NASA Contractor Report 185637

National Aeronautics and Space Administration (NASA)/

American Society for Engineering Education (ASEE)

Summer Faculty Fellowship Program—1990

Volume 1

Richard B. Bannerot, Editor

University of Houston — University Park

Houston, Texas

Stanley H. Goldstein, Editor

University Programs Office

Lyndon B. Johnson Space Center

Houston, Texas

Grant NGT 44-005-803

December 1990

NASA

(NASA-CR-185637-Vol-l) NASA/ASFt SUMMcR N91-27G8ts

FACULTY FELLOWSHIP PROGRAM, 1990, VOLUME 1 —THRU

(Houston Univ.) 207 p CSCL 05? N91-27102

Unclas

G3/99 0020200

https://ntrs.nasa.gov/search.jsp?R=19910017774 2018-05-15T19:07:13+00:00Z
PREFACE

The 1990 Johnson Space Center (JSC) National Aeronautics and Space Administration

(NASA)/American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program

was conducted by the University of Houston—University Park and JSC. The 10-week program was

operated under the auspices of the ASEE. The program at JSC, as well as the programs at other

"Y NASA Centers, was funded by the Office of University Affairs, NASA Headquarters, Washington,

t f--

D.C. The objectives of the program, which began nationally in 1964 and at JSC in 1965, are

1. To further the professional knowledge of qualified engineering and science faculty members

2. To stimulate an exchange of ideas between participants and NASA

3. To enrich and refresh the research and teaching activities of participant's institutions

4. To contribute to the research objectives of the NASA Centers

Each faculty fellow spent at least 10 weeks at JSC engaged in a research project commensurate with

his/her interests and background and worked in collaboration with a NASA/JSC colleague. This

document is a compilation of the final reports on the research projects done by the faculty fellows

during the summer of 1990. Volume 1 contains reports 1 through 14, and volume 2 contains reports 15

through 28.

K
CONTENTS

Volume 1

1. Akundi, Murty A.: "LIF and Emission Studies of Copper and Nitrogen" • 1-1

2. Barnes, Ron: "Compound Estimation Procedures in Reliability" 2-1

3. Bishop, Phillip A.: "Techniques for Determining Total Body

Water Using Deuterium Oxide" 3-1

4. Boyd, Ernest J.: "Mathematical Modeling of the Flow Field and Particle

Motion in a Rotating Bio reactor at Unit Gravity and Microgravity" 4-1

5. Hart, Maxwell M.: "An Air Revitalization Model for Regenerative Life

Support Systems (RLSS)" 5-1

6. Hite, Gerald E.: "Photographic Image Enhancement" 6-1

7. Hooker, John C.: "Nonlinear Systems Dynamics in Cardiovascular

Physiology: The Heart Rate Delay Map and Lower

Body Negative Pressure" 7-1

8. Huntsberger, Terry: "Incorporation of Shuttle CCT Parameters

in Computer Simulation Models" 8-1

9. Johnson, Debra Steele: "Training Effectiveness of an Intelligent

Tutoring System for a Propulsion Console Trainer" 9-1

10. Karimi, Amir: "Re-Examination of Metman, Recommendations on

Enhancement of LCVG, and Development of New

Concepts for EMU Heat Sink" 10-1

11. Kurdila, Andrew J.: "A Nonrecursive Order N Preconditoned Conjugate

Gradient/Range Space Formulation of MDOF Dynamics" 11-1

12. Lacovara, R. C.: "Applications of Formal Simulation Languages in the

Control and Monitoring Subsystem of Space Station Freedom" 12-1

13. Lawless, DeSales: "A Study of Murine Bone Marrow Cells Cultured in

Bioreactors Which Create an Environment Which Simulates Microgravity" 13-1

14. Layne, Charles S.: "The Effects of Deuterium on Static Posture Control" 14-1

Volume 2

15. Morgan, Paul: "Evaluation of Geophysical Properties of the Lunar Regolith

for the Design of Precursor Scientific Missions for the

Space Exploration Initiative" 15-1

16. Morris, Robert A.: "A Design for an Intelligent Monitor and Controller for

Space Station Electrical Power Using Parallel Distributed

Problem Solving" 16-1
17. Murphy, Michael G.: "Fuzzy Logic Control System to Provide Autonomous

Collision Avoidance for Mars Rover Vehicle" 17-1

18. Navard, Sharon E.: "Evaluating the Effect of Accuracy Ratios on the

Percent of Calibrations Which Are Out of Tolerance" ' 18-1

19. Neubek, Deborah J.: "Developing a Taxonomy for Mission

Architecture Definition" 19-1

20. Radhakrishnan, Ramalingam: "Design of a Lunar Oxygen Production Plant" 20-1

21. Rajan, Periasamy K.: "Design of Correlation Filters for Hybrid Vision Systems" 21-1

22. Ricles, James M.: "Development of Load-Dependent Ritz Vector Method

for Structural Dynamic Analysis of Large Space Structures" 22-1

23. Squires, William G.: "Mechanics, Impact Loads and EMG on the

Space Shuttle Treadmill" 23-1

24. Strait, Melissa M.: "Solutions to Problems of Weathering in

Antarctic Eucrites" 24-1

25. Tietze, Karen J.: "Assessment of the Pharmacodynamicsoflntranasal,

Intravenous and Oral Scopolamine" 25-1

26. Uhde-Lacovara, J.: "High Accuracy Optical Rate Sensor" 26-1

27. Williams, Raymond: "Planetary Spacecraft Cost Modeling Utilizing

Labor Estimating Relationships" 27-1

28. Yin, Paul K.: "Structural Concept Studies for a Horizontal

Cylindrical Lunar Habitat and a Lunar Guyed Tower" 28-1
LIF AMD EMISSION STUDIES OF COPPER AND NITROGEN

Final Report

NASA/ASEE Summer Faculty Fellowship Program — 1990

Johnson Space Center

Prepared BY:

Academic Rank:

University & Department:

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleague:

Date Submitted:

Contract Number:

Murty A. Akundi, Ph.D.

Associate Professor

Xavier University

Physics/Engineering Department

New Orleans, Louisiana 71245

Engineering

Structures and Mechanics Division

Thermal

James Milhoan

August 15, 1990

NGT 44-005-803

1-1
ABSTRACT

A technique is developed to determine the rotational

temperature of Nitrogen Molecular Ion (N^ ) from the emission

spectra of B-X transition, when P and R Branches are not

resolved. Its validity is tested on simulated spectra of the

0-1 band of N2 produced under low resolution. The method is

applied to experimental spectra of N, taken in the shock

layer of a blunt body at distances or 1.91 cm, 2.54 cm, and

3.18 cm from the body.

The laser induced fluorescence (LIF) spectra of copper

atoms is analyzed to obtain the free stream velocities and

temperatures. The only broadening mechanism considered is

Doppler broadening. The temperatures are obtained by manual

curve fitting; and the results are compared with least square

fits. The agreement on the average is within 10%.

1-2
INTRODUCTION

There is a strong need for non-intrusive diagnostic

techniques such as passive radiation techniques which utilize

radiation emitted by the plasma or active radiation

techniques such as Laser Induced fluorescence (LIF)

measurements. These techniques are essential to the arc get

flow studies in order to fully understand the nonequilibrium

flow conditions spacecraft encounter during reentry. The arc

jet facilities simulate the spacecraft reentry conditions and

are used for testing thermal protection materials. The

identification, characterization, velocity and temperature

determination of different atomic, molecular and ionic

species makes an important contribution to the arc jet flow

studies. The major species of interest in the spacecraft

reentry flow environment are N2, 92, NO, N2 , N, O, 02 , NO+,

N , O+ and electrons. Concentration of these species change

when the enthalpy of the flow changes. This report is divided

into two parts, one on the analyses of the emission spectra

and the other on the analysis of the LIF data.

Emission studies: During the last couple of years the arc

jet flow diagnostic program at NASA, Johnson Space Center

reported emission studies (Ref.l and 2) of N2 and N2 for

vibrational and rotational temperature determination across

the shock layer. This technique involves calculating the

spectrum for a number of cases and obtain integrals over the

wavelength regions of the spectrum as a function of

temperature. Ratios of these integrals were then related to

the temperatures used to generate the spectra. Spectral

integrals from the measured spectra are then compared with

the calculated values to determine the temperature. This

technique has some limitations and requires numerous

parameters to produce the calculated spectra. This method

requires repetitive calculations be performed each time a

comparison is made. In this report a simpler technique is

presented to find the rotational temperatures of N2 in the

shock layer. This can be applied to other molecules as well.

LIF studies: The LIF measurements reported here probe

different species with a known excitation mechanism using

selective excitation with a narrow band laser. Preliminary

LIF studies of copper are used to calculate the velocity and

temperature are presented here.

MEASUREMENTS

Emission spectra: Details of the experimental set up to

record the emission spectrum of nitrogen in the wavelength

region of 340 run to 480 ran are reported earlier (Ref.3).

1-3
LIF studies on copper: Laser fluorescence spectra of copper

recorded earlier using the experimental setup shown in Fig.l,

are analyzed. The setup essentially consists of a YAG pumped

dye laser system with intracavity etalons in the dye as well

as in the pump laser reducing the dye fundamental band width

to less than 0.08 cm"1. To probe the copper atoms,

Dicynomethylene (DCM) dye is used together with a KD*P

doubling crystal to produce laser light at 327.5 nm. Details

of the laser fluorescence detection and control electronics

along with laser pulse energy used for copper are reported

earlier (Ref.4). Velocity measurements of the free stream for

various mass flow rates and arc currents have been carried

out using copper as the tracer material. The excitation

wavelength is about 327.5 nm (Figs. 2) and the 578 nm

fluorescence is collected at right angles to the flow using

cutoff and narrow band interference filters. Two separate

measurements were taken for Doppler shift studies one with

the laser beam perpendicular and the other at an angle of

60° with respect to the flow direction.

RESULTS AND ANALYSIS

Emission spectra of N2

+: The rotational structure of the 0-

1 band of B-X transition of N2 is shown in Fig. 3. Due to

the limited resolution the P and R branches are not resolved.

In order to analyze and determine the rotational temperature,

we have developed a method described in an earlier report

(Ref.3). For completeness of this report the equations are

shown in Appendix 1 and 2. In order to test the accuracy of

these equations, simulated spectra of N2 using NEQAIR

program under low resolution are produced at various

temperatures. A sample spectra produced at 8000 K is shown in

Fig. 4. We have now used the areas and corrected them for P

and R branches using equations (7) and (8) shown in Appendix

2., at various temperatures (T). Graphs are now plotted: In

[Ipc/(kl+k"+l)] against k1(k'+l) for P-branch and In [

IRc/(k'+lc"+l)] against k1 (k'+l) for R-branch. According to

equation (4) shown in Appendix 1, as given by Herzberg

(Ref.5), the slope of the line gives BQhC/KT from which the

rotational temperature can be determined. The temperatures

(Tp and TR) are now calculated using the slopes of the

straight lines obtained from the graphs for both P and R

branches. The particular set for which the temperature Tp =

TR = T is considered as the rotational temperature. Fig. 5 is

a graph showing the agreement between P and R branches at

8000 K. Table 1 shows the temperatures calculated using the

slopes of the lines at three different temperatures.

This method is now applied to the spectra taken on

February ' 89 at 1.91 cm, 2.54 cm and 3.18 cm positions in

the shock layer of a blunt body . Figs. 6 and 7 shows the

graphs plotted for corrected P and R branch intensities

taking the areas and the results are tabulated in Table - 2.

1-4
The calculated temperatures are slightly less than the

temperatures obtained by Biackweii etal. (Ref. 4) using

computer simulation techniques. This low temperature seems to

be due to the overlap of intensity of some other bands of

the same species or due to the emissions of the species

present in the shock layer in the region analyzed. If an

account can be made for this background intensity rotational

temperatures can be more precisely determined even in

unresolved bands. Work in this direction will be continued in

the future.

LIF studies on copper: A representative spectrum of Doppler

shifted copper spectrum is shown in Fig. 8. The measured

Doppler profiles are used to determine the velocity and

temperature. The velocity is obtained using the relation

V = CAW/ W0 (1)

where V is the velocity of the free stream, C is the speed of

light , W is the measured Doppler shift and W0 is the laser

excitation frequency. A graph of the measured velocity

against bulk enthalpy is shown in Fig. 9 and it demonstrates

the expected increase in velocity with increasing enthalpy.

To determine the temperature, a linear curve fit of the

quadruplet of Gaussian profiles was fit to the measured

profiles. The laser line width was accounted for by folding

its profile with the Doppler profile. Both were taken to be

Gaussian.

The intensity of Gaussian line shape is given by

= I0 exp[ -4 In2 { W0 - W/&W D ) ] (2)

and the Doppler Width &WD is given by

&

WD = wo/c

 ( 8 RT ln2/M)1/2

where

Io = the peak intensity of the Doppler profile

WQ = the frequency at peak intensity

R = gas constant

T = Temperature in Kelvin

M = Mass of copper atom.

Fitted curves at different temperatures are developed

using equation (2) and were overlapped on the experimental

curve. The one that best fits to the experimental curve is

taken to be the temperature at that flow rate. A sample curve

fit using one of the two peaks is shown in Fig. 10. The first

peak is saturated and so only one peak is considered for an

accurate determination of the temperature. Temperatures are

determined using this method at various flow rates and the

results are presented in Table - 3. The results do not

1-5
compare particularly well with the least square fit,

indicating the assumptions used in the simple calculations

are not adequate. More systematic study has to be carried

out and using least square fit Gaussian profiles may yield a

more precise temperature determination. It may be noted that

a Voigt profile (a combination of Gaussian and Lorentzian

profile) may be the appropriate choice for future studies.

CONCLUSIONS

On the basis of the analysis made in both the projects the

following conclusions are made:

1. Rotational temperature measurements can be made within 5%

even in the case of unresolved bands due to a single

species if there is no overlap of other bands.

2. This method can be extended to the observed experimental

spectra, where other species are present provided the

contribution due to the background is accounted for.

3. The method used to find the temperature of Doppler shifted

curves in copper agrees on the average with in 10% with

that obtained using least square fit. The velocity can be

calculated to an accuracy of 10%.

1-6
ACKNOWLEDGMENTS

I wish to take this opportunity to thank NASA/ASEE

summer faculty fellowship program for giving me an

opportunity to work at NASA, Johnson Space center. My sincere

thanks to Dr. Carl Scott and Dr. Sivaram Arepalli for their

constant help and guidance throughout the project period. My

special thanks to Mr. Eric Yuen for providing the manual

curve fit program. I wish to express my thanks to Mr. James

Milhoan, my NASA colleague for providing the facilities and

for continued support. Last but not the least, I wish to

thank all NASA and the Lockheed personnel of the arc jet

facility who made my stay here very pleasant and rewarding.

1-7
REFERENCES

1. Blackwell, H.E., Wierum, F.A., Arepalli, S.and Scott,

C.D., " yibrational measurements of N2 and No shock

layer radiation." 27th Aerospace Sciences Meeting,

AIAA-89-0248, (1989).

2. Blackwell, H.E., Yuen, E., Arepalli, S., and Scott,

C.D., " Nonequilibrium shock layer temperature profiles

from arc jet radiation measurements." 24th

Thermophysics conference, AIAA-89-1679, (1989).

3. Akundi, M.A., " Temperature determination of shock

layer using spectroscopic techniques." NASA summer

faculty report, NGT 44-001-800, PP 1- 17, (1989)

4. Arepalli, S., Yuen, E.H., and Scott, C.D., "

Application of Laser induced fluorescence for flow

diagnostics in arc jets." 5th joint Thermophysics and

Heat transfer conference, AIAA-90-1763,(1990)

5. Herzberg, G., " Molecular Spectra and Molecular

structure, Vol. 1 Spectra of Diatomic Molecules",

D. Van Nostrand Co., Inc., New York, N.Y. (1950).

1-8
Snock Layer

Dllluser •«—

Blunt Body

Fig. JL Experimental setup

2 ,

E

c

in

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m

in

* 2Do

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1/2

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F-2

F-l

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F-1

Fig. 2. Detailed energy level diagram of copper atom

1-9
423.0 424-0 425.0 4Z£.0

Wavelength(rim)

Figure 3.- 0-1 band of Nji B-X system -low resolution

4ZS.O

NLOAIK

UNIT = 16.

NO. OF POINTS INPUT =>

AVERAGE INTERVAL -

20000.0

4 45 4250 425.5 426.0 426.5 427.0 427.5 428.0

WAVELENGTH (NM)

Figure 4.-simulated low resolution spectrum of 0-1 Dana of N£ simulated spectra,80UOK

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Nitrogen Molecular Ion (0,1 )band,3.1 8cm,600amp

P-branch

1000 K

2000 K

3000 K

4000 K

5000 K

6000 K

7000 K

8000 K

9000 K

10000 K

500 1000 1500 2000 2500

Figure 6.-Rotational temperature determination,6337K

Nitrogen Molecular lon(0,1 )band,3.1 8cm,600amp

R —branch

1.000

o1000K

• 2000K

A 3000K

• 5000K

• 6000K

7000K

8000K

100 200 300 400 500 600

Figure 7. —Rotational temperature determination,61 31 K

1-12
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Wovelength(nm)

3000-

2000-

1000-

nFigure 8. -Copper Doppler shift measurements, 700A,0.15lb/s

~ ^>

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f\9/

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0 2000 4000 6000 8000

Enthalpy(Btu/lb)

Figure 9.-Doppler LIF measured velocities in arc jet flows

1E4

.to.

Figure 10.-Copper LIF spectrum and curve fit,300A,0.011b/s,1100K

1-13
TABLE 1.- SIMULATION SPECTRA - COMPARISON

T

(K)

8000

6000

3000

&

7906

6234

3125

%

Error

1.1

3.9

4.2

T

R

(1)

7553

6388

3217

%

Error

5.8

6.5

7.2

TABLE 2.- ROTATIONAL TEMPERATURES OF SHOCK LAYER

Position of

Shock layer

(cm)

(K) Error

T

R

(8) Error

1.91

2.54

3.18

3991

2954

6337

0.4

1.5

5.0

3982

3045

6131

0.2

1.5

2.2

TABLE 3.- COPPER DOPPLER SHIFT DATA

Current Flow Rate Doppler Velocity Temp Enthalpy

(Amps) (lb/s) Shift (m/s) (K) (Btu/lb)

10~3nm Curve least

fit Square

fit

700

500

300

0.

0.

0.

0.

0.

0.

0.

0.

0.

05

10

15

20

25

10

20

10

20

1.

1.

1.

1.

1.

1.

0.

1.

0.

486

500

480

468

519

547

885

232

709

2721

2747

2711

2688

2782

2834

1621

2256

1299

^^^

—1200

1500

— —

1400

1300

1100

600

•»•»

2022

1148

1486

1076

1457

1478

1117

498

7000

5640

4900

4150

3760

4260

3100

2780

1925

1-14
APPENDIX -1

ROTATIONAL TEMPERATURE EQUATIONS

B0 J(J- Dhc

I(P - Branch ) = A - 2 Je

( 1)

KR-branc h ) = A-2(J + l)e

B Q (J+ l)(J + 2)hc

kT (2)

Rearranging equations (1) and (2)

In

L2JJ

"IP "

l_2jj

A '

B0 J(J-l)hc

kT

ln^ (3)

Similarly for R Branch

In

L2U +

B0(J+ l)(J+2)h c

= A<

 kT

(4)

Equation (3) and (4) can general be written for

either case as

= AB'K'(k' + l)hc

kT

where k1 - upper rotational state quantum number

k" - lower rotational state quantum number
APPENDIX - 2

CORRECTED INTENSITIES

EXP R (5)

EXP (6)

Let where and IB are the R

intensities calculated for any temperature

using equations (1) and (2)

I «I

Re EXP Ll + BJ (7)

(85

IRc and Ipc are the intensity contributions

of P and R branches in the observed spectra
N91-2 7

COMPOUND ESTIMATION PROCEDURES IN RELIABILITY

Final Report

NASA/ASEE Summer Faculty Fellowship Program-1990

Johnson Space Center

Prepared By: Ron Barnes , Ph.D.

Academic Rank: Associate Professor

University & Department:

NASA/JSC

Directorate:

Division:

JSC Colleague:

Date Submitted:

Contract Number:

University of HoustonDowntown

Department of Applied

Mathematical Sciences

One Main Street

Houston, Texas 77002

Safety, Reliability and

Quality Assurance

Reliability and

Maintainability

Richard Heydorn, Ph.D.

August 16, 1990

NGT-44-005-803

2-1
ABSTRACT

At NASA, components and subsystems of components in the Shuttle

and Space Station generally go through a number of redesign stages.

While data on failures for various design stages are sometimes

available, the classical procedures for evaluating reliability only

utilize the failure data on the present design stage of the component

or subsystem. Often, few or no failures have been recorded on the

present design stage.

Last Summer, in the NASA Faculty Fellow Program , Bayesian

estimators for the reliability of a single component, conditioned on

the failure data for the present design, were developed. These new

estimators permit NASA to evaluate the reliability, even when few or

indeed no failures have been recorded. Point estimates for the later

evaluation were not possible with the "classical" procedures.

Since different design stages of a component (or subsystem)

generally have a good deal in common, the development of new

statistical procedures for evaluating the reliability, which consider

the entire failure record for all design stages, has great intuitive

appeal.

A typical subsystem consists of a number of different components

and each component has evolved through a number of redesign

stages.

The investigations this Summer considered compound estimation

procedures and related models. Such models permit the statistical

consideration of all design stages of each component and thus

incorporate all the available failure data to obtain estimates for the

reliability of the present version of the component (or subsystem).

A number of models were considered to estimate the reliability of a

component conditioned on its total failure history from two design

stages.

It was determined that reliability estimators for the present design

stage , conditioned on the complete failure history for two design

stages have lower risk than the corresponding estimators

conditioned only on the most recent design failure data.

2-2
Several models were explored and preliminary models involving the

bivariate Poisson distribution and the Consael Process (a bivariate

Poisson process) have been developed. Possible shortcomings of the

models are noted. An example is given to illustrate the procedures.

These investigations are ongoing with the aim of developing

estimators that will extend to components (and subsystems) with

three or more design stages.

2-3
INTRODUCTION

Components in the NASA Shuttle and indeed in many other complex

systems often go through a number of redesign stages. Classical

reliability estimators rely only on the failure data for the present

design. Since previous design stages often have a good deal in

common with the present design, statistical procedures for

estimating reliability may be improved by also taking into account

the failure data on the earlier design versions as well.

Last year in the NASA Summer Faculty Fellow program (SFF),

Bayesian estimators for the expected value of the reliability of a

single component, conditioned on its failure history (for the present

design stage) were developed for the cases of (1) a constant failure

rate - the exponential model and (2) a variable failure rate - Weibull

model [1],[2].

For the constant failure rate model it was shown that:

n+1

E[ R(t)l N(T) = n ] = II (1 +t/T ) (1)

where

R(t) = the reliability or probability that the component will

successfully function up to time t in the future,

N(T) = the number of failures up to time T (in the past failure

history), and

n = the number of failures recorded up to time T for this

component.

These new estimators enable NASA to evaluate reliabilities when

few or even no failures have been recorded. Evaluation in the latter

case was not possible with the previous "classical " estimators.

2-4
In March 1990, these Bayesian estimators were employed along with

the classical estimators in a NASA report on the reliability of Obiter

APU hydraulic hoses [3], Both sets of estimators predicted a very

high reliability for success of the hoses on the next mission (.999..).

This report will focus on investigations to extend the constant failure

rate model to utilize the total failure history on a component with 2

or more design stages. The investigations considered compound

estimation procedures in order to utilize this failure data history.

The report incorporates the Bayesian estimators developed last year

and noted earlier in this report.

Motivation for the Study

Since redesign versions of a component would appear to have some

commonality, the idea of reliability estimators which incorporate the

total failure history of all design stages of a component seems worth

considering. When data occurs, for example, on a number of identical

valves which have been through 2 design stages with the number of

failures on the j-th valve with the first design denoted by Nj: and

the number on the i-th valve with the new design denoted by N2j,

one can plot Nj versus N2 The data often suggest some correlation

between the two failure counts. In general, the number of failures

Nj and N2 are not independent. In the discussion to follow, Nj(Tj)

and N2(T2> the number of failures up to times Tj and T2

recorded for the old and new designs respectively are each assumed

to have a Poisson distribution with possibly different failure rates A j

and ^2 which are unknown. Since Nj(Tj) and ^(T2) are not

assumed to be independent, the problem of obtaining Bayesian

reliability estimators conditioned on the failure data Nj and N2

requires some form of a joint or compound probability distribution

for Ni and No .

i £*

The impact of such estimators that utilize the total failure history

from 2 or more design stages of a component is indicated by the

following result.

2-5
Proposition

), N2(T2))]2 * E[R(t)-E(R(t)l N2(T2))]2

i.e., the estimator conditioned on two stages of failure history has a

lower risk than the corresponding risk for the estimator

conditioned only on the most recent design failure history. Hence as

additional failure data on earlier design stages are included, the

corresponding risk decreases.

Proof

E[R(t)-E(R(t)IN1(T1),N2(T2))]2 =

E[R(t)-E(R(t)IN2(T2))- (E(R(t)IN1(T1),N2(T2))-E(R(t)IN2(T2)))]2 =

E[R(t)-E(R(t)IN2(T2))]2- 2E[(R(t)-E(R(t)IN2(T2))) *

(E(R(t)IN1(T1),N2(T2))-E(R(t)IN2(T2)))] + (2)

E[E(R(t)IN1(T1),N2(T2))-E(R(t)IN2(T2))]2 =

But since

E[(R(t)-E(R(t)IN2(T2)))(E(R(t)IN1(T1),N2(T2))-E(R(t)IN2(T2)))] =

E{E[(R(t)-E(R(t)IN2(T2)))(E(R(t)IN1(T1),N2(T2)) -

E(R(t)IN2(T2)))IN1(T1),N2(T2)] } =

E[E(R(t)IN1(T1),N2(T2))-E(R(t)IN2(T2))]2

then expression (2) becomes

), N2(T2))]2 =

E[R(t)-E(R(t)IN2(T2))]2-E[E(R(t)IN1(T1),N2(T2))-E(R(t)IN2(T2))]2

Since the last term is non-negative the result is established. Note that

this result implies that, if the last term is positive, a strict inequality

holds.

2-6
DISCUSSION

The present investigations have considered two preliminary models

for the distribution of Nj and N2 which lead to reliability estimators.

Model A : Bivariate Poisson Model

The first of these employs the bivariate Poisson distribution.. The

joint probability function for a 2 dimensional Poisson process

(N1(t),N2(t)) with cov( Nj(t),N2(t)) = vt is given in [4] by:

P[N1(t) = n1, N2(t) = n2] = f(n1,n2,t) (3)

where

min(n1, n2)

n2, t) = exp(-X1 t-A2 t + vt)Z ((* i -^)n1 '^2 -^) n2 ' J

j = 0

t

n

1 + n2 - 2J (vtrt/Kr -j)l (n-j)!j! 3 (4).

Note that in the discussion to follow, in place of t in equation (3)

one could use T = T-| + T2 which is the total elapsed time for

failures for both designs. Utilizing expression (4) and Baye's

formula, where X2(t) = 1 denotes that the component in its second

design stage is still operating up to time t, one can show that

E[R(t)IN1(T)=n1,N2(T)=n2] = P[X2(t)=l IN^T^m , N2(T))=n2] =

P[N1(T)=nltN2(T)=n2IX2(t)=l] P[X2(t)=l]/P[ N^T) = n1t N2(T) = n2]

(5)

2-7
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2-8
one can show that the uniform priors, with the limits extended to the

entire first quadrant, give

E[R(t)IN1(T)=n1N2(T)=n2] =

min(n1 , r

[1/0+ t/T)n2-J+1]

J-0

(7)

min(n.|, rv>)

I

= 0

Note that in the case when n1=0 failures one has

E[R(t)IN1(T)=ON2(T)=n2] = e-vt(l/(l+ t/T)n2

+1

 ) (8)

where T is the total elapsed time from the start of the first design.

Notice the similarity of expression (8) to formula (1) developed

previously for the reliability estimator given just the failure data for

the second design.

Also observe that if Nj and N2 are completely independent then

E[R(t)IN1(T)=n1N2(T)=n2] = E[R(t)IN2(T)=n2 ] = !/(!+ t/T)n2

+1

Thus this model would, in some sense, appear to generalize the

earlier model(l) which considered only one design stage.

2-9
Example

As an application of this reliability estimator consider the following

example.

Arbous and Kerrich [5] recorded the number of accidents of 122

individuals (shunters) in two consecutive time periods. For each

individual, the number of accidents in the first 6 year period was

recorded and then after new insurance and safety procedures were

implemented, the number of accidents for the same individual was

recorded in the next 5 years. The authors estimated vT ~ .257 for

the T = 11 years.

One can use expression (7) to evaluate the "reliability" for the next

year of an individual.selected at random, given his/her total past

accident (failure) history. Note that in this case the reliability is just

the probability that a randomly selected individual with the given

accident history will not have an accident in the next t years.

For a randomly selected individual with accident history given by

ni=3 , n2 = 1 , t =1 , vT « .257 , TI = 6, T2 = 5, T = TI + T2=l 1

one finds by using expression (7) that

E[R(t)IN1(ll)=3 N2(H)=1] = .6067624

Thus the reliability estimator obtained from this model suggests that

for a randomly selected individual who experienced 3 accidents in

the first 6 years and 1 in the next 5 years, the probability of no

accidents in the next year is approximately 61 percent. Such

information may be used in the setting of insurance premiums for

the next year for various classes of individuals based on their past

accident histories.

Note that in terms of NASA component reliability:

1. The individuals correspond to different copies of a single

component with two design stages.

2-10
2. Each copy is located in a somewhat similar environment(e.g.

the copies may be located on each of the three space shuttles).

3. Data on failures of each copy were recorded in the first design

stage (i.e. the first 6 years of accident data).

4. A second improved design replaced the first and failures were

recorded.

Then E[R(t)IN1(T1)=n1(N2(T2)=n2 ] gives the probability that the

second design stage with a given failure history in this location will

not fail in the next t time units. Note that the NASA description

assumes that when the component fails it is replaced or repaired so

that it is equivalent to the original system before the failure.

It should be pointed out that in Model A some assumptions about the

relationships between X j ,~\2 , and v were made. In particular,

v<^ p^2

 Su8gests

 that v is related to the priors. With this in mind, a

second preliminary model has been developed.

Model B : Consael Model

As was noted earlier, Nj and N2 are probably not independent in

general. The Consael process [6] defines a bivariate compound

Poisson process by

P[N1(T)=n1N2(T)=n2] =

dAj (9)

2-11
In the Consael process for fixed values of A i and A<> , Ni and N9 A Xr 1 ^

correspond to independent Poisson processes while Aj and /\2>

 nave

a joint density function

If one assumes the triangular density function ( T^- ^i since one

assumes that the newer design is an improvement) one has:

0

for 0 < A i < 9

0< ^2 <

elsewhere

and

(10)

Utilizing expressions (9) and (10) ,and Baye's formula in expression

(6) (and taking limits on the prior distribution) one can again obtain

an estimate for the reliability:

E[R(t)IN1(T)=n1N2(T)=n2]

At the present time investigations are continuing with this estimator

which has a rather complex , highly combinatorial closed form. It is

anticipated that further consideration of this model will indicate

approaches to the development of the general model which can

incorporate failure data from any number of redesign stages .

SUMMARY AND CONCLUSIONS

Various NASA failure data suggests support for the development of

compound/mixture models to estimate the reliability of components

that have failure data recorded on more than one design stage.

Bayesian estimators that can utilize all "relevant" failure data, even

from an earlier design of the component, were investigated.

2-12
A Bayesian estimator based on the bivariate Poisson distribution was

developed and an example illustrating the technique applied to

insurance data was given. The similarity of this example to NASA

reliability problems was also noted.

An additional estimator based on the Consael process was developed.

Investigations into this model are continuing. It is anticipated that

these investigations will lead to a general model to utilize all relevant

failure data on a component (or subsystem of components) that has

experienced more that two design stages.

2-13
CES

1. Heydorn, Richard, unpublished paper "A Bayesian Approach to

Reliability and Confidence," NASA/JSC Reliability and

Maintainability Division, Spring 1989.

2. Barnes, Ron ,"A Bayesian Approach to Reliability and

Confidence", NASA Summer Faculty Fellow Final Report,

August 1989.

3. "A Reliability Assessment of the Orbiter APU Hydraulic Hose",

prepared by NASA/JSC Reliability and Maintatinability

Division, April 1990.

4. Haight, Frank A., Handbook of the Poisson Distribution. John

Wiley and Sons Inc., New York, 1967.

5. Arbous, A. and Kerrich, J. /'Accident Statistics and the Concept

of Accident-Proneness," Biometrics, 7, 340-432, December

1951.

6. Everitt, B.S., and Hand, D.J., Finite Mixture Distributions.

Chapman and Hall, London, 1981.

2-14
BIBLIOGRAPHY

1. Efron,B- and Morris, C. N., "Stein's Estimation Rule and Its

Competitors - An Empirical Bayes Approach," J. Amer. Statist.

Assoc. 68, 117-130, 1973.

2. : , "Stein's Paradox in Statistics,"

Scientific American 236, (5) 119-127, 1977.

3. Haight, Frank A., "Index to the Distributiions of Mathematical

Statistics," Journ. Res. of NBS -B.Math 65B, 1, Jan-Mar. 1961.

4. Heydorn, Richard, and Basu, Rehka, unpublished report

"Estimating Parameters in a Finite Mixture of Probability

Densities"NASA/JSC 1989.

5. Holgate, P. , "Estimates for the Bivariate Poisson Distribution,"

Biometrika 51, 1&2 , 741, 1964.

6. Martz, Harry F. and Waller, Ray A. , Bayesian Reliability

Analysis. John Wiley and Sons Inc., New York, 1982.

7. Stein, Gillian and Juritz, June, "Bivariate Compound Poisson

Distributions," Commun. Statist. - Theory Meth. 16(12), 3591-

3607, 1987.

8 Stigler, Stephen , "The 1988 Neyman Memorial Lecture: A

Galtonian Perspective on Shrinkage," Statistical Science, Vol.5,

No. 1, 147-155, Feb. 1990.

9. Teicher, Henry "On the Multivariate Poisson Distribution,"

Skand. Aktuar. Tidskar. 37, 1-9.

2-15
ACKNOWLEDGEMENTS

The author would like to thank the members of the Reliability and

Maintainability Division of Chief Duane Duston, especially Tom

Edwards and Malcolm Himel. Special thanks also to Mary Gibson and

the staff for their helpful support and assistance.

Finally, thanks to my NASA sponsor, Dr. Richard Heydorn for making

my SFF experiences both stimulating and productive.

2-16
TECHNIQUES FOR DETERMINING TOTAL BODY WATER USING

DEUTERIUM OXIDE

Final Report

NASA/ASEE Summer Faculty Fellowship program-1990

Johnson Space Center

Prepared by:

Academic Rank:

University & Department:

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleague:

Date Submitted:

Contract Number:

Phillip A. Bishop, Ed.D.

Assistant Professor

University of Alabama

Health and Human

Performance Studies

Tuscaloosa, AL 35487

Space and Life Sciences

Medical Sciences

Biomedical Operations and

Research

Helen Lane, Ph. D.

August 27, 1990

NGT-44-005-803

3-1
ABSTRACT

The measurement of total body water (TBW) is fundamental to

the study of body fluid changes consequent to microgravity exposure

or treatment with microgravity countermeasures. Often, the use of

radioactive isotopes is prohibited for safety or other reasons. It was

desired that a safe method of total body water measurement be

selected and implemented for use by some Johnson Space Center

(JSC) laboratories, which permitted serial measurements over a 14

day period which was accurate enough to serve as a criterion method

for validating new techniques. These requirements resulted in the

selection of deuterium oxide dilution as the method of choice for

TBW measurement. This report reviews the development of this

technique at JSC. The recommended dosage, body fluid sampling

techniques, and deuterium assay options are described.

3-2
INTRODUCTION

The measurement of total body water (TBW) is necessary for

studying the response of body fluids to microgravity and

microgravity countermeasures. The measurement of TBW with

deuterium oxide (D2O), has been well studied. This method is safe,

non-radioactive, and potentially very accurate, and is the method of

measuring body water turnover in doubly-labeled water studies of

long-term metabolic rate (Schoeller et al., 1980; Wong et al., 1988;

Schoeller, 1990). By using low doses and measuring the baseline

D2O level, repeated TBW measurements can be made over several

days without compromising subject safety.

DOSAGE

A wide range of D2O dosages have been used in TBW

determinations. The chief limiting factor in determining minimal

dosage is the precision of determination of D2O diluted in a body

fluid sample. Consequently, minimal dosage is a function of the

volume of TBW and the precision of the D2O assay. Minimal dosage

reported in the literature for adults was 1 g (Schoeller et al., 1980).

Such a dosage results in a D2O concentration increase of 29 ppm in a

60 kg female at 20% fat with assumed water fraction of 73% of the

fat free mass or 24 ppm in a 70 kg male with 15% fat. The largest

D2O dosage reported in the literature was 107 g for a 70 kg body

weight male (Nielsen et al., 1971). The natural abundance of D2O in

tap water varies, but is approximately 140-150 ppm (Thomson,

1963; Davis et al., 1987). The body tends to concentrate D2O

slightly, yielding saliva baseline concentrations of about 0.02-0.03

ppm above local levels of ingested water (Halliday and Miller, 1977).

This suggests that a 1 g dose of 99.9% D2O would raise the baseline

value only about 16% for males.

Because many NASA applications require repeated TBW

measurements over 10-13 days, the baseline concentration of D2O

will increase based upon an elimination half-life of about 10 days

(Schloerb, et al., 1950; Schoeller et. al., 1980; Schoeller and Webb,

1984; Wong, et al., 1988; Schoeller, 1990). For maximum accuracy, it

is necessary to minimize baseline levels and maximize D2O

concentration differences between baseline and post dose. This is

accomplished by keeping each dose as small as can be accurately

3-3
150

218

317

349

438

114

114

171

171

228

264

332

488

520

638

76

52

54

49

46

measured after dilution in body fluids. For the purposes of a 13 day

bedrest with requirements to determine TBW before and after a

lower body negative pressure and fluid-loading countermeasure, the

following doses were administered on the days shown:

Estimated D2O Cone, (ppm)*

Pre Dose Post % Increase

Day Dose (grams)

-1 4

5 4

6 6

10 6

1 1 7

* Estimated concentrations for 60 kg subject with 20% fat and 73% of

fat free mass as water.

Total doses=5; total dosage= 27 g.

In cooperation with Dr. Suzanne Fortney of the JSC

Cardiovascular Research Laboratory, this scheduled dosage was

administered to one bed rest subject and six controls. This work is

currently in progress.

Risks

Toxicity of D2O to humans has not been precisely determined,

but it has been used in human research for over 30 years without

reported ill effects. The TD5Q required for reproductive effects in

animals is 840 g/kg weight (Registry of Toxic Effects, 1986). Animal

studies show that D2O concentration must reach 30-35% of total body

water to be lethal. Fusch and Moeller (1988) suggest that D2O

concentrations for short term studies be less than 10 g/ kg of body

water. Schloerb et al. (1950) found no effects in healty or ill

subjects receiving D2O doses of lOOg. Doses in this range far exceed

that normally required for TBW determinations using sensitive

deuterium assay methods.

D2O has been reported to produce nystagmus (Money and

Miles, 1974). In recent studies at Johnson Space Center, a dose of

approximately 200 g for a 70 kg subject was required to produce

symptoms of vestibular impairment in . Therefore, the maximal

total exposure of 28 g is extremely safe.

3-4
FLUID SAMPLING

One of the advantages of D2O measurement of TBW, is that

serum, urine, respiratory water,and saliva have all been used

successfully in the technique. For convenience, safety, and

requirements for non-invasive methods for space flight, saliva

sampling is reviewed as a recommended fluid sampling technique.

The D2O method requires an initial fluid sample to determine

baseline D2O levels. This can be collected by having the subject

expectorate into a small vial. Only approximately 2 ml of saliva is

needed, but a capped 5-10 ml vial such as the Sarstedt saliva

collection kit used at JSC is convenient to use. It is important that

the subject refrain from eating or drinking for 2 hours prior to saliva

sampling as the potential exists for obtaining saliva diluted with

ingested fluid. Food or drink ingested immediately prior to or

following D2O dosing may retard equilibration of D2O with body

water. D2O doses should be weighed to the nearest milligram or

better in order to maintain overall precision in the ppm range

(Schoeller et al., 1980). Because the doses are small, care must be

taken to ensure the subject does not lose any of the deuterium. This

is accomplished by rinsing the dose vial with at least half its volume

of deionized water and having the subject ingest the rinse water.

This rinsing is done twice (Thomson, 1963). Equilibration has been

found to take about three hours in resting subjects (Schloerb, et al.,

1950; Schoeller et al., 1980; Lukaski and Johnson, 1985; Wong et al.,

1988). During the equilibration period, no food or drink should be

taken. Since any D2O lost must be accounted for in TBW

determinations, urine voids during this time must be sampled for

D2O concentration and the volume recorded to adjust for this loss.

Halliday and Miller (1977) have reported that fractionation results

in unequal distributions of D2O in the baseline samples with urine,

plasma, serum, and saliva, all showing concentrations higher than

local drinking water and respiratory water vapor showing lower

baseline concentrations. Fractionation occurs because the heat of

vaporization is 3%, and the heat of fusion is 5.5%, higher in D2O

compared to H2O (Thomson, 1963). Hence, baseline and

equilibration samples should be drawn from the same type of fluid.

3-5
DEUTERIUM ASSAY

Methods for deuterium assay include, infrared

spectrophotometry, gas chromatography, and radio-isotope ratio

mass spectroscopy ( Graystone, et al., 1967; Thomson, 1963). Other

methods include freezing point depression,( Reaser and Burch, 1958),

near-infrared spectrophotometry, refractometry, and falling-drop,

(Thomson, 1963); however, these methods are not sufficiently

accurate for the dilutions used in our applications and will not be

discussed.

Infrared spectrophotometry

Infared spectrophotometry has been used extensively in

assaying D2O. It requires careful and laborious sample preparation.

Lukaski and Johnson (1985) tested the recovery of plasma and urine

using several treatment protocols. Chemical precipitation of proteins

with copper sulfate, cadmium chloride, feric chloride, mercuric

chloride, and stannous chloride and treatment with activated

charcoal all yielded either turbid supernatants, or supernatants could

not be recovered. Only vacuum sublimation or distillation yielded

high recoveries. Turner et al. (1960) and Fusch and Moeller (1988)

used vacuum distillation in which liquid samples were processed at

pressures of 0.05 to 1 mmHg with the vapor subsequently refrozen

in liquid nitrogen or dry ice and isopropanol. Stansell and Mojica,

(1968) used distillation (under atmospheric pressure) with

condensate collected in a water-cooled tube.

Davis et al. (1987) used diffusion in Conway dishes to obtain

clean samples. The diffusion technique is simpler than most other

sample cleansing methods, but it may be inaccurate due to

fractionation between D2O and H2O (Wong and Klein, 1986). Also

accuracy diminishes because the actual concentrations measured are

halved in this method. Volumetric errors in either the sample or the

H2O are possible, and to be exact, the saliva water volume (rather

than saliva volume) should be matched to the H2O volume.

Additionally, the diffusion method would be very laborious for a

large number of samples.

3-6
For potential use in JSC laboratories, a vacuum distillation

system was constructed and tested. Approximately 2 ml of

unpurified sample was placed in a stoppered sample tube connected

with a small plastic three-way valve to a 7 ml vacutainer with twoinch pieces of tygon tubing. Both the sample tube and the

vacutainer were initially heated to approximately 45°C in a water

bath. Vacuum was then applied to both tubes via the three-way

valve with a Dayton (l/4hp) vacuum pump. The stopcock was then

turned to seal off the vacuum side and maintain a vacuum in the

two-tube system. The sample tube and vacutainer were then

allowed to cool to room temperature before the vacutainer was

placed in an acetone-dry ice mixture. Failure to allow the sample to

cool before chilling the vacutainer lowered the system pressure too

low, resulting in boil-over of the sample which contaminated the

vacutainer. After a few minutes, water vapor evolving from the

sample raised the pressure sufficiently to allow returning the sample

to the water bath. The sample then distilled over several hours

until the sample was reduced to dryness. It is important that the

sample be dryed because D2O fractionates at a higher temperature

than H2O resulting in an artificially low D2O concentration if

vaporization is incomplete (Thomson, 1963).

Spectroscopic analysis of the O-D vibrational band at 2500

cm'l (3.98 nm) is conducted with either a single beam fixed-filter

(Lukaski and Johnson, 1985; Stansell and Mojica, 1968) or a dual

beam ( Turner et al., 1960) spectrophotometer in a calcium flouride

cell Thermostated at 15 or 20 °C (Lukaski and Johnson, 1985) or 30

and 48 °C (Stansell and Mojica, 1968) for sample and reference cells,

respectively. For single beam machines, deionized water is used as

the zero reference. Between samples, some investigators cleaned

the cell with dry nitrogen, (Lukaski and Johnson, 1985) whereas

others did not (Stansell and Mojica, 1968). Davis et al. (1987) were

able to measure down to 30 ppm. Reported precision of the single

beam method is 2.5% (Lukaski and Johnson, 1985).

Gas chromatography

The gas chromatography (GC) analysis for D2O requires

minimal sample preparation. A 50 microliter sample is injected

into an evacuated column containing calcium hydride (Arnet and

3-7
Duggleby, 1963; Wong and Klein, 1986). Protium and deuterium gas

evolves and is injected through a 7 or 8 port valve, into a

chromatograph equipped with a 5-20 ml sample loop. The gas is

then passed through a 1 meter long activated charcoal column held

at room temperature, where the hydrogen is cleaned further. From

the column, the gas passes to the detector where the difference in

thermal conductivity between the deuterium enriched gas from the

sample, and the hydrogen carrier gas is measured with a thermal

conductivity cell thermostated at 100°C (Arnet and Duggleby, 1963).

The thermal detector cell voltage is output to a recorder. Any

deuterium in the carrier gas is zeroed out during set-up. The peak

height is measured or better, the area under the curve is integrated

to measure concentration relative to known standards.

Mendez et al., (1970) examined the methodology of GC analysis

and found it to be as accurate as infrared analysis at a concentration

of 1085 ppm (0.12% w/v). They also examined vacuum sublimation

and found it did not significantly improve the accuracy or precision

of the analysis. In fact, both untreated and vacuum distilled saliva

produced exactly the same mean and standard deviation for 11

samples at a concentration of 1356 ppm (0.15%). Duplicate samples

showed very high test-retest means, differing by 1 ppm at 1175

ppm (0.13%). Mean recovery in urine samples was 99.3%.

Ratio-isotope mass spectroscopy

Ratio-isotope mass spectroscopy is the most common method of

measuring deuterium concentrations in studies which use doublylabeled water to measure metabolic rate. D2O is assayed because

the doubly labelled water technique requires that O18 respiratory

turnover be adjusted for water losses of O18. In this method, the

fluid sample is treated with a hot reactive metal such as uranium or

zinc, thereby liberating gaseous hydrogen. The deuterium and

protium evolved are then measured on a mass spectrometer

configured for deuterium/protium analysis. This method can

measure very low concentrations of deuterium. The chief

disadvantages of this technique is the very intricate labware

required for sample preparation and the expense of the mass

spectrometer. Currently the Planetary Sciences Division of JSC is

setting up the procedure to use this method and this would be a

desirable technique for D20 determination when completed.

3-8
CALCULATIONS

The dilution volume determined by the D2O procedure actually

represents hydrogen volume rather than water volume. Evidence

from animal studies suggests that hydrogen space over-estimates

water space by 2-6 percent (Wong et al., 1988; Schoeller, 1990).

Therefore, hydrogen space should be adjusted by about 04% to

obtain the most accurate TBW value. This is most readily

accomplished by dividing the D2 dilution space values by 1.04

(Schoeller, 1990).

In general, the equation used is:

D2 dilution space = (volume D2O ingested- volume excreted)

final D2O equilibrium concentration

When isotope ratio mass spectrometry is used, the asssay

results are expressed relative to a standard, usually a seawater or

precipitation standard such as standard mean ocean water (SMOW)

or standard light arctic precipitation (SLAP). The formula utilized

for calculating TBW is:

D2 dilution space=(d/MW)*(APE/100)*(18:02/(Rstd*delta D2O))

Where:

d=dose of D2O

MW=molecular weight

APE- atom percent excess of deuterium

Rstd= ratio of deuterium to hydrogen in the standard

Delta= increase between baseline and post-ingestion samples

(Dempsey et al., 1984).

The formula provided by Halliday and Miller, (1977) is one of the

most comprehensive:

D2 dilution space (kg)=(Dfd*De)/[(p-x)*1000]

Where:

De= (A-C(y-x))/Df

Where:

3-9
Df=D2O concentration of administered D2O

x=ppm D2O of baseline fluid sample

p=ppm D2O of equilibrated fluid sample

A=weight of D2O dose administered

C=weight of deuterium passed in urine

y=ppm in excreted urine

Weight-volume doses can be converted to volume/volume by

correcting for the density of D2O which is 1.105 at 25°C (Thomson,

1963).

SUMMARY

D2O dilution techniques offer a safe, well-tested method of

determining TBW. Saliva, which may be easily and safely collected,

serves as a suitable body fluid sample. Numerous options are

available for deuterium assay. JSC laboratories have potential access

to GC and isotope-ratio mass spectroscopy, but neither method is

currently operational.

3-10
JCES

Arnet, E. M. and Duggleby, P.M.: A rapid and simple method of

deuterium determination. Anal. Chem. 35, 1420-1424, 1963.

Davis, J.M; Lamb, D.R.; Burgess, W.A.; and Bartoli, W.P.: Accumulation

of deuterium oxide in body fluids after ingestion of D2O-labeled

beverages. J. Appl. Physiol. 63(5):2060-2066, 1987.

Dempsey, D.T.; Crosby, L.O. Lusk, E.; Oberlander, J.L.; Pertschuk, M.J.;

and Mullen, J.L.: Total body water and total body potassium in

anorexia nervosa. Am. J. Clin. Nutr. 40:260-269, 1984.

Fusch, Ch.; and Moeller, H.: Measurement of D2O concentrations at

tracer levels in small samples obtained from paediatric patients. J.

Clin. Chem. Clin. Biochem. 26:715-721, 1988.

Graystone, J., Seitchik, J., Milch, R., Shulman, G. P., and Cheek, D.B.:

Measurement of D2O in plasma water by freezing point elevation,

falling drop, infra-red absorption, and gas chromatography. J. Lab

Clin. Med. 69:885-892, 1967.

Halliday, D., and Miller, A.G.: Precise measurement of total body

water using trace quantities of deuterium oxide. Biomed. Mass

Spect. 4(2); 82-87, 1977.

Lukaski, H.C.; and Johnson, P.E.: A simple inexpensive method of

determining total body water using a tracer dose of D2O and infrared

absorption of biological fluids. Am. J. Clin. nutr. 41:363-370, 1985.

Mendez, J.; Prokop, E.; Picon-Reategui, E.; Akers, R.; and Buskirk, E.R.:

Total body water by D2O dilution using saliva samples and gas

chromatography. J. Appl. Physiol. 28(3):354-357, 1970.

Money, K.C., and Miles, W.E.: Heavy water nystagmus and effects of

alcohol, Nature, 247, 404-405, 1974.

Moore, F.D.: Determination of total body water and solids with

isotopes. Science, 104: 157-160, 1946.

3-11
Nielsen, W.C.; Kryzywicki, H.J.; Johnson, H.L.; and Consolazio, C.F.: Use

and evaluation of gas chromatography for determination of

deuterium in body fluids, J. Appl. Physiol. 31(6):957-961, 1971.

Registry of Toxic Effects of Chemical, 1985-1986, Vol. 5, D.V. Sweet,

ed., DHHS, Washington,1987, p 5108.

Reaser, P.B., and Burch, G.E.: Determiantion of deuterium oxide in

water by measurement of freezing point. Science, 128:415-416,

1958.

Schoeller, D.A., van Santen, E., Peterson, D.W., Dietz, W., Jaspan, J.,

Klein, P.D.: Total body water meassurement in humans with O18 and

H2 labeled water. Am. J. Clin. Nutr. 33:2686, 1980.

Schoeller, D.A., and Webb, P.: Five day comparison of the doubly

labeled water method with respiratory gas exchange Am. J. Clin.

Nutr., 40: 153-158, 1984.

Schoeller, D.A.: Isotope dilution methods, in Obesity, Bjornthorp ed.

Lippincott, In Press, 1990.

Schloerb, P.R., Friis-Hansen, B.J., Edeleman, I.S., Solomon, A.K., and

Moore, F.D.: The measurement of total body water in the human

subject by deuterium oxide dilution J. Clin. Lab. Invest. 29:1296-

1310, 1950.

Stansell, M.J.; and Mojica, L.: Determination of body water content

using trace levels of deuterium oxide and infrared

spectrophotometry. Clin. Chem. 14(11): 1112-1124.

Thomson, J.F.: Biological effects of deuterium. Pergamon Press, N.Y.,

1963.

Turner, M.D.; Neeley, W.A.; and Hardy, J.D.: Rapid determination of

deuterium in biological fluids. J. Appl. Physiol. 15:309-310, 1960.

Wong, W.W., and Klein, P.D.: A review of techniques for preparation

of biological samples for mass spectrometry measurement of

hydrogen2/ hydrogen 1 and oxygenlS/ oxygen 16 isotope ratios.

Mass Spec. Reviews, 5: 313-342, 1986.

3-12
Wong, W.W., Cochran, W.J., Klish, W.J. Smith, E.O.B., Lee, L.S., Klein,

P.D.: In vivo isotope-fractionation factors and measurement of

deuterium- and oxygen 18- dilution spaces from plasma, urine,

saliva, respiratory water vapor, and carbon dioxide. Am. J. Clin. Nutr.

47:1, 1988.

3-13
MATHEMATICAL MODELING OF THE FLOW FIELD AND PARTICLE MOTION

IN A ROTATING BIOREACTOR AT UNIT GRAVITY AND MICROGRAVITY

Final Report

NASA/ASEE Summer Faculty Fellowship Program 1990

Johnson Space Center

Prepared by.

Academic Rank:

University & Department:

Ernest J. Boyd, Ph.D.

Associate Professor

Mankato State University

Department of Mathematics, Astronomy & Statistics

Mankato, Minnesota 56002-8400

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleague:

Date Submitted:

Contract Number:

Space and Life Sciences

Medical Sciences

Biomedical Operations & Research

Steve Gonda, Ph.D.

August 23,1990

NGT-44-005-803

4-1
ABSTRACT

The biotechnology group at NASA Johnson Space Center is developing systems for

culturing mammalian cells that simulate some aspects of microgravity and provide a low

shear environment for microgravity-based studies on suspension and anchorage-dependent

cells. The design of these vessels for culturing cells is based on the need to suspend cells

and aggregates of cells and microcarrier beads continually in the culturing medium. The

design must also provide sufficient circulation for adequate mass transfer of nutrients to the

cells and minimize the total force on the cells. Forces, resulting from sources such as

hydrodynamic fluid shear and collisions of cells and walls of the vessels, may damage

delicate cells and degrade the formation of three-dimensional structures. This study

examines one particular design in both unit gravity and microgravity based on two

concentric cylinders rotating in the same direction at different speeds to create a Couette

flow between them. The study presents a numerical simulation for the flow field and the

trajectories of particles in the vessel. The flow field for the circulation of the culturing

medium is modelled by the Navier-Stokes equations. The forces on a particle are assumed

to be drag from the fluid's circulation, buoyancy from the gravitational force and

centrifugal force from the rotation of the vessel. The problem requires first solving the

system of partial differential equations for the fluid flow by a finite difference method and

then solving the system of ordinary differential equations for the trajectories by Gear's stiff

method. Results of the study indicate that the trajectories in unit gravity and microgravity

are very similar except for small spatial deviations on the fast time scale in unit gravity.

The total force per unit cross-sectional area on a particle in microgravity, however, is

significantly smaller than the corresponding value in unit gravity, which is also smaller than

anticipated. Hence, this study indicates that this design for a bioreactor with optimal rates

of rotation can provide a good environment for culturing cells in microgravity with

adequate circulation and minimal force on the cells.

4-2
The biotechnology group at NASA Johnson Space Center is developing rotating

cylindrical bioreactors for culturing anchorage-dependent mammalian cells on microcarrier

beads. The design of the vessels is motivated by the need to keep the aggregates of cells

and microcarriers suspended in the culturing medium, to provide sufficient circulation for

adequate mass transfer of nutrients to the cells and to minimize the forces on the cells.

These forces, resulting from sources such as hydrodynamic fluid shear and collisions of

cells and walls of the vessels, may damage delicate cells and degrade the formation of

three-dimensional structures. Several studies, such as the research reported by Cherry and

Papoutsakis (refs. 1 and 2) and by Croughan, Hamel and Wang (refs. 3 and 4), have

examined ways to quantitate the hydrodynamic effects damaging the cells. However, these

reports do not consider the complete dynamics of a particle's motion relative to the fluid.

The purposes of this study are to develop a mathematical simulation of a particle's motion

and to calculate the total force on a particle suspended in a rotating cylindrical bioreactor.

To begin this study a simple geometry for the vessel was chosen in order to provide a

uniform flow field throughout the vessel. The vessel consists of two concentric cylinders

both 11 cm long with the outer cylinder having a radius of rQ = 4.0 cm and rotating at Q)Q

rprn's, while the inner cylinder has a radius of r = 2.86 cm and rotating in the same

direction at 0). rpm's. This narrow gap of 1.14 cm between the cylinders is completely

filled with culturing medium into which particles as aggregates of cells and microcarrier

beads are introduced. Figure 1 provides a schematic representation of the vessel.

Cylindrical coordinates (r, 9, z) will be used to indicate positions within the vessel where r

is the radial component outward relative to the cylinders with r. < r < r , 6 is the angular

component measured positively in the direction of rotation of the two cylinders, and z is the

axial direction oriented horizontally in a gravitational field with 0 < z < 11. Mathematical

simulations of more complex geometries, including perfusion of culturing medium, are

being planned.

Gravity

Figure 1.- Schematic representation of the rotating bioreactor.

Assumptions for this mathematical simulation are:

1. The culturing medium is a Newtonian fluid with constant density p measured in

gr/cm3 and constant viscosity \L measured in gr/cm sec;

4-3
2 . Particles are spherical in shape with diameter d measured in cm and density p

measured in gr/cm3, do not interact with one another, and do not affect the flow of

the culturing medium;

3 . The flow of the culturing medium caused by the rotation of the concentric cylinders

is a laminar, axially symmetric Couette flow and is modeled by the Navier-Stokes

equations; and

4. The forces acting on a particle are drag from the fluid's circulation, buoyancy from

the gravitational force relative to the difference between the densities of a particle

and the fluid, and centrifugal force from the rotation of the vessel.

If (u, v, w) represent the (radial, circumferential, axial) components of the velocity of

the flow field measured in cm/sec, then the equations for the flow field are:

(1) r

 dr

_i£ = .C-|V U--Kr2

(3) Dv.MV= ^_f v 2 JL'

W Df r ps v

and

(4) Dr ps

 z ps

where

D_= <L+ U <L + W<L

Dt 3r dr 3z

9z2

f\

and P is the fluid pressure measured in gr/cm sec . Note that axial symmetry implies that

all derivatives with respect to 6 in the Navier-Stokes equations are zero. Boundary

conditions for the flow field are the standard constraints of no slip and no penetration.

The equations for a trajectory of a particle are:

(5) m<L£=. a \QIL. u )-pgco s

dr2

(6)

dr2

and

4.4
(7)

d/2

where m = p 7KT/6, a = 37zrf/A /? = (p - ps)nd /6 and g is the acceleration due to gravity

measured in cm/sec . In this study initial conditions for a particle at r = 0 are r = 3, 6 = 0,

z = 1, 2.5, 4, 7, 8.5 or 10, and the derivatives are all zero.

The values of the parameters for this study are d = 0.0175 cm, ps = 1.02 gr/cm3, p =

•3 "

1.04 gr/cnr, and // = 0.0097 gr/cm sec. These values are approximately correct for the

type of medium and microcarrier beads being used by the biotechnology group at NASA

Johnson Space Center. Preliminary studies consist of four trials using different rotating

speeds a>^ and O)Q for the inner and outer cylinders. The speeds are listed in Table 1 below.

These values provide numerical results from which optimal rotating speeds hopefully may

be estimated.

TABLE 1.- SPEED OF ROTATION IN RPM'S.

Trial Inner Cylinder, cot Outer Cylinder, COQ Differential Rate

1 24 18 6

2 30 18 12

3 36 18 18

4 36 12 24

Dr. Yowmin David Tsao at NASA Johnson Space Center used a semi-implicit finite

difference algorithm employing a hybrid scheme developed by Spalding (ref. 5) to compute

the values of (u, v, w) from the system of partial differential equations in Equations 1-4

on a discrete grid. The grid has 61 subdivisions in the z-direction and ten subdivisions in

the r-direction. Since the flow field is axially symmetric, it can be projected into this

rectangular region of the (z, r)-plane. Note that v is closely approximated by the standard

formula for Couette flow (ref. 6):

(8) v = —-L-rlob^-QJiifJ--^-(fflb-QJi)

with 6*j and Q)Q measured in radians. The finite difference program was advanced in time t

until a steady-state flow was assumed to be reached. This data for the numerical values of

the flow field on the rectangular grid was provided to the author, who used linear

interpolation to produce an approximation to the complete, steady-state, axially symmetric

flow field for (u, v, w) as functions of (r, z).

Figures 2-5 show segments of the secondary flow fields for the four trials. Printed

along each streamline is the circulation time in seconds computed for the segment plotted in

the (z, r)-plane. Circulation is a two-compartmental flow with counterclockwise circulation

in the left half and clockwise circulation in the right half. A Runge-Kutta-Fehlberg

numerical method (ref. 7) was used to generate the streamlines by solving dr/dr = u(r, z)

and dz/d/ = w(r, z). However, the zero boundary conditions along the walls of the vessel

and the limitations in numerical accuracy due to the linear interpolation of the data for the

flow field prevent the complete circulation from being plotted along streamlines in the

neighborhoods of the end walls of the vessel. In these narrow regions circulation will be

4-5
4.0

O

00

X

3.62 -

3.24

2.86

2.75 5.5 8.25

Z AXIS (CM)

11.0

Figure 2.- Streamlines in the zr - plane for Trial 1

with the outer cylinder rotating at 18 rpm and the inner cylinder rotating at 24 rpm.

4.0

3.62 -

00

X

3.24 -

2.86

2.75 5.5

Z AXIS (CM)

8.25 11.0

Figure 3.- Streamlines in the zr - plane for Trial 2

with the outer cylinder rotating at 18 rpm and the inner cylinder rotating at 30 rpm.

4-6
4.0

o

to

X

<

a:

3.62

3.24

2.86

2.75 5.5 8.25

Z AXIS (CM)

11.0

Figure 4.- Streamlines in the zr - plane for Trial 3

with the outer cylinder rotating at 18 rpm and the inner cylinder rotating at 36 rpm.

O

X

3.62

3.24

2.86

0.0 2.75 8.25 11.0

Z 'AXIS (CM)

Figure 5.- Streamlines in the zr - plane for Trial 4

with the outer cylinder rotating at 12 rpm and the inner cylinder rotating at 36 rpm.

4-7
very slow since u and w are close to zero. These figures indicate that there may be some

concern about poor circulation in the middle of the vessel. For instance, Trial 1 shows

circulation time approximately equal to two hours, while increasing rpm's in Trial 4 shows

circulation time decreases to approximately fifteen minutes. Higher differential rates of

rotation will create a stronger secondary flow, but more studies are needed to determine

what rate allows adequate time for mixing of the nutrient supply relative to the cells'

metabolic requirements.

The streamlines are important for studies of mass transfer of nutrients and cellular

waste products, but they do not represent the trajectories of particles as aggregates of cells

and microcarrier beads. Equations 5-7 must be solved for the trajectories given the

steady-state values of (u, v, w). This initial value problem is a two time-scale, threedimensional, second order system of ordinary differential equations. The two time scales

in this problem come from the large difference between the rate of rotation and the rate of

circulation in the secondary flow. The fast time scale for the rotation of the vessel at

approximately 20 rpm's is on the order of seconds, while the slow time scale for the

circulation of the flow is on the order of minutes to hours as indicated above. Being a two

time-scale problem, Equations 5-7 give a stiff system of ordinary differential equations

with a 6 x 6 Jacobian matrix having at least two large eigenvalues and at least two small

eigenvalues. Therefore, Gear's stiff method (ref. 8) was used to calculate trajectories.

In each of the four trials six trajectories are plotted in Figures 6 - 9 at unit gravity (g =

f\ ry

980 cm/sec ) and in Figures 10 -13 at microgravity (g = .0980 cm/sec ). The initial

conditions for these six trajectories are r = 3, 6= 0, z = 1,2.5, 4, 7, 8.5 and 10,

respectively, with all first derivatives initially equal to zero. These figures show that a

particle does not follow the streamlines precisely, but instead migrates across streamlines.

If a particle is within a region of strong circulation, then it does complete its own cycle and

remain suspended in the fluid. However, in most regions of the vessel a particle will not

remain suspended and will hit either the wall of the outer cylinder or an end wall.

Computation of a trajectory was terminated at a time when either it completed one cycle or it

hit a wall of the vessel. The total lengths of time for trajectories are listed in Tables 2-5.

In Trial 1 particles were taking more than twenty minutes to migrate to a wall of the vessel,

while in Trial 4 this time frame was reduced to less than nine minutes. There is no

appreciable difference in the time frames between unit gravity and microgravity. Thus

higher differential rates of rotation do provide stronger circulation, but also appear to

increase the frequency of interactions between the particles and the walls of the vessel. It is

hypothesized that these interactions cause significant damage to the cells. Further analysis

is required to quantitate the amount of damage incurred from a collision with a wall and to

determine the response in a particle's trajectory afterwards.

The most noticable difference between trajectories in unit gravity and microgravity are

the small, rapid oscillations in unit gravity shown in Figures 6-9, but lacking in Figures

10 - 13. These oscillations, which give the particles the appearance of tumbling, occur

once every revolution of the flow field within the vessel and have amplitudes on the order

of 0.02 cm. Figure 14 shows one example of these small deviations in the r-direction for

sixty seconds. The amplitudes of these oscillations increase as r increases, since the outer

cylinder is rotating slower than the inner cylinder, but are uniform in the z-direction.

Intuitively, one can say that these oscillations represent a deviation in the trajectory at unit

gravity from the trajectory at microgravity due to sedimentation downward in a stronger

gravitational field.

The major advantage in using dynamic modeling in this study is the ability to calculate

the total force on a particle as a function of time. Traditional studies have looked at fluid

4-8
4.0 -r

O

CO

X

<

cr

3.62 -

3.24 -

2.86

2.75 5.5 8.25

Z AXIS (CM)

Figure 6.- Trajectories in the zr - plane for Trial 1

with a particle measuring 175 [an in diameter at unit gravity.

4.0-r

3.62 -

00

X

3.24 H

2.86

0.0 2.75 5.5

Z AXIS (CM)

8.25

Figure 7.- Trajectories in the zr - plane for Trial 2

with a particle measuring 175 |im in diameter at unit gravity.

11.0

11.0

4-9
4.0

O

CO

X

<

or

3.62 H

3.24 H

2.86

2-75 5^5 8.25 11.0

Z AXIS (CM)

Figure 8.- Trajectories in the zr - plane for Trial 3

with a particle measuring 175 Jim in diameter at unit gravity.

4.0

O

CO

X

3.62 H

3.24 H

2.86

0.0 2.75 5.5 8.25

Z AXIS (CM)

Figure 9.- Trajectories in the zr - plane for Trial 4

with a particle measuring 175 (am in diameter at unit gravity.

11.0

4-10
4.0

O

00

X

<

cr

3.62 -

3.24

2.86

0.0 2.75 5.5 8.25

Z AXIS (CM)

Figure 10.- Trajectories in the zr - plane for Trial 1

with a particle measuring 175 \im in diameter at microgravity.

4.0

CJ

CO

X

3.24-

2.86

0.0 2.75 5.5 8.25

Z AXIS (CM)

Figure 11.- Trajectories in the zr - plane for Trial 2

with a particle measuring 175 urn in diameter at microgravity.

1 1.0

11.0

4-11
4.0

3.62 -

CO

X

<

o:

3.24-

2.86

2.75 5.5

Z AXIS (CM)

8.25

Figure 12.- Trajectories in the zr - plane for Trial 3

with a particle measuring 175 ^im in diameter at microgravity.

4.0-r

O

(S)

X

<

CL

3.62

3.24 -

2.86

2.75 5.5 8.25

Z AXIS (CM)

Figure 13.- Trajectories in the zr - plane for Trial 4

with a particle measuring 175 ^ini in diameter at microgravity.

11.0

11.0

4-12
4.0

O

3.62 -

ct:

3.24 -

2.86

0.0 15.0 30.0

TIME (SEC)

45.0 60.0

Figure 14.- Three trajectories from Trial 1

showing the r - component for sixty seconds with inital values of 6 = 0 and z = 1.

shear and drag induced by sedimentation in terms that do not reflect the dynamical response

by a particle to the sum of all forces. Traditionally, from Formula 8 fluid shear relative to

the cross-sectional area of a particle measured in dyne/cm is given by

which is between 0.08 and 0.4 for the trials in this study. Drag as a force per unit crosssectional area induced by sedimentation is

where v is the terminal velocity of a particle and the drag coefficient CD depends on the

Reynolds number (ref. 9). For the trials at unit gravity in this study, drag is between 0.5

and 1.0 dyne/cm2. The question to be answered is whether or not these values indicate the

magnitude of the force on a particle in real time. In this study the total force per unit crosssectional area on a particle can be computed in real time by calculating the vector norm of

the sum of the forces in Equations 5 - 7 divided by the cross-sectional area, ltd /4, of a

particle. The maximum values and the average values over time for the total force are listed

in Tables 2 - 5 for each of the six trajectories in each of the four trials at both unit gravity

4-13
f\

and microgravity. The average force ranges from 0.0005 to 0.002 dyne/cm in unit gravity

f\ ^^

and from 0.00003 to 0.0007 dyne/cm in microgravity. The maximum force ranges from

0.002 to 0.013 dyne/cm2 in unit gravity and from 0.0001 to 0.01 dyne/cm2 in

microgravity. In unit gravity drag and buoyancy seem to balance each other at

f\

approximately 0.2 - 0.4 dyne/cm , while centrifugal force is much smaller at approximately

f\

0.004 - 0.007 dyne/cm . In microgravity the same effect is observed, but here drag and

centrifugal force seem to balance each other at approximately 0.004 - 0.007 dyne/cm2,

while buoyancy is much smaller at approximately 0.00002 - 0.00004 dyne/cm2. In

general, the force on a particle in microgravity is an order of magnitude smaller than the

force on a particle in unit gravity. Figures 15 and 16 show profiles in time of the force per

unit cross-sectional area for sample trajectories. All of the trajectories in this study show

similar profiles. Note in Figure 16 the significant increase in force experienced by the

particle during the time when it is close to the end wall indicating that any damage done to

the cells would most likely occur when the particle is in the neighborhood of a wall of the

vessel.

TABLE 2.- RESULTS ON TRAJECTORIES IN TRIAL 1 AT 6 RPM DIFFERENTIAL.

Initial

Z-coord

(cm)

1.0

2.5

4.0

7.0

8.5

10.0

Time

(sec)

1000

1335

1356

1356

1339

1000

Unit gravity

Average

Force

(dyne/cm2)

.0006

.0005

.0005

.0005

.0005

.0006

Maximum

Force

(dyne/cnr)

.0029

.0026

.0016

.0018

.0016

.0029

Time

(sec)

1000

1368

1389

1387

1371

950

Microgravity

Average

Force

(dyne/crrO

.00005

.00004

.00004

.00003

.00004

.00006

Maximum

Force

(dyne/cm ;

.0003

.0001

.0003

.0002

.0003

.0007

TABLE 3.- RESULTS ON TRAJECTORIES IN TRIAL 2 AT 12 RPM DIFFERENTIAL.

Initial

Z-coord

(cm)

1.0

2.5

4.0

7.0

8.5

10.0

Time

(sec)

430

930

980

977

1000

400

Unit gravity

Average

Force

(dyne/cnr)

.0009

.0007

.0007

.0007

.0007

.0010

Maximum

Force

(dyne/cirr)

.0046

.0020

.0026

.0029

.0022

.0029

Time

(sec)

430

960

1013

1010

1160

430

Microgravity

Average

Force

(dyne/cnr)

.00013

.00005

.00005

.00005

.00006

.00013

Maximum

Force

(dyne/cnO

.0014

.0002

.0002

.0003

.0003

.0014

4-14
TABLE 4.- RESULTS ON TRAJECTORIES IN TRIAL 3 AT 18 RPM DIFFERENTIAL.

Initial

Z-coond

(cm)

1.0

2.5

4.0

7.0

8.5

10.0

Time

(sec)

270

905

765

751

684

250

Unit gravity

Average

Force

(dyne/cnr)

.0014

.0010

.0010

.0010

.0011

.0014

Maximum

Force

(dyne/cnr)

.0048

.0026

.0032

.0024

.0083

.0048

Time

(sec)

275

894

845

832

736

9265

Microgravity

Average

Force

(dyne/cm2)

.00028

.00010

.00009

.00009

.00015

.00028

Maximum

Force

(dyne/crrn

.0034

.0004

.0002

.0003

.0018

.0034

TABLE 5.- RESULTS ON TRAJECTORIES IN TRIAL 4 AT 24 RPM DIFFERENTIAL.

Initial

Z-coord

(cm)

1.0

2.5

4.0

7.0

8.5

10.0

Time

(sec)

125

337

541

432

265

125

Unit gravity

Average

Force

(dyne/cm2)

.0021

.0016

.0014

.0016

.0019

.0021

Maximum

Force

(dyne/cm2)

.0107

.0053

.0036

.0063

.0132

.0125

Time

(sec)

125

345

604

600

265

125

Microgravity

Average

Force

(dyne/cm2)

.00068

.00033

.00015

.00031

.00055

.00066

Maximum

Force

(dyne/cm )

.0097

.0034

.0005

.0021

.0115

.0099

In conclusion, the rotating bioreactors being developed by the biotechnology group at

NASA Johnson Space Center do partially simulate microgravity with respect to the

trajectories and time frame of a particle's motion. However, there is still a distinct

advantage to having the bioreactor in microgravity since the total force on a particle would

be significantly reduced. The total force on a particle in a rotating bioreactor is less than

one might anticipate from the values reported by other researchers using different

geometries to model hydrodynamic effects on cell growth. In either unit gravity or

microgravity it appears that the greatest potential for damage to the cells comes when the

particle is near to a wall of the vessel or actually collides with a wall. Hence, further study

needs to be conducted to determine an optimal design and optimal rates of rotation to

minimize the migration of particles toward the outside cyUnder and still provide adequate

circulation for sufficient mass transfer of nutrients and cellular waste products.

4-15
250.0 500.0 750.0

TIME (SEC)

1000.0

Figure 15.- Force per unit area on a particle

for the trajectory starting at r = 3, 6 = 0 and z = 1 in Trial 1 at unit gravity.

237.5 475.0

TIME (SEC)

712.5 950.0

Figure 16.- Force per unit area on a particle

for the trajectory starting at r = 3, 6 = 0 and z = 10 in Trial 1 at microgravity.

4-16
REFERENCES

1. Cherry, R. S.; and Papoutsakis, E. T.: Hydrodynamic Effects on Cells in Agitated

Tissue Culture Reactors. Bioprocess Engineering, vol. 1, 1986, pp. 29 - 41. '

2. Cherry, R. S.; and Papoutsakis, E. T.: Physical Mechanisms of Cell Damage in

Microcarrier Cell Culture Bioreactors. Biotechnology and Bioengineering, vol. 32,

1988, pp. 1001 -1014.

3. Croughan, M. S.; Hamel, J. F.; and Wang, D. I. C.: Hydrodynamic Effects on Animal

Cells Grown in Microcarrier Cultures. Biotechnology and Bioengineering, vol. 29,

1987, pp. 130 - 141.

4. Croughan, M. S.; and Wang, D. I. C.: Growth and Death in Overagitated Microcarrier

Cell Cultures. Biotechnology and Bioengineering, vol. 33, 1989, pp. 731 - 744.

5. Patankar, S. V.: Numericla Heat Transfer and Fluid Flow. McGraw-Hill, New York,

1980, p. 197.

6. Schlichting, Hermann: Boundary-Layer Theory. McGraw-Hill, New York, 1979, p.

87.

7. Burden, R. L.; and Faires, J. D.: Numerical Analysis. PWS-Kent, Boston, 1989, pp.

251-255.

8. Burden, R. L.; and Faires, J. D.: Numerical Analysis. PWS-Kent, Boston, 1989, pp.

302 - 308.

9. Bird, R. B.; Stewart, W. E.; and Lightfoot, E. N.: Transport Phenomena, John Wiley

and Sons, New York, 1960, pp. 190 - 194.

4-17
. N91-270

AN AIR REVITALIZATION MODEL (ARM) FOR

REGENERATIVE LIFE SUPPORT SYSTEMS (RLSS)

Final Report

NASA/ASEE Summer Faculty Fellowship Program—1990

Johnson Space Center

Prepared By:

Academic Rank:

University:

Department:

Maxwell M. Hart

Associate Professor

University of Mary Hardin-Baylor

Dept. of Mathematics and Physics

Belton, Texas 76513

NASA/JSC

Directorate:

Division:

Office:

JSC Colleague:

Date Submitted:

Contract Number:

Space and Life Sciences

Solar System Exploration

Space Resources Utilization

Donald L. Henninger

August 17, 1990

NGT-44-005-803

5-1
7

ABSTRACT

The primary objective of the Air Revitalization Model

(ARM) is to determine the minimum buffer capacities that

would be necessary for long duration space missions. Several observations are supported by the current configuration

of ARM. There are at least two factors affecting the buffer

sizes: the baseline values for each gas, and the day-to-day

or month-to-month fluctuations that are allowed. The baseline values depend on the minimum safety tolerances and the

quantities of life support consumables necessary to survive

the worst-case scenarios within those tolerances. Most, if

not all, of these quantities can easily be determined by ARM

once these tolerances are set. The day-to-day fluctuations

will also require a command decision. It is already apparent from the current configuration of ARM that the tighter

these fluctuations are controlled, the more energy will be

used, the more nonregenerable hydrazine will be consumed,

and the larger will be the required capacities for the

various gas generators. All of these relationships could

clearly be quantified by one operational ARM.

5-2
INTRODUCTION

Earth is, without a doubt, the most successful known

example of a regenerative life support system. Because past

and current space missions continue to be of relatively

short duration, these life support systems all rely heavily

upon expendable materials. Life support systems of many

future space missions may try to imitate Earth's own system.

One of the major problems encountered with this reproduction

is that the amount of buffered air volume on the earth is a

great many times larger, per person, than that available on

a space mission.

The volume of air available to the life support system

can be substantially increased by the use of stored air

buffers of each important gas. However, strict mass and

volume constraints for extended space missions require that

these buffers be kept to a minimum. It will therefore be

necessary to use automated physicochemical systems to modify

the atmosphere and keep the relative abundance of the various gas constituents in balance.

METHODOLOGY

This investigation involves the development of a computer simulation model that emulates operation of the air

revitalization component of an actual regenerative life

support system. The added benefit of this procedure is that

it also reveals the amount of replenishment from outside

sources (e.g. from Earth or locally produced) that would be

necessary under various configurations of the system. The

particular system that is being modeled is an initially

unmanned test bed facility that is now in the earliest

stages of development at JSC. This JSC growth chamber is

being built in support of NASA's long-duration missions to

the moon and Mars. JSC's long-range plans also include

design, construction, and operation of a man-rated test bed

facility for verification of integrated regenerative life

support systems, operations development, and crew-training.

The Air Revitalization Model (ARM) is being designed around

a built-in facility for evolution to allow it to keep pace

with test bed upgrade.

Due to the complexity of this computer model and because of the great danger of undetected errors, it is advisable to approach it's design sequentially. Therefore

development of a fully functional ARM has been subdivided

into three phases. Of these three phases, the first two

have now been essentially completed. Planning is currently

under way for the commencement of phase three. It is hoped

that phase three can be completed during summer, 1991.

5-3
Phase One

In this phase ARM will generate data on a short cyclic

interval. The length of each cycle will be set for any

value from a fraction of an hour up to a full day or more.

ARM will compute the amount of each gas in the storage

buffers and then activate the physicochemical systems whenever any controlled amount falls below a baseline, called

zero, whose value is unimportant to ARM. In phase one there

will be no restriction on the maximum size of any of the

buffers. They will be assumed to be extremely large. The

controlled atmospheric gases will be nitrogen and oxygen

with the possibility of adding a baseline for carbon dioxide

at a later date. Also controlled with baseline values will

be water and hydrogen with the possibility of adding a

baseline for methane at a later date. Available to the

system, but with no baseline, will be hydrazine. Hydrazine

is nonrenewable and must be resupplied when exhausted.

Fortunately, however, hydrazine is often used as fuel and

reserve supplies can be transferred to life support systems

as needed.

ARM will be provided with a leakage variable. This

value will be subtracted from the available amounts in each

cycle. The user may choose any rate in either or both of

two categories: 1) large leaks consisting of breathable air,

or 2) small leaks in which gases are differentiated by

molecular size.

Phase Two

This phase consists mainly of internal reorganization

and restructuring for greater speed and efficiency. The

various baselines will be coordinated and consolidated into

a unified structure. This is all necessary as provision for

a month-by-month emulation capability for ARM.

All essential documentation will be supplied to ARM.

This includes both internal and auxiliary documentation.

Many months, even years, of data will be generated by ARM

and this data will be thoroughly tested for accuracy, reasonableness, and continuity from month to month.

ARM will also be endowed with a table of months and

days so that actual monthly data can be emulated rather than

only generic months of 30 days each. This is a necessary

step before ARM can actually emulate the JSC growth chamber

which will be operating on a real-world basis.

Phase Three

This phase will see the addition of maximum baseline

5-4
values. This will allow ARM to emulate a system with limited

storage capacities. By adjusting these variables we can

discover the reaction of a regenerative life support system

to any variety of reserve storage buffer sizes. Only in

this way can we finally determine the minimum safe capacities for these buffers. It also seems possible to provide

ARM with two additional aspects of limitation. One would be

an absolute lower boundary below the baseline. This lower

boundary would represent an empty tank. The other additional limitation would be an absolute upper boundary. This, by

analogy, would represent a full tank. These two limitations

would open up a whole new realm of possibilities, especially

in the absolute minimum. For one thing it would give us

insight into the use of emergency air rations and improve

our understanding of just how much is really needed for

different types of emergencies.

New overlays will be added to ARM to allow year-by-year

operation. This will provide insight to the long-term

effect of various configurations. The entire structure of

ARM would also need to be redesigned to reduce computer

memory and storage requirements and enable the program to

run on conventional hardware.

When the JSC test bed is completed and in operation,

the various model parameters will be adjusted to reflect the

actual chamber data. As more data becomes available, a

database of various plant growth profiles will be incorporated into ARM to identify different reactions of the environment to the presence of a variety of types of plants.

ARM will be programmed to respond to an assortment of

unscheduled "events." The importance of surviving unexpected occurrences will surely increase the minimum buffer

sizes. This increase can best be calculated by modeling

these events. However, once the values of these increases

have been determined, they can be added (moved) below the

minimum baseline and need not affect the day-to-day operation of the system.

PARAMETERS

System Constants

These values are well known constants and unless an

error is discovered, these constants will not be changed.

These are the values used by ARM:

A. Atomic weights

(Based on IUPAC Atomic Weights of the Elements 1981)

1. Hydrogen = 1.00794

2. Carbon = 12.01100

3. Nitrogen = 14.00670

4. Oxygen = 15.99940

5-5
B.

= 0.45359237

= 0.3048

Conversion factors

(CRC Handbook 1987)

1. Lbs. to kg

2. Ft. to meters

Other factors

(Basic definitions included for exhaustivity)

1. Percent =0.01

2. Total = 100%

Physicochemical system formulas

1.

2.

3.

4.

Sabatier COOxygen generation system

Nitrogen supply system

Methane burner CH4 +

4H2

2H20

N2H4

2§2

4

n

H

<

S

2

CO2H20

2H,

2H2

2H20

Controlled Constants

These values can be easily changed as the system may

require. The values currently being used by ARM are given

here. However, the user should substitute his own constants

for the particular system being modeled.

B.

Crew Cabin

1. Crew size =

2. Cabin volume =

3. Air density =

4. Oxygen conversion =

5. Conversion efficiency = 87%

6. Atmosphere composition

a. Nitrogen = 77.5%

b. Oxygen = 21.0%

c. Water vapor = 1.0%

d. Carbon Dioxide = 0.5%

Plant growth chamber

1

30 cubic meters

1225 grams/cubic meter

0.83 kilograms/man/day

2.

3,

4.

5.

6,

Plant growth Plots

a. Length

b. Width

c. Number

Chamber volume

Air density

COo conversion

Conversion efficiency = 90%

Atmosphere composition

a. Nitrogen = 76.0%

b. Oxygen = 18.0%

c. Water vapor = 3.0%

d. Carbon Dioxide = 3.0%

Time

1. Time between readings = 8 hours

2. Plant cycle daylight = 16 hours

Physicochemical system efficiencies

1. Sabatier = 99%

1.778 meters

0.762 meters

8

25 cubic meters

1225 grams/cubic meter

2.5 grams/square meter/hour

5-6
2. Oxygen generation system = 99%

3. Nitrogen supply system = 99%

E. Leakage rates

1. Whole air type = 0.9% per day

2. Permeable membrane type = 0.1% per day

Input Variables

Some variables will often change from one run to the

next. These must be chosen by the user depending on the

conditions being investigated. They are:

A. Initial quantities of gases in the storage buffers

1. Nitrogen

2. Oxygen

3. Water

4. Carbon dioxide

5. Hydrogen

6. Hydrazine

7. Methane

B. Leaf Area Index (LAI)

C. Leaf growth rate

DISCUSSION

The graph in figure 1 was generated by ARM. It represents a month, January, in which no plants were growing.

Thus the leaf area index has been set to zero. The nitrogen

level can be seen to be dropping below an initial, arbitrarily chosen, value of 30 due to an assumed overall leakage rate of 1% per day. The water vapor level is initially

decreasing very slowly below 5 because of the low percentage

of water vapor contained in the atmosphere. Of course, the

gases which are not contained in the atmosphere are not seen

to be leaking. See hydrogen, for example, at 15. A peek at

the data would reveal that oxygen is leaking by about one

third as much as nitrogen. But even the graph shows that

the rate at which oxygen is dropping below 10 is greater

than the nitrogen decline. This is due to oxygen consumption by the one crew member. This crew member is also

responsible for the increase in carbon dioxide. The zero

line near the bottom of the graph represents the baseline

for each gas in the buffer. It can be seen on the graph

that the excess oxygen is depleted on January 10 when the

oxygen trace reaches the baseline. At this time the oxygen

generation system will begin generating just enough oxygen

to keep the oxygen level from dropping below the baseline.

The oxygen generation system is also responsible for the

hydrogen increase and the greatly accelerated rate of water

decline which begins on January 10.

5-7
A

-5

Figure 1.- RLSS/ARM Graph for January

LAI = 0 N2H4 Used = 0.0 Kg 1.0% LEAK

10 15 20 25

Day of Year >

30 35

Figure 2- RLSS/ARM Graph for February

LAI = 0 N2H4 Used = 0.0 Kg 1.0% LEAK

35 40 45 50

Day of Year >

55 60

5-8
Notice on January 14 that the water level has dropped

to zero. At this time the Sabatier process begins operation

at exactly the right rate to keep the water level from

dropping any further. The Sabatier process causes a decrease in the hydrogen level and the carbon dioxide level on

January 14. It is also responsible for the production of

methane which is seen to begin on January 14. It should be

pointed out that both oxygen and water remain on the baseline for the remainder of January. Also notice, at the top

of the graph, the label that indicates that no hydrazine was

used during January. All of the traces end on the thirtyfirst, the last day of January.

The graph in figure 2 was generated by ARM immediately

after the previous graph without any user intervention.

These are the results for February. It uses the final

values at the end of January as the initial values for

February. It can be seen that the day numbers at the bottom

of the graph are days of the year rather than days of the

month, and each day ends at the corresponding mark.

On day 44 the carbon dioxide is depleted. But since

there are no plants and since both oxygen and water levels

are on the baseline, the carbon dioxide is allowed to go

below the baseline rather than use precious oxygen or water

to try to stop it.

Nothing noteworthy happens for the remainder of February until February 28, day number 59. On this day the

nitrogen is depleted. However, this same situation is

duplicated in the next series of graphs and will be illustrated at that time.

There are two very important reasons for studying the

operation of ARM with an LAI of 0. Initially, it gives us

an opportunity to see this operation without the further

complication of input from the biological component of the

life support system. This makes it easier to understand and

validate ARM. Secondly, this is the mode in which ARM must

operate, at least temporarily, if some misfortune destroys

all of the plants. This will make it possible to determine

the quantities of buffer gases that must be stored for just

such contingencies.

The specifics for figure 3 are similar to those for

figure 1, except that the initial values are set somewhat

differently and the leaf area index is set to 4. The slow

leakage of water vapor from the atmosphere is more noticeable in this graph than it was in figure 1. The wavy nature

of the oxygen trace as well as that of carbon dioxide, and

others to a lesser degree, is due to the day and night

growth cycle of the plants. The plants cause the oxygen

levels to increase and the carbon dioxide levels to decrease

until January 25 when the carbon dioxide is exhausted. At

this time the emulated methane burner converts just the

right amount of methane to hold the carbon dioxide level at

5-9
-5

Figure 3.- RLSS/ARM Graph for January

LAI = 4 N2H4 Used = 0.0 Kg 1.0% LEAK

10 15 20 25

Day of Year >

30

Figure 4.- RLSS/ARM Graph for February

LAI = 4 N2H4 Used = 0.0 Kg 1.0% LEAK

35 40 45 50

Day of Year >

55 60

5-10
the baseline while the water level begins to rise as a byproduct. But, the methane burner also consumes oxygen and

this, too, begins to decline on January 25.

In figure 4 we see that the oxygen is exhausted by day

number 39. This activates the oxygen supply system which

begins using the excess water to produce oxygen and hydrogen. Even though twice as much hydrogen is generated as

oxygen, the hydrogen is seen to rise very slowly. This is

due to the low mass of hydrogen.

Until now, no hydrazine has been consumed. This is

indicated at the top of figures 3 and 4. However, as in

figure 2, the nitrogen is depleted on day 59. There are now

three gases on the baseline. Since nitrogen reaches the

baseline on February 28, we will not see the effects of this

until March 1.

In figure 5 we first notice that the Nitrogen Supply

System that was activated on February 28 consumes hydrazine

and prevents the nitrogen from falling below the baseline.

But, of course it has no effect on the water level, which is

also falling. Thus, we see the excess water depleted on day

63. At this time we have four gases at the baseline. These

four are carbon dioxide, oxygen, nitrogen, and now water.

It is clear that these four cannot all be maintained as

leakage continues. We have essentially the same problem as

seen in figure 2 when carbon dioxide reached the baseline.

We also have the same solution. Carbon dioxide is allowed

to deteriorate below the baseline. You will notice on the

graph of figure 5 that carbon dioxide drops below the baseline just as water is coming onto the baseline on day 63.

This leaves water, nitrogen, and oxygen on the baseline.

The Nitrogen Supply System continues to generate both nitrogen and hydrogen. But this is not enough to prevent the

large drain on the hydrogen supply from using all of the

reserve supply of hydrogen. This occurs on day 87. Now

the Nitrogen Supply System is called upon to balance the

hydrogen drain caused by maintaining the water supply at the

baseline. As we saw, the drain on the water supply was

caused by a shortage of oxygen. This, in turn, was caused

by a lack of carbon dioxide. We will come back to the

carbon dioxide in a moment. On day 87, in order for the

Nitrogen Supply System to balance the hydrogen, it must also

generate huge amounts of nitrogen. This is why the nitrogen

level is seen sailing off the top of the graph on day 88.

The system is now in desperate straits. During the

month of March the RLSS used 120 kg of hydrazine, mostly in

the last few days. During the month of April the system is

able to keep hydrogen, oxygen and water at the baseline, but

only with a huge consumption of hydrazine as indicated by

the label at the top of figure 6, almost 26 metric tons.

This indicates that the physicochemical system will do

everything it can to maintain the baseline integrity until

5-11
30

-5

Figure 5.- KISS/ARM Graph for March

LAI = 4 N2H4 Used = 120.2 Kg 1.0% LEAK

60 65 70 75 80

Day of Year >

85 90

30

Figure 6.- RLSS/ARM Graph for April

LAI = 4 N2H4 Used = 25959.6 Kg 1.0% LEAK

A

</!

D

CD

0} 1 i

> I1

O

JD

0>

90 95 100 105 110

Day of Year >

115

N2

02

H20

C02

H2

CH4

120

5-12
it totally runs out of resources. We can only hope that

never happens.

Now, returning to the carbon dioxide. We have seen

that this whole breakdown of the system was first initiated

by the shortage of carbon dioxide. There are auxiliary

sources of carbon dioxide that can prevent the system from

running down once they are utilized. This includes the

recycling of waste and the eating and digesting of food

which will likely be resupplied from Earth. If these factors are figured in, we will see a totally different end

result. It is therefore very likely that a future version

of ARM will include these features.

Important Discovery

This procedure is probably known, but it was a challenge for me. In order to keep the RLSS in balance it is

quite important to poll the different gas supply systems in

an appropriate sequence. So far, I have found only one

sequence that works. This is an important understanding,

not only for a simulation model, but also for a computer

control system. The sequence used by ARM is given in table

1. Ceiling checks will not be done by ARM until it reaches

phase three. They are included here for reference only. If

the value in the floor check is negative, the corresponding

system will be used to bring it up to the baseline. If the

value in the ceiling check is above established maximums it

will be consumed until brought below the ceiling. It should

be understood that these systems can run simultaneously, but

in three shifts. Systems 1 through 4 can run together as

long as each knows the results of all previous systems and

stops polling in sequence. Systems 5 through 7 and then

systems 8 and 9 can repeat the process. There should,

however, be no time lapse between the three shifts, especially if the leakage rate is high.

It can be seen from this table that the only products

which can be generated above its ceiling will be methane,

water, and nitrogen. Excess water can be stored in liquid

form and excess nitrogen can be used to increase atmospheric

volume or pressure to some degree. Excess methane beyond

storage capacity could be vented or used as fuel.

The only products which can run short are water, carbon

dioxide and hydrazine. Hydrazine is nonrenewable and must

be resupplied from sources beyond RLSS domain, anyway.

Similarly, resupplied food, to supplement the edible biomass

provided by the plants, will help alleviate the shortages of

both carbon dioxide and water when the resupplied food is

digested by the crew.

5-13
TABLE 1.- SEQUENCE OF OPERATION

# Name Floor Check Ceiling Check Byproduct Requisite

o

o

0

o

0

o

o

0

o

0

o

o

o

e

o

o

e

o

e

1.

2.

3.

4.

5.

6.

7.

8.

9.

NSS

S

MB

OGS

S

MB

OGS

S

NSS

0

o

0

o

0

e

o

0

o

0

o

o

o

0

o

0

o

0

e

N2 <0

H20<0

co2<o

°2

 <0

H20<0

C02<0 and

H20>0 or 02>0

°2

 <0

CH4<0

H2 <0

*NSS = Nitrog<

CO

°2

H

2

H

2

CH

H2

H

2

an

2>Max

>Max

0>Max

>Max

4>Max

0>Max

>Max

Supply

e

o

o

o

0

o

o

0

o

0

o

o

e

o

o

e

o

0

o

Sys

H

C

H

H

C

H

H

H

N

te

2

H

4

2°

2

H4

2°

2

2°

2

m

N2H4

co2 &

CH4 &

H20

co2 &

CH4 &

H20

co2 &

N2H4

O

O

H2 •

O

°2 °o

e

0

H2 °e

°2 °0

o

0

o

H2 °o

o

o

S = Sabatier System

MB = Methane Burner

OGS = Oxygen Generation System

5-14
CONCLUSIONS

The Air Revitalization Model (ARM) seems to indicate, on

the basis of minimum baseline constraints only, that Regenerative Life Support Systems (RLSS) can be held on or above all

of the minimum baselines for very long periods, months or even

years. If this feat can be duplicated for maximum baselines,

then only very small buffer storage would be necessary except

that which may be required for recovery from catastrophic

events. However, there is a price. This model does not track

the energy requirements, but it does show a need for a continuous resupply from outside sources, such as from Earth or from

local resource extraction. Under the present configuration of

ARM, resupply would be required only for carbon dioxide, water

and hydrazine. The carbon dioxide and water could, of course

be supplied in the form of food stock, and the hydrazine does

not differ from hydrazine fuel.

Under this configuration, ARM also indicates that the

only large storage buffers beyond those necessary for the

baseline amounts would be for storage of excess methane, water

and nitrogen. However, these storage requirements are diminished if resupply is reliable.

It remains for future enhancements of ARM to determine

the effects of additional constraints on the operation of

RLSS. Some future enhancements which may be considered for

annexation to ARM include:

1) maximum baseline constraints

2) absolute minimum constraints

3) absolute maximum constraints

4) year-to-year overlays

5) plant profiles

6) unscheduled "event" scenarios

7) resupply schedules

8) waste oxidation

9) liquid water recycling

10) tracking of gas production

11) tracking of gas usage totals

12) tracking of energy usage totals

It would seem that there is still much to be done.

5-15
N9 1-

PHOTOGRAPHIC IMAGE ENHANCEMENT

Final Report

NASA/ASEE Summer Faculty Fellowship Program-1990

Johnson Space Center

Prepared by:

Academic Rank:

Universiy & Department:

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleaque:

Date Submitted:

Contract Number:

Gerald E. Hite

Associate Professor

Texas A&M Univ. at Galveston

Dept. of Marine Science

Galveston Texas 77553-1675

lf

Space and Life Sciences

Solar System Exploration

Space Shuttle Earth Observation Office

David E. Pitts

August 10,1990

NGT-44-005-803

6-1
Abstract

Deblurring capabilities would significantly improve the scientific return

from Space Shuttle Crew acquired images of the Earth and the safety of Space

Shuttle missions. This summer, deblurring techniques were developed and

demonstrated on two digitized images that had been blurred in different

ways. The first was blurred by a gaussian blurring function analogous to that

caused by atmospheric turbulence while the second was blurred by improper

focussing. It was demonstrated in both cases that the nature of the blurring

i.e. gaussian and Airy, and the appropriate parameters could be obtained from

the Fourier transformation of their images. The difficulties posed by the

presence of noise necessitated special consideration. It was demonstrated that

a modified Wiener frequency filter judiciously constructed to avoid over

emphasis of frequency regions dominated by noise resulted in substantially

improved images. Even though the deblurred images were similar to the

original unblurred images, their Fourier transformed images were similar

not as similar, indicating that more refined techniques applied to the Fourier

image could result in further improved images. Several important areas of

future research were identified. Two areas of particular promise are the

extraction of blurring information directly from the spatial images and

improved noise abatement from investigations of select spatial regions and

the elimination of spike noise.

6-2
Introduction

The Space Shuttle Earth Observation Office serves as the repository of over

100,000 photographs form the Manned Space Flight Program. Photographs

are taken to monitor both the lift-off and the landing of the Space Shuttle,

and to document environmental, geological, meteorological and

oceanographic phenomena observed from orbit. Inadvertently a number of

these are blurred by improper focussing, relative camera-object motion,

atmospheric distortions i.e. shock waves or thermal gradients, etc.

Atmospheric distortions are particularly annoying since they restrict NASA's

ability to monitor the effects of lift-off on the shuttle and the decent of the

orbiter's wheels during landing. To gain access to important engineering and

scientific information contained in blurred photographs, it is necessary to

apply image processing techniques. The more sophisticated of these involve

digitization of the raw image and subsequent computer processing of the

degitized images or their Fourier transforms.

The research accomplished as a Summer Faculty Fellow involved the

development and implementation of a deblurring procedure to handle a) the

digital gaussian blurring which is analogous to that caused by atmospheric

turbulence and b) blurring due to improper focussing e.g. actual focal lengths

differing from expected values due to thermal effects, etc. Although there is

no apparent indication of the source of blurring in the spatial images, there

are definite indications of the source of blurring in the Fourier (transformed)

images. Thus to improve a spatial image one first diagnoses the Fourier

images for signs of the source of blurring and then used that information to

construct a frequency "filter" that reduces the effects of blurring in the Fourier

image which in turn would produce a sharper spatial image. However, the

presence of unknown noise in the original images and increased by the

digitalization process, necessitates special consideration. In particular, even

though blurring reduces the high frequency components compared to the

lower frequency ones, simple enhancement of the higher frequency

amplitudes will not necessarily improve the image, since it could increase the

overall noise to signal ratio by introducing high frequency amplitudes that

are noise dominated. The trick is to judiciously emphasize only those

frequency regions where the signal to noise ratio is acceptable. There are

many excellent text dealing with digital processing (1,2,3) and discrete Fourier

transforms(4,5) that provide the background for the work described in this

report.

6-3
II Theory and Approach

II.l Blurring as a Convolution Process: the Point Spread Function

In general a blurred image is the result of light that would have arrived at

a particular point being spread over a number of points. If the distribution is

the same for all points in the image and if the light is incoherent then in the

absence of noise the final intensity at a point (pixel) m,n would be given by

/ , A 'J-i••m-m1, n-n' 1 "m", n'

m

1

, n'

P.S.F.m-m'

 n-n' I sr

where P.S.F. is the point spread function, i.e. the image of an ideal point

source in the object plane, f s

m/n is the sharp image that would have formed

in the absence of blurring and noise.

For the images of interest the digitization process yields an image made up

of NxN pixels (N=512). Due to the blurring bringing light rays into the image

region that would have otherwise not nave entered it, the summation in this

expression should include m"s and n"s outside the range of 0 to N-l.

Nevertheless, the sum is usually assumed to be limited to this range to avoid

having to deal with an "underdetermined problem" (6).

Noise is always present in the image. It can be the result of electronic

cross-talk, round-off errors in the digitization process, random,

inhomogeneous chemical processes in the original film, etc. Noise can be

divided into two contributions: one independent and the other dependent on

the signal, i.e. f s(7). In the latter case it could be incorporated into the point

spread function. Since we have little knowledge of the nature of the noise,

except that it is usually dominant at high frequencies, we will describe it by an

unknown function n m/n and write the expression for the blurred image as

* m, n / ,*• •^•^•m-m'/n-n' * m', n' + W m/n (1)

m', n'

The next step is to invert the sum in equation 1 and solve for f s . Since

the summation is usually referred to as convolution, the inverse process is

referred to as deconvolution. The basic technique is to expand all functions

in terms of a complete set of basis functions which will turn the summation

into a simple product of the expansion coefficients.

6-4
II.2 Fourier Transformations

For simplicity we use the traditional discrete Fourier expansion

(2a)

where there are N values of k and 1.

The inverse Fourier transformation is then given by

m,nexp - 2 TI i(km + ln)/N (2b)

k,i =

In the following we will use lower case letters , e.g. f, for the spatial images

and upper case letters, e.g. F, for the Fourier transformed image. The Fourier

transform of the point function,P.S.F., is called the modulation transfer

function,M.T.F..

In terms of the Fourier transformed variables equation 1 takes the form

Fbk,i = Fsk,!.M.T.Fk/1 + Nk / 1 (3a)

Deleting the common subscripts and solving this equation for the Fourier

transform of the sharp image function yields

F

s

 = Fb/M.T.F. - N/M.T.F. (3b)

II.3 Noise Considerations

If the modulation transfer function and the noise, N, were both known

then equation 3b could be used to find F s and a subsequent inverse Fourier

transformation would yield a sharp image. For the sake of discussion let us

assume that we have a reasonably good understanding of the blurring process

and have a good approximation to P.S.F. and thus to M.T.F. Most likely the

blurring extends over a few spatial pixels and M.T.F. will be small at high

frequencies, i.e. large values of k and 1. Blurring due to improper focussing,

relative motion, atmospheric turbulence are in general of this type. The first

two sources of blurring have M.T.F.'s that vanish on contours in the k,l space.

Where ever M.T.F. is small the contribution from noise, N/M.T.F., in

equation 3b can be significant. Consequently, approximating F5 by

pb/M.T.F.can result in large noise contributions. The normal procedure to

avoid this problem is to multiply pb by a "filter" function which uses

information about the noise to approximate 1/M.T.F. where noise is

6-5
unimportant and avoids contributions from regions where noise dominates.

The Wiener filter is the most common filter discussed in the literature

(2,3,4,6):

W1 = M.T.F. •(!+ IN/FS-M.T.F.|2)

As it stands this expression requires knowledge of the amplitude of the

function to be calculated and the unknown noise contribution. A simple way

to suppress noise is to replace N/FS with a constant (3) or a constant times a

gaussian, e.g. C exp c(k2+l2). In the former case the constant could be chosen

to be the value of M.T.F. at frequency in the range where the maximum value

of W is desired. A gaussian would do a better job of modelling N/Fs than a

constant but it involves finding appropriate values for two instead of one

parameter.

Another approach is to notice that when M.T.F. vanishes Fb is equal to N.

Consequently, if Fb

o is the value of Fb

 where M.T.F. = 0, then (Fb -

F

b

0)/M-T.F. would avoid the introduction of excessive noise, since - Fbo

removed the noise.

Ill Applications : A Tale of Two Imaees

In this section we discuss two applications of the deblurring techniques

described in the previous section. The first application involves an image

blurred digitally by convolution with a gaussian spread function. This is the

digital analogy of atmospheric turbulence for long exposure times(l,8). The

second involves an image blurred by defocussing the lens of the digitizer and

thus is an example of blurring due to improper focussing.

ELI Enhancement of an Image Blurred by Gaussian Convolution

Figure la shows the original image and figure Ib shows the image blurred

by convolution with a point spread function which is gaussian within a 5 by 5

square of pixels. Figure Ic shows an enhanced image obtained by applying a

filter to the Fourier transform of the blurred image. It should not be

considered an ultimate product but simply a demonstration of the results that

could be obtained without expenditure of the time needed to fine tune the

enhancement process. Figures 2a,b and c show the Fourier transformed

images corresponding to those shown in figure 1. Clearly the Fourier image

(figure 2c) reconstructed from the Fourier transform of the blurred image

(figure 2b) is an improvement but still differs considerably from the Fourier

transformation of the sharp image (figure 2a) especially in the intermediate to

6-6
high frequency region. Figure 3 shows the inverse of the deblurring filter

used to obtain figure 2c from figure 2b.

There were three important aspects in constructing the deblurring.filter:

1. Only in a 5 by 5 spatial pixel region was the P.S.F. non-zero.

2. Inside that region the P.S.F. could be described by a single coefficient

in the exponent of the gaussian.

3. The filter would have to deviate sufficiently form 1/M.T.F. in the

high frequency region where 1 /M.T.F. would be large and noise

could be expected to dominate.

The Fourier images shown in figures 2a and 2b were used to obtain the

coefficient for the "gaussian" M.T.F. This was done by taking the Fourier

transform of their ratios which in the absence of noise would be the P.S.F.

Although the resulting function did not vanish outside the 5 by 5 pixel

region, presumably due to noise, there was sufficient accuracy within that

region to determine the coefficient within a 5% variance.

Knowing that in the continuous case the Fourier transform of a gaussian

is again a gaussian, a preliminary filter was constructed using a gaussian

M.T.F. The resulting image was unrecognizable, presumably due to high

frequency noise. Next a one constant Wiener-like filter (see section II.3)

which emphasized the medium to low frequencies (N/V^6) was used. This

gave a reasonable but rather grainy image. The final result shown in figures

Ic and 2c was obtained by replacing the gaussian M.T.F. in the Wiener-like

filter by the M.T.F. resulting from a P.S.F. having only a gaussian distribution

within a 5 by 5 pixel region. The squareness of this pixel region gave extra

emphasis to the high frequency components near the axes and consequently

removed most of the graininess. Further refinements could be expected from

a more judicious choice of the constant in the filter or optimization of a two

constant filter (see section II.3).

ni.2 Enhancement of an Image Blurred by Improper Focussing

Figures 4a, b and c show the original, blurred and the first order restored

image and figures 5a, b and c show their respective Fourier transforms. The

first two images were made using the video digitization system. Though it is

no evident from the figures as shown, the top 1/16 of both images is missing

as a result of the digitization process. Such spatial-domain truncation causes

over shooting or ringing in subsequent filtered image (p. 26 ref. 1). A crude

attempt was made to fill in these region, which replaced a few strong 1=0

constant frequency by the scratchy like region of with N/16 centered on the 1

axis as shown in figure 5b. It is thought that remnants of this spatial domain

truncation are the cause of the ringing seen in figure 4c.

Knowing that the blurring process is due to defocussing one can expect to

see the zero contours of the appropriate M.T.F. in the Fourier transform of

6-7
the blurred image. If the P.S.F. is a uniform disk, the the M.T.F. is the

discrete equivalent of the Airy function. A subroutine was then written to

generate Airy-like M.T.F.'s for a uniform solid disk of variable radius

surrounded by an annulus whose value decreases from that of the disk to

zero at a variable outer radius. The halo visible where pb drops down to the

background noise, was used to estimate the radius of the disk. Then using

this estimate, Airy-like M.T.F.'s were generated. A disk with a diameter of

about five pixels and a fuzzy annulus of two pixels width was selected.

Comparing it to the F^ shown in figure 5b, it was seen that the first zero

contour was in the halo region and that the second zero contour just enclosed

the region where pb was still significant. Thus the Fourier transform of an

image blurred by improper focussing contained sufficient information to

identify by visual inspection an appropriate M.T.F. However, there were

other M.T.F.'s resulting from varying the disk radius and the annulus width

that had similar zero contours. The one chosen gave slightly better results

although the fuzzy annulus had little of no effect on the ringing. Having an

appropriate M.T.F. , a Wiener-like filter was chosen that gave maximum

emphasis in a frequency circle of radius 80 pixels. Clearly the resulting.

Fourier image represents an improvement but is not identical to that of the

unblurred image. Perhaps the most improvements in the deblurred image

are to the letters on the wings of the orbiter and the upper regions of the solid

fuel rockets.

IV Future Research

The research described herein revealed several interesting avenues of

future work. Two prominent areas of importance in designing the deblurring

filters are the identification of the appropriate M.T.F. from Fourier transforms

of the blurred images and noise abatement. The latter area of work may lead

to preprocessing the blurred images, e.g. with windowing functions. Another

important investment of research time is that of progressing systematically

through a series of blurred images. These images should be classified as

much as possible beforehand into groups having similar blurring processes.

It is dear that any strategies developed in working with a few images need to

be tested and refined by considering other images. In this section each of

these areas of work will be reviewed.

6-8
V.I Construction of M.T.F.'s from Imaees

Each blurring process can be expected to have its own point spread

function (P.S.F.) and an associated modulation transfer function (M.T.F.). A

priori knowledge of the blurring process is helpful, but not essential. For

example, the circular halo observed in the second but not the first image

considered in section El is characteristic of improper focussing. The lack of a

halo would suggest another type of blurring, e.g. gaussian. Relative motion

would have a line segment for a P.S.F. For the simplest case, that of a straight

line segment, i.e. constant velocity, the resulting M.T.F. would have

rectangular symmetry. A combination of improper focussing and relative

motion has a M.T.F. that is the product of the individual M.T.F.'s for each

process. Blurring due to atmospheric turbulence under certain conditions

would be gaussian and would not result in a halo pattern. In many cases, the

only means of identifying the M.T.F. and the parameters needed to describe

it will be from the Fourier image. Visual inspection of a Fourier image for

the halo pattern probably is the fastest means of identifying the source of

blurring. Having appropriate M.T.F. parameters, e.g. the exponent coefficient

of a gaussian or the diameter of the disk in the case of improper focussing.

How much of this work could be accomplished by a computer remains to be

seen.

In principle, it is possible to extract P.S.F. parameters directly from features

of the spatial image. In particular, if the image pixels associated with a single

point of the sharp image can be identified then one has the P.S.F. In theory

such information is also contained in the profiles of edges and lines in the

blurred image. The change of pixel values perpendicular to an edge can be

shown to be proportional to the pixel values of the P.S.F. measured along the

diameter in the same directions.

FV.2 Noise Abatement

The two examples considered in section HI have clearly shown that

identification of the M.T.F. is only the first step. Care must be taken to avoid

emphasis of noise. The approach used there of a one or two parameter

Wiener-like suppression of high frequency contributions was a rather crude

method of noise abatement. It would be better if the source or the nature of

the noise could be identified and removed by a separate frequency filter. For

example, in working with the first image, it was found that setting all

amplitudes inside circular arcs of radius N/4 around the four corners of the

Fourier image had no visual effect on the unblurred image. In the case of

spike noise, where individual pixels are radically different in value from the

6-9
surrounding pixels, a subroutine could search and remove such "sparkle".

Sparkle is most prominent near the corners of the Fourier image where little

if any signal is present. It is in contrast to the more cloud-like structure •

typical of the low frequency region where signal dominates. It should be

possible to obtain information on noise by studying select portions of the

spatial image, e.g. if a region is known to be uniform in intensity, then any

ripple in its Fourier transform may be assumed to be noise. Identifying

regions or individual pixels of the Fourier image as noise dominated and

their removal would greatly reduce the importance of the choice of

parameters in the deblurring filter.

IV.3 Image Truncation and Windowing

In dealing with the image blurred by improper focussing, ringing

supposedly due to spatial truncation, was observed. In this particular case, the

upper sixteenth of the image was not present due to the digitalization process.

Because of the cut-off of the camera, it is barely noticeable in figures 2a, b or c.

However, an attempt to fill in the missing area removed strong vertical lines

near 1=0 and created the scratchy band about 32 pixels wide, i.e. N/16. This is

an indication of the importance of spatial truncation on the Fourier image. It

would be worthwhile to see what effect the edges of an image have on its

Fourier image. There are many different types of window functions(l) that

remove the effects of the edges and could help us to see which Fourier

features are important and which are spurious.

V Summary and Conclusion

The two examples discussed in section n, demonstrated the significant

improvement that can be accomplished in enhancing blurred images.

Information needed to construct the frequency filters which manipulate the

Fourier images can be extracted from the Fourier as well as the spatial image.

For the two examples considered, the nature of the blurring mechanism was

evident from the presence or absence of halos in their Fourier transforms. It

was also found that once the type of blurring was recognized if was easier to

use the Fourier images to fix the appropriate parameters. Supposedly

methods could be developed to extract the needed information from features

of the spatial images that might complement the work with Fourier images.

Similarly, noise reduction could proceed from identification of spike noise

etc. in the Fourier image or from studying select regions of the spatial image.

In conclusion, it has been demonstrated that blurred images can be

enhanced using information extracted from the images themselves.

However, there is plenty of research and art work to be done before JSC has a

cookbook for deblurring images.

6-1.0
VI References

1 Moik, J.G.,Digital Processing of Remotely Sensed Images, NASA SP-431,

1980

2 Castleman, K.R., Digital Image Processing, ISBN 0-13-21365-7 Prentice-Hall

Inc. 1979

3 Gonzalez, Wintz, Digital Image Processing

4 Press,W.H., B.P.Flannery, S.A. Teukolsky,W.T. Vetterling, Numerical

Recipes, ISBN 0-521-30811-9, Camgridge Univ. Press, 1986

5 Reynolds, G.O., J.B. DeVelis, G.B Parrent Jr.,BJ. THompson, Physical Optics

Notebook: Tutorial in Fourier Optics, ISBN 0-8194-0130-7,1989

6 Menke, W., Geophysical Data Analysis: Discrete Inverse Theory", ISBN 0-

12-490921-3, AP, 1989

7 Ward,R.K., B.E.A. Saleh, Restoration of images Distorted by System of

Random Impulse Resonses, J. Opt. Soc. Am.,A2,ppl254-1259,1985

8 Hufnagel, R.E., N.R. Stanley, Modulation Transfer Function Associated

With Image Transmission through Turbulent Media, J. Opt. Soc. Am, vol.54,

pp 52-61,1964

6-11

C-2.
Figures la, Ib and Ic Figures 2a, 2b and 2c

6-12

ORIG5MAL PAGE !S

OF POOR QUALITY
Figure 3

ORIGINAL PAGE IS

OF POOR QUALITY

6-13
Figures 4a, 4b and 4c

Figures 5a, 5b and 5c

6-14

ORIGINAL PAGE 13

OF POOR QUALITY
N91-270

NONLINEAR SYSTEMS DYNAMICS IN CARDIOVASCULAR PHYSIOLOGY:

THE HEART RATE DELAY MAP AND

LOWER BODY NEGATIVE PRESSURE

Final Report

NASA/ASEE Summer Faculty Fellowship Program 1990

Johnson Space Center

Prepared By:

Academic Rank:

University & Department:

John C. Hooker, Ph.D.

Professor

Houston Baptist University

Department of Biology

Houston Baptist University

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleague:

Date Submitted:

Contract Number:

Life Sciences

Medical Sciences

Space Biomedical Research

Institute

John B. Charles, Ph.D.

August 17, 1990

NGT-44-005-803

7-1
ABSTRACT

This report is a presentation of a preliminary study of

the applicability of nonlinear dynamic systems analysis

techniques to LBNP studies. In particular, the

applicability of the heart rate delay map is investigated.

It is suggested that the heart rate delay map has

potential as a supplemental tool in the assessment of

subject performance in LBNP test and possible in the

determination of susceptibility to cardiovascular

deconditioning with spaceflight.

7-2
INTRODUCTION

The human cardiovascular system is a very complicated,

highly nonlinear, dynamic system. As such, it is a primary

candidate for analysis using the techniques of chaos theory

which have evolved in the recent past in an attempt to

understand the nature of deterministic systems whose outputs

appear to be ramdom.

One tool which has been used for discrete systems —

systems with outputs only at discrete times and described,

at best, by difference equations, as opposed to. systems with

continuous time outputs and described by differential equations — is the delay map. The delay map for discrete

systems is analogous to the phase space trajectory for

continuous systems. Each of these represents a description

of the dynamic behavior of the variable under consideration.

This report discusses some of the findings of a preliminary study into the applicability of the delay map in the

analysis of heart rate varation during lower body negative

pressure (LBNP) tests. This study was performed in the

Cardiovascular Laboratory, Space Biomedical Research Institute, NASA Johnson Space Center, as part of the NASA/ASEE

Summer Faculty Fellowship Program 1990.

DATA ACQUISITION AND METHODOLOGY

The heart rate data used in this study was derived from

data recorded during pre-bedrest, pre-syncopal LBNP tests.

Actual data recorded included ECG (in most cases), blood

pressures (systolic, diastolic, and mean), and chamber pressures (LBNP). Cardiac cycle duration (CCD) was calculated

from the ECG and the blood pressure. Where available, the

CCD from the ECG was used to determine the heart rate as a

function of time. If CCD from the ECG was not available the

CCD from the blood pressure was used. Heart rate was determined as the inverse of the CCD multiplied by 60 seconds per

minute. The time sequence for the heart rate profile was

determined by summing the CCDs. The recorded data was digitized and presented in worksheet format on floppy discs.

Data on four subjects was available.

The heart rate delay map was constructed by comparing

the heart rate after a twelve second delay with the heart

rate before the delay, i.e., the present heart rate versus

the heart rate twelve seconds ago. A simple program was

written in the C language to search back through the heart

rate data to determine the heart rate twelve seconds ago.

7-3
The heart rate delay map was then constructed by plotting

the heart rate after the delay versus the heart rate before

the delay.

RESULTS PRESENTATION AND DISCUSSION

The heart rate delay of twelve seconds represents the

delay associated with autonomic nervous system control of

the cardiovascular system primarily via the sympathetic and

parasympa thet ic inputs to the SA node pacemaker of the

heart. Several researchers (1,2) have shown through spectral analyses of heart rate data that there is a low frequency component of the spectrum at approximately 0.08 Hz

cooresponding to this delay. Based on these analyses the

twelve second delay was used for this study.

The heart rate time profile of Subject A is shown in

Figure 1. Superimposed on that profile is the LBNP.

Each chamber pressure was maintained for approximately three

minutes with the transitions taking only a few seconds. The

LBNP test was terminated when the systolic blood pressure

dropped below a given threshold and the heart rate ceased to

increase or decreased. For Subject A the test was terminated after a few minutes at a LBNP of -50 mmHg.

Figures 2 through 6 present the heart rate delay map

segmented according to the steady LBNPs for Subject A and

Figure 7 shows the composite heart rate delay for Subject A.

The baseline or atmospheric pressure case (Figure 2)

indicates that the heart rate delay map is concentrated in a

small region of the map. If the -20 mmHg condition (Figure

3) is also considered as a non-stressful situation and only

an extension of normal, the heart rate delay map resembles

what Goldberger (1), and others in the chaos liturature,

refer to as a stranger attractor. This attractor pattern

indicates that, although the heart rate is quite variable,

after excursion away from the norm, the heart rate returns.

Note the "butterfly pattern" of Figure 3.

Figures 4, 5 and 6 indicate that as the LBNP stress

increases (lower LBNP) the heart rate increases, becomes

more variable, and the excursions increase in magnitude and

duration. Of significance is the decrease in variability of

the map — a concentrating of the map — during the late -50

mmHg case and a decrease in the heart rate -- seen as the

map trends down and to the right as the end of the test

approaches.

One other subject presented a similar delay map.

7-4
40

200 400 600

TIME (sees)

Figure 1.- HEART RATE

SUBJ A, PRE-BEDREST, PRE-SYNCOPAL TEST

800

120

E

QL

XI

110 -

100 -

u

0)

0)

90 -

80 -

I 70

60 -

50 -

40

Baseline •

40 60 100

Figure 2.—

80

HR (bpm)

HEART RATE DELAY MAP

SUBJ A, PRE-BEDREST, PRE-SYNCOPAL TEST

120

7-5
E

a

.a

120

110 -

100 -

90 -

o

<u

<n

<N 80 - ^~

® -70

;£ 70

o

I 60

50 -

40

40

-20 mmHg

60

1 1 1 1 r

80 100

HR (bpm)

Figure 3.- HEART RATE DELAY MAP

SUBJ A, PRE-BEDREST, PRE-SYNCOPAL TEST

120

120

E

a.

jQ

110 -

100 -

90 -

u

Q>W

CM 80 -

70 H

o

i 60 -

50 -

40

40

-40 mmHg

60 80 100

HR (bpm)

Figure 4.- HEART RATE DELAY MAP

SUBJ A, PRE-BEDREST, PRE-SYNCOPAL TEST

120

7-6
E

Q.

120

110 -

100 -

90 -

80 -

70 -

x 60 -J

50 H

40

40

Figure 5.—

Q.

XI

u

Q>

110 -

100 -

90 -

80 -

~ 70 -

o

I 60 -

50 -

40.

40

Figure 6.—

-50 mmHg

(early)

60 80 100

HR (bpm)

HEART RATE DELAY MAP

SUBJ A, PRE-BEDREST, PRE-SYNCOPAL TEST

120

-50 mmHg(late)

60 80 100

HR (bpm)

HEART RATE DELAY MAP

SUBJ A, PRE-BEDREST, PRE-SYNCOPAL TEST

120

7-7
(tudq) Das

7-8
Subject B (Figures 8 and 9) was able to withstand a

greater LBNP stress as shown by LBNPs of -60 to -80 mmHg. Of

significance in this study is the contrast to Subject A as

seen in the decrease in heart rate variability (Figure 8)

and a narrowing of the delay map (Figure 9) with LBNP

stress. The geometric, rectangular pattern seen in the

upper regions of heart rate (Figure 9) is a function of only

two significant figures in the CCD.

Another subject presented a similar heart rate delay

map to Subject B. It would appear from these two cases that

as the subject is able to move to higher LBNP stress levels

the heart rate delay map narrows.

CONCLUSIONS AND RECOMMENDATIONS

Although

sample study,

potential as an analytic

appear that the delay map has use as a

ascertaining the termination point

particularly, if an on-line,

implemented. The delay

predictor of subject

this was only a prelimimary, cursory and small

it appears that the heart rate delay map has

an analytic tool in LBNP studies. It would

supplemental aid in

of an LBNP test,

real-time presentation is

map may also have potential as a

susceptibility to cardiovascular

deconditioning in spaceflight.

The

studies:

following recommemdations are made for further

1) Longer time profiles of heart

should be analyzed. Such studies

indicators of strange attractors and

and the signicance of such deviations.

rate at constant LBNP

should gave better

deviations from them

2) The longer time profiles should also be subjected to

spectral analyses and correlations done between changes in

the heart rate delay map and the frequency spectrum.

7-9
C/) LUQ_OO

UJ< ^

LdS

~T" CC

O

COQDQ_ onUJIQ

m

0g13v_0)0^ L_

(ujdq)

7-10
(ludq) Das u J9}p

7-11
REFERENCES

1. Goldberger, A. L. , Rigney/D. R., and West, B.J., Chaos

and Fractals in Human Physiology, Scientific American,

Feburary, 1990.

2. Akselrod, S., Gordon, D., Ubel, F., Shannon, D.,

Barger, A., and Cohen, R. , Power Spectrum Analysis of

Heart Rate Fluctuation: A Quantitative Probe of

Beat-to-Beat Cardiovascular Control, Science, vol. 213,

July, 1981.

7-12
8

N9 1-27 0916-'^

INCORPORATION OF SHUTTLE CCT PARAMETERS

IN COMPUTER SIMULATION MODELS

Final Report

NASA/ASEE Summer Faculty Fellowship Program - 1990

Johnson Space Center C _2

Prepared By:

Academic Rank:

University & Department:

S

Terry Huntsberger, Ph.D.

Associate Professor

University of South Carolina

Department of Computer Science

Columbia, South Carolina 29208

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleague:

Date Submitted:

Contract Number:

Space and Life Sciences

Man-Systems

PLAID Laboratory

Linda OnAugust 10, 1990

NGT-44-005-803

8-1
1

Abstract

Computer simulations of shuttle missions have become

increasingly important during recent years. The complexity of

mission planning for satellite launch and repair operations which

usually involve EVA has led to the need for accurate visibility and

access studies. The PLAID modeling package used in the ManSystems Division at Johnson currently has the necessary capabilities

for such studies. In addition, the modeling package is used for

spatial location and orientation of shuttle components for film

overlay studies such as the current investigation of the hydrogen

leaks found in the shuttle fleet.

However, there are a number of differences between the

simulation studies and actual mission viewing. These include image

blur caused by the finite resolution of the CCT monitors in the

shuttle and signal noise from the video tubes of the cameras.

During the course of this investigation the shuttle CCT camera and

monitor parameters are incorporated into the existing PLAID

framework. These parameters are specific for certain camera/lens

combinations and the SNR characteristics of these combinations are

included in the noise models. The monitor resolution is

incorporated using a Gaussian spread function such as that found in

the screen phosphors in the shuttle monitors.

Another difference between the traditional PLAID generated

images and actual mission viewing lies in the lack of shadows and

reflections of light from surfaces. Ray tracing of the scene explicitly

includes the lighting and material characteristics of surfaces. The

results of some preliminary studies using ray tracing techniques for

the image generation process combined with the camera and

monitor effects are also reported.

8-2
INTRODUCTION

Geometric properties such as visibility from a given vantage

point and clearance for movement are adequately modeled with the

PLAID package currently used in the Man-Systems Division at the

Johnson Space Center. This modeling package uses engineering

drawings and sketches to build a full three-dimensional database of

objects based on polygons. This database can then be used to

display a filled polygon view from any viewpoint. Clarity of the

image is only limited by the spatial resolution of the display device,

which is typically 1024 rows by 1024 columns. In an actual

mission scenario, the display device resolution is lower and camera

effects such as noise are inherent in the imaging process. This

study investigates the correction of the computer generated images

for degradation during the imaging process.

Surface material properties and lighting characteristics also

have an effect on the image generation process. There is a dynamic

relationship between the camera iris settings and the relative

brightness of surfaces in a scene. Strong variations in lighting can

be caused by strong reflective surfaces such as satellite shrouds, as

well as shadows due to payload occlusion of light sources.

Incorporation of these properties into the PLAID database structure

and image generation process is another major component of this

study. Preliminary results from some shuttle scenes are also

reported.

IMAGING SYSTEM EFFECTS

Finite monitor resolution and camera noise characteristics can

be modeled using parameters specified by the manufacturers. The

blurring caused by the lower display device resolution can be

modeled as a point spread function. In other words, a point in the

actual scene is displayed as a blurred circle on the monitor. This

process of blurring is illustrated in Figure 1, where Figure l(a)

shows the original intensity of the point in the scene as a narrow

peak and Figure l(b) shows the same point after spreading on the

monitor. The classical point spread function derived using the

8-3
Fourier transform would be a sine. This is an expensive function to

apply to an entire image and the same visual appearance can be

obtained using a Gaussian or triangle point spread function. The

original image is resampled using the horizontal and vertical

resolution supplied by the manufacturer for the display monitor.

(a)

Figure 1. Point spread process caused by monitor phosphors

System noise is the other source of degradation in the imaging

process. Noise manifests itself in the camera videotube and in the

connecting electronics and wires. Since it is extremely difficult to

measure the noise characteristics of the connecting wires, only the

videotube noise will be included in the correction process. If the

tube is in good calibration, noise will appear randomly throughout

the field of view. The amount of noise will depend on the settings

of the camera iris, since an iris setting that is narrow in a low light

setting will lead to a much greater degradation of the image. The

auto-iris setting of the camera causes this to happen most

frequently when there are extremely bright objects such as shroud

covered satellites in the scene. The iris will close down in this

situation with the result that areas in low light are extremely noisy.

Apart from iris effects, a Gaussian white noise process can be

used to model the degradation caused by the camera system. The

intensity of points in the image as sensed by the camera system are

randomly modified by sampling from a uniform Gaussian

8-4
distribution, whose width can be derived from the signal to noise

ratio (SNR) for the camera system. Once again this is information

that is supplied by the manufacturers of the system. This process

is equivalent to adding or subtracting a percentage of the intensity

of the actual image point for point in a random manner. Generally

the noise level of the camera system is plus or minus ten percent.

The next section discusses extensions to the monitor and camera

degradation processes.

SCENE EFFECTS

There are a number of possible extensions to the present

model. First, depth of field effects appear as blurring, dependent

on relative distance of objects in the scene from the camera. This

blurring must be part of the image generation process and can not

be added with post-processing. Second, the diffuse and specular

components of surface materials will have a direct impact on the

overall appearance of the scene. Finally, the effects of limited

lighting conditions or directional light will cause shadows in the

scene, which can obscure objects of interest. Two methods can be

used to add these extensions to the present model. These are ray

tracing and radiosity.

Ray tracing is a technique that recursively follows a light ray

from the observers' viewpoint throughout the scene to any light

source. This process traces the light ray path as it is reflected off of

surfaces or transmitted through transparent surfaces such as glass.

A ray is spawned for each picture element or pixel in the final

image, which is typically on the order of 1024 rows by 1024

columns. Since there are typically thousands of objects in a scene,

this is a computationally intensive task. As such, with the present

generation of computer hardware, it is not a real-time image

generation process such as that used in the present PLAID system.

However, single images can be generated using the present

computer hardware in about nine hours.

Radiosity is a technique that is based on thermal heat transfer

methods applied to light transmission. This method calculates the

light transferred between every pair of surfaces in the scene. As

mentioned previously, this is typically on the order of thousands of

surfaces. A set of simultaneous linear equations which is equal to

8-5
the number of surfaces is set up and solved using any of the

common techniques. This process is then followed by an image

generation step such as ray tracing. What is gained in the radiosity

step before ray tracing is the inclusion of the diffuse component of

scattered light from light sources, such as that cast from the Earth

into the shuttle bay.

Ray tracing was the method that was decided upon for the

preliminary investigations in this report. The shading model that

was used for the rendering portion of the ray tracing process was

that of Phong. This model includes ambient, diffuse and specular

components of the reflection process. It can be expressed as:

ks(R- V)n]

(1)

where Ia is the ambient intensity, IQ is the intensity of the light

source, ka, kd and ks are the ambient, diffuse and specular

coefficients, and n is the specular power factor. The various vectors

depend on the geometry of the surface, viewer and light source as

shown in Figure 2.

XXXXXXX/XXXX/XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

•xxxxxxxxxxxxxxxxx' •

•xxxxxxxxxxxx *

•xxxxxxx*

•xx •

xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

•xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

•xxxxxxxxxxxxxxxxxxxxxxxxxxxxx

•xxxxxxxxxxxxxxxxxxxxxxx* • •*

Figure 2. Scene geometry for surface shading.

Specification of surface characteristics relies on knowledge of kj, ks

and n. These factors can be derived from experimental data

collected in the NASA laboratories.

8-6
An example of this data is shown in Figure 3, taken from JSC

Internal Note 85-SP-l, where orbiter tile reflectance characteristics

are plotted vs. degrees off specular angle.

Reflectance,

percent

100 -p

80 -•

60 ••

s

40 -•

20 -•

0 --

^— Whit Whitee +i

 tile

Black tile

H—I—I—I—I—I—I—I—I—I—I—I—I—I—I—I

10 20 30 40 50 60

Degrees off specular angle

70 80

Figure 3. Reflectance vs. specular angle (From C.D.

Wheelwright, "Orbiter Solar/Artificial Illumination

During STS Flights," JSC Internal Note 85-SP-l).

The reflectance at 80 degrees will be entirely diffuse and this value

is kd. The reflectance at 0 degrees will be a mixture of diffuse and

specular, with the specular component being dominant. The dot

product term is unity at this angle and the total reflectance is equal

to k<i + ks at this point. Since kd is already known, ks can be found

directly. With a fixed light source position for the experiment, the

only variation expected in the reflectance curve would be due to

specular effects. Each experimental point can be then used to find a

value of n, the specular power factor, which is then averaged for

the value used in the Phong shading formula of Equation 1.

Surface colors and lighting positions are found in NASA

documents for the light source intensities and positions in the

Phong shading formula. The geometric database needed to derive

the surface normals, given by the vector N in Figure 2, is taken

directly from the PLAID polygon based description of any structure.

For example, the PLAID package can be used to build a description

of a specific shuttle mission with the appropriate satellites in the

8-7
payload bay. The vector V in Figure 2 is interactively derived

using the PLAID package or can be found in the documented

camera mount locations for most NASA structures.

EXPERIMENTAL STUDIES

Experimental studies were done on a planned shuttle mission

STS-46, which will carry the Tethered Satellite System (TSS) in

1991. Scene geometry was taken directly from the PLAID database

for this mission. The image was generated using the Craig Kolb

rayshade package from Yale University (available via anonymous

ftp at weedeater.math.yale.edu). Parameters for this preliminary

test are (1) diffuse surface materials; (2) image resolution of 512

rows by 512 columns; (3) all shuttle bay lights including the

forward payload bay bulkhead light on; (4) shuttle in the dark zone

of its Earth orbit; and (5) view position of Camera A on the payload

bay forward bulkhead. The result of the ray tracing of this scene is

shown in Figure 4. Although specular reflections are not present in

the scene, most of the visibility related effects are included, with

shadows cast along the length of the payload bay being of primary

importance.

Figure 4 shows the scene as it would appear to a human

observer through the payload bay forward bulkhead window.

Incorporation of the camera and monitor effects is easily

accommodated using the techniques described in the beginning of

this report. Application of the point spread function and the

Gaussian white noise distribution to Figure 4 gives the image seen

in Figure 5. The point spread function is derived using the

published CCTV monitor resolution of 300 rows by 400 columns.

Detail on the TSS is lost in this view due to the blurring.

Visibility studies using a different camera for this scene can

be done by changing the viewpoint. Switching to Camera B

mounted on the aft bulkhead of the shuttle bay should give an

indication of what the visibility is in the shadowed region of the

payload bay. This view is shown in Figure 6, and it can be seen

that there is little improvement in visibility with a change in

camera position.

Visibility in a region of shadow can be enhanced if the

mission is scheduled during the day portion. Substantial

illumination is obtained from reflection of sunlight from the Earth.

8-8
Figure 4. Ray traced image of STS-46 mission

Figure 5. Blurred ray traced image of STS-46 mission

8-9 ORIGINAL PAGE IS

OF POOR QUALITY
Figure 6. Shadow region ray traced image of STS-46 mission

Figure 7. Earthshine model ray traced image of STS-46 mission

8-10

ORIGINAL PAGE IS

OF POOR QUALITY
To accurately model this effect would require a radiosity treatment

of the imaging geometry. An approximation can be found using a

light source that is distributed over a large area during the ray

tracing image generation process. A ray traced scene with the same

viewing parameters as used in Figure 6 but with a distributed light

approximation to the Earth is shown in Figure 7. More of the

surfaces of the other payloads can be seen. The distributed light

approximation gives an indication of the better viewing conditions

and can, with increased time needed for the ray tracing,

realistically model the actual scene.

DISCUSSION

The PLAID modeling package used in the Man-Systems

Division at Johnson maintains an up-to-date geometric database of

NASA structures including the shuttle and Space Station Freedom.

The work discussed in this report extends the PLAID system to

include image degradation processes in the image generation

process. The point spread blurring function and noise

characteristics were taken directly from the shuttle CCTV monitor

and camera documentation, and integrated into a post-processing

step for image rendering.

In addition, this report presents some preliminary studies of

the use of ray tracing techniques for image generation. The PLAID

model database was extended to include surface material

characteristics which were obtained from NASA documentation of

experimental studies. Placement and strength of light sources,

information which is vital for visibility studies, was also obtained

from available NASA documentation. An experimental study of

shuttle mission STS-46 was done. Figure 4 in the main body of the

report shows an unblurred view of the shuttle payload bay for this

mission. After the degradation model is applied, detailed feature

observation is difficult, as can be seen in Figure 5. Visibility in

shadow regions was investigated using the same mission profile.

Figures 6 and 7 show the result of this study, where a night view is

shown in Figure 6 and a day view is shown in Figure 7. The models

used for the Earthshine phenomena are still in development, but an

fairly accurate idea of potential visibility problems can be found in

these first studies. The images shown in this report have lost

8-11
contrast due to the printing process, and can be found in their

original form in the videotape PLAID Graphics Lighting Studies

available as NASA Reference Master 903959 from the Television

Office at the Johnson Space Center or from the PLAID Graphics

Laboratory in the Man-Systems Division at Johnson Space Center.

Future work will include further extensions of the PLAID

modeling framework for faster ray traced previews of scenes. This

will be accomplished using a distributed parallel implementation of

the ray tracing algorithm. Better modeling of light source geometry

will also be studied. With these extensions, the PLAID model

database will be a suitable candidate for simulations of visible and

range sensor views of scenes in a semi-autonomous robotics

environment for NASA development of computer vision algorithms.

8-12
- £3

N9 1-27 00J/5

TRAINING EFFECTIVENESS OF AN INTELLIGENT TUTORING SYSTEM

PCS? A PROPULSION CONSOLE TRAINER

Final Report

NASA/ASEE Summer Faculty Fellowship Program - 1990

Johnson Space Center

Prepared by:

Academic Rank:

University & Department:

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleague:

Date Submitted:

Contract Number:

Debra Steele Johnson, Ph.D.

Assistant Professor

University of Houston

Department of Psychology

Houston, Texas 77204

Information Systems

Software Technology

Robert T. Savely

August 10. 1990

NGT-44-005-803

9-1
ABSTRACT

A formative evaluation was conducted on an Intelligent Tutoring System

(ITS) developed for tasks performed on the Propulsion Console. The ITS,

which was developed tey—AfHRL-primarily as a research tool, provides

training on use of the Manual Select Keyboard (MSK). Three subjects

completed three phases of training using the ITS: declarative, speed,

and automaticity training. Data was collected on several performance

dimensions, including training time, number of trials performed in each

training phase, and number of errors. Information was also collected

regarding the user interface and content of training. Suggestions for

refining the ITS are discussed. Further, future potential uses and

limitations of the ITS are discussed. The results provide an initial

demonstration of the effectiveness of the Propulsion Console ITS and

indicate the potential benefits of this form of training tool for

related tasks.

9-2
INTRODUCTION

Intelligent Tutoring Systems (ITS's) have been developed for a

variety of tasks, ranging from geometry to LISP programming. However,

little systematic evaluation has been conducted on these training

systems. Additional research is needed to systematically examine the

effectiveness of ITS's both during (formative evaluation) and upon

completion (summative evaluation) of software development. Conducting

a formative evaluation enables the developer to determine whether the

tutor is operating as planned and make program modifications as

necessary. A summative evaluation is focused on assessing the training

effectiveness of a completed ITS.

The ITS under consideration is still under development. Thus, a

formative evaluation was conducted to provide information on the

functioning of the system and the effects of the ITS on student

learning. Although there is not .general agreement yet about which

specific evaluation methods are preferred and how to implement them, the

information collected at least partially addresses internal and external

evaluation issues. Internal evaluation addresses how the tutoring

systems functions. External evaluation addresses the educational impact

of the tutoring system on students. The primary focus of the current

project is on external evaluation, although some information on internal

evaluation is also provided. In addition, given that a formative

evaluation was being conducted, the focus of data collection was more on

process measures than outcome measures. Formative evaluations tend to

rely more on process measures (e.g., patterns of task activities) rather

than outcome measures (e.g., task performance upon completion of

training).

BACKGROUND ON PROPULSION CONSOLE ITS

An ITS is under development by AFHRL which simulates use of the

Manual Select Keyboard (MSK) on the Propulsion Console used by flight

controllers. The purpose of the ITS development project was to develop

a tutoring system for a high performance task. A high performance task

is one in which the knowledge required is small, but extensive practice

is required to proceduralize the set of skills involved. This type of

task is often performed in situations in which high risk or expense is

involved. Thus, it may be difficult to provide extensive training in

the actual work environment. An ITS provides students an opportunity to

proceduralize a set of skills in a safe and relatively inexpensive

environment.

The MSK was selected for the training domain because it represents

a high performance task. Although little task information is required,

extensive practice is required to automate performance. Flight

controllers need to automate use of the MSK so that most or all of their

attention is available for performing other important console tasks. In

addition, the MSK ITS provides a demonstration of a training system that

could be expanded to other Propulsion Console tasks, highlighting future

9-3
potential training benefits for Propulsion flight controllers. Finally,

the MSK ITS has implications for other flight controllers because the.

MSK is used not only on the Propulsion Console but also on other flight

control consoles to perform similar tasks. Thus, this tutoring system

has potential training benefits for flight controllers in general.

The MSK ITS includes a domain expert (i.e., an expert model), a

trainee model, a training session manager, a scenario generator, and an

user interface. The domain expert includes information on how to

perform the task. The trainee model includes a record of student

performance. The training session manager provides information to the

student on performance accuracy and speed. The training session manager

also determines the amount and form of remediation to provide. The

scenario generator provides variations of the task actions to the

student. Finally, the user interface enables the student to interact

with the system—for this ITS using a 3-key mouse and five function

keys. (The function keys were only,used during automaticity training.)

As mentioned above, the training session manager provides

information on errors and determines the remediation. The error

messages and remediation provided depend on the phase of training.

Training is provided in three phases: declarative, speed, and

automaticity training. In the declarative phase, task action steps are

first described; guided examples are then provided, followed by unguided

examples. Guided examples require students to complete an action step

following a prompt. Unguided examples require students to complete all

steps in an action without being prompted at each step. To complete

declarative training, the student must correctly perform two consecutive

guided examples, then two unguided examples. Speed training requires

students to perform actions correctly and within a specified amount of

time. Finally, automaticity training requires students to perform dual

tasks correctly and at a specified speed. The primary task is the

performance of MSK actions. The secondary task involves correctly

responding to patterns of beeps. For both speed and automaticity

training, training is completed when the student has accurately

performed each task action twice and within a specified amount of time.

Error messages are provided immediately following an incorrect

step during initial training (i.e., during guided examples) and

following completion of a set of action steps during later training

(i.e., during unguided examples, speed, and automaticity training). If

an error is made during training, the student is remediated to the

previous level of training. For example, if an error is made during

speed training, the student is given an unguided example; if an error is

made on an unguided example, s/he is provided a guided example to

perform. In addition, the amount of tutoring content provided increases

for successive occurrences of a given error during guided examplesThis is consistent with recommendations made by other researchers. '

Remediation during automaticity training occurs only if speed and

accuracy criteria are not met, rather than after each occurrence of an

error.

9-4
METHOD

Task Overview

The MSK ITS trains students to perform five console operations:

TV Channel (TV Chan), Display Request (Disp Req), Display Decoder Drive

(DDD), Analog Event System (AES), and Flight Select (Fit Sel). In

addition, two operations have variations. The AES operation includes:

Select (AES Sel) and Deselect (AES Des). The DDD operation includes:

Select (DDD Sel), Release (DDD Rel), Reset Operation (DDD Reset Op),

Reset Critical (DDD Reset Crit), Select Drive (DDD Sel Drive), Select

Datatype (DDD Sel Data), and Select Lamp (DDD Sel Lamp). Thus, the

student learns a total of 12 task actions relating to 5 console

operations. In the current project, the criterion for promoting

students from speed training to automaticity training is two actions

completed without error and in less than 20 seconds on each of the five

console operations. The criterion for completion of automaticity

training is two actions completed without error and in less than 40

seconds on each of the five console operations. Moreover, the actions

must be completed with 100% accuracy on the secondary task (responding

to beep patterns). Students were asked to respond to two target beep

patterns (e.g., long-long-^short, short-long-short) and not respond to

false alarms (i.e., any of the remaining five beep patterns). Beep

patterns were administered at 3-second intervals.

Subjects and Procedure

Three students completed training on the MSK ITS. Two students

were flight controllers: one was a certified flight controller in onboard navigation with 3 years experience; one was a novice flight

controller on the trajectory console with 6 months experience. Both

were familiar with the MSK as used on their console, but unfamiliar with

its use on the Propulsion console. The third student was a researcher

in ITS's with no console experience. Students were asked to complete

training on the ITS. All instructions were provided by the tutoring

system. Additional informal observations and comments were collected

from the students on ITS content, functioning, and the user interface.

Measures

Performance data was collected by the ITS. For Level 1

(Declarative) training, performance measures included number of trials

and number of errors. For Level 2 (Speed) training, performance

measures included number of trials, number of errors, number of

successful trials, number of trials during remediation, and number of

errors during remediation. A successful trial was operationalized as

completing an action correctly in less than 20 seconds. For Level 3

(Automaticity) training, performance measures included number of trials,

number of errors, number of successful trials, number of remediation

9-5
cycles, number of trials during remediation, number of errors during

remediations. A successful trial was operationalized as completing an

action correctly in less than 40 seconds with 100% accuracy in

responding to beep patterns. Two successful trials of each of the five

operations was required to complete speed training and to complete

automaticity training. Results will be reported by task action for

Level 1 training, but across actions for Levels 2 and 3. In addition,

performance data was collected by action type during Levels 2 and 3

training to assess performance speed.

RESULTS

For Level 1 (Declarative) training, the three students performed

between 45 and 54 trials with between 6 and 9 errors, averaging 49

trials and 7.3 errors (see Table 1). Further, the students required

between 90 and 100 minutes to complete Level 1 training. Moreover, each

student completed additional training on DDD tasks beyond the two

consecutive, correct trials. It is unclear why the ITS administered the

additional task trials. In some cases the additional trials involved

actions on which students had previously made no errors. Further

information is needed to clarify this issue.

For Level 2 (Speed) training, the three students performed an

average of 30 trials (see Table 2). Results are reported across task

actions for this training level. Students required an average of 48.3

minutes to complete the training. During this time, students made 3.7

errors on average. Remediation trials were administered after each

error. On average, students completed 21.7 trials during remediation,

making an average of 3.7 errors during the remediation trials.

One interesting point is that the remediation provided following

an error did not necessarily correspond to the action on which the error

was made. For Fit Sel, TV Chan, and Disp Req, an error was followed by

remediation trials on the same action. However, an error on AES Sel was

often followed by remediation trials on AES Des. Similarly, an error on

one of the 7 DDD actions was often followed by remediation trials on

other DDD actions but not on the DDD action on which the error was made.

It would seem more beneficial to provide remediation on the action on

which the error was made.

Another interesting point is that students were not returned to

speed training following two consecutive, correct actions although this

was the criterion stated. For example. Student 1 correctly performed

the Disp Req action 7 consecutive times and DDD Res action 5 times

before returning to speed training. Student 2 correctly performed the

Disp Req action 9 consecutive times before being returned to speed

training and correctly performed the Disp Req action 3 times following a

second error and the AES Sel action 3 times. Student 3 also correctly

performed actions 3 to 4 consecutive times during remediation trials

before returning to speed training. Additional information is needed on

the decision rules used by the ITS for providing remediation.

9-6
TABLE 1. - PERFORMANCE IN LEVEL 1 (DECLARATIVE) TRAINING.

Student 1 Student 2 Student 3

Operation/ # of

Variation Trials

Fit Sel

Disp Req

TV Chan

AES Sel

AES Des

DDD Sel

ODD Rel

DDD Reset Op

DDD Reset Crit

DDD Sel Drive

DDD Sel Data

DDD Sel Lamp

8

4

4

6

3

4

2

2

4

2

7

2

# of

Errors

2

0

0

2

0

0

0

0

1

0

2

0

# of

Trials

7

4

4

5

7

2

4

4

2

2

2

2

# of

Errors

3

0

0

1

1

0

1

0

0

0

0

0

# of

Trials

11

6

4

4

2

3

6

3

2

6

3

5

# of

Errors

3

2

0

0

0

1

1

0

0

1

1

1

For Level 3 (Automaticity) training, the three students performed

an average of 35.3 trials (see Table 3). They required an average of 75

minutes to complete the training. During this time, students made an

average of 8.3 errors on actions. In Level 3 training, remediation

trials were administered not after each error, but rather if a

performance criteria was not met. The criteria involved beep response

accuracy, performance speed (i.e., > 40 seconds), and action errors.

Only one student received remediation during Level 3 training,

performing 18 trials and making 3 errors across 2 remediation cycles.

It is interesting to note that unlike previous training levels,

students required substantially different amounts of time to complete

Level 3 training. The dual task paradigm was quite novel for the two

flight controllers, at least partially explaining the differing time

requirements. These two students also reported finding performing two

9-7
tasks at one time difficult. The more experienced task controller,

however, appeared to have less difficulty. This may be due to greater

familiarity and experience with MSK tasks and console use.

One other issue relating to automaticity training is that the ITS

did not terminate training upon satisfying the performance criteria for

two of the students. The performance criteria was two successful trials

of each of the five operations (see above). Additional information is

needed to determine why training was not terminated when expected.

TABLE 2. - PERFORMANCE IN LEVEL 2 (SPEED) TRAINING.

# of Trials

# of Errors

# Successful Trials

# Remediation Trials

# Remediation Errors

Time Required (Min.)

Student

28

2

11

16

3

35

TABLE 3. - PERFORMANCE IN

# of Trials

# of Errors

# Successful Trials

# Remediation Cycles

# Remediation Errors

Time Required (Min.)

Student

29

9

10

0

NA

50

1 Student 2

37

3

11

18

2

50

Student 3

25

6

10

31

6

60

LEVEL 3 (AUTOMATICITY) TRAINING

1 Student 2

53

10

21

2

3

150

Student 3

24

13

13

0

NA

25

9-8
Two additional analyses were conducted. First, performance speed

was plotted against amount of task practice. One would expect students'

performance to fit a learning curve during Level 2 and possibly Level 3

(as they learn to perform the secondary task). However, logarithmic

functions did not explain as much of the performance variance as

expected, ranged from 4% to 58% variance accounted for (see Figure 1).

Thus, a second analysis was conducted to determine whether

discrepancies from the expected learning curve could be explained in

terms of amount of practice and response speed on specific task actions.

The 12 actions each had 6 task steps—with the exceptions of TV Chan (5

steps) and Disp Req (7 steps). However, it may have taken students

longer to perform actions they were less familiar with (i.e., had

received fewer trials of practice on). For Level 2 training, though,

TABLE 4. - PERFORMANCE PRACTICE AND SPEED IN LEVEL 2 TRAINING

Student 1

Operation/

Variation

Fit Sel

Disp Req

TV Chan

AES Sel

AES Des

DDD Sel

DDD Rel

DDD Reset Op

DDD Reset Crit

DDD Sel Drive

DDD Sel Data

DDD Sel Lamp

# of

Trials

3

9

3

3

0

5

1

0

0

0

2

0

Average

Response

Time

22.8

24.0

17.9

22.8

MA

24.1

21.9

MA

NA

NA

22.8

NA

Student 2

t of

Trials

7

3

3

6

2

3

5

1

0

1

0

2

Average

Response

Time

25.8

21.9

26.6

23.6

25.5

19.0

20.7

42.5

NA

25.4

NA

35.6

Student 3

# of

Trials

4

4

2

3

2

0

2

0

0

0

1

1

Average

Response

Time

18.7

22.3

14.9

23.2

20.6

NA

19.0

NA

NA

NA

21.5

23.7

9-9
the results do not indicate clear differences between response times for

either amount of practice (i.e., number of trials) or action type (see

Table 4). Similarly, for Level 3 training, the results do not indicate

clear differences between response times for either amount of practice

or action types (see Table 5). No specific pattern of response time

differences were observed across students in either training Levels 2 or

3 with the exception that speed on a specific action type increased with

additional task practice. For example. Student 1 increased response

time on Disp Req from 39.9 to 16.1 seconds across 7 trials of practice.

TABLE 5. - PERFORMANCE PRACTICE AND SPEED IN LEVEL 3 TRAINING

Student 1

Operation/

Variation

Fit Sel

Disp Req

TV Chan

AES Sel

AES Des

ODD Sel

ODD Rel

DDD Reset Op

ODD Reset Crit

DDD Sel Drive

DDD Sel Data

DDD Sel Lamp

# of

Trials

3

3

6

2

1

1

1

1

0

0

0

2

Average

Response

Time

32.8

24.5

20.4

33.0

30.2

34.8

40.5

26.3

NA

NA

NA

27.6

Student 2

# of

Trials

7

10

9

4

2

4

3

0

2

1

0

1

Average

Response

Time

41.3

33.6

18.4

24.8

28.2

26.9

22.0

NA

43.4

50.1

NA

26.3

Student 3

# of

Trials

3

4

2

3

1

0

1

0

1

1

1

1

Average

Response

Time

25.3

25.0

29.0

32.8

19.0

NA

29.5

NA

16.6

51.2

31.0

41.7

The lack of systematic differences in response times in different

action types was unexpected given that smaller amounts of practice were

received on some actions—most notably the 7 DDD actions. Indeed, as

9-10
Student 1 d) Student 1

c)

•o

c

<u

Student 2

Student 3

en

i

JL

01

E

H

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c

i

£

as

w

70-

60

50

40

30

20

10

T

1

n Jf

II , IV /I

illn / iit/1 i L/ \»\/ \/ii L

I I •

0 10 20 30 40 5

Trial

e)

80

2 70

^

g 601

1 50

40

20

10

0

(U

f)

•o

o

9!

§

S-

<u

at

80

70

60

50

40

30

20

10

0

Student 2

10 20 30

Trial

Student 3

40 50

10 20 30 40 50

Trial

Figure I.- Response time for task actions across trials. Speed

training in panels a, b, & c. Automaticity training in d, e, & f.

9-1 )
shown in Tables 4 and 5, no practice at all was received on some actions

in Levels 2 and 3 training. It was expected that the smaller amount of

practice would result in substantially increased response times. This

result was not observed. However, students did report more difficulty

performing the 7 DDD actions and suggested the provision of additional

training on these actions.

Finally, additional informal observations and comments were

obtained from the students on ITS content, functioning, and the user

interface. Several comments addressed training content. Specifically,

the students noted that action steps did not have to be performed in the

trained sequence on the job. Flight controllers using the MSK on the

Propulsion or other consoles may perform the steps of an action in a

variety of acceptable sequences. This was known by the software

developer. However, it was necessary to require action steps to be

performed in a specific sequence to facilitate the automaticity

training. The required step sequences did not affect the novice flight

controller although the experienced flight controller reported

difficulty performing the steps in the required sequence. She had

learned to use the MSK using alternate but acceptable sequences on the

job and reported that her previous experience interfered with task

performance on the ITS. Due to the small sample size (n=l) it is not

possible to draw conclusions, though, regarding the possible

interference between previous task experience and current ITS task

performance. In addition, the experienced flight controller noted that

it is unnecessary to perform some of the steps required for different

actions after the console has been initialized for a flight (Fit Sel).

Another comment addressed the amount of task practice provided on the

DDD actions, suggesting that additional practice be provided for each

action. This system currently treats the 7 DDD actions (and the 2 AES

actions) as part of one operation, which may explain why remediation

following an error in speed training did not necessarily match the

erroneous action. Finally, the novice flight controller reported that

the training was useful, providing information and experience she had

not yet obtained on the job. Similarly, the experienced flight

controller reported the ITS had potential training benefits for

Propulsion Console and other flight controllers although she recommended

modifying the task content to more closely resemble the job and address

additional components of the job.

The students also commented on ITS functioning. One issue raised

was that it was unclear what the criterion was for being promoted from

one phase of declarative training to the next. For example, the flight

controllers expressed some frustration about having to complete multiple

guided and unguided trials on a given action before moving to the next

action. This resulted in part from feedback messages stating that the

student was demonstrating effective performance and then stating that

additional practice would be provided on that action. It may be

appropriate to indicate to students how much additional practice they

can expect (e.g., they will be asked to complete one additional trial or

to successfully complete two consecutive trials). Additional

9-12
explanation may also be appropriate during speed and automaticity

training. For example, students did not initially realize during speed

training that the trial started as soon as the "Goal" (i.e., the action

assigned) was displayed on the screen. One student thought the trial

began (the timer started) when she clicked the mouse the first time

during the action. Moreover, students did not realize what the

performance criteria were for successful completion of speed or

automaticity training. It may be appropriate to give students more

information about what performance levels are necessary to complete

speed and automaticity training. Other student comments indicated that

students did not understand the purpose of the secondary task during

automaticity. Additional explanation could be provided regarding the

purpose of secondary task performance.

Finally, student comments addressed the user interface. One issue

raised was the use of scrolling rather than refreshing the tutoring/

information window. Declarative 'information and task assignments were

made in a window at the lower right portion of the screen. Students

reported difficulty reading the instructions provided, often rereading a

portion of the window because it was unclear where new information or

instructions appeared in the window. Refreshing the window when

additional information or instructions appear would resolve this issue.

A second issue related to the use of color. That is, students reported

difficulty seeing the red cursor (an arrow) against the purple

background. A third issue involved use of the mouse. Students were

initially unclear regarding the different functions of the left, middle,

and right mouse keys; the keyword descriptions provided in the MSK

display window were apparently not sufficient. A brief statement

explaining this could be provided at the start of training. A related

issue was that two mouse keys (left and right) were required to key in

numbers. Students suggested allowing the numbers to cycle from 9 to 0

(and 0 to 9) so that one mouse key could be used to change numbers,

although students appear to want one key (e.g., left key) to cycle

downward and a second key (e.g., right key) to cycle upward.

DISCUSSION AND CONCLUSIONS

The results indicate that students learned to perform 12 MSK

actions using the ITS. Further, they were able to successfully complete

training within approximately four hours. However, it is not clear that

students received sufficient task practice to automatize the skill.

Using the current 20-second and 40-second speed requirements during

speed and automaticity training, respectively, subjects performed any

given action a maximum of 37 times and as few as 2 times. To ensure

automaticity it may be necessary to implement more stringent speed

constraints which would result in additional task trials. Further,

additional information is needed to determine how the ITS functions in

terms of promoting students from one training level to the next and

terminating training. Also, some revisions to training content may be

appropriate to make ITS tasks more closely resemble job actions.

9-13
In terms of the ease of use, students required little or no

assistance in using the ITS. The ITS provided instructions and task

assignments which students could follow without outside assistance.

However, some clarification or additional explanation may be appropriate

to ensure that students understand the performance expectations and

progress of training. Some modifications may also be appropriate to

improve the interface, especially in terms of window refreshing and use

of color.

Finally, the results and student comments provide an indication of

potential training benefits of the ITS and modifications which may

further improve this training system. The results indicate that

students learn the training content. In addition, both flight

controllers reported that the training content was useful, especially

for novice flight controllers. Moreover, the ITS has potential benefits

for flight controllers on other consoles given the similarity of MSK use

across consoles. These potential benefits could be further increased by

expanding the training content to other console activities.

9-14
REFERENCES

Wenger, E. (1987). Artificial Intelligence and Tutoring Systems.

Los Altos, CA: Morgan Kaufmann.

•) Littman, D. & Soloway, E. (1988). Evaluating ITS's: The cognitive

science perspective. In M. C. Poison & J. J. Richardson,

Foundations of Intelligent Tlitoring Systems. Hillsdale, NJ:

Erlbaum.

3

Goldstein, I. L. (1986). Training in Organizations: Needs

Assessment, Development, and Evaluation. Monterey, CA:

Brooks/Cole.

4 Fink, P. K. & Overby, M. A. (1987). Research in Intelligent Tutoring

Systems for Knowledge Poor Domains. (SwRI Proposal 14-4874a). San

Antonio, TX: Southwest Research Institute.

Burton, R. R. & Brown, J. S. (1982). An investigation of computer

coaching for informal learning activities. In D. Sleeman & J. S.

Brown (Eds.), Intelligent Tutoring Systems. NY: Academic Press,

79-88.

6 Reiser, B. J., Anderson, J. R., & Farrell, R. G. (1985). Dynamic

student modelling in an intelligent tutor for LISP programming.

Proceedings of the 9th International Joint Conference on Artificial

Intelligence (Vol. 1, pp. 8-14).

9-15
N91-270 9

RE-EXAMINATION OF METMAN, RECOMMENDATIONS ON

ENHANCEMENT OF LCVG, AND DEVELOPMENT OF NEW CONCEPTS

FOR EMU HEAT SINK

Final Report

NASA/ASEE Summer Fellowship Program -- 1990

Johnson Space Center

\l

Prepared by:

Academic Rank:

University & Department:

Amir Karimi, Ph.D.

Associate Professor

The University of Texas at San Antonio

Division of Engineering

San Antonio, Texas 78285

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleague:

Date Submitted:

Contract Number:

Engineering

Crew and Thermal Systems

Thermal Systems

Chin H. Lin, Ph.D.

November 1, 1990

NGT-44-005-803

10-1
ABSTRACT

METMAN is a 41-node transient metabolic computer code developed in 1970 and

revised in 1989 by Lockheed Engineering and Sciences, Inc. This program relies on a

mathematical model to predict the transient temperature distribution in a body influenced by

metabolic heat generation and thermal interaction with the environment. A more complex

315-node model (Wissler-model) is also available that not only simulates the thermal

response of a body exposed to a warm environment, by-including-in-the model the

-perfusion rate in muscle and the magnitude of counterflow heat exchange between large

-arteries-and-veinsy but is also capable of describing the thermal response resulting from

exposure to a cold environment. It is important to compare the the two models for the

prediction of the body's thermal response to metabolic heat generation and exposure to

various environmental conditions. Discrepancies between the two models may warrant an

investigation of METMAN to ensure its validity for describing the body's thermal response

in space environment.

The Liquid Cooling and Ventilation Garment is a sub-system of the Extravehicular

Mobility Unit (EMU). Designedly ILC-Dover in the 1960's,' this garment, worn under the

pressure suit, contains the liquid cooling tubing and gas ventilation manifolds; its purpose

is to alleviate or reduce thermal stress resulting from metabolic heat generation. There is

renewed interest in modifying this garment through identification of the locus of maximum

heat transfer at body-liquid cooled tubing interface.

The sublimator is a vital component of the Primary Life Support System (PLSS) in

the EMU. It acts as a heat sink to remove heat and humidity from the gas ventilating circuit

and the liquid cooling loop of the LCVG. The deficiency of the sublimator is that the ice,

used as the heat sink, sublimates into space. There is an effort to minimize water losses in

the feedwater circuit of the EMU. This requires developing new concepts to design an

alternative heat sink system.

We-direeted-our. efforts to review and verify the heat transfer formulation of the

analytical model employed by METMAN. We-reeommend a conceptual investigation of

regenenerative non-venting heat-sink subsystem for EMUV < . ,-.-- > •-;.••/ |

10-2
INTRODUCTION

Considerable effort has been made by physical scientists and engineers to develop

mathematical models to describe natural phenomena through mathematical models. Those

efforts include attempts to model the human thermal system. The models are designed to

simulate the effects of heat generation, resulting from physical activities, and the heat

exchange between the body and its environment on heat transfer within the body.

Although our understanding of many important physiological phenomena remains

incomplete, it is important to use mathematical modeling for prediction of human response

to a variety of stressful environmental conditions. These applications become essential in

situations for which it is at least difficult, if not impossible, to conduct experiments on

human subjects. Examples include the thermal effects on astronauts during lunar

missions, or extravehicular activities (EVA), thermal response of humans while diving in

cold water and the effect of thermal stress on workers who must perform their assigned

duties under thermally hostile environments. Applications could be extended to various

survival situations involving accidental immersion in cold water or military personnel who

have to perform their duties under chemical or biological warfare environmental situations.

The threat posed to humans by these conditions has long been recognized.

Mathematical modeling of human thermal systems dates back to 1947, when

Machle and Hatch [1] introduced the concept of core and shell temperatures (rectal and

mean skin temperatures, respectively). In their model the stored energy in the body was

expressed as linear function of core. Pennes1 cylindrical model [2] (1948) provided a

reasonable temperature profile in the forearm. Wissler's first model [3] extended Pennes'

model by employing six cylindrical elements to describe the entire human thermal system.

Extensive application of mathematical modeling of human thermal systems began

with NASA's Apollo program. Stolwijh [4] developed a model to predict the astronauts'

thermal response during the extravehicular activities (EVA). To achieve this a transient

metabolic man computer program (METMAN) was developed to describe the temperature

profile in the body. METMAN's initial construction was based on a two-model point

model and later was extended to an eight-node, a 14-node, a 25-node and to the present 41-

node model [5]. This model has been adequate to predict thermal behavior in the body

resulting from thermal stress. Wissler's latest 250-node and 315-node physiological

models [6,7] were mainly designed to describe the human thermal response resulting from

exposure to cold environments. They have been used to analyze the performance of divers

working in water as deep as 450 meters. In recent years they have also been used to

describe human thermal experience working or exercising in a hot humid environment.

The advantage of Wissler's model over METMAN is that it has a wider range of

applications. It can be used for predication of thermal response for humans exposed to hot

or cold environments, while METMAN's range of application is limited to hot

environments. Wissler's model considers factors which are important in cold subjects.

They include the perfusion rate in muscle and counter flow heat exchange between large

arteries and veins. This thermal model contains mass balances for oxygen, carbon dioxide,

and lactic acid required in equations for perfusion and ventilation. However, Wissler's

model is poorly documented and is difficult to use. METMAN's advantage over Wissler's

10-3
model is that it is well documented and easy to use. It also has been developed specifically

for space application.

The problem of rapid increase in body temperature becomes significant when an

individual has to wear special protective clothing to be isolated thermally and/or otherwise,

from hazardous surroundings. Although such clothing protects the individual from a

hostile environment, it also places additional thermal stress on the individual, as the

generated metabolic heat cannot be directly dissipated into the environment by natural

means. Therefore, to make such micro-environments habitable, fluid-conditioned suits

have been designed to reduce thermal stress. A fluid-cooled garment is usually warn and

is placed in direct contact with the skin.

A fluid-cooled garment may consist of cold liquid flowing in a network of flexible

tubes which come in direct contact with the heat source (body), or conditioned air flowing

against the body or a combination of both. A cold fluid (typically, in the range 5 to 20 °C)

is used to remove a portion or all of the metabolically generated heat from the body. On

return cycle, heat is rejected to a heat sink medium. The ILC Dover liquid cooled

conditioned vest has been used in space applications. A modified (half-length) version of

this suit is also been used by USAF for military application. In recent years USAF has

directed its efforts in intermittent method of ambient air cooling. References [8-11] provide

typical performances of liquid cooled garments and air conditioned suits.

A heat sink for a life support system may consist of an ice pack heat exchanger, a

small vapor-compression cooling unit. A thermal heat sink is a vital component of the

Primary Life Support System (PLSS) in the Extravehicular Mobility Unit (EMU). It is

required to remove heat and humidity from the gas ventilating circuit, to cool the liquid

cooling loop of the LCVG, and to eliminate other EMU equipment thermal load. The

present heat sink subsystem in the EMU consists of a sublimator. The ice formed in the

sublimator is used as the heat sink for heat removal and the vapor product is vented into

space. To minimize the water losses in the feedwater circuit of the EMU, NASA has

identified a need for developing a regenerable non-venting heat sink (RNTS) subsystem for

advanced extravehicular activities (EVA). The subsystem must address the EMU thermal

control requirements of the existing Shuttle Orbiter, the Space Station EVA mission, and

the Man-Mars mission.

The Shuttle EVA missions require RNTS operations of up to four hours duration

with a cumulative heat removal capacity of up to 7240 Btu. They require heat removal rates

in the range 310-3445 Btu/hr, with an average rate of 1810 Btu/hr for the entire EVA

mission. The liquid-cooling and ventilation garment (LCVG) inlet water temperature should

not exceed 45°F at maximum thermal load during the Shuttle EVA mission. The Space

Station EVA mission has a maximum duration of 8 hours with a cumulative heat removal

capacity requirement of up to 11,680 Btu. It requires an RNTS operation with a heat

removal rate in the range of 310-2695 Btu/hr, with an average rate of 1460 Btu/hr for the

entire mission. The liquid-cooling and ventilation garment (LCVG) inlet water temperature

should not exceed 60°F at maximum thermal load during the space station EVA mission.

A series of feasibility studies have been conducted [12-14] for the development of

a RNTS thermal control for the EMU. The studies suggested a thermal control subsystem

utilizing a water/alcohol phase change thermal storage for the Shuttle EVA mission and a

thermal control subsystem consisting of a vapor compression heat pump/space radiator

10-4
integrated with a water/ethanol phase change medium thermal sink for the Space Station

EVA mission. The proposed thermal control subsystems are heavy for the lunar and Mars

EVA missions.

This report concentrates on a review of mathematical modeling and physical

concepts used in the METMAN. Its purpose is to point out shortcomings of the model

and, when possible, to make recommendations for improvement.

DESCRIPTION OF THERMAL MODEL

Both METMAN and Wissler's models are transient-state models which predict

thermal and metabolic changes that occur during a certain period of time. Given initial

values for all dependent variables and specification of independent variables, they both

evaluate nodal temperatures at various time periods and compute thermal storage within the

body. Each program is capable of predicting body-thermal behavior subject to different

modes of operation. The modes of operation of METMAN include shirt-sleeve, normalsuited intravehicular activity (IVA), extravehicular activity (EVA) and helmet off. The

METMAN and Wissler's models are based on similar descriptions of the human body. In

METMAN, as shown in Figure 1, the human form is divided into 10 cylindrical elements:

head, trunk, right and left arms, right and left legs, and right and left feet. Each element is

further divided into four concentric compartments. They include a central core, muscle, fat

layer and skin. Each compartment is represented by a nodal point. Therefore, including

the central blood as a compartment, the METMAN model is constructed around 41 nodal

points. The temperature throughout each compartment is assumed to be uniform, equaling

its nodal point.

The Wissler model as shown in Figure 2 is based on 15 major cylindrical elements:

head, upper torso, lower torso, right and left proximal arms, right and left medial arms,

right and left distal arms, right and left proximal legs, right and left medial legs, right and

left distal legs. Within each element there are 15 nodal points representing a

conglomeration of tissue, bone, fat, skin and a vascular system containing arteries, veins

and capillaries. The model includes up to six additional nodal points, external to the body,

for computation of temperature and accumulation of sweat within clothing. Thus, the

nodal points in this model may exceed 300, depending upon the mode of operation.

DISCUSSION

A human thermal model must account for the following factors. It should be

capable of describing temperature as a function of position and time. It should account for

the geometry of the human body. It should consider that properties vary with position

throughout the body. It should account for metabolic heat generation resulting from various

types of work and environmental conditions. It should account for heat and mass transfer

in the respiratory tract. And it should account for all thermal interactions of body with its

environment. Thus it is important that the physical modeling of thermal behavior in the

body also include the effects of fluid-cooled garment-body interactions.

10-5
MAGNIFIED VIEW OF HAND

SEGMENT

SHOWING POUR COMPARTMENTS

9 10

-99*

' (r)

JO CYLINDRICAL SEGMENTS OF THE

BODY

TmweW

0

Core

Ctna

Skin

Figure 1, Geometric Representation of Human Body by METMAN Model

10-6
PROXIMAL MEDIAL DISTAL

LEFT ARM LEFT ARM LEFT ARM

HEAD

PROXIMAL MEDIAL DISTAL

RIGHT ARM RIGHT ARM RIGHT ARM

LOWER

TORSO

PROXIMAL

LEFT LEG

MEDIAL

LEFT LEG

DISTAL

LEFT LEG

UPPER

TORSO

PROXIMAL

RIGHT LEG

MEDIAL

RIGHT LEG

DISTAL

RIGHT LEG

Figure 2. Geometric Representation of Human Body by Wissler's Model

10-7
The heat transfer formulation of METMAN model is described in detailed in [5]. Therefore,

we limit this report to few equations necessary, and refer the reader to this document for

detailed description of thermal system.

The energy balance for each compartment is based on the following general

relationship.

Qst = Qm t Qct Qr - Qe t Qk t Qres

Where Qa is the rate of energy storage, Qm is the metabolic heat generation, Qc is

convective surface heat transfer, Qr is the radiation heat transfer at the surface, Qe is the

rate of evaporation losses, Qkis the rate of conductive heat transfer, QKS is the rate of heat

transfer through respiratory tract and Q is the heat transfer with the liquid-cooled

garment.lt should be noted that Qc, Qr and Qe are zero for internal compartments and they

are important at skin compartment.

The rate of energy stored in each compartment can be expressed by:

The rate of heat generation, Qm, in the body is the sum of the basal metabolic rate

and heat generated through work or shivering by muscles. METMAN model considers the

effect of the height and the mass of an individual in evaluating the basal metabolic rate. The

relations used in evaluation of heat generation are given in [5]. METMAN uses a

distribution coefficient, Km** to evaluate the heat produced by work in each muscle

compartment. These distribution coefficients are presented in Table 1. It indicates that the

leg muscles' contribution to heat generation dominates all other body elements. These

distribution coefficients are reasonable for work in a gravitation field. However, in a

micro-gravity environment the major work is done by the arms. Therefore, it appears that

the METMAN uses unreasonable distribution coefficients for the evaluation of heat

production in the muscle compartments.

The heat transfer between internal body compartments occurs through conduction

and vascular convection. The METMAN model assumes a uniform temperature, equal to

the nodal point temperature, throughout each compartment. It employs the thermal resistant

analogy, as shown in Figure 3, to evaluate the conductive heat transfer between two

adjacent compartments. The internodal conductances are calculated based on the following

relationship:

In

n >1

 +.

g

i

The variables in Equation (3) are defined in Figure 3.

10-8
Table 1. DISTRIBUTION COEFFICIENT, K^ OF HEAT PRODUCED BY WORK

AMONG THE MUSCLE COMPARTMENTS

Body Element KOJW

Head OOO

trunk 0.30

Arms 0.08

Legs 0.60

Hands 0.01

Feet OJU

1.00

A uniform temperature distribution assumption for each compartment would

present temperature discontinuities at the interface of two adjacent compartments. To

improve the model we recommend the addition of appropriate boundary conditions for each

compartment. Along the axis of each cylindrical element the boundary condition (central

core) is

8T.

Equation (4) indicates that along the element's central axis the temperature is either a

minimum or a maximum. Subscript j refers to jp element At the interface between the

compartments, both temperature and thermal conduction must be continuous. This implies

that

-OJ^ (5)

and

9T. 8T.

subscripts i and i + 1 refers to the 1th and (i + I)1*

1

 compartment of the j* element

Intrinsic convection is the result of heat transfer between the tissue compartments

and the vascular system. The heat transfer between skin and environment depends on the

micro or macro environments. The mechanism for this mode of heat transfer may include

extrinsic convection, radiation, latent heat transfer (evaporation of sweat), heat transfer to

the undergarment, heat transfer to the liquid-cooled garment and respiratory heat transfer.

These modes of heat transfer are described in detail in [5].

Four active controllers are included in the METMAN model. These are sweat

production, shivering, vasodilation and vascodilation. They play an important role in

maintaining the body in an isothermal state. The relations used to describe the human

thermoregulatory system are based on experimental results.

10-9
c/5

D

C

.

>

u

O

>

ca

•g

C

UJ

Q

o

1

:

tJJO

10-10
In various mode of operations METMAN compares the effect of natural convection

with forced convection and chooses the greater value for convective heat transfer. The

forced convection is presented by:

qsenc = 0.212 (Pcab Vcab )1/2

 KI

 Ac (Tug - Tcab ) (7)

and the free convection is given as:

qsenc = 0.06 [ G (Pcab )2

 I Tug - Tcab I ]1/4 K2 Ac (Tug - T cab) (8)

However relation are available for combined effects of free and forced convection. The

following relationship is used to establish the dominant regions of free and forced

convection.

Gr

 _g(3(T w - Te o )L

Re2 u

2

o

When the LHS of Eq. 9 » 1 then the free convection dominates. If the LHS of Eq. 9 «

1, then forced convection dominates, in all other cases forced and free convections are of

comparable magnitude. References [15-23] describe the combined free and forced

convections for various geometric configurations.

In general heat transfer between the skin and environment depends on the mode of

operation. The METMAN model can be applied to various modes of operation. This

includes the shin-sleeve model which emulates a man in a cabin, or in any environment,

wearing an undergarment, as well as the suited mode which describes a man in a space

suit. The space suit model itself can be applied to several modes of operation. The EVA

suited mode is used to model extravehicular activity. The IVA model is used to identify

intravehicular activity. METMAN is also capable of modeling the suited modes of

operation for both the helmet off and the purge flow activity.

The METMAN program utilizes a number of subroutines and functions which are

generally used to determine physical parameters and thermophysical properties. Among

these subroutines are Function DEWPT and Function VVP. Function DEWPT evaluates

the saturation temperature for a given vapor pressure. Function VPP determines saturated

vapor pressure for a given temperature. Both functions are based on old relations in which

three separate equations are used to describe the vapor pressure curve. Each equation is

valid only within a limited range of temperature and pressure. In addition, the equation

used by METMAN for the evaluation of dewpoint at very low pressures (0.0<P<0.0185

Psia) is highly inaccurate.

There are modern equations of state and fundamental equations [23-27] available now that

describe a wide range of thermodynamic regions with a single relation. The fundamental

equation developed by Haar et. al [27] is the most recent and accurate relation for

thermodynamic properties of water. A FORTRAN computer code is included in [14] for

the evaluation of the thermodynamic properties of water. Inclusion of this computer code

will enhance the METMAN model.

10-11
There are many parameters that should be considered in selection and design of a

thermal control subsystem for the EMU. These include the size and the weight of the

subsystem, thermophysical and thermal transport properties, and operational safety during

an EVA mission. For example, the selection of a heat sink medium should not be' based

solely on the total heat capacity of the heat sink material, but should also consider the size

of equipment required for the freezing and melting processes.

We must identify a heat sink concept that will minimize the size and the weight of

the thermal control subsystem required for the EMU. To achieve this goal we must to reexamine and extend the existing alternative technologies for the heat sink medium. This

includes a feasibility study of:

o phase change materials with a suitable melting-freezing temperature

o heat pipe technologies

o eutectic binary solutions

o thermoelectric technologies

o heat of solution of mixtures

o endothermic and exothermic heat of chemical reactions

CONCLUSIONS AND RECOMMENDATIONS

The METMAN thermal model in its present form is adequate to describe the heat

transfer phenomena in a warm subject. However, there are deficiencies present in the

current model. Following is a summary of the shortcomings of the present model and

recommendations for improvement.

1. The distribution coefficients used by METMAN to evaluate the heat generation in the

muscle compartments are unreasonable for space application. These coefficients should

be adjusted for EVA missions in the microgravity environment. Further physiological

study is recommended in this area.

2. The METMAN model can be further improved by including appropriate boundary

conditions along the central axis of each cylindrical element and along the interface of

two adjacent compartments. These boundary conditions are presented in Equations (4-

6) in the text.

3. The present equations used by METMAN for the evaluation of dewpoint temperatures

and water vapor pressures are inaccurate. We recommend that the FORTRAN

computer code given in [14] for the evaluation of the thermodynamic properties of

water be incorporated into the METMAN model.

4. Addition of external nodal points for the evaluation of temperatures and the amount of

sweat accumulation will enhance the METMAN model

5. The heat transfer formulation of METMAN is based on old knowledge. We recommend

that METMAN be revised to include advances in heat transfer research.

A conceptual investigation in desired to determine alternative heat sink for the

EMU.

10-12
REFERENCES

1. Machle, W., and Hatch, T.F. Heat: Mass exchanges and physiological responses.

Phvsiol. Rev. 27, 200-227, 1947.

2. Pennes, H.H. Analysis of tissue and arterial blood temperatures in the resting forearm.

J. Appl. Phvsiol. 1, 93-122, 1948.

3. Wissler, E.H. Steady-state temperature distribution in man. J. Appl. Phvsiol. 16,

734-740, 1961.

4. Stolwijk, J. A. J., and Hardy, J.D. Temperature regulation in man - A theoretical

study. Pflugers Arch. 291. 129-162, 1966.

5. Bue, G.C., Milliken, A.H., Cook, D., and Franklin, G.C., "Computer program

documentation-41-Node Transient Metabolic Man Program," Lockheed Engineering

and Sciences Co., LESC-27578, CTSD-0425, October 1989.

6. Wissler, E.H. Comparison of results obtained from two mathematical models - A

simple 14-node model and a complex 250-node model. J. Phvsiol. (Paris') 63. 455-

458, 1970.

7. Wissler, E.H. A mathematical model of the human thermal system. Bull. Math.

Biophvs. 26, 147, 1964.

8. Burton, D. R., "Performance of Water Conditioned Suits," J. Aerospace Medicine.

(May 1966), pp. 500-504.

9. Chen, T. Y., Bomalaski, S.H. and Constable, S. H., "Development of a Light Weight

Ambient Air Cooling Unit for Use During Operations in a Chemical Defense

Environment," USAF/Sam Brooks AFB., 1990.

10. Constable, S. H., "Alleviation of Thermal Stress in Ground Crew Supporting Air

Operations During a Chemical Warfare Scenario," USAF/SAM Brooks AFB.

11. Harrison, M. H. and Belyavin, A.J., " Operational Characteristics of LiquidConditioned Suits," J. Aviat. Environ. Med.. 49(8) (August 1978), pp. 994-1003.

12. "Subsystem Conceptual Study Report for the Regenerable Non-venting Thermal Sink

(RNTS)," United Technologies, Hamilton Standard, Final Report, Contract No.

NAS9-16609, December, 1982.

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Activity Portable Life Support System (Regenerable Nonventing Thermal Sink -

RNTS I),", United Technologies, Hamilton Standard, Final Report, NAS9-16609,

DRL No. T-1700, March 1986.

14. "The Advanced Nonventing Extravehicular Activity Cooling System (RNTS II),",

United Technologies, Hamilton Standard, Final Report, NAS9-17301, DRL No. T1833, January 1988.

10-13
15. Lloyd, J.R.., and E.M. Sparrow: "Combined Forced and Free Convection Flow on

Vertical Surfaces, Int. J. Heat Mass Transfer. 13:434-438 (1970).

16. Wilks, G. "Combined Forced and Free Convection Flow on Vertical Surfaces," Int. J.

Heat Mass Transfer. 16:1958-1964(1973).

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Approximation in Horizontal Boundary Layers," J. Hydronautics. 6:34-39 (1972).

18. Robertson, G.E., J.H. Seinfeld, and G.E. Leal: "Combined Forced and Free

Convection Flow Passed a Horizontal Flat Plate," AIChE J.. 19:998-1008 (1973).

19. Yuge, T.: "Experiments on Heat Transfer from Spheres Including Combined Natural

and Free Convection," J. Heat Transfer. 82Q214-220 (1960).

20. Mucoglu, A., and T.S. Chen: "Mixed Convection across a Horizontal Cylinder with

Uniform Surface Heat Flux," J. Heat Transfer. 99C:679-682 (1977).

21. Newell, P.H., and A.E. Bergles: "Analysis of Combined Free and Forced Convection

for Fully Developed Laminar Row in Horizontal Tubes, J. Heat Transfer. 90C83-93

(1970).

22. Sabbagh, J.A., A. Aziz, A.S. El-Ariny , and G. Hamad: "Combined Free and Forced

Convection in Circular Tubes," J. Heat Transfer. 98C:322-324 (1976).

23. Patankar, S.V., S. Ramadhyani, and E.M. Sparrow: "Effect of Circumferentially

Nonuniform Heating on Laminar Combined Convection in a Horizontal Tube," £.

Heat Transfer. 100C63-70 (1978).

24. Irvine, T.F., and Lilely, P.E., Steam and Gas Tables with Computer Equations.

Academic Press.New York, 1984.

25. Karimi, A. and Lienhard, J., "A Fundamental Equation Representing Water in Stable,

Metastable and Unstable States", EPRINP-3328, RP 1438-2, Final Report, December

1983, 322 pp.

26. Keenan, J.H., Keyes, F.G., Hill, P.G., and Moore, J.G., Steam Tables (S.I. Units).

John Wiley & Sons, New York, 1978.

27. Haar,L., Gallagher, John S., and Kell, G.S..NBS/NRC Steam Tables. McGraw Hill,

New York, 1984.

10-14
BIBLIOGRAPHY

1. Cook, D.W., Nguyen, N.H., "Liquid Cooled Garment Overall Heat Transfer

Coefficient Definition," Technical Memorandum, Lockheed Engineering and

Management Services Company, LEMSCO-15410 (August 1980).

2. Cook, D.W., and Nguyen, N. H., "Shirt Sleeve Comfort as Affected by Body Size,"

Lockheed Electronics Company, LEG-13401 (May 1979)

3. Cook, D. W., "Addition of Solar Effect Option to 41-Node Man Program," Technical

Memorandum, Lockheed Electronics Co., LEG-10195 (March 1977).

4. Fanger, P.O., Thermal Comfort, McGraw-Hill, New York (1970).

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6. Houdus, Y. and Ring, E. F., Human Body Temperature. Its Measurement and

Regulation. Plenum Press, New York, 1982.

7. Inouye, J., Hick, F.K., Tesler, S.E., and Keetan, R.W., "Effect of relative humidity

on heat loss of men exposed to environments of 80, 76, and 72°F," ASHRAE Trans.,

Vol. 59 (1953), p. 329.

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Coefficient," Technical Memorandum, Lockheed Engineering Management and

Sciences Company, LEMSCO-25665, (June 1988).

9. Karimi, A., "A Thermal Evaluation of the 'LSSI' Liquid-Cooled System: An

Engineering Perspective", USAF Summer Faculty Program, Technical Report, Vol.

1/2, Report No. 48, September 1983, 23 pp.

10. Karimi, A. and Patel, P., "A Liquid-Cooled Garment-Body-Interfaced Model Study

for Intermittent Cooling", Final Report, Brooks AFB (In preparation).

11. Karimi, A., "Design and Evaluation of Intermittent Liquid Cooling System for Ground

Crew Personnel", Final Report, Brooks AFB, 1988.

12. Karimi, A., "Thermodynamic Analysis of Liquid Cooling Technology", Final Report,

SCEEE/ARB/85-63, May 1986, 52 pp.

13. Karimi, A., "A Thermal Evaluation of a Portable Battery-Operated Vapor Compression

Cooling System", Final Report UES/F49620-85-C-0013, September 1985, 25 pp.

14. Karimi, A.," An Experimental Study of the Portable Liquid-Cooled System", Final

Report, SCEEE/RPI Subcontract No. 83 RPI20, December 1984, 35 pp.

10-15
15. Keslake, D. M., "Errors Arising from the Use of Mean Heat Exchange Coefficients in

the Calculation of the Heat Exchanges of a Cylindrical Body in Transverse Wind,"

Temperature. Vol. 3, Biology and Medicine. J.D. Hardy (Editor), New 'York,

Reinhold (1963), pp. 183-190.

16. Lin, C.H. and Berenson, P.J., "Study of the Thermal Processes for Man in Space,"

Air Research Manufacturing Co., NASA CR-216 (1965).

17. Nguyen, N. H., Hu, A.S., "Body Size Effect on Shuttle EMU Comfort Curves,"

Technical Memorandum, Lockheed Engineering and Management Services Company,

LEMSCO-16363, (March 1981).

18. Nguyen, N. H., "Shuttle EMU Comfort as Affected by Body Size," Technical

Memorandum, Lockheed Engineering and Management Services Co., LEMSCO14567 (March 1980).

19. Nguyen, N. H., "Updated Shuttle EMU Comfort Curves," Technical Memorandum,

Lockheed Electronics Company, AMD/173 (December 1978).

20 Olschewski, H. and Bruck, K., " Thermoregulatory, Cardiovascular, and Muscular

Factors Related to Exercise after Preceding," J. Appl. Physiol.. 64(2), 1988, pp.

803-811.

21. Pimental, N. A., Cosimini, H. M., Sawka, M. N., and Wenger, C. B., "Effectiveness

of an Air-Cooled Vest Using Selected Air Temperature and Humidity Combinations,"

Aviation. Space, and Environmental Medicine. (February 1987), pp. 119-124.

22. Shitzer, A. and Chato, J.C. "Analytical Solutions to the Problem of Transient Heat

Transfer in Living Tissue," J. Biomedical Engineering. Vol. 100, (November 1978),

pp. 202-210.

23. Smith, E., "Establishing a Minimum UA for LCG," Internal Memorandum, Hamilton

Standard, I.D. # H 78-003-GC (March 1978).

24. Stolwijk, J.A. J," A Mathematical Model of Physiological Temperature Regulation in

Man," NASA CR-1855, (August 1971).

25. Stolwijk, J.A.J., "Expansion of a Mathematical Model of Thermoregulation to Include

High Metabolic Rates," NASA CR-1855 (1971).

26. Werner, J., and Buse, M., "Temperature Profiles with Respect to Inhomogeneity and

Geometry of the Human Body'" J. Appl. Phvsiol. 65 (3), 1988, pp. 1110-1118.

10-16
N91-2709 Q

A NONRECURSIVE ORDER N PRECONDITIONED

CONJUGATE GRADIENT / RANGE SPACE

FORMULATION OF MDOF DYNAMICS

Final Report

NASA/ASEE Summer Faculty Fellowship Program -1990

Johnson Space Center

Prepared by:

Academic Rank:

University & Department:

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleague:

Date Submitted:

Contract Number:

Andrew J. Kurdila

Assistant Professor

Texas A&M University

Department of Aerospace Engineering

College Station, Texas 77843

Engineering

Navigation, Control and Aeronautics

Guidance and Control Systems

John Sunkel

Tuyen Hua

Larry McWhorter

August 10,1990

NGT-44-005-803

11-1
ABSTRACT

While excellent progress has been made in deriving algorithms that are efficient for certain

combinations of system topologies and concurrent multiprocessing hardware, several

issues must be resolved to incorporate transient simulation in the control design process for

large space structures. Specifically, strategies must be developed that are applicable to

systems with numerous degrees of freedom. In addition, the algorithms must have a

growth potential in that they must also be amenable to implementation on forthcoming

parallel system architectures. For mechanical system simulation, this fact implies that

(^Algorithms are required that induce parallelism on a fine scale, suitable for the

emerging class of highly parallel processors.'' ; , «

s»(iii)vTfansient simulation methods must be automatically load balancing for a wider

collection of system topologies and hardware configurations.

;v -: Q^:, , • <-r\

This-paper»addresses Jhese problems/by employing a combination range space /

preconditioned conjugate gradient formulation of multi-degree-of-freedom dynamics. The

method described hereinJias several advantages. In a sequential computing environment,

the method has the features that:

"(iy^By employing regular ordering of the system connectivity graph, an extremely

efficient preconditioner can be derived from the ''range space metric", as

opposed to the system coefficient matrix.''

Cr-^

#

s(ii)yBecause of the effectiveness of the preconditioner , preliminary studies indicate

that the method can achieve performance rates that depend li nearly upon the number

of substructures, hence the title "Order N". o »' \^^==>

JFhe method is non-assembling, i.e.j it does not require the assembly of system

mass-or'stiffness matrices, and is consequently, amenable to implementation on

work-stations**

Furthermore, the approach is promising as a potential parallel processing algorithm in that

(iv)'JThe method exhibits a fine parallel granularity suitable for a wide collection of

combinations of physical system topologies / computer architectures.' O; '- %V,

j

^v)yThe method is easily load balanced among processors, and does not rely upon

system topology to induce parallelism.

11-2
INTRODUCTION

There is no doubt that an effective design process for the space station absolutely requires

that high fidelity simulations of the transient response to control inputs.be rapidly

attainable. Much research has been carried out over the past few years that concentrates on

improving the performance of methods for simulating the dynamics of nonlinear,

multibody systems [4],[5],[14]. The research has primarily been devoted to

(i) the derivation of more efficient formulations of multibody dynamics, and to

(ii) the derivation of parallel processing algorithms.

Perhaps the most significant research addressing these two areas has been the introduction

of the recursive, Order N algorithms in [6], and their subsequent refinements in [2], [14]

for systems of rigid bodies. As noted in [14], these methods have the feature that the

computational cost of the solution procedure is linear in the number of degrees of freedom

N of the system, while conventional Lagrangian formulations are of cubic order . The

conclusion that the Lagrangian methods are of cubic order derives from the fact that a

system generalized mass/inertia matrix of dimension N X N must be factored at each time

step. Just as importantly, the computational structure of the recursive Order N algorithms

is amenable to parallel computation for some system topologies. If the system to be

modelled has many independent branches in its system connectivity graph, the

computational work required by the algorithm can be distributed among processors by

assigning branches to independent processors. As an example, [2] considers the

simulation of an all terrain vehicle. Because of the system connectivity and specific

hardware architecture, excellent performance improvements and processor utilization are

achieved in [2],

Due to these successes for rigid body simulations, it is well-known that many research

institutions are presently investigating adaptations of the original recursive method to model

systems comprised of flexible bodies. No doubt, the result will be highly efficient

algorithms that perform well. Still, three key goals must be resolved before a general

parallel processing algorithm can be obtained.

(i) Algorithms are required that induce parallelism on a finer scale, suitable for the

emerging class of highly parallel processors.

(ii) Concurrent transient simulation methods must be automatically load balancing

for a wider collection of combinations of mechanical systems and concurrent

multiprocessing hardware.

(iii) The transient simulation method should also be amenable to vector processing

implementation on each independent concurrent multiprocessor.

Based upon preliminary investigation, these goals should be very challenging if the algorithm is

based upon an recursive Order N formulation.

An innovative strategy based upon these goals is derived in this paper. In part, its

foundation can be traced to element-by-element methods already in use in finite element

solution procedures [7]. As regards sequential computing environments:

(i) The combination range space formulation / PCG solution is an extremely

efficient sequential algorithm for a class of problems described in the paper. The

11-3
efficiency is primarily due to the selection of a Block Jacobi preconditioner that is

rapidly convergent.

(i) The method is non-assembling, i.e. , it does not require a large amount of incore storage, and consequently is also attractive as a candidate for implementation

on workstations.

(iii) Preliminary studies indicate that due to the rapid convergence achieved by

using the selected preconditioner, the method can achieve performance rates that

depend linearly upon the number of substructures.

Moreover, the method should be readily implemented on parallel processors:

(iii) A vast literature exists on the amenability of the PCG solution procedure to

both concurrent and vector processing.

(iv) The method is relatively easily load balanced among processors, and does not

rely upon system topology to induce parallelism.

This paper focuses on the fundamental dynamical formulation using a combination range

space / PCG solution, and its performance on sequential computing machines. Although

the potential application of the method on parallel architectures is outlined, the details of a

concurrent implementation are presented in a forthcoming paper.

RANGE SPACE / PRECONDITIONED CG EQUATIONS

The range space formulation of dynamics has been derived in the aerospace and mechanism

dynamics research literature in [1,11,12]. Its theoretical foundation can be traced to the

range space formulation of constrained quadratic optimization [3]. Still, despite the fact

that it is often less computationally expensive than the nullspace methods, the nullspace

method seems to have received more attention in the literature [1,9,13,15...]. If the

dynamics of a nonlinear, multibody system are governed by the collection of differentialalgebraic equations

(M(q)]q=f(q,q,t)

subject to constraints in linear, non-holonomic form

the range space solution of these equations are given by explicitly solving for the

multipliers

l = -((C(q)](M(q)]-\C(q)]Tr'{(C(q)](M(q)ff (q, q, t) - e(q, q,t)}

and substituting to achieve a govering system of ordinary differential equations.

q = [M(q)]\f(q,q,t)-(C(q)]T

{((C(q)][M(q)]-\C(q)]T)-'{lC(q)](M(q)ff(q, q, t)- e(q,q , t)}}

11-4
In the above equations, the constraints have been differentiated twice to yield

(C(q)]q=--£-t((C(q)])q=e(q,q,t)

Any standard explict-predictor / implicit-corrector, or Runge-Kutta integration scheme can

be applied to these equations provided that the condition number

of the constraint metric

(C(q)lM(q)]-\C(q)]T

does not become too large. The restriction that the condition number above remains small

precludes the possibility of redundant constraints (for example, as associated with

singularities arising from closed loops) and remains an underlying assumption throughout

the rest of the paper.

One advantage of the range space equations for systems having many independent

structures to be assembled is that the system coefficient matrix is block diagonal and,

consequently, the factorization and back-substitution required to form the product of the

inverse of the mass matrix and a given vector is relatively inexpensive to calculate. It

requires that one calculate the factorization of the individual substructure mass matrices

alone. In fact, one need not even assemble the system mass matrix, and the factorizations

can occur in parallel. Unfortunately, if one subdivides the overall system into finer

collections of substructures (to facilitate the factorization of the system coefficient matrix),

numerous constraints are introduced into the model.

The approach taken in this paper is to finely subdivide the system to be modelled, and thus

accrue the benefits of having a system coefficient matrix with smaller block diagonals, but

also employ a solution procedure that ameliorates the cost associated with the increasing

dimensionality of the constraint metric. Specifically, the calculation of the Lagrange

multipliers in

f (q, q, t) - e(q, q,t)}

is carried out using the preconditioned conjugate gradient procedure.

THE PRECONDITIONED CONJUGATE GRADIENT SOLUTION

The preconditioned conjugate gradient procedure is an "accelerated" variant of the classical

conjugate gradient procedure. If it is required to solve the linear system of equations

Ax= b

the procedure can be summarized as follows:

11-5
For k = 1,... n

then

x = xk

else

Solve

k-Z

Careful inspection of the algorithm shows that the most computationally expensive tasks in

the procedure are the

(i) calculation of the product of the coefficient matrix A and a given residual

vector,

(ii) and the solution of a linear system of equations requiring the factorization of the

preconditioner Q.

The rate of convergence of the preconditioned conjugate gradient algorithm is accelerated

by employing a user-defined "preconditioning matrix." This matrix must have two

properties to be an effective preconditioner:

(i) It must be relatively easy to factor.

(ii) It must be an approximate inverse to the constraint metric in a sense to be made

precise below.

The reason for employing the preconditioned conjugate gradient solution method is that the

convergence rate of the conjugate gradient algorithm (that is, with Q = I) is governed by

x - *." r /-T^-?k

^-^/K(A)

X - X,

A

i + V K(A)

Thus, the rate of convergence of the algorithm improves as the condition number

11-6
decreases. It has been shown in several publications that the convergence of the

preconditioned conjugate gradient method is governed by the same expression, but with A

replaced with

Q

2

A Q 2

Clearly, if the preconditioner is identical to the coefficient matrix, then the condition

number of * is minimized. Hence, the preconditioner is sought such that its inverse

approximates the inverse of the coefficient matrix. Many methods exist for the calculation

of preconditioners . It should be noted that while the motivation for the use of many of

these preconditioners is mathematically sound, the final choice invariably involves some

heuristic.

THE CHOICE OF THE PRECONDITIONER

The choice of the preconditioner employed in this paper is based upon the following

assumptions regarding the structural/mechanical system to be modelled:

(i) The system closely resembles a series of chains of bodies

(ii) The number of interface degrees of freedom is small relative to the number of

interior degrees of freedom for a substructure.

(iii) The system does not contain any closed chains.

To a large extent, these assumptions have been driven by the physical structure of the space

station in its assembly complete configuration.

The preconditioner for the system constraint metric is based upon the topology of a chain of

substructures, such as those comprising the early configurations of the space station. If

(C,(q)]e /?"'""

denotes the constraint matrix connecting two bodies at the ith interface, the system

constraint matrix has the form

1C,]'

IxN

The system constraint metric can then be written

11-7
[C2][M]~W

(c3](M]\cf

_(ck][M]\c) (ck](M]~\ck]

T

 _

Based upon the structure of the constraint metric above, the preconditioner is selected to be

the block diagonal matrix

~

[C2][M]-\C2]

T

[ck](M]~\ck]

T

Although the off -diagonal blocks

(for i not equal to j) are not generally identically equal to zero, this choice of preconditioner

is shown to be extremely efficient for the class of problems described in the next section.

Furthermore, this preconditioner satisfies the two essential criteria of good preconditioners:

(i) It is block diagonal, with small diagonal blocks, and is relatively easy to factor.

(ii) It has an inverse that provides a good approximation to the inverse of the full

system coefficient matrix.

This latter conclusion results from the well-known fact [16] that the directed graph

representing the connectivity of an open loop system can be regularly ordered. The regular

ordering results in a system constraint metric that has a reduced bandwidth. That is, many

of the off-diagonal blocks

are identically zero for i»j. The choice of preconditioner shown above is often denoted

the Block Jacobi preconditioner and is known to be highly effective for classes of systems

of equations arising from elliptic partial differential equations.

11=8
SPACE STRUCTURE SIMULATIONS

Numerous simulations have been carried out to verify the attributes of the algorithm cited

earlier. In this section, only two simulations are described. More detailed simulations can

be obtained from a forthcoming presentation at the 32nd Structures, Dynamics and

Materials Conference.

Figure (1) depicts a space mast simulation in which z-truss substructures having 63 degrees

of freedom each are assembled end to end. As shown in figure (2), the preconditioned

conjugate gradient method is rapidly convergent using the block Jacobi preconditioner

derived from the constraint metric. In fact, the number of iterations required for

convergence remains constant independent of the number of degrees of freedom. Figure

(3) shows that the method is indeed Order N in computational cost in that the total time per

integration time step increases linearly as a number of the degrees of freedom.

A second example simulation of the space station in its permanently manned capability is

depicted in figures (4) through (6). Figure (4) depicts the components comprising the

station and their relative positions in the overall assembly. Figures (5) and (6) summarize

the performance of the algorithm for the entire assembly. Figure (5) plots the total time per

integration time step evaluation versus the number of degrees of freedom. As

demonstrated earlier, the simulation time does grow as a linear function of the total number

of degrees of freedom. Figure (5) illustrates the important fact that the primary

computational cost of the algorithm is associated with

(i) system coefficient matrix multiplication and

(ii) preconditioner application,

both of which are trivially parallelizable. Figure (6) shows that the number of PCG

iterations required for convergence is nearly independent of the number of

substructures/dof as in the previous case.

11-9
Substructure 2

Substructure 1

18

\

Constraints (3 nodes x 3 dof)

Constraints (3 nodes x-3 dof) to ground.

Figure 1.- Z Truss / Space Mast Assembly.

11-10
100

80-

cn

O

< 60

cc

UJ

O

5 40

m

20-

•Q- eg iterations

•*- peg iterations

0 5 10 15 20

BAYS (DOF/63 : 63 OOF PER SUBSTRUCTURE)

Figure 2.- Iterations Versus Degrees of Freedom for Z-Truss.

300

•a

o 200

o

a

I ,00

0 200 400 600. 800 1000 1200 1400

OOF (54/substructure)

Figure 3.- Computational Cost per Integration Step for Z-Truss.

11-11

1000

800-

•o

I

600-

400

200

Matrix Multiply / Preconditioner Apply

200 400 600 800 1000 1200

Number ol Degrees of Freedom

1400 1600

Figure 5.- Computational Cost per Integration Step for Space Station

12

10

I

g

o

1 H

4 -

2-

T • 1

6 8

Substructures

—I—

10 12 14

Figure 6. - Iterations for PCG Convergence Versus Number of Substructures

11-13
CONCLUSIONS / RECOMMENDATIONS FOR FUTURE WORK

The primary conclusions of this report can be summarized as follows:

(I) Although the recursive, Order N multibody dynamics formulations can yield excellent

performance in many simulations, they are not a panacea as regards applications to all

classes of problems in multibody dynamics.

(IT) It is distinctly counterproductive to limit research to recursive, Order N methods. The

order N algorithm traces its roots to simulation methods for low dimensionality robotic

simulations. The benefits of the method for simulating systems with thousands of degrees

of freedom, such as the space station, have yet to be firmly established.

(IE) There are three reasons why alternative formulations to the recursive Order N

algorithm should be pursued:

(i) trends in parallel computing architectures

(ii) underutilization of numerous concurrent multiprocessors

(iii) difficulties in load balancing

(IV) An alternative nonrecursive, Order N algorithm has been presented in this report that

has many advantages for a sequential computing environment:

(i) It is rapidly convergent

(ii) It can achieve Order N computational cost.

(iii) It is non-assembling.

In addition, the method addresses the issues noted above for a parallel computing

implementation.

(i) It exhibits a fine parallel granularity suitable for emerging computer

architectures.

(ii) The method is easily load balanced.

(iii) A vast literature exists on parallel preconditioned conjugate gradient methods.

The research described in this report has provided a promising new avenue for further research. In

particular, the range space/PCG formulation of multibody dynamics should undergo further

research, to be carried out in three primary phases:

(i) The extremely promising computational cost estimates for concurrent multiprocessing

should be validated by implementing the method for linear simulations of the space station.

The class of potential concurrent multiprocessing architectures could include

BBN Butterfly 32 processors

N-Cube 32+processors

Capps 8064 32 processors

(ii) While research in this report has been concerned with the feasibility of an alternative

concurrent method, the work has been limited to linear systems. The formulation should

be extended to include nonlinear, multibody effects

(iii) The resulting linear/nonlinear simulation capability should be incorporated in a

controls design procedure package for carrying out the tasks of computational control and

control design required for the development of attitude control systems for the space

station.

11-14
REFRENCES

[I] Agrawal, O. P., "Dynamic Analysis of Multi-body Systems Using Tangent Coordinates",

In E. Bautista, J. Garcia-Lomas, and A. Navarro, editors, The Theory of Machines and

Mechanisms, pp. 533-536, Pergamon Press, Oxford, 1987.

[2] Bae, D. and Haug, E. J., "A Recursive Formulation for Constrained Mechanical System

Dynamics: Parts i, ii, iii. Mechanics of Structures and Machines, 1988. To appear.

[3] Gill, P. E., Murray, W. and Wright, M. H., Practical Optimization, Academic Press,

London, 1981.

[4] Gluck, R., "Hope for Stimulating Flexible Spacecraft", Aerospace America, pp. 40-44,

November 1986.

[5] Haug, E. J., "Elements and Methods of Computational Dynamics", In E. J. Haug, editor,

Computer Aided Analysis and Optimization of Mechanical System Dynamics, pp. 3-37,

Springer-Verlag, Berlin, 1984.

[6] Hollerbach, J. M., "A Recursive Lagrangian Formulation of Manipulator Dynamics and a

Comparative Study of Dynamics Formulation Complexity", IEEE Trans, on Systems,

Man, and Cybernetics, 10:730-736, 1980.

[7] Hughes, T. J. R., The Finite Element Method, Prentice-Hall, Englewood Cliffs, New

Jersey, 1987.

[8] Huston, R. L., "Useful Procedures in Multibody Dynamics", In G. Bianchi, editor,

Dynamics of Multibody Systems, pp. 69-78, Springer-Verlag, Berlin, 1986.

[9] Kim, S. S., and Vandorploeg, M. J., "QR Decomposition for State Space representation

of Constrained Mechanical Dynamic Systems", Journal of Mechanisms Transmissions,

and Automation in Design, 108:103-188, June 1986.

[10] Kurdila, A., Kamat, M. P., "Concurrent Multiprocessing Methods for Calculating

Nullspace and Range Space Bases for Multibody Simulation", AIAA Journal, April 1990,

accepted for publication.

[II] Kurdila, A., Papastavridis, J. G. and Kamat, M. P., "On the Role of Maggi's Equations in

Computational Methods for Constrained Dynamical Systems", AIAA Journal of

Guidance, Control and Dynamics, Vol. 13, No. 1, Jan. 1990, pp. 113-120.

[12] Placek, B., "Contribution to the Solution of the Equations of Motion of the Discrete

Dynamical System with Holonomic Constraints", In E. Bautisa, J. Garcia-Lomas, and A.

Navarro editors, The Theory of Machines and Mechanisms, pp. 379-382, Pregamon Press,

11-15
Oxford, 1987.

[13] Singh, R. P., and Likins, P. W., "Singular Value Decomposition for Constrained Dynamical Systems, Journal of applied Mechanics, 52:943-948, Dec. 1985.

*

[14] Singh, R. P., Schubele, B. and Sunkel, J. W., Efficient Algorithm for the Dynamics of

Multi-Link Mechanisms, AIAA Paper No. 89-3527-CP, 1989.

[15] Webage, R. A., and Hung, E. J., "Generalized Coordinate Partitioning for Dimension

Reduction in Analysis of Constrained Dynamic Systems", ASM E Journal of Mechanical

Design, 104:242-255, January 1982.

[ 16] Wittenburg, J., Dynamics of Systems of Rigid Bodies, B. G. Teubner, Stuttgart, 1977.

U-16
APPLICATIONS OF FORMAL SIMULATION LANGUAGES

IN THE CONTROL AND MONITORING SUBSYSTEM

OF SPACE STATION FREEDOM

Final Report

NASA/ASEE Summer Faculty Fellowship Program -1990

Johnson Space Center 5

a

A Q f

*

Prepared By:

Academic Rank:

University & Department

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleague

Date Submitted

Contract Number

R. C. Lacovara, Ph.D.

Assistant Professor

Stevens Institute of Technology

Dept. of Electrical Engineering

and Computer Science

Engineering

Tracking and Communications

Communications Performance

and Integration

James C. Dallas

August 17,1990

NGT-44-005-803

12-1
1. Abstract

The notions, benefits, and drawbacks of numeric simulation are introduced.

Two formal simulation languages, Simscript and Modsim are introduced. The capabilities of each are discussed briefly, and then the two programs are compared.

The use of simulation in the process of design engineering for the Control

and Monitoring System for Space Station Freedom is discussed. The application

of the formal simulation languages to the CMS design is presented, and recommendations are made as to their use.

12-2
2. Simulation and the Scope of this Paper

This paper discusses certain formal simulation techniques and tools, and

makes observations and recommendations on the use of these techniques in a

specific environment: the Control and Monitoring Subsystem (CMS) for Space

Station Freedom.

The concept of simulation and varieties of simulation are discussed briefly. After that discussion, the application of simulation to the CMS is presented. The formal languages are presented and compared. Lastly, some recommendations for the use of these tools are advanced.

2.1. Rationale for Simulation

Simulation is one of many methods of obtaining information about physical

or conceptual systems. The chief feature of simulation is that the information

is not obtained by methods of formal analysis. Instead, a model of the system

which includes the pertinent behavior is constructed and the model is exercised. Possibly, the model is exercised using pseudo-random input conditions,

and the model may be exercised many times to smooth out variations in results

due to the pseudo-random inputs, or internal psuedo-random events.

(In this paper, the term "random" will be used to describe the behavior of

pseudo-random sequence generators. The differences and implications of this

choice, and the definition of pseudo-random are beyond the scope of this work.)

The chief advantage of simulation accrues from the chief feature. Simulation is an interesting methodology precisely when (a) no formal analysis is

possible or (b) no physical system is available from which to make observations. Any number of reasons will occur to the reader which may cause case (b).

Case (a), the lack of formal analysis, occurs whenever the system to be studied

has no known system of equations which describe it, or when the complexity,

inherent non-linearities, pathologies, or plain old intractability of the system make the search for analytical description impractical. A cold appraisal of

the world leads workers to conclude that case (a) is the rule, not the exception.

In brief, simulation is applied to problems for which formal analysis is

unavailable or for which no physical system is available for observation.

12-3
3. Categorization of Simulation

Simulations may be usefully categorized in several ways. The process domain

of a simulations refers to the description of time in which the system operates. Discrete time and continuous time descriptions will be familiar to most

electrical engineers.

The computational domain describes the facility used to model the system.

Although most facilities are digital computers, some analog computers are used

in simulations.

The simulation scheme refers to the method in which the simulation passes

time. This may be synchronously, in which the program advances time in small

quanta and determines what, if anything, should occur. Otherwise, the simulation might be asynchronous, in which the program maintains a list of scheduled

events and proceeds directly from one scheduled event to another regardless of

the intervening time.

3.1. Process Domain

Process domain refers to the basic view of time taken by the simulation. A

natural view of the progression of time is that of continuous time. The time

variable may take on any value, and this is certainly the most common view of

processes such as ballistic bodies, electronic circuits and similar systems.

The other common description of the passage of time is discrete time, in which

the time as an independent variable takes on only specific values, usually of

the form

t = nT

where T is the smallest identifiable duration, and n is the actual independent

variable.

The difference between continuous and discrete time signals is more fundamental however. Continuous time systems are those which may be described by

differential equations, whereas discrete time systems are described by difference equations. Analytic solutions to continuous time systems are therefore the

solutions to ordinary and partial differential equations with boundary conditions, usually facilitated by the use of Laplace transforms. Analytic solutions

for discrete time systems satisfy difference equations with forcing functions,

and a common technique is that of z-transforms.

12-4
Often it is convenient to model a naturally continuous system with a discrete time model. This may entail a choice of T such that no significant events

occur in a period of time less than 2T. Unfortunately, it is not always clear

what constitutes a "significant event1, and further, other subtleties (such as

solution stability concerns) may intrude.

As a practical matter, most formal simulations are in fact discrete time.

Philosophical arguments aside, digital computers (the most common vehicle of

simulations) represent quantities discretely (in finite precision.)

3.2. Computational Domain

Calculations may be performed in many different ways. Mechanical and hydraulic systems have been designed to perform logic and arithmetic. The only interest here is in electronic methods.

3.2.1. Analog Computers

Analog "computers" are good examples of analog simulators. These devices

are actually arrays of operational amplifiers configured as summers, integrators and differentiators. As a result, analog computers are well suited to the

solution of systems of linear differential equations. As an illustration, note

that voltage or current is made the analogue of some physical quantity, and

time is made the analogue of the independent variable, usually time. This is in

contrast to something like a phonograph recording, in which vertical mechanical

displacement of a grove is made the analogue of acoustic pressure, and linear

displacement along the groove is made the analogue of time.

Analog computers are most often set up on plugboards to represent a particular differential equation. An applicable forcing function is applied, and the

behavior of the system as a function of time is observed and scaled.

3.2.2. Digital Computers

Digital computers are the most common vehicle for calculation and simulation. Inherently, these machines represent discrete variables, and are naturally suited to represent systems which are characterized by difference equations.

Various strategies allow the system to represent continuous time systems with

acceptable results.

12-5
Digital "computers" could be constructed in the same manner as analog computers. Collections of adders, subtracters and delays could be assembled to

exactly represent some particular difference equation. This is uncommon,

although such an arrangement might be one of the fastest methods of obtaining a

solution to a set of equations.

A slightly less hardware-intensive method is to use digital signal processing chips to implement the difference equations. These single-chip computers

use specialized architectures and instruction sets to efficiently evaluate

difference equations.

The majority of computational applications are performed on general-purpose

computer architectures. This includes formal simulation languages.

3.3. Simulation Methodology

There are two primary simulation methods. These differ in the manner in

which simulated time is advanced. An important distinction is that simulation

time is unrelated to run time, or actual time. Simulation time is advanced

either by identical small quanta (synchronous simulation) or advanced from

event to event listed in a process list (asynchronous simulation.)

3.3.1. Synchronous Simulation

Synchronous simulations are used in systems which require interaction with

exterior hardware. Examples are systems which are interfaced to hardware or

certain recording systems. These systems have stringent timing requirements:

the simulation must be able to advance simulation time at least as fast as real

time.

Synchronous simulations are common even when there are no exterior requirements. This is not surprising, since synchronous simulations are often easier

to code than asynchronous simulations.

Coding a synchronous simulation proceeds as follows. Prior to coding, the

analyst determines the largest time slice which will suit the problem. An initial state of the problem is chosen. Then, for each element of the system, the

analyst computes (guesses?) the probability (formally, a transition probability) that a particular element of the simulation changes state in during a time

slice.

12-6
Code is written which can store the state of the system during any particular time slice, and update the state during the next slice. This is done by

making a number of draws from a suitable probability distribution, and mapping

the results into the new state of the system.

This technique has the advantage of simplicity. If the code is hosted on a

sufficiently fast platform, the simulation is by default "real-time". (For

example, if the time quanta chosen is 0.1 second, and the program completes all

transition probability draws in less the 0.1 second, then the program is not a

rate limiting part of a larger system, hence is real-time.)

There are drawbacks to this arrangement. If real-time performance is required, and the code does not run fast enough, then there is little recourse

except a full re-write, or a port to a faster host. Further, a view of a process from the level of the time slice makes is difficult to implement a

"process-wide" view of the system. Interactions between processes in the simulation are not obvious, and not necessarily easy to implement.

For certain classes of problems, the synchronous approach is sparing of a

programmer's time, and may allow real-time operation in some cases. A discussion and exposition of a non-trivial synchronous simulation is found in

[Lacovara 87].

3.3.2. Asynchronous Simulation

For more complex systems, or systems in which there is significant interaction between parts of the system, synchronous simulations present non-trivial

coding problems. Further, the size of the time slice determines to a great

extent the rate at which the simulation runs. A choice of small time slices

will slow the system, and many slices may pass without any activity. Large time

slices will allow simulated time to pass faster, but large slices may not allow

sufficient fidelity in the simulated world.

Asynchronous simulation is an approach which resolves the time slice dilemma. In an asynchronous simulation, the time of occurrence of an event is predicted by a draw from an appropriate distribution. The predicted event is then

placed as an event notice in a linked list of events, often called an event

list. After all predictions which can be made from the present state and simulation time of the system have been make, simulation time is advanced to the

12-7
event notice closest in simulation time. Any changes needed to the state of the

system implied by the current event are made, any new event notices are posted

to the event list, and simulation time is advanced again.

The principal feature of asynchronous simulation is that simulation time

advances from event to event. No compute time is spent evaluating time slices

in which no events occur, and the 'View" of the simulation is at the process

level.

The advantages of asynchronous simulation are often great. A more intuitive

view of the system may be use to create, maintain, and interpret the simulation. The simulation will permit interaction between its component processes.

The disadvantage, however, is that the creation and maintenance of event lists

and process notices are non-trivial, and certainly not advised for casual, even

if experienced, programmers.

The formal simulation tools discussed below have the great advantage that

the mechanics of the simulation, linked lists, queues, priority chains and so

on, are hidden from the programmer. With the use of these tools, powerful simulation constructs are available to users who do not plan to spend their entire

career writing code.

4. Formal Languages: Simscript and Modsim

In this study, two formal asynchronous simulation tools produced by CACI

Products Company of La Jolla, California were used. These languages are Simscript and Modsim. They are entirely different approaches to the problem of

simulation, and have overlapping but not identical domains of applicability.

4.1. Simscript

Simscript (from simulation script) is an old (1962) hence mature product.

It imposes on the programmer a "View" of a system divided into processes. This

is not altogether artificial, as the Simscript model of a bank consists of

processes which represent a) customers, b) tellers, and c) customer arrival

generator.

Simscript maintains a complex internal system of queues, lists, and other

data structures. The maintenance of these structures is transparent to the

programmer for the most part. In the bank example, customer arrivals are

12-8
"generated" by introducing event notices of arrival in an event list. The bank

teller is represented by a teller "resource", a process which incorporates a

waiting queue and other flags to indicate teller status. When a customer arrives at a teller, the Simscript system determines whether the teller is "busy"

with a previous customer. If busy, the customer is placed in a waiting queue

until the teller is free to process the customer.

Simscript manages the teller's waiting queue transparently. It checks the

teller's status flags and determines whether the customer may be served or must

wait. In addition to manipulation of these internal structures, Simscript monitors selected parameters of the simulation automatically. Quantities such as

queue size, maximum, minimum, average and other statistics are accumulated

without explicit programmer intervention.

As a result of the internal features, a certain class of simulation may be

implemented in Simscript in an elegant and straightforward fashion. From a

descriptive point of view, Simscript is well suited to systems which involve

queuing theory: processes in which requests for service contend for limited

resources.

Simscript includes facilities for screen graphics. Pre-defined screen constructs include graphs, indicators and clocks. Moving icons may be designed and

animated by the simulation. These are relatively straightforward to use, and

seem to be quite useful. Some are quite impressive.

4.2. Modsim

Modsim is a relatively recent language product. It is syntactically based

on Modula 2, which is similar to Pascal. Basically, Modsim adds formal object-oriented structures to Modula-2, and provides simulation capability by

providing a library of objects which can pass simulated time. Due to the Modula

2 underpinning, Modsim has considerable general purpose characteristics. It

would be perfectly feasible to use Modsim wherever Modula 2 or Pascal is employed.

A description of object-oriented programming is beyond the scope of this

paper. However, it is necessary to note that the pertinent features of

"objects" are these. Objects are data structures comprised of typed-fields, and

a list of procedures (called methods) which are the only procedures which act

12-9
on the data structure. The implications are these: objects may interact only

through a object's allowed methods. An object's external fields may be read by

other objects, its internal fields remain invisible. An object's fields may not

be modified directly, but only through the agency of its allowed methods. The

purpose of this strict control of access is to impose a discipline on the construction of the program, and to provide a type of safety in the control of

actions performed on data structures.

Modsim extends the notions of object-oriented programming in the following

manner. Methods are available in two classes, "ASK" and 'TELL". An ASK method

corresponds to the original methods noted above. When invoked upon an object,

some action ensues in instantaneous simulation time. TELL methods, however, are

asynchronous: simulation time may elapse before the desired changes occur. This

is accomplished by the mechanism of an event-list. As in Simscript, the control

and maintenance of the event list for the asynchronous simulation aspects of

Modsim are implicit.

Modsim provides a complex and general programming environment.

(Translation: Modsim is powerful, difficult, and sometimes obscure.) It would

appear to be suitable for a very wide range of simulations. Like Simscript, it

contains provisions for complex screen graphics.

4.3. Comparison of Simscript and Modsim

Be advised that the author's programming experience is as follows: considerable expertise in assembly languages, Fortran, Pascal, and C, and operating

systems. The author has written numeric simulations on several systems, but is

new to Simscript, Modsim, and object-oriented programming.

It seems to be easier to write simulations in Simscript than Modsim. In

many ways, Simscript seems to bridge the conceptual gap between the system

under consideration and the programming model in a more direct fashion. Modsim's object constructs however correspond to identifiable processes in the

real world. Modsim's power and complexity initially interfere with the process

of writing code: Modsim requires a substantial amount of "overhead" code to

just get started.

The author designed a simple multiplexer as a simulation example for both

Modsim and Simscript. The multiplexer accepts "data packets" about every 75

12-10
milliseconds. The packets face two servers. One is a high speed server, the

other is a low speed server. The multiplexer enforces the following service

discipline. If the queue size for the low speed server is twenty-five or fewer

packets, the incoming packet joins the low speed queue. Otherwise, the packet

joins the high speed queue. The simulation accumulates statistics on the sizes

of the queues, and the distribution of the time taken by every packet to traverse the system.

The Simscript version of this code is about 40 lines. These 40 lines compile into about 250K bytes for a Sun Sparcstation. The Modsim version is only

about 50% larger, but compiles into about 1M bytes for the same machine. Modification of the server discipline is about the same difficulty in either language. As features are added to either version, the Simscript object file grows

somewhat, but the Modsim does not seem to expand much at all. The simplest

interpretation of this behavior is that the Simscript object file is growing

proportionally to the additional lines of code. The Modsim compiler seems to be

able to perform one of the selling points of object-oriented programming: the

ability to reuse many parts of the code through inheritance and recursion.

Of course, the Modsim object starts out about four times the size of the

Simscript model, but this is not really serious on large machines.

Both Modsim and Simscript seem to utilize whatever processor power is available, as judged by a Sun performance meter.

The screen graphics package for Modsim is very similar to that of Simscript, but available in a more advanced version, and is therefore preferable.

Overall, Modsim seems to be a more general and versatile simulation system

than Simscript. It carries with it corresponding penalties is size and programmer learning curve. Simscript is almost as versatile, and seems to be a very

good choice if only one package is to be available to the general analyst working with small to medium sized systems. For very large projects, Modsim may be

a better choice, since in large systems the organizational advantages of object-oriented programming will begin to be felt.

5. Simulation of Control and Monitoring Subsystem

The Control and Monitoring Subsystem (CMS) for Space Station Freedom is a

collection computers and busses which determine the configuration and operate

12-11
various hardware systems. Some tasks include health observation, fault diagnosis and recovery, and other system-wide tasks.

5.1. Functional Simulation

The process of design of this system includes several generations of simulation of the CMS. However, these simulations are not operational, but functional. As an example, other applications on the Space Station communicate with the

CMS via a local area network. The present simulations of CMS accept these commands, and provide a simulated response. This simulation system does not depend

heavily on stochastic processes. Instead, the simulation must "merely" accept

communication from exterior agencies and provide a sensible response. As a

result the current simulations are written primarily in ADA and C.

5.2. Use of Operational Simulations in the CMS

There are several areas in which operational simulations may be of use in

the CMS scheme. These are primarily incidental, but of some interest.

The current fault generation in the CMS simulator is manual. If there is no

automatic fault diagnosis and isolation, this is probably adequate. If automatic detection, diagnosis, isolation, and correction are to be implemented, good

testing practice would dictate that the simulated flaws occur without warning

to the simulation operators.

Some aspects of the simulation are time-varying. Some require knowledge of

the state of other components of the simulation. Either simulation tool would

be of some use here. If complex time-dependent behavior was required, the tools

would have some advantages over C or ADA.

5.3. Disadvantages in the CMS Simulation Environment

Simscript and Modsim have common properties which do not fit well with

current simulation and software philosophy on Space Station. Neither tool resembles ADA, is written in ADA, or is likely to be available in ADA in the foreseeable future. An ADA ideology permeates the Space Station software engineering

efforts, possibly to the exclusion of other useful concepts and directions in

computer science.

A secondary item of dogma is object-oriented programming. Modsim fills this

12-12
bill nicely, and brings with it all of the overhead and performance penalties

built in to this paradigm. However, Simscript is not strictly object-oriented.

Simscript is modular, but it retains some characteristics from its early origins. (A new line is read from a disk file by the keywords "START NEW CARD".)

The disadvantages, quirks and structural awkwardness of either program are far

outweighed by the advantages they bring to simulation.

6. Recommendations

In the context of the current software requirements of EE7 and in support

of engineering efforts for Space Station Freedom, I offer the following recommendations.

a) One civil service employee of the branch should learn Simscript or Modsim well enough to write a small, but non-trivial simulation. This will

bring some experience in formal simulation tools into the branch. I suspect

that this will pay off rather sooner than later, as requirements and tasks

evolve.

b) A portion of the CMS demo which could use graphics output might be identified and coded in Modsim. Modsim has convenient and useful graphics capability, and it is possible that it could be the most efficient means of

generating many graphics displays.

c) Some demonstration of Simscript's or Modsim's capabilities should be

shown to staff involved in analysis tasks in other branches. These tools

are potentially most useful to people who write operational simulations or

perform formal analysis. They should know that the tools exist on-site.

7. Reference

Lacovara 87

R. C. Lacovara, Dissertation: Adapted Packet Speech Interpolation. Stevens

Institute of Technology, University Microfilm 88-17309 Issue 4907 DAI January

1989.

12-13
5 N9 1-271 o

Prepared By:

Academic Rank:

University and Department

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleague:

Date Submitted:

Contract Number:

A STUDY OF MURINE BONE MARROW CELLS CULTURED IN BIOREACTORS

WHICH CREATE AN ENVIRONMENT WHICH SIMULATED MICROGRAVITY

Final Report

NASA/ASEE Summer Faculty Fellowship Program-1990

Johnson Space Center

Brother DeSales Lawless, Ph.D.

Associate Professor

f 0

Fordham University ""

Division of Science and Mathematics

New York, N.Y., 10023

Space and Life Sciences

MEDICAL SCIENCES

Biomedical Operations and Research

Steve Gonda, Ph.D.

August 2,1990

NGT 44-005-803

13-1
'ABSTRACT

This study is a continuation of work undertaken at Johnson Space Center in the summer,

1 gsgr—That^'research indicated that mouse bone marrow cells could be grown in conditions of

simulated microgravity. This environment was created in rotating bioreactor vessels4which.

.were-fabrieated by the Biotechnology Instrument Laboratories-of-the Johnson.Space Center.

On three attempts mouse bone marrow cells were grown successfully in the vessels. The

cells reached a stage where the concentrations were doubling daily. Phenotypic analysis using

a panel of monoclonal antibodies indicated that the cell were hematopoietic pluripotent stem

cells. They-did-noUshow-surface markers- characteristic of. differentiated myeloid, lymphoid or

-ery.thr.oioLcells.^ Furthermore,-they stained positively for an antibody which has been shown to

Jbe^pr.esent. on stem cells. —T-hese-eells—for-med^colonies—when -grownr on=_ soft* agar..

Morphologically, they appeared clonic. One unsuccessful attempt was made to reestablish the

immune system in immunocompromised mice using these cells.

Since last summer, several unsuccessful attempts were made to duplicate these results .

It was determined by electron microscopy that the cells successfully grown in 1989 contained

virus particles. It has been suggested that these virally parasitized cells had been

immortalized,

The work of this summer is a continuation of efforts to grow mouse bone marrow in these

vessels. A number of variations of the protocol have been introduced. Certified pathogen free

mice have been used in the repeat experiments. In some attempts the medium of last summer

was used; in others Dexture Culture Medium containing Iscove's Medium supplemented with

20,%?horse serum and 10-6 M hydrocortisone. The Dexter medium proved to be unsuitable for

growth in the vessels but was excellent for growth of static cultures at unit gravity.

•0ur.efforts this summer were directed solely to repeating the work of last summer. -We

had- planned many--investigation-if-.we-sueceedediin-isolating the stem cells. We-would-attempt

immortalization of the undifferentiated stem cell/by transfection with oncogenic vector. We**

would induce^selective differentiation in the stem cell line by growing it with known growth

factors and immune response modulators. ^We-were particularlynnterested in identifying any

surface antigens unique to stem cells that would help in their characterization.

Another goal was to search for markers on stem cells that would distinguish them from

stem cells commited to a particular lineage; these are the cells referred to as precursor cells.

We~believe-that-the stem cell is self-renewing while the precursor cell obeys the restrictions

-prfigosed by^,Leonard Hayflick (Hayflick, L, 1965). \(i

If we-obtained the undifferentiated hematopoietic stem cellfwe-would study the pathways

that would terminally convert it to myeloid, lymphoid, erythroid or other cell line^ We-would=^

-Jike4o-transfecUit with*a known gene/and then convert-it to a terminally identifiable/cell.

•->. * ' ^ / ' L :

13-2
INTRODUCTION

This research is a study of murine bone marrow cells cultured in simulated microgravity.

It has been shown by several investigators that gravity is an environmental factor which affects

growth and functionality of cells (Lorenzi, G., 1986). When flown on a space mission where

they encountered zero gravity, human lymphocytes showed less than 3% of mitogenic

activation to Concanavalin A as similar cells which had been cultured at unit gravity (Cogoli,

1985). It has been further demonstrated that microgravity depresses and hypergravity

enhances cell proliferation rates. These effects are particularly strong in cells which are

undergoing differentiation. The cellular proliferation rates of several different cell types were

found to increase by 30% in hypergravity while the consumption per cell of glucose was lower

than at unity gravity (Tschopp, 1983). A summary of the effects of spaceflight on single cell

organisms, plant and mammalian cells has appeared in the literature. (Gmunder, F.K. and A.

Cogoli, 1988). The effects of spaceflight on levels and activity of immune cells has been

reported by Sonnenfeld, et al (1990).

We have undertaken this research encouraged by the work of these investigators and

others who have demonstrated that gravity affects cell behavior. Our particular interest in

bone marrow is associated with its importance in clinical medicine and several areas of basic

research. It is important that the stem cell be isolated and characterized. The investigation of

hematopoiesis is limited by the by the lack of a definitive in vitro assay for the most primitive

hematopoietic stem cell. (Rowley, et al, 1987). No antigenic determinant has been found to date

that is specific for mouse stem cells. The antigens that are positive for stem cells are not

specific. (Van de Rijn, et al., 1989) It is estimated that only 0.02% of bone marrow cells are

undifferentiated stem cells. It is postulated that these cells are the only ones with self-renewal

potentialities. (Spangrude, et al., 1988).

Among the premises upon which this research is predicated are: (a) cell-cell contacts

would be minimized in the bioreactors; (b) cell differentiations would be curtailed since the

adherent cells that make up the microenvironment would would not thrive in the vessels; (c)

cytokine communications could be lessened by periodic changes of the medium; (d) stem cells,

unlike differentiated cells, are self-renewing. Stem cells would outlast precursor cells. We

consider the precursor cells those that have been committed to a specific differentiation.

Among approaches investigators have used in their quest for the hematopoietic stem cells

in bone marrow are: density gradient centrifugation (Yoichi Takave, 1989), elutriation

(Nijhof, et al., 1985), cell sorting by flow cytometry (McAlister, I., et al., 1990),

immunomagnetic bead separation (Bertoncello, I., et al., 1989), and antibody-complement

cytotoxicity (Spangrude, et al., 1988).

An efficient time and material saving protocol for stem cell isolation would help in gene

therapy, bone marrow transplants, elucidation of cellular differentiation pathways, etc.

The work reported here includes a review of our work of the previous summer. We

were confident that we had achieved the goal of stem cell isolation and characterization. We

have since learned that the cells we described were infected with a virus and our conclusions

became suspect. We have taken a number of different approaches to be used with the

bioreactors including the use of Dexter medium with horse serum and hydrocortisone. We have

also added some conditioned medium to the vessels. Our mice were certified pathogen-free.

13-3

0-3
MATERIALS AND METHODS

Mice: Certified pathogen-free CD2/F1 male mice 6-7 weeks old were purchased from Taconic

Farms, Germantown, New York, 12526.

Cells: Mice were sacrificed by cervical dislocation. The bone marrow cells were obtained by

flushing tibiae and femora of ten mice with Phosphate Buffered Saline (PBS) without calcium

and magnesium and supplemented with 1% Bovine Serum Albumin. These cells were washed

twice and resuspended in growth medium. The growth medium in one experiment was Dexter

formulation: Iscove's Minimal Essential Medium (Sigma Chemical Co.) containing 20% horse

serum (heat-inactivated at 56 deg C for 30 min) (HyClone, Upton, Utah) and 10-6 M

hydrocortisone succinate sodium salt (Sigma). This medium was supplemented with 100 U/ml

Penicillin-Streptomycin (Gibco, Grand Island, N.Y.). Cells in this medium were grown at 33

degC.

In a second experiment the medium was that used in the summer, 1989: RPMI-1640 (Gibco),

10% Fetal Calf Serum (Flow Laboratories, Raockville, MD), and supplemented with

Penicillin-Streptomycin (Gibco). The Fetal Calf Serum was heat inactivated at 56 deg C for 30

min. Cells in this medium were grown at 37 deg C.

Cell concentrations in both reactor vessels was 1 x 10-6/ml. The vessel volumes were 50 ml.

and were rotated at 8 rpm in an incubator in an atmosphere of 5% carbon-dioxide and 95%

humidity. The bone marrow used in both controls and in experiments in microgavity initially

was partially depleted of monocytes by removal of adherent cells by incubating the bone marrow

cells overnight in polystyrene flasks at 37 deg C.in RPMI medium supplemented with 5% Fetal

Calf Serum.

Simulated Microgravity:The cells were grown in one of NASA JSC's horizontally rotating culture

vessels that simulates some aspects of microgravity. This vessel consists of a motor-driven

rotating vessel with a separate air pump connected by tubing to the central shaft of the culture

vessel. It operates in an ordinary laboratory tissue culture incubator. The cells are oxygenated

by pumping 5% CO2 to 95% incubator air through the internal silicone membrane which

surrounds the central vessel shaft.

Cell counts. Cell counts were obtained on a standard Coulter Counter Model ZM (Coulter

Electronics, Inc., Hialeah, Fl., 330IO) or by counting on a light microscope with a

hemacytometer. Viabilities were determined by trypan blue exclusion.

Oxygen consumption and carbon-dioxide production were determined using a Corning 168, pH

Blood Gas Analyzer (Corning, Medfield, MA, 02052). Glucose utilization was determined on a

Beckman Glucose Analyzer 2 (Fullerton, CA, 92634).

13-4
Monoclonal Antibodies: The panel of antibodies included the following from clones purchased

from American Type Culture Collection, Rockville, MD: TIB-104 (Lyt-1); TIB-120 (Anti

la-b,d,q haplotypes); TIB-I28 (Anti-MAC-1, macrophages and granulocytes); TIB-146 (Anti

B cell, anti B cell precursors with antigen B220); TIB-150 (Anti Lyt 2.2 expressed on T

suppressor-cytotoxic cellsd); TIB-1264 (Anti murine B cell); TIB-207 (anti-L3T4-T

helper-inducer subsets). The following antibodies were from Sigma: FITC-anti Thy 1.2 (cell

surface differentiation antigen), and the secondary antibodies FITC-anti Rat IgG and FITC Goat

anti-mouse. We obtained from Becton-Dickinson Co., Mountain View, CA: Anti-mouse Lyt-1

and anti- mouse I-A. The anti-stem cell antigen antibody E13-161-7 was from ATACC. 2.4G2

(anti-mouse Fc receptor was gift of Dr. MaryAnn Principato of the National Institutes of Health,

Bethesda, Md.

Staining: In direct staining, FITC-conjugated antibodies were used. In indirect staining, the

unconjugated antibodies were incubated first with the bone marrow cells for 30 min on ice,

washed, and incubated with the secondary FITC-conjugated antibody for 30 min on ice. After two

washings, the cells were fixed for 10 minutes at 4 deg C with 3.7% formaldehyde, washed and

resuspended in PBS-1% BSA/0.02% azide. If we had immediate access to the FACScan, the cells

were not fixed but were incubated with a solution of propidium iodide which enabled us to sort

out dead cells for the flow cytometric analysis.

Flow Cytometry. Experimental data from the control cell populations grown in static culture at

unit gravity and from the cells grown in microgravity in the bioreactors were obtained using

Coulter Electronics EPICS V Cell Sorter (Coulter Electronics, Hialeah, FL). 10,000 events

were scored on each test. Dead cells and cell aggregates were gated from the cells under study

using propidium iodide. The percentage of positive cells was estimated by using bone marrow

with irrelevant antibody as controls. Cell size distribution was assayed by forward scatter of

unseparated bone marrow cells. The percentage of cells with staining above tghe background is

determined for each of the monoclonal antibodies in the panel. For DMA analysis, the cells were

stained according to the Method of Krishan as modified by McDivitt, et al. Cells were fixed by

suspension in a solution of 67% ethanol for 30 min. The staining solution was made of 0.005%

propidium iodide (Calbiochem-Behring, San Diego, CA., 0.002 % RNAse A (Sigma). After 30

min at 4 deg C the cells were washed and rsuspended in PBS.

Stem Cell Bioassay. (Hemopoietic colonies in vitro). Stem cells in complete medium were added

to soft agar formed colonies. The ratio of the of colonies formed with the stem cell preparation

and normal bone marrow cells was recorded. CFU-c was determined as described by Jacobs and

Metcalf (I979). CFU-e was determined according to the method of Mcleod (1974). BFU-e was

determined as described by Peschle, et al (1979). CFU-GEMM was determined by the method of

Johnson and Metcalf (1977).

Immunological Reestablishmeht; Three sets of ten mice each were irradiated with 900 rads at

MD Anderson Cancer Center, Houston, TX. One set of the mice was kept as controls. A second set

received fresh bone marrow injections. The test group was given 100 cell/mouse of the cells

which had been circulating in the microgravity vessel for 40 days. Records were kept of animal

viabilities.

13-5
Phenotypic and functional assays: (a) Among the surface antigens to be studied by our panel of

antibodies are: Thy-1, CDS, CD4, CDS, CDS, H-2 Class I and II, slg, 14.8, SCA and Mac-1.

(b) histochemical staining of the cells for monocyte detection will use specific esterase and for

granulocyte/monocytes will use peroxidase.. (c) To determie if the cells secrete constitutively

or after induction, we will use various hemopoietic growth and diferentiation factors: IL-1,

IL-2, IL-3 IL-4, CAP and INF-gamma. These phenotypic and functional assays were performed

in the Laboratory of Dr. Chris Platsoucas of the M.D. Anderson Hospital in Houston, Texas.

13-6
RESULTS

Cells grown at unit gravity in T-flasks using Dexter formulation medium- were our most

successful cultures. They continued to produce non-adherent cells through a two month period.

The cells grown under the same conditions using RPMI-10% Fetal Calf Serum grew well for

only a twelve day period. Cells in both Dexter medium and in RPMI-10%FCS medium in the

bioreactor vessels declined in numbers steadily until there were very few viable cells by day

12. This was very unlike our three experiences in the summer of 1989. In the studies of last

summer, the cell cultures were doubling every twenty-four hours by day twelve.

Phenotypically they were the cells we sought - the undifferentiated, hematopoietically

pluripotent stem cells. We had apparently succeeded last year in producing a self-renewing

immortalized cell line. Electron microscope photography indicated that the cells contained a

virus. The virus could have accounted for their immortalization.

The cells grown with Dexter medium in the HARV did not survive beyond a few days;

however similar cells grown in static culture in T-flasks at unit gravity were growing

vigorously after five weeks. The cell suspension in the bioreactor by day twelve contained

floating precipitate which we judged to be protein coming out of solution from the horse serum.

The cells present had increased in size and resembled blasts. We concluded that the horse

serum proteins precipitated which resulted in osmolarity and pH changes. Changes in either of

these parameters would cause plasmolysis and lysis of the cells. We repeated the experiment

several times and found the same results . We did not detect precipitated protein when the

RPMI-10% Fetal Calf Serum was used; however, the cells did not survive after the 12 day

incubation period. All of the horse serum in the Dexter composition was from a single batch; it

is possible that this material was subject to denaturation in the vessels.

In the 1989 experiment we successfully monitored the conditions of the cultures in both

static controls and in the rotating vessels using the parameters: osmolarity, pH, glucose and

oxygen consumption and carbon dioxide production. We were also able to follow the depletion of

the cells with lineage markers for cell surfce antigens. The remaining, immortalized culture,

was frozen away for future studies. When thawed a year later, the cells readily went into

culture and continued to double in number daily. The cells stained positively for Thy-1 and for

SCA-1. They were negative the Fc-receptor. The cells were negative to staining with the

lineage markers.

The cells that were monitored for reestablishment of their immune systems in the 1989

experiments did not give us positive results. It may have been that the 900 rad radiation was

too high a dosage; it may have been that we did not inject sufficient numbers of the stem cells

from the rotating vessels. This test will be included in any study of stem cells isolated using

microgravity.

Our conclusions are that the conditions that produce an environment of microgravity in

the bioreactors will be most helpful after some basic science questions have been answered.

There are apparently some growth factors needed from the stromal cell environment that are

unique for the stem cell. This factor is different from a proliferation factor. There may be

needed articulation with some stromal cells in the microenvironment formed by the adherent

cell population. Our continued studies will consider each possibility.

13-7
DISCUSSION

This research was undertaken to determine the growth characteristics of murine bone

marrow cells in the bioreactors of NASA-Johnson Space Center. Since these vessels offer an

environment that partially simulates the microgravity environment, the data obtained would be

relevant to the space program.

The major premises upon which this research was based are reasonable; if they are

sound, we would expect the self-renewing stem stell to survive in the environment of

microgravity and we would not expect differentiated cells to do so.

Our investigations have been concerned exclusively to this point with murine bone

marrow cells. We want to expand the study to include human bone marrow. We are also anxious

to explore the behavior of murine fetal liver cells in microgravity. The proliferative rates

of fetal liver cells are considerable greater than bone marrow rates. They are also a

self-renewing population.

We are confident that the microenvironment will yield the stem cell clone. The

procedure must be "fine tuned" and optimal conditions and media identified. We would use cells

from this clone to search for any antigens that might be unique to the stem cell. We would also

seek pathways from the stem cell to terminally differentiataed cells - myeloid, lymphoid,

erythroid, as well as cells of current interest in medical research, e.g., the dendritic cell.

While we probably unintentionally immortalized the stem cell line in 1989, we are

planning to transfect our isolated stem cells with a well defined oncogenic vector to produce an

immortalized clone. In one experiment, canine bone marrow cells that were cultured for more

than thirty weeks were found to be virally infected. (Schuening, F.G., et al, 1989). Murine

bone marrow cells have been transformed in vitro with v-raf/v-myc retrovirus to yield

mature B cells and macrophages. (Principato, M, et al., 1988) We would seek the stem cell

clone using the same v-raf/v-myc vector. Retroviral vectors have been used with murine

long-term bone marrow to transfect human glucocerebrosidase (Nolta, J..A., et al., 1990) and

human adenosine deaminase (Wilson, J.M., et al, 1990). We are formulating protocols to

transfect the stem cell clone if we succeed in isolating it. Erythropoietin cDNA has been

transferred to murine bone marrow stromal cells and yielded hemoglobinized red blood cells.

We would transfect our clone with cDNA and study the progeny. (Corey, C.A., et al 1989.)

The stem cell is deserving of further work in microgravity. Its isolation and

characterization will be of particular relevance in bone marrow transplantation,

immunodeficiency disorders, genetic engineering and long term space flights protection.

We are eager to study cells other than stem cells and self-renewing cells in microgravity,

e.g., cells of the neuro-endocrine production.

The background preparation required for this study of murine bone marrow cells in

simulated microgravity has been most rewarding. Our studies have prompted to ask many

questions and now we must seek the answsers to these questions.

13-8
Are bone marrow stem cells indefinitely self-renewing? They appear to be

programmed for division. When one of them under stimulus is targeted to become a particular

differentiated cell, then another stem cell seemingly undergoes mitosis. This appears to be the

case since the percentage of stem cells seems to be the same in infants and in adult humans. The

role of the stromal cell microenvironment in hematopoiesis is well documented. Specific

stromal cell lines have been isolated and cloned and some their growth factors, differentiation,

factors and proliferative factors have been identified. Factors tht inhibit the differentiation of

stem cells have not been identified, if they exist. Neither have proliferation factors, been

identified that are specific for the stem cells.

It is important that the distinction between stem cells and precursor cells be defined.

The literature is confusing. Investigators use the terms interchangeably. It is our conclusion

that stem cells are programed and once they are committed to become a specific differentiated

cell line, they cease to be stem cells and become precursor cells. The reaction is apparently

irreversible.

The bioreactor vessels which provide an environment of simulated microgravity is a

major advance in cellular investigations. When the vessels become more widely available to

investigators, reports of their applicability will appear in scientific publications. It is

understandable that the efforts of the NASA engineers in providing such an apparatus will be a

boon to the space program. The environment of space is one of hypogravity and conclusive

evidence that some cells behave differently in altered gravity has been well documented.

Humans in space will be exposed for longer periods in altered gravity as space exploration

advances. The bioreactor vessels can serve as model systems for in vitro studies which could

give information that could be extrapolated to situations that will be encountered on missions to

Mars and beyond.

13-9
BIBLIOGRAPHY

Cogoli, A., 1985. Lymphocyte Reactivity During Spaceflight. IMMUNOLOGY TODAY, 6:1.

Cogoli, A., Tschopp, and P. Fuchs-Bislin. Cell Sensitivity to Gravity. SCIENCE, 13 July, 1984,

228-230, vol 225.

Corey, A.C., Desilva, A., and Williams D.A., 1990. Erythropoiesis in Murine Long-term

Marrow Cultures following Transfer of the Erythropoietin cDNA into Marrow Stromal

Cells. EXP HEMATOL 18: 201-204.

Dexter, T. Michael. 1987. Growth factor involved in haemopoiesis. J. CELL SCIENCE, 88, 1-6.

Gmunder, F.K., and A. Cogoli. 1988. Cultivation of Single Cells in Space. APPL. MICROGRAVITY

TECH. 1,3, 115-122.

Hayflick, L. 1977. The Cellular Basis for Biological Aging. In Finch, C.D., Hayflick, L. (eds):

HANDBOOK OF BIOLOGY OF AGING. New York: Van Nostrand Reinhold Co., 159-179.

Jacobs, P,. and D. Metcalf. 1979. Bone Marrow Culture in Vitro. EXP. HEMAT. 7:177.

Johnson, G.R., and D. Metcalf. 1977. Pure and mixed erythroid colony formation in vitro.

PROC. NATL ACAD. SCI, USA, 74:3879.

Keever, A.A., Waite, K, Small T, Levick, J, Sullivan, M, Hsauch, M, Evans, R.L., O'Reilly, R.J.

1987. Interleukin 2-activated killer cells in patients following transplants. BLOOD,

70 (6) 1893-1903.

Lorenzi, T. 1986. Effects of Hypergravity on "whole blood" cultures of human lymphocytes.

AVIAT. SPACE ENVIRON. MED. 57:1131-1135.

McDivitt, R.W., Stone, K.R., Meyer, J.S. 1984. A Method for Dissociation of Viable Human

Breast Cancer Cells that Produces Flow Cytometric Kinetic Information. CANCER RES.,

44, 2628.

Nijhof, W. and Wierenga, P.K. 1985. Characterization of a Cycling Pluripotent Stem Cell

Population. EUR J. CELL BIOL 39,136.

Nolta, J.A., Sender, L.S., Barranger, J.A., and Kohn, D.B., 1990. Expression of human

glucocerebrosidase in murine long-term bone marrow cultures after retroviral

vector-mediated transfer. BLOOD, 75, (3) 787-797.

Ploemacher, R.E., and Brons, N.J. 1988. Isolation of hemopoietic stem cell subsets from

murine bone marrow. EXP. HEMATOL. 16, 210-26.

13-10
Principato, M., Klinken, S.P., Cleveland, J.L., Rapp. U.R., Holmes, K.L, Pierce, J.H., and

Morse, H.C , 1988. In vitro transformation of murine bone marrow cells with a

v-raf/v-myc retrovirus yields clonally related mature B cells and macrophages. CURR

TOP MICROBIOL IMMUNOL, 141, 31-41.

Rowley, S.D., Sharkis, S.J., Hattenburg, C., and Sensenbrenner, L.L., 1987. Culture

from Human Bone Marrow of Blast Progenitor Cells. BLOOD, 69, 804-808.

Schuening, F.G., Rainer, S. Meyer, J, and Goehle, S., 1989. Long-term Culture of Canine Bone

Marrow Cells. EXP. HEMATOL 17; 411-417.

Sonnenfeld, G, Mandel, A.D., Konstantinova, I.V., Taylor, G.R., Berry, W.D., Wellhausen S.R.,

Lesnyak, A.T., and Fuchs, B.B., 1990. Effects of Space flight on Levels and Activity of

Immune Cells. AVIA SPACE AND ENVIRON MED, 648-653.

Spangrude, G.J., Heimfeld, S, Weissman, I.L. 1988. Characterization of Mouse Hematopoietic

Stem Cells. SCIENCE. 241, 58-62.

Van De Rijn, M, Heimfeld, S., Spangrude, G.J., and Weissman, I.L., 1989. Mouse hematopoietic

stem-cell antigen Sca-1 is a member of the Ly-6 antigen family. PROC. NATL. ACAD.

SCI. USA, 86, 4634-4638

Wilson, J.M., Danos, O., Grossman, M., Raulet, D.H., and Mulligan, R.C., 1990. Expression of

human adenosine deaminase in mice reaconstituted with retrovirus-transduced

hematopoietic stem cells. PROC NATL ACAD SCI USA, 87, (10), 439-443.

Worton, R.G., McCulloch, E.A., and Till, J.E. 1969. Physical separation of hemopoietic stem

cells from forming colonies in culture. J. CELL PHYSIOL. 74,171.

13-11
SUMMARY

The data summarized graphically are from the successful culture growths of murine bone

marrow in summer, 1989. The cells were grown in bioreactor vessels in an environment

which simulated some aspects of microgravity.

Page 13-13. Test Run #1

These cells were growing in simulated microgravity after 24 days. Their

numbers at that time were doubling daily. The number of days of growth is

plotted along the x axis and the log of the cell count number along the y axis.

Page 13-14 This graphical data is from the flow cytometer program. The cells monitored are

shown to be positive for Thy-1 and negative for FcReceptor antigen. This data is

consistent with that expected for stem cells. Fluorescence intensity is plotted on

the abscissa and cell numbers on the ordinate.

Page 13-15. This data from flow cytometer shows that the cells monitored are positive for

the "stem cell antigen" known as SCA-1. The clone which produces this antibody

is availabale from ATCC. Fluorescence intensity is plotted against forward

light scatter.

The program was gated to read only the viable cells in quadrant four.

13-12
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THE EFFECTS OF DEUTERIUM ON STATIC POSTURE CONTROL

Final Report

NASA/ASEE Summer Faculty Fellowship Program - 1990

Johnson Space Center

Prepared by:

Academic Rank:

University and Department:

NASA/JSC

Directorate:

Division:

Branch:

JSC Colleague:

Date Submitted:

Contract Number:

Charles S. Layne, Ph.D.

Assistant Professor

Kansas State University

Department of Kinesiology

Manhattan, Kansas 66506

Space and Life Sciences

Medical Sciences

Space Biomedical Research

Institute

Millard Reschke, Ph.D.

July 27, 1990

NGT-44-005-803

14-1
ABSTRACT

A significant operational problem impacting upon the Space

Shuttle program involves the astronaut's ability to safely egress

from the Orbiter during an emergency situation. Following space

flight, astronauts display significant movement problems. One

variable which may contribute to increased movement ataxia is

deuterium (D^O), an isotope of hydrogen/ Deuterium is present in

low levels within the Orbiter's water supply but may accumulate to

significant physiological levels during lengthy missions. Deuterium

has-been linked to a number of negative physiological responses,

including motion sickness, decreased metabolism and slowing of

neural conduction velocity. The purpose of-the present study was to

investigate the effects of D20 on static postural control in response

to a range of dosage levels?\ Nine subjects were divided into three

groups of three subjects each. The groups were divided in to a low,

(50 g/70 Kg body water), medium (100 g/70 Kg body water), and a

high (200 g/70 Kg body water) D20 dosage group. The subjects

static posture was assessed with the use of the EquiTest system, a

commercially available postural control evaluation system featuring

movable force plates and a visual surround that can be servoed to

the subject's sway. In addition to the force plate information, data

about the degree of subject sway about the hips and shoulders was

obtained. Additionally, surface electromyographic (EMG) data from

the selected lower limb muscles was collected along with saliva

samples used to determine the amount of deuterium enrichment

following D2o ingestion. Two baseline testing sessions were

performed using the EquiTest testing protocol prior to ingestion of

the D2Q. Thirty minutes after dosing, subjects again performed the

test. Two more post-dosing tests were run with an intertest

interval of one hour. Preliminary data analysis indicates that only

subjects in the high dose group displayed any significant static

postural problems. Future analyses of the sway and EMG is expected

to reveal significant variations in the subjects's postural control

strategy following D20 dosing. While functionally significant static

postural problems were not commonly observed, subjects in both the

medium and high dosage groups displayed significant, and in some

cases, severe voluntary movement problems. These problems

included locomotion and hand-eye coordination deficits.

14-2
INTRODUCTION

It is well documented that Space Shuttle crews are posturally

ataxic following flight. This instability results from

neurovestibular readaptation to a unit gravity environment, muscle

deconditioning, and to some extent, cardiovascular deconditioning.

Postural instability is a significant operational problem impacting

upon rapid emergency egress from the Orbiter. Understanding the

processes involved in movement control problems is critical if

countermeasures are to be developed to increase the probability of

successful emergency Shuttle egress.

One possible factor contributing to movement problems following

space flight is an increase in the levels of deuterium oxide (D20) in

the crew's physiological systems. Such an increase is likely to

occur because of the presence of D2fj in the Shuttle's drinking water

at levels exceeding those found in the nation's water supply. While

the absolute levels of deuterium oxide in the Shuttle water are

limited, it can be expected that a potentially physiologically

significant amount may accumulate during extended duration flights.

This increase results from the fact that D20 is not "washed out" of

the system with continuous ingestion of the Orbiter's drinking

water.

While deuterium oxide has been shown to have a number of

negative effects on mammals, few studies have attempted to assess

the effects of D^O on humans. In an effort to understand the impact

of deuterium oxide on postural stability, a pilot study was conducted

in June, 1990, as part of the Neurophysiology Laboratory's ongoing

effort to probe the inherent complexities of the human motor control

system. This project was undertaken in conjunction with the

Nutritional Biochemistry Laboratory.

BACKGROUND TO THE PROBLEM

Deuterium oxide, the non-radioactive isotope of hydrogen, has

been reported to have a variety of effects on physiological systems.

Some of the effects include decreased metabolism rate (Reuter, et

al., 1985), decreases in peripheral nerve conduction velocity

(Thompson, 1963), decreases in maximum muscle twitch tension

(Sato and Fujino, 1987) and positional alcohol nystagmus(Money and

Myles,1974). While these symptoms are observed in response to

14-3
relatively high dose levels of D2

0, it can reasonably be expected

that the physiological processes responsible for these symptoms are

functioning similarly in response to lower levels of deuterium oxide.

Thus, it becomes important to investigate what role, if any, the

isotope plays in the disruption of normal functioning.

The majority of studies employing human subjects are designed to

investigate the effects of deuterium oxide on the vestibular system.

Money and Myles (1974) reported that their subjects experienced

dizziness, nausea, and strong sensations of bodily rotations

following D20 ingestion. These symptoms primarily occurred while

the subjects were lying on their sides. It was also reported that the

subjects displayed a variation of positional alcohol nystagmus (PAN

I) while in the lateral position. Nystagmus is an involuntary

oscillating movement of the eyeballs in which they repeatedly turn

slowly in one direction and then rapidly reverse direction. The

direction of the nystagmus is identified based on the direction of

the fast phase of the eye movements. Drinking large amounts of

ethyl alcohol results in the eyes moving to the right during fast

phase of the nystagmus if the head is held with the right side down.

PAN I is called positional because it occurs when the head is

maintained in a certain position relative to gravity.

After drinking D20, Money and Myles subjects displayed what

these authors termed as PAN II. PAN II differs from PAN I in that

the direction of the fast phase of the nystagmus is in the direction

opposite from the side the head held in the lateral position. For

example, if the subject is lying on his or her left side the fast phase

is to the right. Nystagmus can be observed with the use of Fresnel

lenses placed over the subjects eyes. These specially designed

spectacles provide an opaque display to the subject while

magnifying the subject's eyes to the observer. In this manner, rapid

movements of the eyes can readily be detected.

Money and Myles (1974) suggested that deuterium oxide elicits

nystagmus by the following mechanism. The cupula of the

semicircular canal floats in a surrounding liquid (endolymph) which

has the same density. Under normal circumstances, angular

accelerations cause the cupula to move as a result of circular

endolymph movements. However, because of its neutral buoyancy the

cupula is not moved by linear accelerations or by gravity. Following

ingestion of deuterium oxide, the cupula acquires D20 faster than

the surrounding endolymph because of the prominence of blood

14-4
capillaries near the base of the cupula. The cupula's neutral

buoyancy is therefore lost as it becomes heavier than the

surrounding endolymph. This imbalance allows gravity to move the

cupula, thus, producing positional nystagmus responses when the

head achieves specific orientations relative to gravity.

Greven, et al., (1977) have also reported similar responses to

D

2

0. More importantly, perhaps, is their finding that the speed of

the fast phase of the PAN II nystagmus was increased during

exposure to G-loads of 2 and 3 G. Thus, increased level of gravity

appear to enhance the response of the vestibular system to

deuterium oxide.

The reported findings have important implications for astronauts

attempting rapid egress from the Space Shuttle as it is well known,

from work with vestibular patients, that altered vestibular input is

disruptive to both postural and movement control. Greven, et al's.

(1977) results suggest that even low levels of D20 in the

astronaut's physiological systems may pose a problem during the

high gravity loads experienced during re-entry. This report

describes a preliminary attempt to characterize the effects of three

different dosage levels upon static postural control.

PROJECT SUMMARY

Methods

The static postural control of nine volunteer subjects was tested

both prior to and following ingestion of deuterium oxide. The nine

individuals were divided into three groups of three subjects each.

Each group was administered a different dose level which were

characterized as low, medium or high doses. The absolute amount of

D

2

0 administered to each subject varied as levels were adjusted to

percentage of body water levels based upon percentage of body fat

measures. The three dosage levels were equivalent to: a) 50 g/70 Kg

body water; b) 100 g/70 Kg body water and c) 200 g/Kg body water.

The dosage levels were consistent with the range of levels reported

in the literature. The D20 supply was 99.9% atom percent (ICON

Services).

The standing static posture of the subjects was tested using the

EquiTest protocol (Neurocom International). The EquiTest system

consists of a motor-driven footplate, capable of translations in the

14-5
anterior-posterior directions and rotations about the ankle joint. A

motor-driven visual surround allows for rotational movements about

the subject's ankles. The force platform provides information about

the ground reaction forces exerted along the X.Y.and Z axes and

horizontal sheer. Sway bars interfaced with potentiometers, are

attached to the shoulders and hip area and provide information about

the degree of movement about these two joints. The testing

protocol was comprised of a series of movement coordination and

sensory organization tests. The subjects attempted to maintain

equilibrium without lifting their feet from the platform while their

arms remained folded across their chest.

The movement coordination test was subdivided into four unique

tasks.

1. Anterior translations (resulting in backward sway)

2. Posterior translations (resulting in forward sway)

3. Toes-up rotations

4. Toes-down rotations

Subjects experienced three trials of Conditions 1 and 2 and five

trials of the two remaining conditions.

The sensory organization test is designed to determine the

relative contribution of different sensory systems to the subject's

overall equilibrium strategy. This can be accomplished because of

two features of the EquiTest system. The visual surround can be

made to move in response to the pressure exerted by the subject's

feet on the force platform. As a subject sways forward, the visual

surround sways forward an equivalent distance. In this situation,

visual feedback about the degree of subject sway is nulled out. If a

subject were to rely exclusively on visual input to maintain balance

he or she would soon fall forward. Thus, to maintain upright stance,

the subject must learn to utilize vestibular and proprioception

inputs.

The second feature of the EquiTest systems which enables

investigators to determine to what extent a subject relies on a

specific sensory input is the platform's ability to sway in response

to changes in the subject's applied foot pressure. For instance, if

the subject begins to exert pressure on the front of the platform the

support surface begins to rotate downward. In this situation the

subject receives inappropriate proprioception information from the

ankle joints. If the subject were to rely exclusively on this

inappropriate input, which is indicating to the subject he or she is

14-6
not actually swaying forward because the initial ankle angle is being

maintained, the subject would soon lose balance. By combining the

above two features in either eyes open or eyes closed conditions, a

complete profile of the relative weighting each subject gives to the

various sensory inputs can be achieved.

The sensory organization test was subdivided into six unique

tasks.

1. Normal vision, fixed support surface

2. Absent vision (eyes closed) fixed support surface

3. Sway-reference vision, fixed support surface

4. Normal vision, sway-reference support surface

5. Absent vision (eyes closed), sway-reference support surface

6. Sway-reference vision, sway-reference support surface

Each task was 20 seconds in duration with tasks 3,4,5 and 6 being

repeated three times.

The following parameters are routinely derived from the above

testing protocol and are a output from the system in a hardcopy

format following completion of the testing.

Movement Coordination Tests:

Static Symmetry: Average right/left weight distribution during

test.

Force Latency: Time from onset of support surface perturbation

until initial active force response. This is calculated separately for

each leg.

Strength Amplitude: Average slope of initial active force response

to support surface perturbation. This is calculated separately for

each leg.

Dynamic Symmetry: Average right/left strength amplitude

distribution during test.

Sway Amplitude: Average (rms) and peak-to-peak amplitudes of

anterior-posterior sway calculated for center of mass, ankle angle,

hip displacement, shoulder displacement, and head displacement.

14-7
Adaptation: Relative decrease in sway amplitude occurring with

repeated presentation of the ankle rotation stimulus.

Strategy: Relative contributions of ankle and hip joint motions to

sway control following support surface translations.

Sway Amplitude: Average (rms) and peak-to-peak amplitudes of

sway calculated for center of mass, ankle angle, hip displacement,

shoulder displacement, and head displacement during test.

Strategy: Relative contributions of ankle and hip joint motions to

sway control during test based on force, transducer and joint

position measurements.

Equilibrium: Relative stability of the subject's sway control during

each individual test.

Composite Equilibrium:: Composite estimate of the relative

stability of the subject's sway control based on weighted sums of

individual test equilibrium scores.

In addition to the above parameters, surface electromyography

(EMG) was used to monitor the activity of the following muscles of

the left lower limb: soleus, gastrocnemius, bicep femoris

(hamstring), and rectus femoris (quadricep). EMG data from the

movement coordination tests was analyzed by obtaining latency and

amplitude variables. Latency measures were obtained by

determining the initial increase in muscle activity relative to

platform movement. Amplitude measures were defined as the

average (rms) amplitude from platform movement onset until the

end of the active force response. Both variables were determined

independently for each muscle, for each trial. The Pensacola

Coriolis Sickness Scale was administered throughout the testing

procedures in order to monitor the subject's level of possible

physical discomfort. The Pensacola Coriolis Sickness Scale has been

extensively used to obtain a subjective measure of motion sickness.

All testing was completed in the Dynamic Posture Laboratory

located in the KRUG Life Sciences' portion of the Intermetrics

building (1100 Hercules Drive, Houston, Texas). Subjects arrived at

14-8
the testing site and were prepared for EMG collection. This involved

shaving and lightly abrading the skin above the electrode placement

sites. The electrodes where then positioned over the muscles, and

skin impedance measures were obtained. Before the subjects

mounted the platform, they donned a safety harness. The safety

harness attached to a safety bar that looped over the platform such

that it was impossible for the subjects to collapse if postural

equilibrium was completely lost. Once the subjects stepped onto the

platform the EMG lead were connected to the amplifiers and EMG

signal quality was checked. The testing procedures began by

positioning the subject's feet precisely on the platform and asking

the subject to fold their arms across their chest. Headphones

providing white noise designed to eliminate external cues from the

platform, were then placed on the subjects.

In order to obtain baseline values, the motor coordination and

sensory organization test protocol were completed two times.

There was a one hour intertest interval between the baseline

collection sessions. Immediately following the second baseline

testing session, the subjects ingested the pre-determined amount of

deuterium oxide. The subjects then assumed a comfortable lying

position on their left side.

Thirty minutes after dosing, subjects again mounted the posture

platform and were subjected to the motor coordination and sensory

organization tests. Then subjects then resumed their reclining

position. Two additional post-dosing sessions were completed with

an intertest interval of one hour. Both prior to mounting the

platform and at the conclusion of each testing session the Pensacola

Coriolis Sickness Scale was administered. Prior to each of the

baseline testing sessions, a saliva sample was collected in order to

determine the baseline levels of deuterium. Following D^O dosing

and prior to each of the enrichment of the sample. In some cases,

Fresnel lenses were applied and the subject was checked for

nystagmus. Following completion of the posture tests, the subjects

drank two liters of water. This procedure was employed to increase

the rate at which the deuterium oxide was "washed out" of the

system.

14-9
Results and Discussion

The saliva samples were centrifuged at Johnson Space Center in

the Nutrition Biochemisty Laboratory and then sent to University of

Chicago Medical Center for stable isotope analysis. The results of

this analysis are unavailable at the present time.

Preliminary analysis of the data obtained from the EquiTest

system printout revealed that D20 had little affect upon the

subjects static postural control. This was especially true for the

low dosage group. However, at the medium and high dosage levels,

initial analysis of conditions 5 and 6 of the sensory organization

tests, revealed subjects were less stable post-dose relative to

baseline measures. This result is consistent with the previously

reported findings that vestibular system functioning is altered as a

result of deuterium oxide ingestion. Both condtions 5 and 6 are

configured such that the subject must preferentially rely on

vestibular input to maintain upright stance. Therefore, is was

hypothesized that the results from these two conditions would be

most sensitive to changes in postural stability following D20

ingestion.

Results from the Pensacola Coriolis Sickness Scale revealed that

none of the subjects in the low dosage group indicated any unusual

physical sensations other than a feeling of being chilled. This

finding may possibly be explained by the fact that deuterium has

been reported to decrease metabolism. Similar sensations were

reported by the subjects in the medium dosage group.

On the other hand, subjects in the high D20 dosage group reported

a variety of physical symptoms, including movement illusions both

of their body and the environment. All three subjects in this group

displayed nystagmus based on Fresnel lense observation. One

subject vomited repeatedly. This subject's nausea was most violent

following changes in body postion, i.e., moving from either a

reclining position to standing or vice versa. Despite these

symptoms, this subject was able to achieve static balance measures

consistent with his baseline scores. Consistent with the reports of

Money and Myles (1974), the only subject to become significantly

nauseated refrains from all exposure to ethyl alcohol. The reason

for this is unknown, but it may be that drinkers have developed

compensatory processes allowing them to function relatively

14-10
unimpaired in response to low to moderate levels of alcohol

consumption. These compensatory processes may have been

operating in response to altered vestibular input resulting from

deuterium ingestion.

One interesting phenomenon was observed in all members of this

group and in one subject in the medium dosage group. These subjects

reported (and displayed) numerous movement coordination problems

when asked to make voluntary limb movements. The subjects

became very unstable when asked to walk even short distances. This

instability was compensated for by adopting wide gait patterns.

This behavior closely resembled that of patients with cerebellar

disturbances. These subjects also reported disturbances in handeye coordination. For instance, one subject displayed great

difficulty in securing a buckle similar to a commen seat belt about

his waist. It is possible that the above symptoms may be partially

the result of neuromuscular processes which were impaired by the

relatively high level of deuterium.

Due to both time limitations and technical problems, further

analysis of the hip and shoulder sway data and the EMG data has not

been completed. Sway data is currently being evaluated by members

of the Dynamic Posture Laboratory working group. The EMG data will

be analyzed in the coming months in the Neuromuscular Laboratory

at Kansas State University.

Conclusions

The preliminary results of the present study indicate that high

levels of deuterium in the body's physiological systems can result in

significant movement problems, as well as produce epigastric

sickness in some subjects. Static postural control appears to be

only slightly impaired, even with relatively high dosage levels of

deuterium. However, subsequent analysis of body sway parameters

and EMG data is expected to reveal that the subjects were, in fact,

less stable following ingestion of deuterium oxide. Future research

should focus on the processes responsible for the observed voluntary

movement problems displayed by the current subjects. Obviously,

any factor which contributes to impaired movement control greatly

impacts upon an astronaut's ability to safely egress from the Space

Shuttle in an emergency situation.

14-11
REFERENCES

Sato, Y. and Fujino, M. Inhibition of arsenazo III Ca transient with

deuterium oxide in frog twitch fibers at a resting sarcomere length.

Japanese Journal of Physiology. 37 (1) 149-53, 1987.

Money, K. E. and Myles, W. S. Heavy water nystagmus and effects of

alcohol. Nature. 247 (5440) 404-405, 1974.

Reuter, H. D. Fischer J. H., and Thiele, S. Investigations on the

effects of heavy water (D20) on the functional activity of human

platelets. Haemostasis. 15 (3) 157-63, 1985.

Greven, A. J., Oosterveld, W. J. and Samson, G. The influence of heavy

water on the vestibular system: A study of heavy water nystagmus

in Advances, in Oto-Rhino-larvng. vol 22, p.152-159.

Thomson, J. F. Biological Effects of Deuterium. Pergamon Press:

New York, New York, p. 80, 1963.

14-12
NASA

National Aeronautics and

Space Administration

REPORT DOCUMENTATION PAGE

1. Report No.

NASA CR 185637

2. Government Accession No. 3. Recipient's Catalog No.

4. Title and Subtitle

NASA/ASEE Summer Faculty Felllowship Program-.-1990.

Volume 1 }

5. Report Date

December 1990

6. Performing Organization Code

7. Author(s)

Richard B. Bannerot and Stanley H. Goldstein, Editors 8. Performing Organization Report No.

9. Performing Organization Name and Address

University of Houston-University Park

Houston, TX 77204

10. Work Unit No.

11. Contractor Grant No.

NGT 44-005-803

12. Sponsoring Agency Name and Address

National Aeronautics and Space Administration

Washington, D.C. 20546

13. Type of Report and Period Covered

Contractor Report

14. Sponsoring Agency Code

15. Supplementary Notes

16. Abstract

The 1990 Johnson Space Center (JSC) National Aeronautics and Space Administration

(NASA)/American Society for Engineering Education (ASEE) Summer Faculty Fellowship Program

was conducted by the University of Houston-University Park and JSC. The 10-week program

was operated under the auspices of the ASEE. The program at JSC, as well as the programs

at other NASA Centers, was funded by the Office of University Affairs, NASA Headquarters,

Washington, D.C. The objectives of the program, which began nationally in 1964 and at JSC

in 1965, are (1)

 to further the professional knowledge of qualified engineering and

science faculty members; (2) to stimulate an exchange of ideas between participants and

NASA; (3) to enrich and refresh the research and teaching activities of participants'

institutions; (4) to contribute to the research objective of the NASA Centers.

Each faculty fellow spent at least 10 weeks at JSC engaged in a research project

commensurate with his/her interests and background and worked in collaboration with a

NASA/JSC colleague. This document is a compilation of the final reports on the research

projects performed by the faculty fellow during the summer of 1990. Volume 1 contains

reports 1 through 14, and Volume 2 contains reports 15 through 28.

17. Key Words (Suggested by Author(s)) 18. Distribution Statement

Unclassified - Unlimited

19. Security Classification (of this report)

Unclassified

20. Security Classification (of this page)

Unclassified

21. No. of pages 22. Price

For sale by the National Technical Information Service. Springfield. VA 22161-2171

JSC Form 1424 (Rev Aug 89) (Ethernet Jan 88)