tracing chemical plumes in turbulent waters jiri janata, hiroshi ishida, timo kikas school of...

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TRACING CHEMICAL PLUMES IN TURBULENT WATERS Jiri Janata, Hiroshi Ishida, Timo Kikas School of Chemistry and Biochemistry Georgia Institute of Technology Atlanta, GA 30332-0400, USA ACKNOWLEDGMENTS: GEORGIA INST. OF TECHNOLOGY: D. WEBSTER TOKYO INST. OF TECHNOLOGY: T. MORIIZUMI FUNDING (1998-2000): DARPA: Project Number: N00014- 98-1-077

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TRACING CHEMICAL PLUMES IN TURBULENT WATERS

Jiri Janata, Hiroshi Ishida, Timo KikasSchool of Chemistry and Biochemistry

Georgia Institute of TechnologyAtlanta, GA 30332-0400, USA

ACKNOWLEDGMENTS:

GEORGIA INST. OF TECHNOLOGY: D. WEBSTERTOKYO INST. OF TECHNOLOGY: T. MORIIZUMI

FUNDING (1998-2000): DARPA: Project Number: N00014-98-1-077

How to make the best use of signals from sensor array?

Outline

• Where is the information in the plume?

• Data acquisition

• Correlation analysis

- theory- bandwidth- experiments

• Conclusions

Outline

• Where is the information in the plume?

• Data acquisition

• Correlation analysis

- theory- bandwidth- experiments

• Conclusions

0.7 mm cylinder 2.54 cm downstream from the nozzle

f = (St).U/d = 1.2 Hz

Unmodulated Modulated

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Simulated Microelectrode Sensor Array

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50 cm from the source on the centerline.Spacing between sensors is 1 cm.

Blue crab has chemo-receptors on 8 legs.

Blue crab has chemo-receptors on 8 legs.

ARRAY CAN DETECT FLOW VELOCITY

FLOW

WHERE IS THE OTHER INFORMATION?

TIME-VARYING SIGNAL HAS TWO PARTS, THE MEAN VALUE AND THE FLUCTUATING PART

S (t) = S + s (t)

HYPOTHESIS: THE INFORMATION IS IN THE FLUCTUATING PART OF THE SIGNAL

VIRTUAL PLUME SET-UP

CORRELATION ANALYSIS

-3

-2

-1

0

0 200 400 600 800 1000Time [sec]

Current [n

A]

-3

-2

-1

0

0 200 400 600 800 1000Time [sec]

Current [n

A]

0

2

4

6

0 2 4 6 8 10

0

2

4

6

0 2 4 6 8 10

0

0.03

0.06

0.09

0.12

0.15

0 2 4 6 8 100

0.2

0.4

0.6

0.8

1

0 2 4 6 8 10

Time series of channel 1 Time series of channel 2

Auto-power spectrumdensity of channel 1

Coherencespectrum

Cross-power spectrumdensity of channels1 and 2

Auto-power spectrumdensity of channel 2

FREQUENCY CONTENT OF THE PLUME

FLUIDIC BANDWITH

TWO-FREQUENCY MODULATION

COHERENCE PEAK ASSIGNMENTS

Sensors 3 & 5

0 2 3 4 5Frequency [Hz]

0.5

Sensors 5 & 7

Sensors 1 & 4

Average of 21 pairs

Average of 10 pairs

1

CO

HE

RE

NC

E

0.5 cm

COHERENCE AVERAGING

ARRAY

Do they use the frequency mode of information acquisition?Do they use the frequency mode of information acquisition?

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AQUATIC ANIMALS---

Conclusions

• Information about source location appears to be frequency encoded in 0 ~ 5Hz bandwidth

• Coherence was found to be sensitive to:

- Orientation of the sensor array,

- Spacing between the sensors.

- Edge of the plume.

- Distance from the source

• Coherence in frequency-modulated plume shows peak at the modulation frequency given by the size and shape of the source

• Coherence is not sensitive to flow or dilution,

• Encoding in multiple frequencies is possible

• Blue crabs are very smart!

Electroanalysis , 12 (2000) 974 “Virtual Plume”

Biol. Bull., 200, (2001) 222 "Plume-tracking robots: a newapplication of chemical sensors,"

Anal. Chem., 73 (2001) 3662 “Chemical Plume Tracking, Part I:Chemical Information Encoding”

Anal. Chem., 73 (2001) 3669 “Chemical Plume Tracking, Part II:Frequency Modulation”

Environmental Fluid Mechanics “ A Multidisciplinary Study ofSpatial and Temporal Scales Containing Information in TurbulentChemical Plume Tracking”

Anal. Chem., 2002 “Chemical Plume Trackin g, Part III: Ascorbic Acid– a Viable Biological Marker”