, "Filtration Performance",
UNESCO Monograph on Ocea nographi c Methodology, no. 2,
27-56, 1968.

10. Vannucci, M., "Loss of Organisms Through the Meshes,"
UNESCO Monograph on Oceanographi c Methodology, no. 2,
77-86, 1968.

92

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Thesis 166837

M646 Mitchke

c.l Design and wind tunnel
testing of a size sam-
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Thesis 166837

M646 Mitchke

Design and wind tunnel

testing of a size sam-

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Design and wind tunnel testing of a size

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