NASA Contractor Report 201 377 

National Aeronautics and Space Ad~inistration 

(NASA)/American Society for Engineering Education 

(ASEE) Summer Faculty Fellowship Program - 1995 

Volume 1 

William A. Hyman and Donn G. Sickorez, Editors 

Grant NGT 44-001 -800 

August 1996 
NASA Contractor Report 201 377 

National Aeronautics and Space Administration (NASA)/American 

Society for Engineering Education (ASEE) Summer Faculty 

Fellowship Program - 1995 

Volume 1 

William A. Hyman, Editor 

Texas A&M University 

College Station, Texas 

Donn G. Sickorez, Editor 

LyAdon €3. Johnson Space Center 

Houston, Texas 

Grant NGT 44-001 -800 

August 1996 
This publication is available from the NASA Center for Aerospace Information, 

800 Elkridge Landing Road, Linthicum Heights, MD 21090-2934, (301) 621 -0390 

ii 
The 1 995 National Aeronautics and Space Administration (NASA)/American Society for 

Engineering Education (ASEE) Summer Faculty Fellowship at the Lyndon B. Johnson 

Space Center (JSC), including the White Sands Test Facility, was conducted by Texas 

A&M University and JSC. The program at JSC, as well as the programs at other NASA 

centers, was funded by the Education Division, Higher Education Branch, NASA 

Headquarters, Washington, D.C., with additional funds from the centers. The 

objectives of the program, which began nationally in 1964 and at JSC in 1965, are 

To further the professional knowledge of qualified engineering and science faculty 

members. 

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

0 To enrich and refresh the research and teaching activities of the participants' 

institutions. 

To contribute to the research objectives of the NASA centers. 

Each faculty participant spent at least 10 weeks at JSC engaged in a research project 

in collaboration with a NASNJSC colleague. In addition to the faculty participants, the 

1995 program included 5 students. The reports of two of the students are integral with 

that of the respective fellow. Three students wrote separate reports. Volume 1 

contains reports 1 through 15. Volume 2 contains reports 16 through 27 and the three 

student reports, S-1 through S-3. 

iii 

Contents 

Volume 1 

Acharya, R.S. 

Akl, F.A. 

Anderson, G.T. 

Baker, S.D. 

Barrera, E.V. and 

Olivas, J.D. 

Coornbs, C.R. 

Corey, K.A. 

Duncan, A.B. and 

Sciascia, V.M. 

Hall, E.B. 

Hogan, H.A. 

Janikow, C.Z. 

Khorsandi , M . 

Kleis, S.J. 

Knopp, J. 

Leon, J.V. 

Characterization of Microgravity Effects on Bone 

Structure and Strength Using Fractal Analysis .................. 1-1 

Test Outline for Flutter Analysis of Rectangular 

Panels in Rarefied Flow Conditions ................................ .. 2-1 

Predictive Modeling of Cardiac Ischemia ........................ .. 3-1 

Some Considerations in the Determination of the 

Accuracy of a Measurement in Space of the 

Newtonian Gravitational Constant (G) ....... ...................... .. 4-1 

Material Assessment of Components of the 

Extravehicular Mobility Unit .............................................. 5-1 

Regional and Localized Pyroclastic Deposits on 

the Moon ............................................................................ 6-1 

Design of Plant Gas Exchange Experiments in a 

Variable Pressure Growth Chamber .................................. 7-1 

Investigation of Two-Phase Flows in Piping Bends 

and Elbows ........................................................................ 8-1 

A Velocity Distribution Model for Steady State 

Heat Transfer ............................ ........... ...................... .. ..... 9-1 

Trabecular Bone Mechanical Properties and Fractal 

Dimensions ........................................ ... ..... ................... ..... 10-1 

Constraints in Genetic Programming .................................. 1 1-1 

Orbiter Flight Deck Redesign (A Physical Layout for 

a Futuristic Flight Deck ....................................................... 12-1 

Fluid Dynamic Verification Experiments on STS-70 .......... 13-1 

LCTV Holographic Imaging ............................................... 14-1 

Intelligent Planning and Scheduling for Controlled 

Life Support Systems ................ ........ ........ ...................... .. 15-1 

V 
Contents 

Volume 2 

Loganantharaj, R. 

McGinnis, M.R. 

Pate, D.W. 

Perry, E. 

Richardson, A.O. 

Rob, M.A. 

Shearrow, C.A. 

Snow, L.D. 

Tan, A. 

Taneja, V.S. 

Watson, J.C. 

Waugaman, D. 

Theory and Ontology for Sharing Temporal Knowledge ... 

Evaluation of Automated Yeast Identification Systems ..... 

A Human Factors Analysis of EVA Time Requirements .... 

Stable isotope Analysis of Molecular Oxygen From 

Silicates and Oxides Using CO, Laser Extraction ............. 

Iliad Testing and a Kalman Filter for 3-D Pose 

Estimation ... ... . . . .. . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . .. . . . . . 

Feasibility Study of Velocity and Temperature 

Measurements of an Arejet Flow Using Laser 

Resonance Doppler Velocimetric (LRDV) Technique ....... 

Design and Implementation of a Windows NT Network 

to Support CNC Activities. ................................................. 

Dextroamphetamine: A P harmocologic 

Countermeasure for a Space Motion Sickness 

and Orthostatic Dysfunction .............................................. 

Detecting the Dynamical State of the Atmosphere 

From the Orbital Decay of the Oderacs Sphere ................ 

Proportional and Scale Change Models to Project 

Failures of Mechanical Components With Applications 

to Space Station ................................................................ 

An Optimal User-Interface for Epirns Database 

Conversions and SSQ 25002 EEE Parts Screening ......... 

Support of Gas Flowmeter Upgrade .................................. 

16-1 

17-1 

18-1 

19-1 

20-1 

21-1 

22-1 

23-1 

24-1 

25-1 

26-1 

27-1 

vi 
Cauthen, C. 

Marble, E. 

Whitaker, L.O. 

Contents 

Student Papers 

Volcanism in Eastern Africa ............................................... S-1 

Measuring the Spectral Emissivity of Thermal 

Protection Materials During Atmospheric 

Reentry Simulation ............................................................ 5-2 

An intelligent Crop Planning Tool for Controlled 

Ecological Life Support Systems ....................................... S-3 

vi i 
Characterization of Microgravity Effects on Bone Structure and 

Strength Using Fractal Analysis 

Final Report 

NASA/ASEE Summer Faculty Fellowship Program-% 

Johnson Space Center 

Raj S. Achqa 

Associate Professor 

Electrical & Computer Engineering 

State University of New York at Buf€alo 

Buffdo, NY 14260 

achqa@eng. buf€alo.edu 

Linda Shackelford 

Technical Lead, Bone & Muscle Lab 

NASA Johnson Space Center 

Houston, Texas 77058 

1-1 
1 Abstract 

Protecting humans against extreme environmental conditions requires a thorough understanding of the pathophysiological changes resulting from the exposure to those extreme conditions. 

Knowledge of the degree of medical risk associated with the exposure is of paramount importance 

in the design of effective prophylactic and therapeutic measures for space exploration. Major 

health hazards due to musculoskeletal systems include the signs and symptoms of hypercalciuria, 

lengthy recovery of lost bone tissue after flight, the possibility of irreversible trabecular bone loss, 

the possible effect of calcification in the soft tissues, and the possible increase in fracture potential. In this research, we characterize the trabecular structure with the aid of fractal analysis. 

Our research to relate local trabecular structural information to microgravity conditions is an 

important initial step in understanding the effect of microgravity and countermeasures on bone 

condition and strength. The proposed research is also closely linked with Osteoporosis and will 

benefit the general population. 

1-2 
1 Hypot hesis/Rationale 

0 The rationale for this research is based on the premise that microgravity conditions change 

bone structure in addition to bone mass. 

0 Bone structure can be characterized by fractal geometry. 

0 Fractal characterization of bone structural changes due to microgravity conditions is not 

only optimal but also pragmatic. 

2 Specific Aims 

The overall goal is the characterization of bone structural changes due to microgravity with 

the aid of fractals. 

0 We propose the use of the Alternating Sequential Filters (ASF) method to estimate (he 

fractal dimension of images. When only small window sizes are available, Continuous 

Alternating Sequential Filters (CASF) will be used for fractal dimension estimation. 

0 We compute the fractal dimension of subjects participating in the bed rest study. 

0 We apply fractal analysis to samples of human bone and relate it to mechanical strength. 

3 Significance 

Protecting humans against extreme environmental conditions requires a thorough understanding of the pathophysiological changes resulting from the exposure to those extreme conditions. 

Knowledge of the degree of medical risk associated with the exposure is of paramount importance 

in the design of effective prophylactic and therapeutic measures for space exploration. Major 

health hazards due to musculoskeletal systems include the signs and symptoms of hypercalciuria, 

lengthy recovery of lost bone tissue after flight, the possibility of irreversible trabecular bone loss, 

the possible effect of calcification in the soft tissues, and the possible increase in fracture potential. Our research to relate local trabecular structural information to microgravity conditions 

is an important initial step in understanding the effect of microgravity and countermeasures on 

bone condition and strength. The proposed research is also closely linked with Osteoporosis and 

will benefit the general population. 
4 Background 

The effect of micro-gravity on the musculoskeletal system is currently being studied. Significant changes in bone and muscle have been shown after long term space flight. Similar changes 

have been demonstrated due to bed rest. Bone demineralization is particularly profound in 

weight bearing bones. Much of the current techniques to monitor bone condition use bone mass 

measurements. However bone mass measurements do not completely describe the mechanisms 

to distinguish Osteoporotic and Normal subjects.l It has been shown that the overlap between 

normals and osteoporosis is found for all of the bone mass measurement technologies: single 

and dual photon absorptiometry, quantitative computed tomography and direct measurement of 

bone area/volume on biopsy as well as radiogrammetry. A similar discordance is noted in the 

fact that it has not been regularly possible to find the expected correlation between severity of 

osteoporosis and degree of bone loss 

Structural parameters such as trabecular connectivity have been proposed as features for 

assessing bone c0nditions.l It has been shown that in vertebral crush fracture patients, elements 

such as vertical trabeculae are retained more or less intact, while elements such as horizontal bracing trabeculae are resorbed entirelp6 . This results in disconnection of large number 

of trabecular elements. However, in non-fracture patients connections between elements were 

preserved. Long vertical trabeculae are subject to buckling under loading. When they lose 

their lateral connections to adjacent trabeculae, the degree of buckling may exceed the inherent 

strength of the bone. Structure can be thw be seen as an important feature in assessing bone 

condition. In this research, we propose the we of fmctals to model the trabecular bone structure. 

5 Fractal Analysis 

In the past few years a significant amount of effort has been devoted to the study of chaotic 

phenomena. A part of this effort is directed towards the study of fractals. As defined by 

Mandelbrot,12 fractals are surfaces whose dimensions are strictly greater than their topological 

dimensions. Intuitively, fractals are surfaces which are embedded in between the m and m + 1 

dimensional manifolds. A fractal object can be characterized by it’s dimension which may be 

interpreted as the quantity of space occupied by the object between the m and m+ 1 dimensional 

manifolds. Various alternative definitions of dimension have been proposed in the literature. For 

a detailed discussion of these different definitions the reader is referred to.141516 This research 

employs the definition commonly know as the capacity dimen~i0n.l~ 

It was Kolmogoro$l who originally proposed the capacity of a set as 

1-4 
where if the set in question is a bounded subset of a pdimensional Euclidean space Rp , then 

N(E) is the minimum number of pdimensional cubes of side e needed to cover the set. For a 

Ractal set, d cun be a non-integer. 

Fractals are known to obey the self-similarity property. Self-similarity implies that the statistical properties of a fractal are independent of the scale or resolution of observation. 

There are number of ways in which fractal geometry can be applied to the analysis of image 

texture. Pentland et all' used a method related to the co-occurrence matrix technique of texture 

classification based on fractal dimension. They found the standard deviations of the difference of 

gray levels separated by a given vector and plotted it against the vector lengths as a log-log graph. 

Maragos has used Morphological Covers to estimate Fractal dimension of Synthetic Images.17 

In another technique7 a two dimensional gray level image is represented as a three-dimensional 

surface whose height at each point represents the gray level at that point and the surface area 

is measured at different scales. It has also been shown that8 an n-dimensional fractal object 

can be characterized by the fractional Brownian motion of n variables and that the relationship 

between the power spectral density and r are independent of the projection.30 This makes the 

fractal dimension computed from the projections of an n-dimensional fractal object represent 

the original object. Several studies have modeled radiographic bone images using fractional 

Brownian motion and have used maximum likelihood estimation to find the fractal dimensi~n.~~~ 

A recent study has indicated that fractal analysis can distinguish between dental radiographs 

of pre and post menopausal women.13 Analyses of dental radiographs have been shown to be 

independent of imaging conditions involved in taking the radiographs (such as the =@e between 

x-ray collimator and anatomical structure of interest) to a significant extent.l0 These preliminary 

studies also suggest that the fractal measure is to a major extent, independent of the anatomical 

site being analyzed. Another study used fractal dimensions to attempt predicting osseous changes 

in ankle fractures?' 

A variety of methods have been proposed to estimate the fractal dimension of trabecular bone 

str~ct~res.~~~~~~~~ An important problem is the estimation of fractal dimensionbm images when 

only small window sizes of the desired structures are available. In this proposal, a new method 

based on Alternating Sequential Filters (ASF), is presented to estimate the dimension of a fractal 

object. When only small window sizes (between 16 x 16 to 64 x 64) are available, we propose 

the use of Continuous Alternating Sequential Filters (CASF) for fractal dimension estimation. 

Frequently MRI studies are carried out to provide images of the spine. The individual vetebra 

occupies only a small region of the entire image of the spine (window size less than 50 X 50 ). 

CASF methods are well suited to handle these small window size situations. However, if the 

window size is greater then: 64 x 64, ASF methods can be used. 

1-5 
5.1 Alternating Sequential Filter (ASF) 

The method presented here to estimate fractal dimension is based on using Alternating Sequential Filters (ASF). Due to space limitation, a very brief review of ASF is presented. For 

further details on the morphological concepts presented here the reader-is referred to?212226 Alternating Sequential Filters appeared initially in the work of Ste~mberg.~~ Theimage X is filtered 

by a closing operation 41 followed by an opening operation 71, then it is filtered again by a larger 

closing 42 and a larger opening 72, etc ..., which in essence produces the operator 

Transformations that apply prod&ts of openings and closing in Werd introduce less distortions 

than individual operation such as dilations. The operations openings and closing, tend to preserve 

the 'rough' nature of the image X . Although the use of dilations and erosions have been proposed 

in the literature to estimate the fractal it was observed in the scope of this work 

that ASF's are more suitable for estimating fractal dimension. 

Let 2 be a complete lattice. Now define two mappings, a pair of primitives, (A,X) + 7A(X) 

and (A, X) 4 yA(X) from R+ x C into C such that for all A > 0, yA is an opening and q5A is a 

closing such that 

Note that A represents the size of the structuring elements used and X is any arbitrary set on 

2. Now let mA be an operator defined as: 

A 2 p * 7A < 7p and $9 > 4p (3) 

and for pairs A, A' E W+ with A' construct the sequence of products 

A morphological filter called an Alternating Sequential Filter with primitives 7 and 4 and bounds 

A and A' is defined to be: 

M = Mit = /\&(A, A'), (6) 

where M is the infimum over all Mk. The mapping M is increasing and idempotent for A' > A. 

Once an ASF representation of the image is obtained, the fractal dimension can be easily 

computed with the aid of equation 1. 

1-6 
5.2 Continuous Alternating Sequential Filters (CASF) 

We propose the use of CASF when only small window sizes of the desired structure are 

available in the image. With larger window sizes, ASF methods can be used. The lattice C is 

assumed to be a locally compact Hausdorf topological space. In the digital case the definition 

of compactness of a space has to be handled more carefully. Let 5: be the sampled version of an 

arbitrary d-dimensional function F, where m < d is the topological dimension of F. It is assumed 

that Q is the only function available. All characteristics of F at higher resolutions are lost and 

as such have to be estimated from Q. Compactness of the function Q has to be considered at 

each scale value at which the function B is being observed. The following assumptions are made 

about an arbitrary function E, 

F is a measurable, continuous, convex and a smooth function with known number of continuous derivatives. 

A variety of techniques can be employed to reconstruct the function F from the function Q 

given that some of the above assumptions are satisfied.% 

Let Q be a d-dimensional fiactal set. It is noted that d is not necessarily an integer. Also Q is 

embedded between m and m + 1 dimensional euclidean manifolds such that m < d < m + 1. Let 

8 = ASF(B) be a morphological mapping from W+ x C into C over some arbitrary neighborhood 

U defined by the size of the structuring element B. Note that the ASF is being used as the locally 

smoothing operator A4 described above. The use of ASF filters preserves the global nonlinear 

characteristics of 5: while performing some level of smoothing over the local neighborhood U. 

Let 5:& = T (c) be the reconstructed object 5: at a resolution scale e and cE = ASF(Gc). The 

sets c& provide a pyramidal representation as different scale values e are used and the size of ce 

is changed accordingly. As in (l), let N(E, U) be the number of m-dimensional cubes required 

to cover the neighborhood U of c&. Over any arbitrary neighborhood U , the function N(e, U) 

is a mapping from R+x C 

- 

W+. The fractal dimension d can then be estimated by: 

log N(E, U) = d log E 

Note that the sum above is taken over all compact, closed, neighborhoods U of G&. 

6 Preliminary Experimental Results. 

6.1 Bedrest Studies 

(7) 

Fractal analysis was performed on calcaneus regions of subjects undergoing bedrest study. 

Fig 1 shows one slice of the calcaneus region imaged with the MRI scanner. Figure 2 shows the 

1-7 
location of 5 different window locations in which the fractal dimension was computed. Figure 3 

shows that the fractal dimension of the calcaneus region as a function of time. 

6.2 Fractal Analysis of Tibia 

MRI images of an isolated tibia were obtained. Fig 4 shows a slice of the MRI image of the 

tibia. Fig 5 shows the location of the 53 windows in which the fractal dimension was computed. 

Fig 6 shows the plot of the fractal dimension as a function for the 53 different window locations 

in the image. 

7 Summary and Conclusions 

We have used the fractal dimension to characterize the trabecular bone structure. We have 

computed the fractal dimension in the calcaneus region of a bedrest subject. We have also 

computed the fractal dimension of an isolated tibia scanned in the -1 scanner. We plan on 

relating the fractal dimension to mechanical strength in an ongoing research project. 

8 REFERENCES 

[I] R. P. Heaney, ‘Osteoporotic Fracture Space: An Hypothesis’, Bone and Mineral, ~016, ppl13, 1989. 

[2] J. Samarabandu, R. Acharya, E. Hausmann, and K. Allen, “Analysis of Bone X-Rays Using 

Morphological Fractals”, IEEE iprans. on Medical Imag., Vol. 12., No. 3, Sept. 1993. 

[3] N. Gache et al, “Fractal Dimension Estimators for Fractional Brownian Motions” pp3557- 

3560, ICASSP 91. 

[4] A. Morales and R. Acharya, ”An Image Pyramid with Alternating Sequential Filters”, IEEE 

Transactions on Image Processing, June 1995. (In Press) 

[5] E. Kleerekoper et al, ”Calcaneus Bone Architecture and Bone Strength”, in Editor: Christinsen C, Osteoporosis 1987, Viborg, Denmark Norhaven A/s-1987, pp 289-300. 

[6] J. E. Aaron et al, ”The Microanatomy of Trabecular Bone Loss in Normal Aging Men and 

Women”, Clin Orthop Res, ~01215, pp260-271, 1987. 

[7] S. Peleg et al, ”Multiple Resolution Texture Analysis and Classification”, IEEE PAMI, vol 

6, NO 4, ~~518-523, July 1984. 

1-8 
[8] T. Lundhal et al, "Fractional Brownian Motion: A Maximum Likelihood Estimator and It's 

Application to Image Texture", IEEE TMI, vol5, pp152-161, Sep 86. 

[9] C. Fortin et al, "Fractal Dimension in the Analysis of Medical Images" , IEEE Engineering 

in Medicine and Biology Magazine, vol 11, pp65-71, 1992. 

[lo] R. L. Webber et al, "Evaluation of Site Specific Differences in Trabecular Bone Using Fractal 

Geometry" , Journal of Dental Research, Abstract no 2095, 1991. 

[ll] A. Pentland, "Fractal Based Description of Natural Scenes" , IEEE-CWR, pp209-210, June 

1983. 

[12] B. B. Mandelbrot, "Fractals: Form, Chance and Dimension" , Freeman, San Francisco, 1977. 

[13] U. E. Ruttimann, "The Use of Fractal Geometry to Quantitate Bone Structures from Radiographs,', J Dental Research, Abstract 1431, 1990. 

[14] J. D. Farmer, E. Ott, J. A. Yorke, "The Dimension of Chaotic Attractors", Physica YD, pg. 

153 -180, North-Holland Publishing Company, 1983. 

[15) T. S. Parker and L. 0. Chua, Practical Numerical Algorithms for Chaotic Systems, pg. 

167-199, Springer-Verlag 1989. 

1161 A. Lasota and M. C. Mackey, Chaos, Fractals ana' Noise, pg. 432-437, Second Edition, 

Springer-Verlag, 1994. 

1171 P. Maragos et al, "Measuring Fkactal Dimension of Signals: Morphological Covers and 

Iterative Optimization", pp 108-121, IEEE Transactions on Signal Processing, vol41, No 1, 

Jan 1993. 

[18] S. G. Mallat, "A Theory for Multiresolution Signal Decomposition: The Wavelet Representation", IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 11, No. 7, pg. 

674693, Jul. 1989. 

[19] U. E. Ruttiman and J. A. Ship, "The Use of Fractal Geometry to Quantitate Bone Structure 

From Ftadiographs" , J. Dent. Res., pg. 69, 1990. Abstract no. 1431. 

[20] S. Majumdar et al, "Application of Fractal Geometry Techniques to The Study of Trabecular 

Bone", Med. Phys. 20 (6), Nov/Dec 1993. 

[21] J. Serra, Image Analysis and Mathematical Morphology, New York, Academic Press, 1982. 

[22] J. Serra, Image Analysis and Mathematical Morphology, Vol. 2, New York, Academic Press, 

1988. 

E231 C. L. Benhamou et al, "F'ractal Organization of Trabecular Bone Images on Calcaneus 

Radiographs", pp1909-1918, Journal of Bone and Mineral Research, vol9, No 12,1994. 

1-9 
[24] Von Mises, Richard, ”Mathematical Theory of Probability and Statistics”, Academic Press, 

1964. 

[25] SPSS: Statistical Package for the Social Sciences, ed Norman H. Nile, McGraw Hill. 

[26] C. Giardina and E. Dougherty, Morphological Methods in Image and Signal Processing, New 

Jersey, Prentice Hall 1988. 

[2?] S. R. Sternberg, ”Morphology for Grey Tone Functions”, Computer Vision Graphics and 

Image Processing, Vol. 35, 1986. 

[28] A. P. Korostelev and A. B. Tsybakov, Minimax Theory of Image Reconstruction, SpringerVerlag, 1993. 

[29] R. L. Webber et al, ”Predicting Osseous Changes in Anlsle Fractures”, IEEE Engineering 

in Medicine and Biology, pp103-110, March 1993. 

[30] W. S. Kulinski et al, ”Application of Fractal Texture Analysis to Segmentation of Dental 

Radiographs”, vol 1092, Medical Imaging-3, SPIE Proceedings, 1989. 

[31] A. N. Kolmogorov, ”A New Invariant for Transitive Dynamical Systems”, Dokl. Acad. Nauk 

SSSR, pg. 861-864, NO. 119, 1958 

1-10 
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1-11 
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TEST OUTLINE FOR FLUTTER ANALYSIS OF 

RECTANGULAR PANELS IN RAREFIED FLOW CONDITIONS 

Final Report 

NASNASEE Summer Faculty Fellowship Program--1 995 

Johnson Space Center 

Prepared By: 

Academic rank: 

University & Department: 

NASNJSC 

Directorate : 

Division : 

Branch: 

JSC Colleague: 

Date Submitted: 

Contract Number: 

Fred A. Akl, Ph.D., P.E. 

Professor 

Louisiana Tech University 

Department of Civil Engineering 

Ruston, Louisiana 71 272 

Engineering 

Structures and Mechanics 

Structures and Dynamics 

James D. Dagen 

August 7,1995 

NGT-44-001-800 

2- 1 
ABSTRACT 

Jet plume impingement forces acting on large flexible space structures 

may precipitate dynamically unstable behavior during space flights. Typical 

operating conditions in space involve rarefied gas flow regimes which are 

intrinsically distinct from continuum gas flow and are normally modeled using the 

kinetic theory of gas flow. Docking and undocking operations of the Space 

Shuttle with the Russian Mir space laboratory represent a scenario in which the 

stability boundaries of solar panels may be of interest. Extensive literature 

review of research work on the dynamic stability of rectangular panels in rarefied 

gas flow conditions indicated the lack of published reports dealing with this 

phenomenon. 

A recently completed preliminary study for NASA JSC dealing with the 

mathematical analysis of the stability of two-degree-of-freedom elasticallysupported rigid panels under the effect of rarefied gas flow was reviewed. A test 

plan outline is prepared for the purpose of conducting a series of experiments on 

four rectangular rigid test articles in a vacuum chamber under the effect of 

continuous and pulsating Nitrogen jet plumes. The purpose of the test plan is to 

gather enough data related to a number of key parameters to allow the validation 

of the two-degree-of-freedom mathematical model. The hardware required 

careful design to select a very lightweight material while satisfying rigidity and 

frequency requirements within the constraints of the test environment. The data 

to be obtained from the vacuum chamber tests can be compared with the 

predicted behavior of the theoretical two-degree-of-freedom model. Using the 

data obtained in this study, further research can identify the limitations of the 

mathematical model. In addition modifications to the mathematical model can be 

made, if warranted, to accurately predict the behavior of rigid panels under 

rarefied gas flow regimes. 

2-2 
INTRODUCTION 

This study is a step toward the development of an engineering tool 

capable of predicting the stability boundaries of solar panels while taking into 

consideration their unique structural characteristics. Although research on flutter 

analysis of structures in continuum gas flow regimes is well documented in the 

published literature, work on flutter analysis of structures in rarefied gas flow is 

virtually non-existent. In recent years, scientists and engineers at NASA JSG 

and elsewhere conducted a number of investigations to study the physics of jet 

plumes and their impingement loads on stationary rigid objects in vacuum 

chambers and in space (1,2,3,4,5). 

Literature review of the jet plume impingement forces and the dynamic 

stability of rectangular panels in rarefied gas flow conditions was undertaken. 

The review focused on a recently completed study dealing with the theoretical 

analysis of the flutter of a two degree-of-freedom rigid body model (6,7). A brief 

test outline is given for the purpose of investigating the experimental behavior of 

rectangular panels in a vacuum chamber under the effect of continuous and 

pulsating Nitrogen jet plume. Three of the four test articles will be attached to a 

flexible element which will allow torsional and bending vibrations, and one test 

article is stationary. Validation of the stability boundaries predicted by the 

theoretical rigid body model is the primary objective of the test plan. 

TEST OVERVIEW 

Tests on a total of four rectangular panels of 40" by 20" are outlined. The 

first test article (TA-I) consists of a rigid metal panel mounted on a rigid support. 

The second and third test articles (TA-II and TA-Ill) are elastically-supported 

rigid panels. The fourth test article (TA-IV) is an elastically-supported flexible 

panel. The tests will be conducted in Vacuum Chamber B at NASA JSC to study 

the dynamic stability of rectangular panels when subjected to rarefied gas 

continuous and pulsating flow in vacuum conditions. A number of key 

parameters will be varied to study the phenomenon of dynamic stability of these 

panels under different conditions. 

TEST SETUP 

The test setup is referenced to a global set of axes (XYZ) whose origin 

(O,O,O) is located at the center of the floor of Vacuum Chamber 8. The XY plane 

is parallel to the floor. The X-axis is oriented to the geographic east and the Yaxis is oriented toward the geographic north. The Z-axis is vertically upward for 

positive direction. 

2-3 
The gas nozzle will be located at (0, 0, 10 ft). The longitudinal axis of the 

nozzle will be parallel to the X-Y plane. The nozzle will be mounted on a turning 

table which will allow orientation of the nozzle axis to be at an angle 9 of 0" for 

TA-I, 90" for TA-II, 180" for TA-Ill and 270" for TA-IV, where the angle 0 is 

measured positive counterclockwise with respect to the positive X-axis. 

All the test articles (rigid or flexible) will be oriented with their transverse 

axis parallel to the Z-axis. The orientation of the longitudinal axis of the test 

articles (angle of attack) will vary during the tests. The longitudinal axis of the jet 

nozzle will be passing through the geometric center of the test articles during 

testing. Test article TA-I will be stationary during the tests. Test articles TA-II, 

TA-Ill and TA-IV will be supported along the transverse axis to provide the 

specified torsional frequency of 1 Hz for the test artidedsupport system while 

restricting the bending frequency of the system to at least 10 Hz. 

The far end of the support for test articles TA-II, TA-Ill and TA-IV will be 

secured to a mounting rig at or near the Vacuum Chamber floor such that 

translations and rotations about the X, Y, and Z axes are restrained. The 

mounting rig for TA-II shall be attached to a slider which will allow the distance 

between the test article and the nozzle exit to be varied within f 1 ft. The 

mounting rigs for all four test articles will also provide the facility to change the 

angle of attack of the test articles by rotating them about the Z-axis. 

A video camera, laser targets and a number of transducers will be set up 

on and around the test article. Data acquisition will be setup outside the 

Chamber for data A/D conversion and collection. 

JET PLUME 

Type: Nitrogen 

Nozzle: 

Flow: Continuous until plume collapse 

Pulsating flow: 

Dia. = 0,0065 in k0.0005 in single orifice. 

two scenarios: periodic square and periodic half-sine waves. 

Pulse duration to = 0.1 sec 

Pulse separation At = 0.2 sec. 

2-4 
TEST ARTICLES 

Test Article I (TA-I) 

TA-1 consists of a 40" by 20" rigid aluminum panel of uniform thickness 

with a Kapton thin film bonded to the front side. The panel will be supported by 

brackets, or other type of support, which will restrain the plate during the tests. 

The thickness of the aluminum plate is governed by the distance needed to 

accommodate the pressure transducers to be attached to the test article. Three 

pressure transducers will be used to measure the dynamic pressure. Six 

thermocouples will used to measure the temperature of the plate surface. 

Test Article II (TA-II) 

TA-II consists of a 40" by 20" panel. The panel is made of a framework of 

114" composite tubes. A three mill Kapton film will cover the front side of the 

panel. A pretension force will be applied to the Kapton film during fabrication. 

The Kapton film is then secured to the back side of the outer composite tubes. 

The test article will be mounted on a slider which will allow the distance between 

the nozzle exit and the front of TA-II to vary from 3 ft to 5 ft. The mass moment 

of inertia of the test article/support system about the Z-axis, I, is equal to 60 

Ibm.in2. The torsional natural frequency of the test article/support system, fz, is 

equal to 1 Hz. 

Test Article 111 (TA-Ill) 

TA-Ill also consists of a 40" by 20" panel to be made of a honeycomb 

paper with two triangular cutout areas. A two mill Kapton (or mylar) film covers 

the front and back sides of the panel. An adhesive film of 5.5 mil will be used to 

glue the films to the panel. The mass moment of inertia of the test article/support 

system about the Z-axis, I, is equal to 60 Ibm.in2. The torsional natural 

frequency of the test article/support system, fi, is equal to 1 Hz. 

Test Article IV (TA-IV) 

TA-IV consists of a 40" by 20" flexible metal panel such that the bending 

frequency of the panel itself about its transverse axis (Z-axis) is 2 Hz. The mass 

moment of inertia about the Z-axis, I, is equal to 60 Ibm.in2. The torsional natural 

frequency of the test article/support system, fz, is equal to 1 Hz. 

2-5 
REFERENCES 

[l] 

[2] 

[3] 

[4] 

[5] 

[6] 

[7] 

Fitzgerald, S.M., Bouslog, S.A. and Hughes, J.R.," Model for Predicting 

Orbiter PRCS Plume Impingement Loads," NASA JSC Report #26507, 

Rev. A, June 1995. 

Bouslog, S.A., Fitzgerald, S.M. and Machin, R.A.," Instrument 

Characterization Tests in a Nitrogen Free Jet," NASA JSC Report #26706, 

March 1995. 

Fitzgerald, S.M., and Hughes, J.R.," Orbiter PRCS Plume Impingement 

Tollkit," NASA JSC Report #26583, March 1995. 

Fitzgerald, S.M., Bouslog, S.A. and Hughes, J.R.," Model for Predicting 

Orbiter PRCS Plume Impingement Loads," NASA JSC Report #26507, 

January 1994. 

Machin, R.A., et al, "Shuttle Plume Impingement Flight Experiment 

(SPIFEX) Data Reduction," NASA JSC Report #27030, Vol. 1. 

Storch, J.A., Flutter of Solar Arrays Subjected to Rarefied Plume 

Impingement," Draper Laboratory Reports, September 1994 and January 

1995. 

Storch, J.A., Solar Array Flutter in Pulsed Rarefied Flow," Draper 

Laboratory Report, June 1995. 

2-6 
PREDICTWE MODELING OF CARDIAC ISCHEMIA 

Final Report 

NASNASEE: Summer Faculty Fellowship Program- 1995 

Johnson Space Center 

Prepmd By: 

Academic Rank. 

University & Department 

NASNJSC 

Directorate: 

Division: 

Branch: 

Date Submitted: 

Contract Number: 

Gary T. Anderson, Ph.D. 

Associate Professor 

University of Arkansas at 

Dept. of Applied Sciences 

Little Rock, AR 72204 

Little Rock 

Information Systems 

Technology Systems 

Client/Server 

811 1/95 

NGT-44-001-800 

3- 1 
ABSTRACT 

The goal of the Contextual Alarms Management System (CALMS) project is to 

develop sophisticated models to predict the onset of clinical cardiac ischemia before it 

occurs. The system will continuously monitor cardiac patients and set off an dam when 

they appear about to suffer an ischemic episode. The models take as inputs information 

from patient history and combine it with continuously updated information extracted 

from blood pressure, oxygen saturation and ECG lines. Expert system, statistical, neural 

network and rough set methodologies are then used to forecast the onset of clinical 

ischemia before it transpires, thus allowing early intervention aimed at preventing morbid 

complications from occurring. The models will differ from previous attempts by 

including combinations of continuous and discrete inputs. 

A commercial medical instrumentation and software company has invested funds 

in the project with a goal of commercialization of the technology. The end product will 

be a system that analyzes physiologic parameters and produces an alarm when 

myocardial ischemia is present. If proven feasible, a CALMS-based system will be added 

to existing heart monitoring hardware. 

3-2 
INTRODUCTION 

Cardiovascular disease is the leading cause of death in the US, Ut 43% 

of all mortalities. Each year, more than 5 million patients anive at Rooms 

(ER) with chest pain, with 35-40% of these suffering from acute ischemia [Selker, 19891. 

Coronary Care Units (CCUs) have proven to be extremely effective in preventing death 

from ischemic cardiac events, but the cost of these units limits their presence to only 22% 

of hospitals. When cardiac patients arrive at a medical facility, a decision must be made 

as to whether they belong in the CCU or in a less expensive facility such as a Monitored 

Care Unit (MCU). For patients arriving at a hospital without a CCU, a decision must be 

made as to whether they can be treated in-house, or should be transported to a tertiary 

care facility with a CCU. 

The cost of wrong triage decisions can be staggering. Estimates of the percentage 

of patients needlessly admitted to the CCU range from 50% [Rollag, 19921 to 70% 

[Fineberg, 19841. Selker [ 19891 concludes that each year perhaps $4 billion dollars are 

spent on CCU care for such patients. In addition, many patients who would benefit from 

CCU services are not admitted. It is estimated that about 11% Fleming, 19911 of ER 

patients with acute ischemic disease are inadvertently sent home. Of those admitted, 9 to 

12% [Rollag, 1992; Fleming, 19911 who should be admitted to the CCU are sent to the 

ward or a step down care facility. 

Criteria for admission to a CCU can vary, depending on hospital practice 

[Weingarten, 19931. It is known that CCU interventions can significantly lower mortality 

of patients with acute myocardial infarctions. If implemented in the first 6 - 12 hours 

after an MI, arrhythmia prophylaxis, cardiac monitoring, thrombolytic therapy and 

resuscitative interventions available in the CCU can all reduce mortality and morbidity 

rates for cardiac patients. Quick diagnosis and triage decisions are critical for preventing 

or effectively treating complications of an MI. However, cardiac triage decisions in the 

emergency mom are often made under severe time pressure, making optimal placements 

difficult. The proposed CALMS technology will assist the ER physician in making 

difficult mage decisions by giving them an objective, computer-based second opinion on 

patient prognosis. 

The most difficult triage decision concerns patients with unstable angina, chest 

pain that is non-responsive to drug treatment. 80-90% of these people will respond to 

medical therapy, while 10-208 will progress to a myocardial infarction (MI). Based on a 

pilot study of patients at the University of Arkansas for Medical Sciences, about 8% of 

people in an MCU will later be transferred to the CCU, indicating that the severity of 

their illness was originally misinterpreted by the attending cardiologist. Emergency room 

physicians and family practitioners in rural settings could be expected to have a higher 

misdiagnosis rate. Once in a CCU, very few life-threatening incidents transpire. If 

surgery patients, catheterization patients, people admitted to the CCU because they are in 

the midst of a potentially lethal event and co-morbidity patients (who experience chest 

pain along with another unrelated illness) are excluded, less than 10% of the remaining 

population will experience life-threatening episodes. One reason for the low event rate is 

because of interventions available only in a CCU (e.g., administration of intravenous 

nitroglycerine or dobutamine), which probably prevented morbid incidences that would 

have occurred otherwise. However, overcautious admission of people to the CCU likely 

accounts for a large portion of the low event rate [Selker, 19891. 

3-3 
PREDICTrVE MODELS 

previous myocardial infarction [Nishi, 19923, and serum ma [Marik, 19901 have all been 

shown to have short-term prognostic significance. Recently, ch 

variability has also been shown to be a precursor of clinical ischemia 

Several researchers have developed models to predict which patients could most 

benefit being in the CCU [Pozen, 1984; Brush, 1985; Weingarten, 1989, Se 

Pozen et. al developed a model based on seven discrete inputs to the logis 

This model worked best at excluding patients from the CCU (rather than predicting who 

should be admitted), but missed some obvious candidates [Green, 19881. In addition, two 

of the criteria can not be reliably found in a patients medical records (nitroglycerine use 

and history of heart attacks), and another two may have ambiguous interpretations (S-T 

segment “straightening” and chest pain as the chief complaint). An improved version of 

the logistic model [Selker, 19911 used twelve discrete inputs and was shown to perform 

about as well as an ER physician. To be generally accepted by physicians, however, a 

decision aid must perform significantly better than physician judgment. 

Brush [1984] developed a model based on an “ECG score” that predicted 

complications in cardiac patients, but the model had disappointing performance when 

used outside the environment it was developed in [Green, 19881. Other groups have 

developed practice guidelines based on expert opinions on how to treat cardiac patients 

weingarten, 19931. These guidelines work best at selecting patients for early transfer 

Erom the CCU, rather than choosing patients suitable for admission. 

MODELING TECHNIQUES 

Neural Networks 

Artificial neural network techniques show excellent promise in being able to 

overcome the limitations of presently used computer methods to predict patient 

prognosis. This is because these networks can be trained to recognize complex 

relationships that exist between inputs (Le., physiologic data) and outputs (i.e., patient 

outcome) [de Villiers, 19931. These subtle relationships in the data are automatically 

recognized by the network, even if they are unknown to clinicians. Because neural 

networks can learn any arbitrary relationship between a given set of inputs and outputs, 

they can normally be expected to perform at least as well as and usually better than any 

other modeling technique. As the complexity of the problem increases, so does the 

superiority of neural networks over most other methods. Importantly, neural network 

techniques have previously been shown to be able to handle the inaccuracy and 

inconsistency associated with patient histories and physical findings [Pike, 1992; 

Edenbrandt, 1992; Bat, 1991; Marik, 1990; Gheorghiade, 19881. Further, the networks 

appears to be able to deal with the complexities of disease states characterized by several 

totally differing clinical presentations Passen, 19901. 

The disadvantage of neural network models is that, while they often have 

excellent overall results, they do not reveal how a given prediction was made. Physicians 

sometimes feel uncomfortable with this “black box” approach to patient management in 

3-4 
complicated cases because it is difficult to know when to overrule the network prediction. This objection can be overcome by having a model that can demonstratively perform 

much better than standard physician judgment. 

Rough Sets 

Rough sets is a new and powerful technique for extracting rules from data 

[Pawlak, 19841. Rough sets have been shown to create impressive predictor models and 

are especially well suited for problems with inconsistent data, as is often the case with 

medical problems. Like neural networks, rough sets is a completely data driven technique 

that can find relationships that exist between problem parameters. A major advantage of 

rough set models is that they can explain the reason a certain decision was made by 

revealing what rules were fired. This makes it easier for a physician to reject a decision 

made by the model on the rare occasions when an unusual set of circumstances suggests 

such action. 

In order to create a mugh set model, continuous data must be divided into discrete 

categories, (e.g., high, medium and low). The rough set algorithm will compare the 

discretized inputs and output, and eliminate redundant inputs. From the remaining data, a 

set of rules will be generated that indicates what the likely outcome will be for a given 

combination of inputs. Certain rules are generated from consistent examples and 

uncertain rules are generated from inconsistent data. For example, an uncertain rule might 

state that under given conditions the outcome will be positive 80% of the time. Various 

methods are employed to give strengths to different rules so that when contradictory rules 

are fired the most important one will determine the decision. 

Rough sets have a few minor disadvantages that have to do with the requirement 

for discretization of continuous data. If a problem has more than a few inputs, a large 

amount of data is required to extract rules for all possible combinations of input 

categories. If a rule has not been generated for a particular combination during training 

(Le., rule extraction from a training set of example cases), then no decision can be made 

when this particular combination occurs during model use. Also, several examples of 

each combination of categories are desirable to ensure the rules work for a majority of 

cases. Therefore, a large number of training examples are necessary for the rough set 

model to genera=, reliable rules for all possible scenarios. 

A second slight disadvantage of rough sets has to do with the crispness of the 

categories defined for continuous data. For example, a heart rate of 40 - 60 might be 

considered low, 61 - 80 medium and 81-120 high. Two people may have nearly identical 

physiologic signs, but one has a heart rate of 80 and the other a heart rate of 81. These 

people would be considered as being in different categories (80 = Medium, 81 = High), 

even though they are nearly identical. If a large set of examples is available to extract 

rules from, this disadvantage can be overcome by using a large number of categories for 

important variables. 

Logistic Regression 

Logistic regression is a standard statistical tool that has been used for predictive 

models with some success [Pozen, 1984; Selker, 19911. Logistic regression assumes the 

desired output (usually a “yes” or a “no”) fits the sigmoid-shaped logistic equation. The 

technique has advantages over discriminant analysis in that it can accept combinations of 

categorical and normal or non-normal continuous data. Data is fit to the equation: 

3-5 
where Y is the desired outcome, X are the inputs, bn are the coefficients of X and u = bo 

+ blX1 + b2X2 + ... + bp Logistic regression has been shown to work well with 

categorical and non-norm inputs. Its major disadvantage is that it assumes the data fits a 

rigid form of equation that may not reflect the subtle interactions actually present 

between factors in the problem. 

DATA ANALYSIS 

A pilot study, based on an NSFWhitaker Foundation planning grant, was 

conducted to determine the feasibility of developing neural network and rough set 

predictive models from CCU data. A total of 118 records from patient who had gone 

through the CCU of the University of Arkansas for Medical Sciences’ University 

Hospital in the past five years was input into a database. Surgery patients, catheterization 

patients and people admitted to the CCU because they are in the midst of a potentially 

lethal event were excluded. Thirty seven physiologic parameters from the patients charts 

were recorded, with 28 model inputs recorded at admission and 9 upon admission to the 

CCU (see Table I). Four possible adverse outcomes were noted 1. Type II2nd degree 

AV block or 3rd degree AV block; 2. More than 15 seconds ventricular tachycardia; 3. 

Blood pressure less than 85 with the use of pressors; 4. Death. A total of 44 of the 

patients suffered serious events while in the CCU. Due to the small number of total 

events, all four adverse outcomes were combined into a single outcome that was positive 

if any of the four complications occurred. 

Model Input Selection 

Data from 118 cases was collected, but only 40 of these had a complete set of 

inputs. The type of data collected creates special problems for model development for 

several reasons: 1) there are too few training cases for the number of inputs present; 2) 

the inputs are correlated; and 3) bad data points probably exist in both the inputs and 

outputs. A set of predictive model inputs was chosen in a two step process. First, data was 

divided into two groups based on the outcome (yes = event and no = no event). Student ttests are a method of testing whether the mean of two groups are equal. t-tests were run to 

look for differences in each variable between the two groups. Afterwards, stepwise 

logistic regression was run on the variables selected by the t-tests to choose the final set 

of model variables. The t-tests were necessary because stepwise regression is performed 

only on cases that have a full set of all inputs. If a single input is missing from a example, 

then the entire case is removed from the procedure. This, when applied over the entire 

dataset, then leaves very few complete cases for model development. On the other hand, 

t-tests can be performed on all cases where the variable under consideration is present, 

irrespective of whether any of the other inputs are missing. This allows each candidate 

input to be evaluated over a larger sample size, thus giving a more solid basis for 

elimination of parameters that show no difference between outcome groups. After 

candidate inputs are selected by the t-tests, stepwise regression is performed to eliminate 

redundancies in the inputs caused by correlations between variables. 

Eighteen variables were chosen by the t-tests (pc0.1 using either the yes and no 

groups pooled or separated for calculation of variances) as being possible candidates for 

the model inputs. The eighteen were: sex, age, weight, diabetes, chest pain, systolic 

pressure, respiration rate, white blood count, ventricular arrhythmias, ST segment 

depression, des, syncopy, S3 heart sound, temperature in CCU, diastolic pressure in 

CCU, respiration in CCU, aspirin use, class III drug use, class IV drug use, and change in 

body temperature between ER and CCU. After running stepwise logistic regression, 

seven inputs were chosen for model development: sex, age, weight, diabetes, ST segment 

3-6 
INPUT PARAMEi'I'ERS FOR THE P 

IEmLIx 

1 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

31 

32 

33 

34 

35 

36 

37 

7 

sex 

age 

weight 

smoking 

history of diabetes 

previous MI 

chest pain 

heart rate 

systolic blood pressure 

diastolic blood pressure 

body temperature 

respiration rate 

hematocrit 

serum K 

white blood count 

creatine 

current MI 

anterior Mi 

amal arrhythmias 

ventricular arrhythmias 

ST segment depression 

ST segment elevation 

# of ventricular ectopics in a run 

rales greater than 1/3 up 

syncope 

height 

s3 

history of congestive heart failure 

heart rate in unit 

systolic blood pressure in unit 

diastolic blood pressure in unit 

respiration in unit 

aspirin 

class I drugs 

class I1 drugs 

class III drugs 

class N drugs 

continuous 

continuous 

continuous 

yes or no 

yes or no 

yes or no 

yes or no 

yes or no 

yes or no 

continuous 

yes or no 

yes or no 

continuous 

yes or no 

yes or no 

continuous 

continuous 

continuous 

continuous 

yes or no 

yes or no 

yes or no 

yes or no 

yes or no 

depression, respiration rate in CCU and aspirin use. A total of 95 out of the original 118 

cases had all se 

3-7 
concluded that factor analysis was not an effective means of reducing this particular 

dataset. 

Training and Testing Set Selection 

Model development and validation were performed by dividing the database into 

two categories, one for model training and the other for model testing. Ideally, a training 

set should capture the important features in the data. The training set should normally be 

unbiased (Le., have an equal number of yes and no outcomes), or be intentionally biased 

to favor a particular result. It is also desirable to have the testing set representative of the 

data as a whole, so as to get a me idea of model performance. To accomplish these, the 

data set was clustered by cases, using a nearest neighbor algorithm. Six clusters were 

visually identified, with between 2 and 31 members in each cluster. Four cases were far 

from all others, and these were placed in the test set. Two training sets were developed, 

one with 61 cases and the other with 40. The set with 40 cases was nearly equally 

balanced between yes and no answers, while the other one had 24 extra no outcomes. 

The test set, which contained 33 cases, had all clusters represented and contained 13 

positive and 20 negative outcomes. 

Neural Network Results 

The models created were evaluated by using sensitivity and specificity: 

sensitivity -tp - tp+fn 

tn specificity = - tn+fp 

where tp is true positives, tn is true negatives, fp is false positives and fn is false 

negatives. Sensitivity is a measure of how likely a model will predict a condition if it is 

actually present, while specificity indicates how likely a condition is to be present if the 

model results are positive. Several neural network architectures were investigated, with 

the best results shown in Table 2. 

TABLE 2.- NEURAL NETWORK RESULTS FOR 7 INPUT MODELS. 

In Table 2, average % correct is the average of the sensitivity and specificity x 100, while 

3-1 indicates a four layer network with three nodes in the first hidden layer and one node 

in the second hidden layer. The results for three hidden nodes used the training set with 

40 cases, while the others used the set with 61 cases. 

It was thought that the test set results may have suffered from too many inputs for 

the number of training cases, so a reduced set of inputs was chosen for further model 

3-8 
generation. The new inputs were age, weight, ST segment depression and respiration rate 

in the CCU. The training set for this network had 61 cases. A network with 2 hidden 

nodes had the following results: 

Average % Correct = 70.5, sensitivity = 0.46, specificity = 0.95 

The results are significant. While the model only correctly predicted about one half of all 

the cardiac events, when it did forecast an event the patient was extremely likely to suffer 

one (19 out of 20 cases). This network can therefore be used as a screening tool to help 

decide to place patients in the CClJ or, if they are already in the CCU, to keep them there. 

Another technique tried to improve model performance was to combine the 

outputs of the best networks for sensitivity and specificity. These were used as the inputs 

for a second neural network, with the idea that if each of the original models searched a 

different area of the solution space then combining them will produce results better than 

either alone. The output from the network that had a sensitivity of 0.62 (see Table 2) and 

the one that had a specificity of 0.95 (described above) were combined. The best 

architecture had four nodes in a single hidden layer: 

Average % Correct = 64.5, sensitivity = 0.54, specificity = 0.75 

The results are in between the original networks for sensitivity and specificity, thus 

indicating that the networks were probably keying in on the same features. 

The final method tried was to add simulated training cases in order to increase the 

allowable degrees of freedom in the problem. This procedure also forces the network to 

learn relationships between inputs. The procedure is as follows: 

1. Calculate an average value over all the cases in the training set for each input. 

2. For each case, the number of new exemplars created will equal the number of inputs to 

the model. 

3. Each new exemplar replaces a single input with its mean, so that the number of 

simulated cases created equals the original number of cases times the number of model 

inputs. 

The procedure described above allows a network to be trained with a larger number of 

hidden nodes without overtraining the network. The inputs for this model were: sex, age, 

weight, diabetes, ST segment depression, respiration rate in CCU and aspirin use. The 

original training set had 41 cases, 19 of which were positive outcomes and 22 negative. 

The new training set had 328 cases with 152 positive outcomes and 176 negative ones. 

The best network had a single hidden layer with four hidden nodes: 

Average % Correct = 66, sensitivity = 0.57, specificity = 0.75 

The results improve upon those shown in Table 2, but are slightly worse (66% vs. 70.5% 

average correct) and not as useful as those from the network with a reduced set of inputs. 

The limited number of training cases and the combining of four disparate events into a 

single outcome probably preclude better model performance on this dataset. 

Logistic Regression and Rough Set Results 

A logistic model was also developed from the same dataset. The training set with 

61 inputs was used ient determination (see Equation l), and the standard 33 

case test set was used for model validation. The best validation results were obtained 

3-9 
with the following inputs: age, weight, ST segment 

plus the interactions age x ST segment depression, and 

The results are not as 

networks developed. The logistic model there 

compare the neural network models to, because it gives an indication if the optimal neural 

network architecture has been developed for a given problem. 

A rough set model was developed fiom four inputs: age, weight, ST segment 

depression and respiration rate in the CCU. Continuous inputs were divided into four 

equally spaced categories that spanned their range. Twelve rules were extracted fiom the 

61 case training set, five for negative decisions and seven for positive decisions. The rule 

certainty was 100% for eleven rules, and 96% for the twelfth. Each negative rule had 

between four and twenty-five cases supporting it, with positive rules having between one 

and six cases supporting them. Decisions were made in 31 of 33 cases in the test set. 

Model results were: 

Average % Correct = 73.5, sensitivity = 0..58, specificity = 0.89 

These results are excellent compared to logistic regression and neural network 

techniques. Although the specificity was slightly less than the best neural network model, 

its overall performance was better. Moreover, the rough set model made no decision in 

cases that were not similar to those it was developed on, whereas neural networks will 

always give an output for all cases. 

CONCLUSIONS 

Rough sets, neural networks and logistic regression have all proven to be effective 

tools for predicting the outcome of cardiac patients in a CCU. The rough set model gave 

the best overall results, and has the advantage of being able to explain how a decision was 

made. Also, rough set models will not make decisions on cases that are far from the ones 

they were developed on, adding a degree of confidence to the results. The best neural 

network model proved to be the most practical, with a specificity of 0.95, although 

overall results were not quite as good as with rough sets. Logistic regression proved 

useful as a benchmark against which other methods could be tested. 

The key to developing these prognostic models is to choose a good set of 

predictor variables. This was done in a two step process, using student t-tests and 

stepwise logistic regression. Selection of cases for training and testing models is also 

crucial for model creation and validation. A clustering algorithm that measures the 

distance between cases, while iring subjective decisions, has shown itself to be 

useful. 

Future work in s applying the data analysis techniques described above to 

the Contextual Alarms ement System (CALMS . The goal of CALMS is to 

develop sophisticated models to predict the onset of cardiac ischemia before it 

occurs. The system will continuously moni and set off an alarm when 

take as inputs information 

with continuously updated information extracted 

saturation measurements and five ECG leads. Data 

is now being collected on twenty patients at the cardiac catheterization laboratory at 

ut to suffer an ischemic epis 

3-10 
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3-1 1 
Selker, HP, 44Coronary unit triage decision aids: how do we know they work?“, American 

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for patients hospitalized with chest pain using medical practice guidelines and opinion 

leaders, American Journal of Cardiology, 7 1:259-262,1993. 

3-12 
SOME CONSIDERATIONS IN THE DEflERMINATION OF THE 

ACCURACY OF A MEASUREMENT IN SPACE OF THE 

NEWTONIAN GRAVITATIONAL CONSTANT (G) 

Final Report 

NASNASEE Summer Faculty Fellowship Program-- 1995 

Johnson Space Center 

Prepared By: 

Academic Rank: 

College and Department: 

NASNJSC 

Directorate: 

Division: 

Branch 

JSC Colleague: 

Date Submitted 

Contract Number: 

Stephen D. Baker, Ph.D. 

Professor 

Rice University 

Physics Department MS-6 1 

6100 South Main Street 

Houston, TX 77005- 1892 

Space and Life Sciences 

Earth Science and Solar 

System Exploration 

Planetary Mssions and 

Materials 

Wendell W. Mendell 

October 23,1995 

NGT-44-001-800 

4-1 
ABSTRACT 

A commonly suggested method for determining the Newtonian constant of universal 

gravitation (G) is to observe the motion of two bodies of known mass moving about each 

other in an orbiting laboratory. In low Earth orbit (LEO), bodies constructed of even the 

densest material available experience a gravitational attraction that is several times 

smaller than the "tidal" forces (due to their proximity to the Earth), which tend to pull 

them apart. While the tidal forces do not preclude stable orbits of the two objects about 

each other, they and the Coriolis force (in the rotating laboratory) dominate the motion, 

and the gravitational attraction of the two bodies may be considered a weak (but 

significant) contribution to the motion. As a result, compared to an experiment that 

would be performed in a laboratory far from the Earth, greater accuracy of measuring the 

motion of the two bodies may be required for a given accuracy in the determination of G. 

We find that the accuracy with which positions must be determined is not much different 

in an experiment in LEO than in one performed far from the Earth, but that rotational 

periods must be determined more accurately. Using a curvature matrix analysis, we also 

find that a value of G may be extracted (with some loss in accuracy, but probably some 

practical gain) from an analysis of the time dependence of the distance between the 

bodies rather than of a full specification (distance and direction) of their relative 

positions. A measurement of the gravitational constant to one part in 104 continues to be 

thinkable, but one part in 10s will be very difficult. 

4-2 
INTRODUCTION 

A commonly suggested method for determining the Newtonian constant of universal 

gravitation (G) is to observe the motion of two bodies of known mass moving about each 

other in an orbiting laboratory. In low Earth orbit (LEO), bodies constructed of even the 

densest material available experience a gravitational attraction that is several times 

smaller than the "tidal" forces (due to their proximity to the Earth), which tend to pull 

them apart. While the tidal forces do not preclude stable orbits of the two objects about 

each other, they and the Coriolis force (in the rotating laboratory) dominate the motion, 

and the gravitational attraction of the two bodies may be considered a weak (but 

significant) contribution to the motion. As a result, compared to an experiment that 

would be performed in a laboratory far from the Earth, greater accuracy of measuring the 

motion of the two bodies may be required for a given accuracy in the determination of G. 

In this report, we show that the accuracy with which positions must be determined is not 

much different in an experiment in LEO than in one performed far from the Earth, but 

that rotational periods must be determined more accurately. In the final section of this 

report, we briefly describe a curvature matrix anitlysis which shows that a value of G may 

be extracted (with some loss in accuracy, but probably some practical gain) from an 

analysis of just the time dependence of the distance between the bodies rather than of a 

full specification (distance and direction) of their relative positions. 

If a system of two balls is far from any other objects, the balls can move around each 

other in elliptical Keplerian orbits, where the relationship between the gravitational 

constant 6, the period T of the motion, the average (half the sum of the minimum and the 

maximum) separation a of the balls, and the total mass m of the system is given by 

This leads us to the following result. If a, T, and m are measured with accuracies Aa, AT, 

and Am, respectively, we may determine the fractional error in G from the fractional 

errors in a, T, and m as follows: e)= 26)+ 3($)+ (e) . 

Thus, to achieve a given fractional accuracy in the determination of G, the fractional 

accuracy of the period must be at least two times better, the fractional accuracy of the 

orbit size must be at least three times better, and the fractional accuracy of the mass must 

be at least as good. 

SIMPLE ORBITS IN LOW EARTH ORBlT 

For the motion of two balls in an orbiting laboratory in a low Earth orbit (LEO), we must 

take into account the tidal forces and the Coriolis forces and integrate numerically the 

equations of motion (assuming the laboratory is in a circular orbit about a spherically 

symmetric Earth). It turns out that two balls may still orbit about one another in a stable 

fashion, but the motion is complicated by the presence of the Earth. I will lay out the 

equations of motion here, and I will then comment on them in the following paragraph. 

4-3 
The equations of motion are 

0. 

X= 

0. 

Y=-Y 

2;. - p x [x2 + y2 + z2]-3/2 

0. 0 

z = 32 -2x 

- p y [x2 + y2 + z2]-3/2 

- p z [x2 + y2 + 221-312 (3) 

where x is along an axis in the direction of motion of the orbiting laboratory, z is along 

an axis directed toward the Earth from the laboratory (NASA convention), and y is the 

third Cartesian coordinate. The distances x, y, and z are measured in dimensionless units 

relative to a characteristic length d in the laboratory, time is measured in dimensionless 

units relative to the reciprocal of the ahgular velocity of the laboratory about the Earth, 

and the quantity p is defined 

p = (m/M)(A/d)3 (4) 

where m is the mass of the two-ball system, M is the mass of the Earth, and A is the 

radius of the laboratory's orbit about the Earth. 

The tidal forces (the frrst terms on the right side of the expressions for 7 and 'z' ) and the 

Coriolis forces (the velocity dependent terms) can be large compared to the gravitational 

attraction (the last term in all three expressions). It turns out that if the two balls are of 

equal mass and are made of material the density of tungsten, and if d (the length scale) is 

chosen to be the distance between their centers when they are in contact, the quantity p is 

very nearly equal to unity in LEO (for sintered tungsten balls of 10 kg each, density about 

19.1 g/cm3, the distance between their centers when they are touching is about 10 cm.) 

Thus, in LEO, for real balls moving about one another, the gravitational attraction term 

will be small compared to the average values of the other terms in Eq. (3), and the 

motion will be only gently (but for our purposes still importantly) affected by the 

gravitational attraction between the two balls. 

An example of a possible stable orbit of two balls about each other is shown in Figure 1, 

which shows the motion of one ball relative to the other. Parameters of the motion are 

described in the caption. Generally, the orbits (unlike the Keplerian orbits) are not 

closed. Moreover, the initial conditions must be chosen carefully to give motion in which 

the particles remain close for a long time. Fig 2 shows an example of the relative motion 

of the balls in which they do not stay close together for long. For the purposes of the next 

section, it was necessary to determine the parameters for the special case of closed orbits, 

several of which are shown in Fig 3. Here we see that large orbits have periods 

approaching 27c and a motion with is simple harmonic in x and in z, with a ratio of 

amplitudes of 2. Smaller orbits are more nearly circular and have shorter periods. They 

are ovals but they are not ellipses. 
-4 1 

Figure 1 .- Relative position in xz plane of two balls moving about each other in LEO. 

The x direction (horizontal axis) is in the direction of motion of the laboratory, and the z 

direction (vertical axis) is toward the Earth from the laboratory. p = 1, xo=-6.0, vox = 0.1, 

v,, = 2.5, all other initial values of coordinates and velocity components are zero. The 

mohon is stable in the sense that the balls remain within about 7 length units indefinitely. 

The trajectory shown is for the time interval between t = 0 and t = 4otd3 (6.67 orbits of 

the laboratory about the Earth). 

-8 1~ 

Figure 2.- Relative position in xz plane of two balls moving about each other in LEO. p 

= 1, ~~16.0, vox = 0.1, voz = 2.1, all other initial values of coordinates and velocity 

components are zero. the motion is unstable, and after just one loop around the origin, 

the trajectory continues to the right in a cycloidal fashion. The trajectory shown is for the 

time interval between t = 0 and t 3 41c (about two orbits of the laboratory about the Earth). 

4 

2 

0 

-2 

-4 

-6 -4 -2 0 2 4 6 

Figure 3.- Relative position in xz plane of two balls moving about each other in LEO. p 

= 1. The initial values of coordinates and velocity components have been chosen to give 

closed orbits. The time interval between dots is 0.10; for the largest orbits, the period is 

close to 21c, for smaller orbits the period is smaller. 

4-5 
ERRORS ASSOCIATED WIT 

Equations (3) tell us that when the particles are close together, the gravitatio 

attractions between them is more important than the tidal and Coriolis forces. 

is not possible in LEO, it would be possible if the laboratory were farther fro 

The motion of the two balls is in Keplerian orbits, and the relationship between period 

(dimensionless units), maximum separation a (dimensionless units), and p is 

where p = (mR~l)(A/d)~. Note the similarity to the expression for the Kepler motion of an 

isolated binary; Gm is simply replaced by p. 

The task of measuring G becomes the task of measuring p. From the above relation, 

Eq.(5), we see that, far from the Earth, 

(:)= Zg)+ 3e) 

The issue is: How does E) - depend on r) T and - when the experiment is carried ("a") 

out in LEO? That is, what happens to the factors 2 and 3 in the equation above? (Of 

course, getting from p to G also involves knowing the mass of the binaries, the length 

scale, and the radius of the orbit of the laboratory about the Earth. Since we should be 

able to know these to the 1: 106 level, we will ignore them now, so the accuracy with 

which p is determined is practically the accuracy with which G is determined. ) 

Here is a description of the calculation. With p set equal to 1, for each of several values 

of a (maximum separation) we found the orbit which was closed and determined the 

period of the orbit. We also determined numerically the partial derivative of T with 

respect to a, (aT/aa), and the partial derivative of T with respect to p, (aT/ap). We can 

then determine the fractional change in p which results from given fractional changes in a 

and T, as follows. 

We may write 

aT aT dT =x da+-dp, 

a0 

which may be rearrangid to give 

4-6 
Dividing all terms by p and multiplying numerator and denominator of the two terms on 

the right side of the equal sign by T or a, respectively, we obtain 

Eq. (10) indicates how the coefficients A and S are calculated. If the orbits were 

Kepierian (small a, assuming p is unity), the values of A and B would be 2 and 3, 

respectively, as we see in Eq. (6). The actual values for larger, and potentially usable 

values of a, are shown in Figure 4. What we find is that the p becomes much more 

sensitive to the time measurement. This is reasonable because as the orbits become 

larger, the effect of the gravitational attraction of the masses becomes smaller, and the 

period becomes practically independent of the size of the orbit. What may be surprising 

(it is surprising to me) is that the fractional precision with which the size of the orbit must 

be determined varies very little from the value of 3 for the values of a'in our region of 

interest. 

100 

muitiplier of fractional error 

in period 

a multiplier of fractional error 10 

in maximum separation 

1 

1 10 

maximum separation, a 

Figure 4.- Values of the coefficients A. (solid squares) and IB (open squares) versus 

the size of the orbit of the relative motion of the two balls. See text for explanation. 

4-7 
We can now understand the effect of LEO on the accuracy with which we need to 

measured with much greater fractional accuracy, whereas the size of the orbit still needs 

to be measured with about the same fractional accuracy as before. 

. measure the orbital motion to extract G. What we find is that the period must be 

CURVATURE MATRIX ERROR ANALYSIS 

In the analysis of an actual experiment, data points, consisting of position and time 

measurements, will be fit to a numerical model of the motion. The parameters of the 

model (initial position and velocity, strength of the gravitational interaction, effect of 

other masses) are determined by a least squares search process and the precision of the 

parameters is deduced form the curvature of the chi-square hypersurface in parameter 

space. We may first consider a slightly simpler problem. We calculate the orbits with 

parameters and produce positions at regular intervals of time. By changing each of the 

parameters and each pair of parameters by small amounts, we can calculate a chi-square 

which characterizes the deviation of the modified set of positions from the original set. 

From these chi-squares, we determine the curvature matrix which describes the 

dependence of chi-square on the parameters. Inverting this curvature matrix then gives 

an indication of the sensitivity of the motion to each of the parameters, in particular to the 

gravitational attraction between the members of the orbiting binary. One would expect 

this analysis, which is more sophisticated than the analysis of the simplest, closed orbits, 

described in the previous section, will agree with the error analysis of the simple closed 

orbits but can be extended to orbits which are not closed and which reflect more complex 

environments. 

We have analyzed an orbit of two 10 kg tungsten balls with parameters d = 10 cm, p = 1, 

xo=-6.0, vox = 0.1, voz = 2.1, all other initial values of coordinates and velocity 

components being zero. Supposing the position is determined at 100 points, each with a 

precision of about 10 pm, at time intervals of 0.25 (for a total time of about 6 orbits of 

the laboratory about the Earth), we find that the precision with which p (for these 

assumptions) is determined is about 2.7 x 10-5, consistent with the simpler analysis 

described above. This indicates that a determination of G to one part in 104 is thinkable 

(but one part in 105 will be difficult). 

It is interesting to note that one may also perform such an analysis with the chi-square 

calculated not from the relative positions of the particles (separation distance and 

direction) but from the deviation of just the separation of the particles (in analogy with 

the analysis of lunar laser ranging data). Some information is lost in doing this, but for 

the same conditions as in the previous paragraph, the precision with which p is 

determined is about 4.4 x 10-5, not much worse than before. 

In conclusion, a measurement (of the kind discussed above) in LEO of the gravitational 

constant to one part in 104 continues to be thinkable, but one part in l@ will be very 

difficult. 

4-8 
MATERIALS ASSESSMENT OF COMPONENTS OF THE 

EXTRAVEHICULAR MOBILITY UNIT 

Final Report 

NASNASEE Summer Faculty Fellowship Program-1995 

Johnson Space Center 

Prepared By: 

Academic Rank: 

and: 

University and Department: 

NASNJSC 

Directorate: 

Division: 

Branch 

JSC Colleague: 

Date Submitted: 

Contract Number: 

Enrique V. Barrera, Ph.D. 

Assistant Professor 

John D. Olivas 

Graduate Student 

Rice University 

Mechanical Engineering and 

Materials Science 

Engineering 

Crew and Thermal Systems 

Chin Lin, Ph.D. 

August 9,1995 

NGT-44-001-800 

5- 1 
ABSTRACT 

Current research interests for Extravehicular Mobility Unit (EMU) design and 

development are directed toward enhancements of the Shuttle EMU, implementation of the 

Mark III technology for Shuttle applications, and development of a next generation suit (the 

X suit) which has applications for prolong space flight, longer extravehicular activity 

(EVA), and Moon and Mars missions. In this research project two principal components 

of the EMU were studied from the vantage point of the materials and their design criteria. 

An investigation of the flexible materials which make up the lay-up of materials for 

abrasion and tear protection, thermal insulation, pressure restrain, and etc. was initiated. A 

central focus was on the thermal insulation. A vacuum apparatus for measuring flexing of 

the materials was built to access their durability in vacuum. Plans are to include a Residual 

Gas Analyzer on the vacuum chamber to measure volatiles during the durability testing. 

These tests will more accurately simulate space conditions and provide information which 

has not been available on the materials currently used on the EMU. Durability testing of the 

aluminized mylar with a nylon scrim showed that the material strength varied in the 

machine and transverse directions. Study of components of the EMU also included a study 

of the EMU Bearing Assemblies as to materials selection, engineered materials, use of 

coatings and flammability issues. A comprehensive analysis of the performance of the 

current design, which is a stainless steel assembly, was conducted and use of titanium 

alloys or engineered alloy systems and coatings was investigated. The friction and wear 

properties are of interest as are the general manufacturing costs. Recognizing that the 

bearing assembly is subject to an oxygen environment, all currently used materials as well 

as titanium and engineered alloys were evaluated as to their flammability. An aim of the 

project is to provide weight reduction since bearing weights constitute 1/3 of the total EMU 

weight. Our investigations have shown favorable properties using a titanium or nickel base 

alloy in conjunction with a coating system. Interest lies in developing titanium as a more 

nonflammable material. Methodology for doing this lies in adding coatings and surface 

alloying the titanium. This report is brief and does not give all necessary details. The 

reader should contact the authors as to the detailed study and for viewing of raw data. 

5-2 
INIXODUCTION 

A broad-based project aimed at studying the flexible materials and the bearing 

assemblies on the Extravehicular Mobility Unit (EMU) was initiated. The emphasis of the 

study of the flexible materials became the themal insulation layers of aluminized mylar 

with nylon scrim and its durability in flexure testing. The emphasis on the bearing 

assemblies was focused on flammability and improving the flammability of titanium and its 

alloys. Both components to this project were aimed at current Shuttle EMU material 

systems, applying Mark UI technology, and criteria of the next generation suit, the X-suit. 

The outcome of this project is a plan in place for flexure testing of the flexible materials 

used on the Shuttle EMU where the materials evaluation occurs in vacuum to simulate 

space conditions. The plan is presented in this report as well as the assessment of the 

aluminized mylar. Recommendations for reducing frequent replacement of the aluminized 

mylar are also included. For the study on the bearing assemblies several recommendations 

are presented and methodology for further assessment is also given. In this summer 

program the faculty fellow and student participant focused on accomplishing the initial 

stages to a hopefully continued study. The objective of the program is to maintain a 

continued relationship where NASA interests are fulfilled. The report outlines solutions for 

that goal. 

VACUUM DURABILITY TESTING OF EMU FLEXIBLE MATEUS 

Objectives 

The durability and breakdown resistance of fabric materials currently used on the 

Shuttle Extravehicular Mobility Unit (EMU) will be determined using a Flex Machine 

developed during the 1995 NASA-ASEE Summer Faculty Fellowship Program. The Flex 

Machine is designed to simulate the flexing movements made by the astronauts during 

extravehicular activity (EVA) in vacuum conditions resembling that of low earth orbit 

(LEO). The tester is designed to work in vacuum and to minimize gas evolution from the 

fixture. Volatile gases will be measured during the testing. Gases that evolve during the 

tests are a product of the material degradation. As a result, the findings of this study will 

be used to improve materials that see frequent replacement or repair and to aid in selecting 

materials for prolonged EVA and time in space. Both current Shuttle EMU and X-suit 

materials will be evaluated. The benefits of conducting the tests in vacuum are that the 

volatile gases that would outgas in space can be measured and the modificatioddegradation 

of the materials being exposed to vacuum can be induced for observation by electron 

microscopy, microprobe analysis, and x-ray photoelectron spectroscopy. It is apparent that 

knowing the properties of the material degradation due to use in vacuum will further play a 

role for space suits left on the space station or that make trips to the Moon and Mars. 

Aluminized mylar with a nylon scrim, the current thermal insulation material was 

tested in tension and in flexure modes in ambient conditions. The aluminized mylar failed 

before the nylon scrim and the machine direction was significantly stronger than the 

transverse direction. Expectations are that the method of processing the material system 

results in reduced strength in the transverse direction. Optical micrographs of the material 

showed lines in the material resembling Luder's bands. These features are under continued 

study. The scrim shows two different conditions where nylon is twisted tight in one 

direction and is laid loose in the perpendicular direction. It is suspected that this feature 

percent elongation of 

before failure. The 

n causes the aluminized mylar to show draw up 

5-3 
possibly due to shrinkage. This may impart small creases in the aluminized mylar which 

are associated with the low strength 

Background 

ers of various 

materials for flame, abrasion, and tear resistance, thermal insulation, micrometeorid 

protection, and pressure restraint [l]. The current materials and the selection process itself 

has gone through an evolution since the suits for the Mercury program were first designed, 

placing more and more emphasis on lighter weight, material stab extended 

kas 1964 

and continues as full mock up testing [3]. Current test apparatus at JSC allow for vacuum 

testing but do not provide for volatile gas measurement and extended materials analysis. 

Furthermore, durability tests are run in ambient conditions which serve as a Safe Life test 

(materials designed such that no failure will take place in the design lifetime). Many 

materials currently used and those being considered for the X-suit are composite materials, 

meaning that they take advantage of the properties of a number of component materials 

which make up one part or fabric [4]. These materials allow for some built in redundancy. 

Research plan 

Flex testing in vacuum will be conducted on current Shuttle flexible materials to 

evaluate durability for Shuttle and prolonged use. Temperature control will be put on the 

chamber during the project year. Extended materials analysis will be conducted on the 

vacuum tested materials. Material outgassing conditions will be mathematically modeled. 

Further design of current materials will be conducted in collaboration with Crew and 

Thermal Systems personnel and contractor companies. Emphasis is placed on improving 

the performance of the EMU while setting up a criteria for materials selection based on gas 

evolution during use in space (simulated on earth). 

In the summer program, preliminary tests were conducted on the aluminized mylar 

in ambient conditions and the flex tester for vacuum testing was built. The following list of 

deliverables demonstrates the methodology by which this research will be continued and 

the long term goals of this study. 

in the transverse direction. 

Current flexible materials on the Shuttle EMU include eight 

durability[2]. Vacuum testing of space suit materials was conducted 

August 8, 1995: 

October 15, 1995 

January 15,1996 

February 15, 1996 

May 14,1996 

Project starting date. Test and redesign frequently 

repaired or replaced materials. 

Submission of a Regional University Grant 

Proposal: "Development of thermal and radiation 

insulation". 

Report I Interim report. 

Submission of an unsolicited proposal: 

"Development of composite material for weight 

savings and functionality". 

Project ending date. 

June 14,1996 

Recommendations 

on S 

Final Report: Including expendimes 

a nylon scrim is the current choice for 

mber of repairs currently seen for the 

sulation 

t care 

5-4 
must be taken in aligning the material with the machine direction in the direction of the 

- major loads. Cross plying sounds like a possible solution yet will result in failure of half 

the layers as opposed to failure of all the layers. Recommendations of this study are to 

align the machine direction with the direct of maximum loading. This will lead to a longer 

life of the insulation and no failure in the transverse direction. 

MATERTAL SELECTION FOR EMU BEARING ASSEMBLES 

In analyzing the application of a material system to the EMU bearing assembly, the 

selections were evaluated based on the qualifying parameters listed in Table 1. Prior to 

evaluating potential material systems, baseline data of the current material selection was 

compiled to provide a starting point for evaluation. This criteria established the minimum 

needed to justify making a material change. The material properties are seen in Table 2. 

TABLE 1.- REQUIREMENTS FOR EMU BEARING MATERIAL SELECTION 

TABLE 2.- BASELINE DATA FOR EXISTING BEARING MATERIALS [3] 

Given the bearing requirements, the most stringent is compatibility of the material 

with an oxygen enriched environment [5]. There are two engineering components to the 

issue of combustion; ignition source and material combustion. Non-flammable materials 

are those in which combustion is not supported in an oxygen enriched environment, as 

defined by NASA White Sands Test Facility (WSTF) [6J. Risk of ignition can be 

minimized by reducing the potential for spark or flame ignition. Ideally both aspects 

should be satisfied, however, significantly reducing one may increase the ability to use the 

material. In order to evaluate a greater number of materials, the investigation was divided 

into three material classes; metals, ceramics and composites. A number of materials of 

5-5 
each class were evaluated based on the above criteri 

material class follow each section as well as an overall re 

Metals evaluation 

using published ASM data [7] and available vendor information. Re 

which were initially identified as having a density lower than that of 

PH) were titanium, aluminum, graphite, beryllium and their associat 

designs eliminated aluminum as a potential choice due to low stiffne 

low toughness. Although beryllium has an excellent strength to weight ratio, poor fracture 

toughness and toxicity also eliminated this material as a potential selection [SI. 

Titanium and titanium alloys were determined to be the best potential selection 

among metal systems. A comparison of several commercially available titanium alloys are 

listed in Table 3. These represent those alloys which possess comparable properties to the 

baseline data in Table 1. 

commendations based on 

Investigation of potential metal selections for bearing applications was performed 

TABLE 3.- RELEVANT MECHANICAL PROPERTIES FOR TITANrUM ALLOYS 

Draw backs to this material selection class are in the area of combustion. WSTF 

demonstrated clearly that titanium, Ti-6Al-4V, and several other titanium alloys provided 

the poorest combustion performance for all metals tested [9]. Recognizing that the primary 

alloying agent is highly combustible, it is expected that other systems would perform 

comparably, although different phases appear to play a role in the combustion of some 

systems. 

It is acknowledged that the bearings would not likely be exposed to direct flame 

contact as simulated in WSTF material combustion test. Testing a proposed bearing in the 

configurational and component test may provide sufficient support to warrant the use of 

titanium in this application, however, with regard to the initial criteria, titanium cannot be 

recommended in the as commercially available conditions without the risk of being 

consumed in a combustion condition. In conclusion, of the metals currently available and 

which have been tested by WSTF, none can be recommended without a compromise in 

either mechanical or combustion properties. 

Ceramics evaluation 

Several important properties are characteristic of this class material. In general, 

at higher temperature, have high strengths and low weights, are 

mewhat machinable. However, drawbacks include the potential for 

5-6 
low fracture toughness (brittle), varying degrees of porosity, poor surface finish, and 

difficulties in some fabrication processes. The ceramics which are presented posses the 

most favorable of these initial concerns and comply with the requirements as defined in 

Table 1 unless otherwise stated. 

Ceramic bearings and bearing elements (balls, races, etc.) have been fabricated 

since the early 1980’s and a significant amount of work has been reported in the literature. 

Although problems were encountered early in the development of the material system, 

many of the obstacles have been overcome. Table 4 represents the properties of the most 

common and well studied structural ceramic material for bearing and load carrying 

applications. 

TABLE 4.- FELEVANT MECHANICAL PROPERTIES FOR CERAMICS 

Of the ceramics listed, the only material for which WSW combustion test data 

exists is Si3N4 (NBD-200) [8]. This performed very well and appears to satisfy all the 

characteristics defined in Table 1. Mass fabrication and production of bearing parts and 

bearing assemblies have proven to be successful in many commercial application [ 13-19]. 

For example, ceramic bearings were used successfully in the LOX turbo pump on STS-70. 

Strides which the ceramic industry have made in the last 10 years have been significant in 

resolving the problems with using these materials in bearing applications. Based on 

published information and communication with material vendors, the sizes required by the 

EMU can be fabricated. In order to keep cost down on fabrication of raw material, it may 

be necessary to consider some slight alterations in the current design. 

Composite evaluation 

Most of the composite systems which rely on internal reinforcement for increased 

strength characteristics will intuitively posses the same problems as do the metals. That is, 

the exposure of a combustible material to an environment conducive for combustion will 

lead to material and component failure. Regressing from these conventional ideas, a 

composite can also be designed by applying a protective coating developed to protect the 

base material from the combustion environment. Thus the susceptibility of the bulk 

material to failure can effectively be eliminated. Furthermore, the coating (or film 

depending on thickness) could be tailored to specifically satisfy other demands placed on 

the surface. Since the 1950’s, the bearing industry has been using a variety of diffusion 

and deposited coatings on load bearing surfaces to increase hardness, reduce wear, or 

increase corrosion resistance [20-221. 

5-7 
Recalling from the materials outlined in Section 2, titanium alloys would be an 

excellent choice provided that one could prevent the material from corning into contact with 

an ignition source or combusting. Therefore, proper coating selectio 

additionally satisfy the wear, friction, strength, and material complia 

that titanium alloys could safely be used in the oxygen enriched environments. The coated 

titanium alloy assembly will result in a weight savings over the stainless steel systems 

currently used. 

Since titanium alloys are inherently self passivating and very corrosion resistant, 

published coating technology has been limited to increasing surface hardness [23]. 

Similarly, since titanium alloys do not posses the type of hardnesses traditionally found in 

bearing materials, it represents only a small portion of total data available from bearing 

applications in contrast to more popular metals such as 440C or M-50 steels. However, 

several deposition techniques exist (eg., Chemical Vapor Deposition, Physical Vapor 

Deposition, Sublimation Deposition, etc.) and the design of such a coating is possible with 

further research. Table 5 demonstrates differences in surface hardness of substrates and 

coatings the properties of some typical coating used in bearing applications. Additionally, 

significant data exists on wear properties of various coating combinations. Presented in 

Table 6 are friction and wear characteristics of a few coating combinations [22]. 

Many non-combustible metals and alloys are applied to steel alloys for 

enhanced wear and protection characteristics, such as chrome and nickel electroplating. It 

is also acknowledged that both are less combustible than titanium. While no previous work 

of these system on titanium was discovered, applications are possible. Similarly, elements 

such as cobalt and copper metals and alloys are not combustible in oxygen enriched 

environments and may prove to be a potential coating selection. 

TABLE 5.- HARDNESS OF COATINGS AND RELEVANT METALS USED IN 

BEARING APPLICATIONS 

I Material substratekoating - I Hardness I 

44OC stainless steel (HRC 

(HV) 

697 

, 60) 

17-4 PH stainless steel 471 

(HRC 47) I 

Ti-6Al-4V MRC 36) I 354 I 

J 

' Hard chrome plating 1000-1200 

Nitrided steel 1300-1700 

wc+co -~ 1400- 1800 I TiN I 2000 I 

Ruby, sapphire, corundum I 2500-300 

Sic 

__ - I 4000 ... 

B4C I 5000 

Diamond I >10000 

5-8 
TABLE 6.- PIN 

Recommendations 

Although a material which satisfies all the requirements listed is not readily 

available, a number of opportunities exist in solving the problem. The quickest solution 

may lie in fabricating the bearings from Si3N4. While bearings approaching the size of the 

waist bearing assembly are not fabricated in bulk, current machining technology may be 

able to accommodate the design. Major manufacturers such as Timeken and SKF may 

have capabilities in fabricating these components. Additionally there are two manufacturers 

(in Japan and Germany) who specialize in ceramic bearings and are accustomed to special 

orders. They may also be able to aid in redesigning to accommodate more standard sizes 

and special considerations in using ceramics. 

Another opportunity exists in trying to alter the microstructure of an existing 

titanium alloy or design a new one. Chemical composition being held constant, gamma 

titanium has demonstrated better combustion characteristics than alpha, alpha-beta, or beta 

microstructures as measured by WSTF. This dependency on microstructure gives rise to 

the need to underst the mechanisms behind combustion of solid metals. Since 

theoretical models do not adequately predict this behavior [23-291, it is recommended to 

conduct research into developing a more suitable mathematical model of Combustion. This 

work can then be implemented on developing a more suitable material with optimal stable 

phases which suppress the combustion process and maintain desired strength levels. While 

5-9 
it is not likely that this option will completely 

- sufficiently alter the characteristic such that certain 

mposite system using 

s another attractive 

ustion problems, it may 

rarely coated, therefore, research would be required to investigate 

compatible. There has been sufficient work done in this field to 

coating would be possible. Additionally, some degree of control on specific characteristics 

such as hardness, wear, and friction, can be exercised in the new design. 

DISCUSSION 

Many of the materials used as flexible materials on the EMU are polymeric and in 

turn exhibit some outgasing in a vacuum condition. Short term outgasing is expected to be 

either minimum in intensity or to happen quickly at the onset of vacuum. Knowledge of 

the long term exposure to vacuum of the current materials is unknown. Continued 

degradation of less than thirty years or for durations considered long term exposure limit 

these materials for use on the X-suit. This is the reason for vacuum flex testing and volatile 

gas measurement. Any of the solutions recommended for the bearing assemblies would 

have broad appeal to commercial industry. While specific to the EMU, reporting the results 

of this application will be immediately evaluated by industries where light weight, high 

strength, and combustion potential exists. These may include, but are not limited to, gas 

turbine, chemical processing, and utility distribution applications. For any the 

recommendations selected, a sound theoretical model would go a long way toward 

understanding fundamental kinetics and thermodynamics which drive the combustion 

process. The development of noncombustible titanium would impact the space program as 

a whole since there are a number of applications where good strength to weight titanium in 

the nonflammable condition would be of interest. 

CONCLUSIONS 

A study was conducted on aluminized mylar, the thermal insulation on the Shuttle 

EMU and bearing assemblies used on the various EMU designs. Recommendations for 

improved perforrriance were presented for both problems and long range studies were 

outlined to further contribute to enhanced EMU design. 

1. 

2. 

3. 

4. 

5. 

6. 

7. 

8. 

9. 

10. 

11. 

REFEiRENCES 

Shuttle EMU Space Suit Assembly Materials and Application Functions, provided 

R. D. Kozloski, U.S. Space Gear: Outfitting the Austronaut, Smithsonian 

Institution Press, Washington (1994). 

Space Environment Test System, AVCO model 354, Contract no. NAS9-3625. 

AVC), Tulsa Division. 

K. K. Chawla, Composite Materials, Springer-Verlag, New York, 1987. 

R. Christianson and J. M. Stoltzfus, Proc. ASME Win Ann Mtg, (1993). 

S. Sircar, J. Stoltzfus, C.Bryan, and J. Kazaroff, ASTM STP 1267,7 (1995). 

by E. Omdoff, NASA-JSC. 

.), Metals Handbook, 9th ed., 2 (1987). 

n and J.E. Franklin, ASTM STP I111,5 (1991) 354. 

unaji, S. Sircar and H. Beeson, ASTM STP 1267,7 (1995). 

S. Jahanmir, Mat Res Soc Symp Proc, 140 (1989) 285. 

E. Kingsbury, Mat Res Soc Symp Proc, 140 (1989) 437. 

5- 10 
12. 

13. 

14. 

15. 

16. 

17. 

18. 

19. 

20. 

21. 

22. 

23. 

24. 

25. 

26. 

27. 

28. 

29. 

R. N. Katz and J. G. Hannoosh, Int J High Technology Cennics, 1 (1985) 69. 

T. E. Fischer and H. Tomizawa, Wear, 105 (1985) 29. 

J. W. Lucek, Gas Tur Aero Cong Exp, (1990). 

G. W. Hosang, AIAA 23rd Join Prop Con5 (1987) 1. 

H. Tomizawa and T. E. Fischer, ASU Trans, 30 1 (1986) 41. 

D. L. Allen, ASLE Trans, 37 2 (1986) 410. 

S. Jahanmir and T. E. Fischer, ASMWASLE Trib Con& (1986) 1. 

H. Arm&, Y. Shoda, Y. Morishita and T. Sawamoto, J Trib, 110 (1988) 693. 

J. L. Spodnik and J. J. Wert, , ASMElASLE Trib Con& (1986) 309. 

A. K. Gangopadhyay, M. E. Fine and H.S. Cheng, , ASMElASLE Trib Con5 

(1986) 293. 

H. E. Hintermann, Thin Solid Films, 84 (1981) 215. 

S. Sircar, D. B. Wilson and J. Stoltzfus, Met Trans B, 24B (1993) 395. 

F. J. Benz and J.M. Stoltzfus, ASTM STP 910,2 (1986) 39. 

F. J. Benz, R. C. Shaw, J. M. Homa, ASTM STP 910,2 (1986) 135. 

W. W. Yuen, ASTM STP 910,2 (1986) 59. 

S. Sircar, D. B. Wilson, S. Hornung and J. Stoltzfus, (1995) in press. 

T. A. Steinberg, S. Sircar, D. B. Wilson, J. M. Stoltzfus, (1995) in press. 

D. B. Wilson, (1995) in press. 

5-1 1 
REGIONAL AND LOCALIZED DEPOSITS ON THE MOON 

Final Report 

NASMASEE Summer Faculty Fellowship Program - 1995 

Johnson Space Center 

Prepared By: 

Academic Rank: 

University & Department 

NASNJSC 

Directorate: 

Division: 

JSC Colleague: 

Date Submitted: 

Contract Number: 

Cassandra R. Coombs, Ph.D. 

Assistant Professor 

College of Charleston 

Department of Geology 

Charleston, S.C. 29424 

Space and Life Sciences 

Solar System Exploration 

David McKay, Ph.D. 

August 3,1995 

NGT-44-001-800 

6- 1 
ABSTRACT 

Earth-based telescopic remote sensing studies have provided important information concerning 

lunar pyroclastic deposits. Combined with the returned lunar sample studies and analyses of lunar 

photography, we have learned a great deal about the nature and origin of these explosive volcanic materials. 

Lunar pyroclastic deposits are more numerous, extensive, and widely distributed than previously thought. 

Two generic classes of lunar pyroclastics have been identified, regional and localized. From the former, two 

separate spectral compositional groups have been identified; one is dominated by Fe*+-bearing glasses, the 

other is composed of ilmenite-rich black spheres. Comparatively, three separate spectral groups have been 

identified among the localized deposits: highlands-rich, olivine-rich, and mare-rich. Returned sample studies 

and the recently collected Galileo and Clementine data also corroborate these findings. Albedo data and 

multispectral imagery suggest that the thicker core deposits of the regional dark mantle deposits (FtDMD) 

are surrounded by pyroclastic debris and subjacent highlands material. The presence of a major component of 

pyroclastic debris in the regolith surrounding the core regional deposits has important implications for the 

resource potential of these materials. Both telescopic and orbital spectra indicate that the regional pyroclastic 

deposits are rich in iron, titanium and oxygen-bearing minerals. Particle shapes vary from simple glass 

spheres to compound droplets with quench crystallized textures Their small grain size and friability make 

them ideal indigenous feedstock. Compared to other resource feedstock sources on the Moon, these 

pyroclastic materials may be the best oxygen resource on the Moon. 

6-2 
INTRODUCTION 

Explosive volcanic, or pyroclastic, materials are unique phases in the lunar soils and are important 

as they hold clues to the history of lunar volcanism. As impact craters can be used as wi 

interior, volcanic deposits can be used as windows to the deep lunar interior. Craters 

materials from depths ranging from the near-surface to as much as 1/10 the crater diameter (Pieters a, 

1994). Pyroclastic glasses, among the most chemically “primitive” of lunar rocks, directly sample depths as 

great as 400 km (Delano, 1986) and thus can help address two major science theme strategies put forth by 

the Lunar Exploration Science Working Group, LExSWG to better understand the formation of the EarthMoon system and the thermal and magmatic evolution of the Moon (LExSWG, 1992), while helping us to 

plan better for upcoming lunar missions. 

Earth-based telescopic studies have provided most of our information concerning lunar pyroclastic 

deposits. Combined with the returned lunar sample studies and analyses of spacecraft photography, we 

continue to gain insight into the nature and origin of these explosive volcanic materials. Two generic 

classes of lunar pyroclastics are recognized: regional and local. Our previous work has shown that the larger 

regional deposits are more numerous, extensive, and widely distributed than previously thought (e.g., 

Coombs, 1988; Hawke d, 1989; Coombs & Hawke, 1995), leading us to suggest that they may exhibit 

distinct compositional variations. Returned sample studies and the recently collected Galileo and Clementine 

spacecraft data also corroborate these findings (e.g., Greeley a, 1993; McEwen a, 1994). 

Whole and broken green glass beads were fEst found in abundance at the Apollo 15 site. On the 

Apollo 17 mission, orange glass beads and their quench-crystallized black equivalent were found in high 

concentration at Shorty Crater Station 4 (Figure 1). Various interpretations for the origin of these glass 

beads were proffered: (1) impact melt ejecta from large impacts which had penetrated to more mafic material 

at depth (Carr and Meyer, 1972; Hussain, 1972), (2) vapor condensates (Cavaretta et, 1972; Quaide, 

1973), (3) splash droplets from impacts into lava lakes (Roedder and Weiblen, 1973), or (4) pyroclastic 

material (McKay and Heiken, 1973; McKay et, 1973; Huneke, 1973; Carter etal., 1973; Reid a, 

1973; Heiken and McKay, 1974). The explosive volcanic, or pyroclastic origin is now commonly accepted 

for the Apollo 17 orange and black glass spheres and Apollo 15 green glass. Similarly, it is now 

commonly accepted that the widely spread dark mantle deposits present elsewhere on the Moon also formed 

in similar explosive eruptions. 

Figure 1: Trench at Apollo 17 revealing orange 

soil. Samples collected from this area also 

collected black glass spheres. 

Since their initial identification and classification, 

many more dark mantle deposits have been identified. 

Among the largest of these are the Aristarchus 

Plateau, Mare Humorum, South Mare Vaporum, and 

Sulpicius Gallus deposits. Characteristically, the 

lunar pyroclastic deposits are very smooth, low 

albedo (0.079 - 0.096; Pohn and Wildey, 1970) units 

that cover and subdue underlying temain.he regional 

pyroclastic deposits occur as thick accumulations in 

topographic lows and are thin or absent on adjacent 

hilltops (e.g., Lucchitta and Schmitt, 1974). Visual 

observations by Apollo astronauts and 2m-resolution 

Orbiter photographs indicate that the surface of these 

deposits is relatively fine textured with a velvety 

smooth appearance (Lucchitta, 1973; Schmitt, 1974; 

Lucchitta and Schmitt, 1974; Gaddis 6 1985) 

Color varies among the deposits from a bluish-gray to a reddish-brown and locally may have a strong red, 

orange or blue hue (e.g., Schmitt, 1974). 

During the past decade an enlightened attitude developed toward man‘s exploration and colonization 

of space. As part of this reawakening, the possibility of establishing a manned lunar base needs to be 

revisited. When established, such an endeavor should provide sound economic benefits as well as being a 

solid base from which to conduct scientific experiments. In the immediate post-Apollo era it was suggested 

by a number of workers that titanium production might be a profitable economic activity for a permanent 

6-3 
needs to be revisited. When established, such an endeavor should provide sound economic benefits as well 

as being a solid base from which to conduct scientific experiments. In the immediate post-Apollo era it 

was suggested by a number of workers that titanium production might be a profitable economic activity for . a permanent manned lunar base. Following that, it was suggested that fine-grained lunar regolith material 

would be usefbl for shielding orbiting space stations or military facilities. In the past few years, attention 

has focused on the production of oxygen propellant and helium-3 as nuclear fusion fuel both for use at the 

base and to transport materials back to Earth (e.g., Simon, 1985; Gibson and Knudson, 1985; Kulcinski a 

1986; Kulcinski, 1988). From these early studies, ilmenite-rich material became the preferred source 

for the production of these resources (see Mendell, 1985; Hawke g& 1989a,b). Hawke && (1990) 

discussed the resource potential of lunar pyroclastic deposits and suggested that they would make an 

excellent site for locating a lunar base. Most recently, Allen (1995) extracted 6% 02 from Apollo 17 

glass spheres, the highest amount collected yet. In this paper we summarize some of what is known about 

these deposits, discuss models for their emplacement, and fiuther explore their scientific, engineering and 

resource-related advantages as lunar base sites. 

LUNAR PYROCLASTIC MATERIALS 

REGIONAL VS LOCAL 

Based on recent geologic and remote sensing data, the lunar pyroclastic deposits have been 

divided into two genetic classes: regional and localized (e.g., Lucey &&, 1984; Gaddis a, 1985; 

Coombs, 1989; Hawke && 1989). These subdivisions are based upon their compositions as well as 

overall size and distribution. The regional dark mantle deposits cover a relatively large area of the lunar 

surface with respect to the smaller, localized deposits. Indeed, the regional deposits vary in size from 4,000 

to 30,000 km2. These large deposits are located in highlands areas adjacent to (and in some cases are 

superposed on) many of the major maria. The explosive fire-fountaining that formed these regional deposits 

may have been associated with some of the early mare-filling volcanic episodes (McGetchin and Head, 

1973; Head, 1974). Endogenic craters and other irregular depressions are thought to be the source vents for 

these deposits (e.g., Zisk && 1973; Head, 1974; Gaddis && 1985; Coombs and Hawke, 1988). 

The localized pyroclastic deposits are more widely spread across the lunar nearside than are the 

regional pyroclastics. These deposits too were emplaced via volcanic fue-fountaining. On average, the 

localized deposits cover 250-550 km2 although some may be as small as 80 km2, and some as large as 

700 km2 (Coombs &&, 1987; Coombs, 1988; Hawke &&, 1989). They are concentrated around the 

perimeters of the major lunar maria and are commonly found in the floors of large Imbrian and pre-Imbrian 

aged impact structures (e.g., Head and Wilson, 1979; Coombs and Hawke, 1988). The localized deposits 

are generally associated with small endogenic source craters (<3 km) and are aligned along crater floorfractures andor regional faults. Typically, these source craters are irregular in shape and lack obvious crater 

rays. 

The explosive eruptions that formed the lunar dark mantle deposits have been likened to some 

types of terrestrial volcanic activity. The regional deposits most likely formed in a manner similar to 

terrestrial strombolian fue-fountaining, while the smaller, more localized deposits most likely formed by 

"vulcanian-type'' explosions (Wilson and Head, 1979; Head and Wilson, 1981; Coombs, 1988; Hawke 

&, 1989). A strombolian, or continuous eruption cycle is consistent with the volatile coated spheres 

returned from the Apollo 17 landing site, which chemical studies have shown to have originated deep in 

the lunar interior (<300 km). 

In a strombolian eruption relatively small time-transient explosions occur at intervals ranging 

from less than 0.1 second to hours. Gas and pressure build up as the magma rises to the surface. The rising 

magma eventually reaches the surface through propagating cracks and or faults in the overlying rock. 

Explosive decompression occurs as the pressure is released and the magma and gas rise in an expanding 

column of erupting material. Environmental conditions on the Moon cause the particles to spread out over 

an area roughly six times larger on the Moon than they would for a similar eruption on Earth. With the 116 

gravity and lack of atmosphere on the Moon, no pyroclastic flows will occur, rather, the pyroclasts will be 

spread over a broad area, with a size-gradiig of the clasts. Larger fragments will be deposited closest to the 

vent while finer grained particles may travel 100's km before settling out (Wilson and Head, 1979). 

In the vulcanian-type eruptions that formed the localized pyroclastic deposits? magma, gas and 

pressure build up beneath a cap-rock in the conduit. Eventually, when enough pressure builds up, explosive 

decompression occurs and the caprock is blown away, along with the rising magma and gas. These 

eruption columns too will spread out more evenly on the Moon and cause the settling pyroclasts to cover a 

larger area than they would on Earth (Coombs, 1988; Coombs 1989). 

6-4 
Due to their small areal extents and relative thinness, however, it is thought that the smaller, 

localized deposits would be less efficient for use in extracting lunar resources, and thus will be left out of 

the current discussion and evaluation as a potential lunar resource. 

Pyroclastic Soil Evolution 

Sample work done on the returned Apollo 17 orange and black glasses indicates that they are 

chemically indistinguishable from each other; the only difference being that the black spheres are partially 

quench-crystallized. Collectively, the glass beads are fine grained and have a mean grain size of -40 pm 

and their shapes vary from subequant spheres to angular fhgments. Many of them are coated with 

sublimates and or micromounds. Fig. 2 illustrates the breakdown of the mean grain size versus standard 

deviation for the A17 soils. From this figure, it is clear that the orange and black glasses are finer grained 

than most mature lunar soils. 

Figure 2: Mean grain size versus standard 

deviation for lunar soils. Note where the Apollo 

17 orange glass lies in relation to other lunar 

soils. It is much finer grained than even mature 

lunar soils. 

A size equilibrium is reached within lunar 

soils as a result of meteorite reworking. Basically, 

the grain size of any soil is determined by the 

amount of fresh ejecta present. For example, if there 

is a lot of fresh ejecta present, the soil will be fairly 

coarse grained. Or, if not much fresh material is 

introduced, the grains will become smaller and 

smaller over time as the mature soil is continuously 

being reworked by micrometeorites and impacts. 

Eventually, the soil or regolith is made into 

agglutinates that in turn, are reworked and mixed 

materials then continue to be reworked. In time, it 

appears that with thicker soils, such as the 30 - 50 m thick dark mantle deposits, the steady addition of 

ejecta from fiesh bedrock will go away and the continuous reworking of the already present regolith is 

continued. 

If the supply of fresh material diminishes, the grain sizes will reduce to approximately 20 p. 

Earlier studies by McKay a (1974), indicate that this 20 pm size is the smallest fraction that the glass 

beads to which will break down. The grain size is determined by the ratio of large to small particles. If 

there is no longer a significant input of larger particles, then the grain size will continue to decrease and 

u1 

250 rrn 125~ 62.5 m 31.3 Frn 

together with extraneous exotic materials. These MEAN GRAIN SIZE (M,) 

_. 

Figure 3: Vesicles within glass sphere 60095 

from retuned Apollo 17 sample suite. Clast size 

is approximately 1 cm. Vesicles due to presence 

of internal gas during formation and cooling 

phase. 

The maximum estimated thickness for a 

regional pyroclastic deposit is -50 m. Based on 

early work by McKay and Heiken (1974) and 

Carrier (1974) the mean grain size within this 

deposit will be 5.35 0 or 25 p. For an average 

thickness of 30 m, the mean grain size expected for 

a mature deposit would be 29 pm or 5.110. 

Analyses of the entire orange and black glass 

collection have yielded no single particle size 

greater than 1 mm, although some fragile clods of 

agglutinate material were larger than lmm. 

6-5 
Morphology of Pyroclasts 

Looking a little more closely at these glasses, the particle shapes vary from simple glass spheres 

to compound droplets with quench crystallized textures that vary from fine-grained dendrites to subequant 

skeletons. The bulk of the returned glass samples is comprised of frne grained fragments and shards, which 

raises a question about their origin and emplacement. These fragments are now interpretted to be the esult 

of anexplosive eruption, as mentioned above, whereby the material erupted, landed, bounced and more 

material was deposited on top. As a result, a process of self collision and breakdown occurs. These 

fragments are beneficial to the resource potential of these glasses. That is, the more surface area exposed, 

the more solar wind that can be adsorbed by the glasses. Quick calculations indicate that the surface area of 

a small bucket full of lunar pyroclastic materials is the equivalent surface area of an American football field 

(K. Joosten, pen. communication). 

Vesicles are seen in less than 6% of the returned samples. Vesicles form in pyroclastic material by 

trapping gases in the magma during the fre-fountaining phase. The gases become isolated and trapped as 

the magma blebs cool and solidify during flight. These gases may represent volatiles released during the 

volcanic activity, and thus may be representative of the interior composition of the Moon. Possible vesicle 

gases include flourine compounds, sulfur, solar-wind gases and carbon monoxide (Goldberg &A, 1976). 

Carbon monoxide remains among the favorite of the vesicle-forming gases. Laboratory studies performed 

by Gibson d (1 975) found that most of the C in mare basalts is released as CO and C02 as trapped 

magmatic gases. This, in addition to atmospheric and sputtering losses and recycling into subsequent lava 

flows, may account for the low C content currently detected in lunar soils. 

Figure 4 Compound droplet collected from the 

74001/2 core tube sampled at Apollo 17. 

Many of the glass beads form compound 

droplets (Figure 4), whereby one bead cooled and 

another hot droplet hit the bigger one while it was 

still soft and "squished" around it. Some of these 

secondary or parasitic droplets have been shown to be 

partly crystallized just beneath the surface. It is 

thought that the film, composed of Zn, Ga, Pb, 

Cu,Ti, S, F, C1 and other elements condensed on the 

surfaces during lava fountaining. Meyer et al. (1 975) propose an anhydrous sulfide, chloride, and flouride 

rich vapor, originating from a pyroxenite layer deep inside the Moon. In addition, many of the glys beads 

are coated with a thin film of micromounds (Figure 5). The micromounds range in size fhm 20 - 500 

diameter (McKay et al., 1973). These are interpretted to be vapor condensate features that formed by 

venting gases, similar to the condensate deposits found around terrestrial volcanic/fumarolic centers. The 

micromounds found on the lunar glasses are enriched in sulfur, with some Zn, K, and Na also present 

(Clanton &&, 1978). 

A in 

Morphologic textural features present within 

the Apollo 17 glass sample suite include the 

predominance of olivine and ilmenite crystals. These 

are thought to be due to devitrification of the glass 

bead. Parasitic crystals have also been found on the 

surfaces of some beads. The exact composition of 

these crystals is unknown, however, the larger ones 

are predominately of two compositions, potassiumchloride and sodium-chloride. The surfaces of some 

orange glass beads were also found to contain 

ameoboid blebs of iron. 

Figure 5: SEM photomicrograph of sublimate 

micromounds on the surface of a glass sphere. 

6-6 
Table 1 : Pristine Lunar Glass Varieties Arranged According to wt % Ti02 Abundance 

1) Apollo 15 Green C 

2) Apollo 15 Green A 

3) Apollo 16 Green 

4) Apollo 15 Green 

5) Apollo 15 Green D 

6) Apollo 15 Green E 

7) Apollo 14 Green B 

8) Apollo 14 VLT 

9) Apollo 11 Green 

10) Apollo 17 VLT 

1 1) Apollo 17 Green 

12) Apollo 14 Green A 

13) Apollo 15 Yellow 

14) Apollo 14 Yellow 

15) Apollo 17 Yellow 

16) Apollo 17 Orange 

17) Apollo 17 Orange 

18) Apollo 15 Orange 

19) Apollo 17 Orange 

20) Apollo 11 Orange 

21) Apollo 14 Orange 

22) Apollo 15 Red 

23) Apollo 14 Red 

24) Apollo 14 Black 

25) Apollo 12 Red 

48.0 0.26 7.74 

45.5 0.38 7.75 

43.9 0.39 7.83 

46.0 0.40 7.92 

45.1 0.41 7.43 

45.2 0.43 7.44 

44.8 0.45 ‘7.14 

56.0 0.55 9.30 

43.7 0.57 7.96 

45.3 0.66 9.60 

44.3 0.91 6.89 

44.1 0.97 6.71 

42.9 3.48 8.30 

40.8 4.58 6.16 

40.5 6.90 8.05 

39.4 8.63 6.21 

38.5 9.12 5.79 

37.9 9.12 5.63 

38.8 9.30 7.62 

37.3 10.0 5.68 

37.2 12.5 5.69 

35.6 13.8 7.15 

35.6 15.3 4.81 

34.0 16.4 4.6 

33.4 16.4 4.6 

0.57 

0.56 

0.39 

0.55 

0.55 

0.54 

0.54 

0.58 

0.46 

0.40 

n.a. 

0.56 

0.59 

0.41 

0.63 

0.67 

0.69 

0.65 

0.66 

0.63 

0.86 

0.77 

n.a. 

0.92 

0.84 

0.19 18.2 8.57 

16.5 

19.7 0.22 17.2 8.65 

21.9 0.24 16.9 8.44 

19.1 n.a. 17.2 8.75 

20.3 0.22 17.6 8.43 

19.8 0.22 18.3 8.15 

19.8 0.24 19.1 8.03 

18.2 0.21 15.9 9.24 

21.5 n.a. 17.0 8.44 

19.6 0.26 15.0 9.40 

20.2 0.23 19.5 7.40 

23.1 0.28 16.6 7.94 

22.1 0.27 13.5 8.50 

24.7 0.30 14.8 7.74 

22.3 0.25 12.6 8.64 

22.2 0.28 14.7 7.53 

22.9 n.a. 14.9 7.40 

23.7 n.a. 14.9 7.41 

22.9 0.29 11.6 8.55 

23.7 n.a. 14.3 7.62 

22.2 0.31 14.5 7.04 

21.9 0.25 12.1 7.89 

23.7 n.a. 13.0 6.49 

24.5 0.31 13.3 6.90 

23.9 0.30 13.0 6.27 

n.d. 

n.d. 

n.d. 

n.d. 

n.d. 

n.d. 

0.06 

0.11 

n.d. 

0.27 

0.10 

n.d. 

0.45 

0.42 

0.39 

0.4 1 

0.38 

0.36 

0.39 

0.3 1 

0.28 

0.49 

0.50 

0.23 

0.05 

n.d. 

n.d. 

n.d. 

ad. 

n.d. 

n.d. 

0.03 

0.07 

n.d. 

0.04 

n.d. 

n.d. 

n.d. 

0.10 

n.d. 

0.04 

n.d. 

n.d. 

n.d. 

n.d. 

0.29 

0.12 

n.d. 

0.16 

0.12 

n.a.: not yet analyzed 

n.d.: not detected 

Modified from Delano (1986). 

6-7 
GEOCHEMISTRY OF THE LUNAR PYROCLASTIC DEPOSITS 

Geochemistry Of Returned Samples 

Since their return, many microprobe, SEM, TEM, and petrographic analyses have been done on 

the lunar glass droplets (e.g., Chao a, 1970; Reid &&, 1972, 1973; Ringwood, 1973; Heiken and 

McKay, 1974; Green &&, 1975; Glass, 1976; Marvin and Walker, 1978; Warner- 1979; Green and 

Delano, 1980; Delano and Livi, 1981; Chen && 1982; Delano, 1986). As a result of these many detailed 

studies Delano (1986) identified and confumed the existence of twenty-five varieties of pristine, or 

volcanic, glass. These classes are based on their individual compositions and include: Apollo 11 green and 

orange; Apollo 12 red; Apollo 14 green (A & B), VLT, yellow, orange, black, and red, Apollo 15 green 

(A, B, C, D, E), orange, yellow, and red; Apollo 16 green; and Apollo 17 orange, yellow, VLT, and green 

(see Table 1). To accomplish this, Delano synthesized all of the previously published data and removed 

any interlaboratory bias by consistently using the Apollo 17 pristine orange glass composition as a 

working standard throughout his investigations of the high-Ti glasses. Likewise, the Apollo 15 pristine 

yellow glasses and Apollo 15 pristine green A glasses, respectively, were used as standards for other glass 

droplets containing medium- and low-Ti abundances (Delano, 1986). 

The laboratory data indicate a composition rich in Si02, FeO and MgO for the various pyroclastic 

classes. These values are consistent with remote sensing data collected over the various regional pyroclastic 

deposits and discussed below. 

REMOTE SENSING OF LUNAR PYROCLASTIC DEPOSITS 

Orbital Geochemistry 

The Apollo15 and 16 spacecrafb each flew a flourescent X-ray experiment package from which 

intensity ratios for the elements Mg, A1 and Si were measured. In a procedure outlined by Bielefeld (1977), 

the various intensity ratios were converted to geochemical concentration ratios by weight. From these data, 

a positive correlation was noticed between high Mg/Al ratios and the presence of dark mantle material 

(Schonfeld and Bielefeld, 1978). Of the four large, regional pyroclastic deposits mentioned thus far, 

Sulpicius Gallus has the highest overall average Mg/Al values. Studies by Butler u(1978) show that 

the green, orange and brown pyroclastic glasses have extremely high Mg/A1 concentration ratios (2.7,2.6 

and 1.7, respectively) compared to ordinary mare soils (ave. 0.61). When these glasses are mixed with the 

mare soils, an overall increase in Mg and decrease in A1 concentration occurs. Mixing models performed by 

Schonfeld and Bielefeld (1978) estimate that approximately 32-37% of the Sulpicius Gallus formation is 

composed of orange and black glass. Similarly, they estimate that the two glasses compose 28% of the 

Taurus-Littrow deposit. Returned samples, however, indicate that only about 10-25% of the Apollo 17 soil 

was composed of orange and black glass, with the exception of Shorty Crater where pure concentrations of 

orange and black glass were found (AFGIT, 1973). This discrepancy may be due to the 50 km distance 

between the Apollo 17 landing site and the Taurus-Littrow deposit. 

Other similar correlations between high Mg/Al ratios and the presence of dark mantle pyroclastic 

material were found at the craters Picard (Olson and Wilhelms, 1974) and Pierce (Casella and Binder, 

1972) in Mare Crisium as well as in Mare Fecunditatis. 

Andre a (1 975) also analyzed the orbital geochemistry data collected over the Apollo 17- 

Taurus Littrow site. They looked at the AYSi concentration and found that a decrease in intensity of the 

AySi ratio correlates with a distinct chemical boundary between the highland and dark mantle units. Less 

pronounced, however, was the distinction between the dark mantle unit and the floor of Mare Serenitatis. 

Here, the X-ray flourescence data indicated only a slight variation in AVSi between the two materials 

(Andre 1975). Nine Taurus-Littrow basalt samples studied by Nava (1974), Rhodes a (1974), and 

Rose d (1974) have an AVSi concentration ranging from 0.22 to 0.28, or an intensity ratio between 

-0.50 to -0.66. The average concentration ratio yields an AYSi intensity ratio of -0.59, which corresponds 

to the average value for four orbital data points in the mare proper (Andre 1975). The calculated 

concentration and intesity ratios for the orange and black glass are 0.19 and 0.48 respectively. These data 

correspond nicely with the visible albedo data of Pohn and Wildey (1970), the color-difference photograph 

of Whitaker (1972), and the relative spectral reflectivity curves of McCord d (1972), Gaddis && 

(1985), Coombs (1988), and Hawke && (1989). 

6-8 
Earth-Based Radar 

regional pyroclastic deposits lack signal-scatterers, or rocks and boulders in the 1-50 cm . the data indicate that the surfaces of these deposits are smooth and block-free, and, that the 

zones of these deposits are also block-free (Zisk etal.. 1974; Thompson, 1979). With the 1 

incidence in the 3.8-cm radar images, the polarized signals returned are largely a knct 

The unpolarized signals, on the other hand, are almost entirely dependent upon the inherrent properties of 

the surface materials, and exhibit little or no slope effects. These data support the field observations made 

by Apollo 17 astronauts, Cernan and Schmitt, during their EVA at Shorty Crater (Bailey and Ulrich, 

1975), where they cored into a dark mantle deposit. In general, within any particular dark mantle deposit, 

areas of high radar return, or where a small impact penetrateted the pyroclastic mantle and exposed higher 

albedo material, are rare. 

As discussed briefly above, 3.8- and 70-cm radar backscatter images show that the surfaces of the 

Earth-Based Telescopic Spectra 

Earth-based telescopic spectral reflectance studies have provided important information concerning 

the composition of regional pyroclastic deposits (e.g., Adams &&, 1973; Pieters, 1973, 1974; Gaddis, 

1985; Lucey &&, 1986). Figure 6 shows a number of near-ineared spectra that were collected from 

regional pyroclastic deposits on the lunar nearside (e.g., Sinus Aestuum, Rima Bode, Mare Vaporum, 

Taurus Littrow, Aristarchus Plateau). These spectra were collected from the University of Hawaii 2.2 meter 

telescope on Mauna Kea and processed according to the methods outlined by McCord &&, 198 1. 

The spectra indicate that the regional pyroclastic deposits are rich in iron, titanium and oxygenbearing minerals. Some minor compositional variations do exist between the deposits. For example, the 

top three spectra in Figure 6 from Taurus Litrrow, Sinus Aestuum, and Rima Bode, indicate a composition 

rich in iron, titanium and oxygen. The absorption bands in the continuum removed spectra are shallow and 

broad, with somewhat irregular base curves. The bottom two spectra from, Mare Humonun and the 

Aristarchus Plateau, on the other hand indicate that these deposits are rich in F&'-bearing glass (Gaddis 

A, 1985; Lucey &&, 1986; Coombs, 1988; Hawke etal.. 1989). Here the absorption bands exhibit 

broader, deeper and more smooth or uniform signatures and extend to longer wavelengths. 

1.1 

1.m 

8.m 

1.m 

Figure 6 Continuum removed spectra collected 

from the U.H. 2.2 m teslescope on Mauna Kea 

of some regional pyroclastic deposits. 

Multispectral ratios of these deposits exibit 

very high 0.40/0.56 pm values and the deposits 

appear "blue" in 0.40/0.56 pm images presented by 

Pieters a (1974) and McCord (1976). 

RESOURCE POTENTIAL OF LUNAR 

PYROCLASTIC MATERIALS 

The surfaces of the lunar dark mantle 

deposits are uniform and exhibit a low amount of 

contamination (Pieters &&, 1974; McCord 

1976, 1979; Gaddis &&, 1981, 1985; Coombs, 

1988; Hawke gt & 1989). The deposits are 

widespread and cover large areal extents. They are 

relatively deep, varying &om 10-50 m thick. The 

deposits are homogeneous with uniform sizes and 

compositions and are relatively unconsolidated. 

The mechanical properties of the pyroclastic deposits are predictable as compared to typical mare 

or highland regoliths, where there is much more variation in heterogeneity. Thus, it would be much easier 

to design a rover and other such necessary mining equipment to traverse the pyroclastic deposits. Mining 

and excavation will be straightforward in this material due to its fine-grained nature. These deposits have 

an excellent resource potential as they are relatively high in solar wind contents and the bulk chemistry of 

the glass is enriched in Si, Fe, Mg, and Ti. Also, these deposits would provide an extremely useful source 

6-9 
of shielding and construction material. The high density of the deposit materials makes these glass beads 

ideal for radiation protection. Also, the combination of high density and potentially thick, fine-grained 

deposits make tunnelling for habitats extremely attractive. A mere 10-20 m covering of this material will 

provide a year-round ambient temperature of zero degrees C and would almost eliminate radiation 

(1994) demonstrated that the 

Apollo 17 orange and black glasses release the most oxygen when exposed to hot hydrogen than any other 

lunar material. Compared to other resource feedstock sources on the Moon, these pyroclastic materials may 

just be the best oxygen resource on the Moon. Additionally, we now know that the orange and black glass 

spheres are rich in easily accessible sulfur and other sublimates as mentioned above. These samples have 

approximately 700 ppm by weight, sulfur in the bulk glass sample. Sulfur may be easily extracted from 

the lunar glass beads by heating them to relatively low temperatures compared to other samples. Gibson 

and Moore (1974) heated beads from sample 74220,84 and determined that sulfur is released at 

temperatures as low as 25OOC to 650-700OC. The iron-rich pyroclastics may also be very good feedstocks 

for producing construction material such as sintered concrete-like blocks and for extracting metallic iron for 

a lunar base power system. 

Recent laboratory studies performed here at JSC by Allen 

CONCLUSION 

An evaluation of the remote sensing data confirm that lunar pyroclastic deposits are more 

prevalent and widespread than intially mapped. In addition, more material is thought to have erupted and 

been distributed than previously thought. Results of the geologic and remote sensing studies now lead us 

to believe that some pyroclastic deposits are exposed remnants of much larger regional deposits that are 

now largely buried by crater ejecta andor subsequent lava flows. 

Laboratory compositional evaluations and soil studies support the use of these materials as 

resource feedstock. Not only are they readily avaiable in the most useful form - friable, fine-grained 

spheres, they are full of needed resource elements which can be readily beneficiated and used to establish 

and maintain a lunar base. 

As with so many topics, we now know enough about lunar pyroclastics to know taht we need to 

know much more before we can claim we understand them. Recently returned satellite data and future 

missions such as Questions we will address in the future with the help of the higher resolution 

Clementine and Galileo data include: What is the ‘true’ geographic extent of the pyroclastic deposits? Can 

we actually identify potential source vents and how do the volcanic deposits relate to them? How does the 

composition of a deposit vary? How does the Apollo 17/Taurus-Littrow deposit, a comparatively well 

studied site from which we have samples, relate to similar, remote sites like Sulpicius Gallus or Rima 

Bode? How well can we extrapolate our findings to other sites? How do the regional sites compare to the 

local sites? How do the glass samples in most lunar soils fit into the picture? We know that the Apollo 

17/Taurus Littrow spectra and samples correlate, but how far can we extend this correlation and our 

comparative methods? Do Apollo 11, 12, 14, 15, and 16 samples correlate with Clementine/Galileo 

spectra, and if so, how? What do the fkesh craters tell us about these deposits? Can we find fiesh, pristine 

exposures on the crater rimdwalls? Can we determine the relationship of regolith maturity to grain color? 

How do the spectral signatures of individual pyroclastic glass particles relate to the signatures of larger 

scale deposits? What is the relationship, if any, between the regional and local deposits? 

6- 10 
Adams, J.B., Pieters, C.M., and McCord, T.B. 1974. Orange glass: Evidence for regional deposits of 

AFGIT (Apollo Field Geology Investigation Team) 1973. Geologic exploration of Taurus-Littrow: Apolo 

17 landing site. Science 182:672-680. 

Allen C.C, G.G. Bond, D.S. McKay (1994) Lunar oxygen production - a maturing techonology, in 

Engineering, Construction and Operations in Space IV, pp. 1157-1 166, Am. SOC. Civil Eng., New 

York, 1994. 

Andre, C.G., Hallam, M.E., Weidner, J.R., Podwysocki, M.H., Philpotts, J.A., Clark, P.E., and Adler, I. 

1975. Conelation of AYSi X-ray flourexcence data with other remote sensing data ibm the TaurusBailey, N.G. and Ulrich, G.E. 1975. Apollo 17 voice transcript pertaining to the geology of the landing 

Bielefeld, M.J. 1977. Lunar surface chemistry of regions common to the orbital X-ray and gamma-my 

Butler, P.Jr. 1978. Recognition of lunar glass droplets produced directly fiom endogenous melts: The 

evidence hm S-Zn coatings (abstract). In Lunar and Pkg@ Sa .. K (Lunar and Planetary Institute, 

Houston), pp. 143-145. 

Car, M.H. and Meyer, C.E. 1972 Chemical and petrographic chamcteristics of the regolith at the Apollo 

15 landing site. In . (The Lunar Science Institute, Houston), pp. 48- 

50. 

Carter, J.L. , Padovani E., and Taylor, H.C. 1973. Morhology and chemistry of particles hm Apollo 17 

Casella, J.C. and Binder, A.B. 1972. Geologic map of the Cleomedes Quadrangle of the Moon. Y.S.G.S, 

Cavaretta, G., Funiceileeo, R., Giles, H., Nicholls, G.D., Taddeucci, A., and Zussmm, J. 1972. 

Geochemistry of green glass speres hm Apollo 15. In The (Lunar 

Science Institute, Houston), pp. 202-203. 

Chao, E.C.T., Boreman, J.A., Minkin, J.A., James, O.B., and Desborough, G.A. 1970. Lunar glasses of 

impact origin: Physical and chemical characteristics and geologic implications. J. Geophvs . Res. 

75 : 7445-7479. 

Chen, H.K., Delano, J.W., and Lindsley, D.H. 1982. Chemistry and phase relations of VLT volcanic 

pyroclastic origin on the Moon. 1 pp. 171-186. 

Littrow area Proc. Lunar and Planet. Sci. ~~w 5th. pp. 2739-2748. 

site. U.S.G.S. Rpt. 74-03L 361 pp. 

experiments. , pp. 113 1-1 147. 

soils 74220,74241 and 74081 (abstract). E0s.v~. U r\inn 54582-584. 

Rpt. 1-707, (LAC 44). 

glasses hm Apollo 14 and Apollo 17. in, J- Geophvs. Res, 

87tA171-18 1. 

Int'l Cod on Volczglnsts . Kagoshima, Japan. pp. 416-419. 

Coombs, C.R., Hawke, B.R., Lucey, P.G., Owensby, P.D., and Zisk, S.H. 1990. The Alphonsus region: 

Coombs, C.R., McKay, D.S., Heiken, G.H., and Hawke, B.R. 1991. Should the future lunar base be 

Delano, J.D. 1986. Pristine lunar glasses: Criteria, data aud implications. p-, 

Delano, J.D. and Livi, K. 1981. Lunar volcanic glasses and their constraints on mare petrogenesis. 

Gaddis, L.R., Adams, J.B., Hawke, B.R., Head, J.W., McCord, T.B., Pieters, C.M., and Zisk, S.H. 

ic units in the Rima Bode region of the Moon 

Gaddis, L.R., Pieters, C.M., and Hawke, B.R. 1985. Remote sensing of lunar pyroclastic mantling 

Gibson E.K. and G. W. Moore (1974) Sulfur abundances and distributions in the vally Taurus-Littrow. 

A geologic and remote-sensing perspective. Pmc. 20th -and. Sci. CQKL , pp. 161-174. 

located on a pyroclastic deposit? (abstmct) M. on Near Fa#h.Space Resouigi, Tuscon, AZ. 

SCi. CO& In J.w. Rs 91:D201-D213. 

45: 2137-2149. 

ar and Planet. Institute, Houston), pp. 3 18-320. 

deposits. 61:461-489. 

Proc. LunarSci. Con$ 5th p. 1823-1837. 

6-11 
Gibson, M.A. and Knudsen, C.W. 1985. Lunar oxygen production hm ilmenite. In 

SDace Ad ivities of the 21st Centqv ,ed. W. W. Mendell, (Lunar and Planetq Institutes, Houston). 

pp. 543-550. 

Glass, B.P. 1976. Major elemnet composition of glasses from Apollo 11, 16 and 17 soil samples. &,& 

Green, D.H., Ringwood, A.E., Hibberson, W.0, and Ware, N.G. 1975. Experimental petrology of Apollo 

Hawke, B.R., Coombs, C.R., and Clark B. 1989a Pyroclastic deposits: An ideal lunar resource (abstract). 

HaWke, B.R., Coombs, C.R., and Clark B. 1989b. Ilmenite-rich pyroclastic deposits: An ideal lunar 

Hawke, B.R., Coombs, C.R., Gaddis, L.R., Lucey,P.G., and Owensby, P.D. 1989c. Remote sensing and 

and PW. Sc i. Con€ 

Hawke, B.R., Coombs, C.R., and Clark B. 1990. Pyroclastic deposits as sites for lunar bases. EppEL 

Head, J. W. 1974. Lunar dark mantle deposits: Possible clues to the distribution of early mare deposits. 

Head, J.W. and Wilson, L. 1979. Alphonsus-type dark halo miters: Morphology, morphometry and 

Heiken, G.H, McKay, D.S. , and Brown, R.W. 1974. Lunar deposits of possible pyroclastic origin. 

Geoch im. Cosmochim. Actpl 38:1703-1718. 

Huneke, J.C., Podesek, F.A., and Wasserburg, G.J. 1973. An argon bouillabaisse including ages hm the 

Luna 20 site (abstract). In mar Science IV, (The Lunar Science Institute, Houston), pp. 403-405. 

Hussein, L. 1972. The Ar- Ar and cosmic ray exposure ages of Apollo 15 crystalline rocks, breccias and 

glasses (abstract). In The Apollo 15 Lm (The Lunar Science Institute, Houston), pp. 374- 

376. 

Kulcinski, G.L. 1988. ed., Astmfiel for the 21st Cenu (College of Engineering, University of 

Wisconsin, Madison). 20 pp. 

Kulcinski, G.L., Santarius, J.F., and Wittenberg, L.J. 1986. Presentation at the 1st Lunar Development 

Symposium. September, 1986, Atlantic City, N.J. 

Lucey, P.G., Hawke, B.R., Pieten, C.M., Head,J.W., and McCord, T.B. 1986. A compositional study of 

the Aristarchus region of the Moon using near-inM mflectance spectroscopy. Proc. Lunar and 

Planet. Sci. Conf. 16th in, J. Geophvs. R~s, 91:D344-D354. 

Lucchita, B.K. 1973. Photogeology of the dark material in the Taurus-Littrow region of the Moon. EppEL 

Lunar Planet. Sci. Ca pp. 149-162. 

Lucchita, B.K. and Schmitt, H.H. 1974. Orange material in the Sulpicius Gallus Formation at the 

Marvin, U.B. and Walker, D. 1978. Implications of a titanium-rich glass clod at Oceanic Procellarum. 

McCord, T.B., Pieters, C.M., and Feierberg, M.A. 1976. Multispectml mapping of the lunar surf& using 

McCord, T.B., G&W, M.A., Feierberg, M.A., MacLaskey, D., and Pieters, C.M. 1979. Lunar 

multispectral maps: Part II of the lunar nearside. kjms 37: 1-28 

McCord, T.B., Clark, R.N., Hawke, B.R., McFadden, L.A., Owensby,P.D., Pieters, C.M., and Adams, 

J.B. 1981. Moon: Near-hhed spectral dectance, a first good look. J. Geonhvs. R~s, 86:10,883- 

10,892. 

Lunar Sa. Conf 7thA 679-693. 

17 mare basalts. Proc. Lunar Sci. Conf 6th . 871-893. 

In Lunar and P langggy science (Lunar and Planetary Institute, Houston). pp. 387-390. 

resource. Proc. Lunar and Planet. Sa. Conf 20th pp. 249-258. 

geologic studies of localized dark mantle deposits on the Moon. groc, 

19th. pp. 255-268. 

Space 90 Conf, pp. ??-??. 

P pp. 207-222. 

eruption conditions. & , pp. 2861-2897. 

. 

soutwestem edge of Mare Semitatis. €'roc. L- Sci. Conf 5& pp. 223-234. 

Am. Mind 63~924-929. 

Wmd-d-based tele~cope~. 29 1-34. 

McGetchin,T.R. and Head, J.W. 1972. Lunar cinder cones. 18068-71. 

McKay, D.S., Clanton, U.S., and Ladle, G. 1973. Scadng electron microscope study of Apollo 15 green 

McKay, D.S. and G.H. Heiken 1973. Petrography and scanning electron microscope study of Apollo 17 

Mendell, W.W. 1985. ed., Space Act ivities of the 21st C- . (Lunar and Planetary 

Nava, D.F. 1974. Chemical compositions of some soils an drock types hm the Apollo 15, 16, and 17 

glass. pp. 225-238. 

orange and black glass (abstract). EOS. 'J&Bs. Amer. GWD~VS. Un ion 54599-600. 

Institute, Houston), 866 pp. 

Bases 

lunar sites. pp. 1087-1096. 

6-12 
Olson, A.B. and Wilhelms, D.E. 1974. Geologic map of Mare Undanun Quadrangle of the Moon. 

Pieters, C.M. , McCord, T.B., Zisk, S.H., and Adams, J.B. 1973. Lunar black spots and the nature of the 

Pieters, C.M., McCord, T.B., Charette, M.P., and Adams J.B. 1974. Lunar surfixe Identification of the 

Pohn, H.A. and Wildey, R.L. 1970. A photoelectriophotgmphic study of the normal albedo of the Moon. 

Quaide, W.L. 1973. Provenance of Apennine Front regolith materials (abstmct). In Lunar Sa 'ence JV, (The 

Lunar Science Institute, Houston), pp. 606607. 

Reid, A.M. , Warner, J., Ridley, W.I., Johnston, D.A., Harmon, R.S., Jakes, P. and Bmwn, R.W. 1972. 

The major element compositions of lunar rocks as inferred fiom glass compositions in the lunar soils. 

Reid, A.M., Lofgren G.E., Heiken G.H., Brown, R.W., and Moreland, G. 1973a Apollo 17 orange glass, 

Apollo 15 green glass and Hawaiian lava fountain glass (abstract). EOS. Trans. Amer. Geop h vs, 

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Rhodes, J.M., Rogers, K.V., Shih, C., Bansal, B.M., Niquist, L.E., Wiesmann, H., and Hubbard, N.J. 

1974. The relationships between geology and soil chemistry at the Apollo 17 landing site. Proc. Luws 

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Conf 7th. 1697-1722. 

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(abstract). EOS. Trans. Amer. GeoDhvs. l&&& 54512413. 

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U.S.G.S. Rpt. 1-837 (LAC 62). 

Apollo 17 landing J. Geoohvs. Res, 785867-5875. 

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' f . 363-378. 

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3.8-cm wavelength. The Mm 1017-50. 

6-13 
DESIGN OF PLANT GAS EXCWGE EXPERIMENTS 

IN A VARIABLE PRESSURE GROWTH CHAMBER 

Final Report 

NASNASEE Summer Faculty Fellowship Program--1995 

Johnson Space Center 

Prepared By: 

Academic Rank: 

University & Department 

NASNJSC 

Directorate: 

Dieion: 

Branch 

JSC Colleague: 

Date Submitted 

Contract Number: 

Kenneth A. Corey, Ph.D. 

Associate Professor 

University of Massachusetts 

Dept. of Plant & Soil Sciences 

Amherst, MA 01003 

Engineering 

Crew & Thermal Systems 

Life Support & "hemal Systems 

Daniel J. Barta, Ph.D. 

August 1,1995 

NGT-44-001-800 

7-1 
ABSTRACT 

Sustainable human presence in extreme environments such as lunar and martian 

bases will require bioregenerative components to human life support systems where plants 

are used for generation of oxygen, food, and water. Reduced atmospheric pressures will 

be used to minimize ass and engineering requirements. Few studies have assessed the 

metabolic and devel responses of plants to reduced pressure and varied oxygen 

atmospheres. The first tests of hypobaric pressures on plant gas exchange and biomass 

production at the Johnson Space Center will be initiated in January 1996 in the Variable 

Pressure Growth Chamber (VPGC), a large, closed plant growth chamber rated for 10.2 

psi. Experiments were designed and protocols detailed for two complete growouts each of 

lettuce and wheat to generate a general database for human life support requirements and to 

answer questions about plant growth processes in reduced pressure and varied oxygen 

environments, 

The central objective of crop growth studies in the VPGC is to determine the 

influence of reduced pressure and reduced oxygen on the rates of photosynthesis, dark 

respiration, evapotranspiration and biomass production of lettuce and wheat. Due to the 

constraint of one experimental unit, internal controls, called pressure transients, will be 

used to evaluate rates of C02 uptake, 02 evolution, and H20 generation. Pressure 

transients will give interpretive power to the results of repeated growouts at both reduced 

and ambient pressures. Other experiments involve the generation of response functions to 

partial pressures of 02 and C02 and to light intensity. Protocol for determining and 

calculating rates of gas exchange have been detailed. In order to build these databases and 

implement the necessary treatment combinations in short time periods, specific 

requirements for gas injections and removals have been defined. A set of system capability 

checks will include determination of leakage rates conducted prior to the actual crop 

growouts. Schedules of experimental events for lettuce and wheat are outlined and include 

replications in time of diurnal routines, pressure transients, variable p@, pO2/pCO2 ratio, 

and light intensity responses. 

7 -2 
INTRODUCTION 

Pres such as 

lunar and m 

environment. Establishing an atmosphere for advanced closed life support systems 

involves consideration of requirements suitable for both autotrophs and heterotrophs. 

Human life support includes requirements for oxygen supply and carbon dioxide removal, 

roles served at least in part by plants in advanced life support systems having a 

bioregenerative component. In recent years, large, closed, controlled environment 

chambers have been constructed by NASA for gas exchange and plant growth studies (4, 

10,22,29,3 1,32). 

Optimum gas environments for plants and people may not be the same even though 

the atmosphere of the biosphere has evolved to establish gas compositions which reflect the 

recipricol exchange of oxygen and carbon dioxide. While the atmospheric composition of 

the biosphere is suitable for the survival of both, it is not optimum for all growth and 

development processes. For example, it is well established that the carbon dioxide 

concentration of the biosphere is considerably lower than the level at which photosynthesis 

of plants is saturated (2,6,12,16,18). This knowledge has been applied to crop production 

in greenhouses and other closed environment settings where atmospheres are commonly 

enriched with carbon dioxide to accelerate growth rates. 

Hypobaric Effects 

Hypobaric pressures will likely be used to decrease the mass and engineering 

requirements for establishing and sustaining life support systems at extraterrestrial 

outposts. Recent studies suggest that plant growth may be enhanced at hypobaric 

pressures particularly when com.bined with decreased partial pressures of oxygen 

(1,8,9,11,19,23). At present, it is not clear what may explain effects of hypobaric 

pressure on plant processes, particularly photosynthesis. However, there are two major 

possibilities based on well established physical principles and the current state of 

knowledge in plant metabolism. First, the diffusion coefficient of gases in air increases at 

atmospheric pressures below those of ambient sea level. The relationship is expressed as 

D' = D0(T1/293)m(760/Pl), 

where Do is the diffusion coefficient in air at 293 K and 760 mm Hg in em%, T is the 

temperature in K, Pi is the pressure in mm.Hg, and m is a factor that depends on 

characteristics of the diffusing gas and for Co;! in air is equal to 2. The calculated 

diffusion coefficients in air for C02 and H20V at a range of pressures at 23 C (baseline 

temperature to be used for crop production tests) are presented in Figure 1. Comparing 

ambient sea level press= with the baseline pressure to be used for hypobaric plant growth 

experiments illustrates that the diffusion coefficients for C@ and H20 increases by a factor 

of 1.44 at the lower pressure. Increased rates of C02 diffusion will result in a more rapid 

rate of transport to the site of photosynthesis assuming that stomatal conductance and leaf 

boundary layer resistance also remain unaffected (13). Photosynthetic enhancement 

attributable to increased carbon dioxide diffusivity would be expected to be greater at 

carbon dioxide concentrations well below saturation with the effect becoming negligible as 

7-3 
saturating concentrations are approached. Also, the C02 concentration required to saturate 

Ps is highly dependent on genotype (me 

temperature. Water diffusion at to 

n 

v) \ 

cu 

0 

c 

a> 

0 

a 

1.5 

W 

*-, 

.- 

1.0 

s 

* Water Vapor 

Carbon Dioxide 

2.0 

c 

.- 0 

v) 

= 

D (527)/0(760) = 1.44 

Y- 3 0.5 

n 

0.0 

0 200 400 600 800 

Pressure (mm Hg) 

Figure 1.- Diffusion coefficients of C02 and H20 calculated for a range of 

pressures at 23 C. 

greater rates of transpiration (Ts). Increased rates of Ts with decreasing pressure have 

been reported in several studies (1 1 14,19). Given that the vapor pressure deficit (VPD) is 

held constant at different Pt, it should then be possible ta determine the influence of Pt on 

Ts solely through its effect on D(H2OV). 

A second major possibility for reduced pressure effects relates to the effects of 02 

on plant metabolic processes. If a reduction in atmospheric pressure is accompanied by a 

reduction in the partial pressure of oxygen, other effects may occur considering the range 

of oxygenases that regulate plant metabolism. A well established effect of decreased 

oxygen partial pressure is the decrease in activities of ribulose bisphosphate carboxylaseoxygenase (RUBISCO) and glycolic acid oxidase (12,16). The net effect of the activities 

of RUBISCO and photorespiratory enzymes in C-3 plant species is an increased carbon 

loss which can be lessened at lowered partial pressures of oxygen (15,18,20,21,25,26). 

7-4 
Thus, optimizing productivity of plants also may involve a combination of hypobaric 

pressures and lowered partial pressures of oxygen. In addition, there is an effect of 

lowered oxygen on background or dark respiration @R) (7,8,9,17,27,28) which may 

kther increase the rate of biomass production through decreased carbon loss. Since 

cytochrome oxidase, the terminal electron acceptor in the mitochondrial electron transport 

chain, has a high affinity far oxygen and the stomatal resistance in the light is low, there 

may be only minimal effects on background respiration of shoots in the light at pQ down 

to about 1.5 psi. There may be greater affects of p02 on root respiration depending on the 

nature of the culture medium (e.g. solid matrix, solution culture, nutrient film technique), 

and the density and resistance of the root mass and root surfaces. For certain plant species 

such as wheat and lettuce, which can be grown under continuous light, the dimunition of 

overall, whole canopy DR (shoots and roots) may increase the rate of crop growth. 

However, in some plants there may be intermediates produced at sea level p@ values 

which serve key roles in developmental processes such as seed germination. Perhaps there 

are different PO;? optima for the periods. before and after attainment of photosynthetic 

competence during seedling development. 

Defming Atmospheres 

Given that people and plants have different optima for atmospheric regimes, what 

atmospheres should be generated which would be suitable for an integrated system, and 

alternatively, for isolated systems? The issue of designing appropriate atmopheres for 

people in isolation has been well researched and various regimes have been implemented 

for space missions (Table 1). An open, but perhaps not critical issue in human physiology 

is whether there are any detrimental effects of prolonged exposure to lowered atmospheric 

pressures which are necessarily accompanied by lowered partial pressures of N2. At this 

point, there is no strong evidence to indicate that N2, the major component of the Earth's 

atmosphere, serves any vital long range function in human physiology. 

human Life support is not established for plants, though physiological responses to partial 

pressures of C02 and 02 have been documented. Furthermore, since there is a greater 

genetic diversity to consider for plants than for the human species, responses of individual 

species and genotypes of plants to varied atmospheric conditions are expected to vary more 

widely than responses of humans. Approaches to the problem of defining atmospheres for 

plants could be tailored to the situation. One Scenario is to define those conditions which 

are optimum for growth and development regardless of human needs. It is likely that such 

conditions may not also be suitable to people, necessitating compartment isolation and 

procedures to enable brief periods of human integration with a plant compartment If 

isolation is feasible in future closed environments and if it translates into more efficient 

production of biomass, then implementation may be advantageous. Working from this 

assumption, how is the "best" atmospheric regime for plants determined? There are few 

reports on this subject except for the aforementioned effects of carbon dioxide enrichment 

and lowered partial pressure of oxygen. What effects, if any, will decreased atmospheric 

pressures and decreased partial pressures of oxygen have on rates of biomass production? 

Another approach to defining atmospheres for plants is to assume a regime which 

will be integrated with people. This automatically places contraints on the minimum 

oxygen partial pressure and maximum carbon dioxide partial pressure which can be used 

safely and comfortably. The partial pressure of carbon dioxide which maximizes plant 

A set of gas composition and atmospheric pressure values similar to those for 

7-5 
TABLE 1.- ATMOSPHERIC REGIMES USED FOR HUMAN LIFE SUPPORT IN THE 

U.S. SPACE PR0GRAM.a 

Pressureb 

Program Total @Pa) oxygen (kpd Carbon Dioxide (Pa) 

Apollo 34.5 (5.0) 34.5 (5.0) ------------ 

Skylab 34.5 (5.0) 22.7 - 26.9 (3.3 -3.9) 660 (5.0) 

Orbiter 101.2 (14.7) 20.3 - 23.8 (3.0 - 3.5) 1010 (7.6) 

Orbiter 

Space Station 

(EVAPreP) 70.3 (10.2) 18.3 - 19.3 (2.7 - 2.8) 1010 (7.6) 

Freedom 70.3 (10.2) 68.9 - 71.7 (10.0 - 4.0) 1013 (7.6) 

aadapted from Tables B-1 and B-3 in Wieland, P.O., 1994, pages 184-185 (ref. 33). 

b psi given in parentheses except carbon dioxide where it is mm Hg. 

growth is fortunately well below the defined safety limit for people. The partial pressure 

of oxygen is perhaps considerably higher than what could be established for optimum plant 

growth and would have to be a set condition based on human requirements. However, 

there is considerable latitude in the selection of the total pressure environment, which, for 

safety issues, would involve the use of a diluendquenching gas such as nitrogen or helium. 

During the Skylab missions, the atmosphere consisted of an oxygen partial pressure of 160 

mm Hg and 90 mm Hg nitrogen, with carbon dioxide maintained below about 5 mm Hg. 

The oxygen level was the same as ambient sea level, but the reduced nitrogen gave a total 

pressure environment of about one-third atmosphere with no documented deleterious 

effects on human health for a mission that lasted nearly three months. A reduced pressure 

database for plants needs to be developed which will include conditions that meet the goal 

of optimizing plant productivity and conditions which would also be suitable for human life 

support. 

Variable Pressure Growth Chamber 

The first tests of hypobaric pressures on plant gas exchange and biomass 

production at the Johnson Space Center will be initiated in January 1996 using the Variable 

Press= Growth Chamber (VPGC) with tests of chamber and subsystem function 

beginning in September .1995. The VPGC, which is rated for a 10.2 psi pressure 

atmosphere and has a growth area capability of 11.2 m2 (4) will be used for two complete 

growouts each of lettuce (Luctuca sativa Waldmann's Green') and wheat (Triticum 

aestivum 'Yecora Rojo' or a new dwarf genotype, 'Utah-20-1-41'). A primary objective 

of these experiments is to determine the effects of subambient pressure on gas exchange 

7-6 
and yield of plant species selected as candidate crops for the Controlled Ecological Life . Support Systems (CELSS) program. The mass balance of metabolic 

important for matching plant requirements and reso 

humans (3). A set of values for the key environmen 

be established and at specific stages of development, 

answer specific questions about gas exchange resp 

environment. A peripheral, but important issue related to plant growth in closed 

environments is the evolution of volatiles which may accumulate to physiologically active 

levels. The plant volatile and hormone ethylene, is of special concern because of its wi& 

range of metabolic effects. Since the synthesis and action of ethylene are dependent on the 

partial pressure of oxygen, ethylene concentration will be measured routinely and will be of 

particular interest in the context of variable p@ experiments. 

Large scale experiments in growth chambers or in chambers designed as prototype 

CELSS have been concerned mainly with defining and implementing environmental 

conditions considered optimum for plant growth. Growouts of specific crops may also 

involve the conduct of experiments to characterize gas exchange responses to light, carbon 

dioxide, temperature, and vapor pressure deficit. The VPGC presents the opportunity to 

conduct similar experiments at subambient pressure. Unique to the scale of this chamber 

and a pertinent focus to experiments conducted during VPGC growouts will be the use of 

different partial pressures of oxygen. 

OBJECTIVES 

A. Database 

The following objectives relate to the overall goal of developing a database on crop 

gas exchange and biomass production for advanced closed life support systems using the 

VPGC as a tool. 

1. Determine gas exchange rates (Le. Ps, DR, and Et) of lettuce and wheat 

2. Compare biomass production and rates of gas exchange in hypobaric and 

3. Develop photosynthetic response functions for light intensity (PPF') and 

4. Determine changes in concentration of ethylene in the atmosphere during crop 

throughout growth and development. 

ambient pressure environments. 

carbon dioxide concentration. 

development. 

The following is a lit of questions relevant to issues of plant processes and 

B. Investigative 

growth in closed li€e support systems and can be addressed on a large scale plant canopy 

using the VPGC as an experimental unit. 

1. Does hypobaric pressure enhance photosynthesis and biomass 

production of lettuce and wheat? 

2. Are rates of gas exchange (Le. Ps, DR, and Et) influenced by total 

atmospheric pressure and by partial pressure of oxygen? 

3. What are the physiological explanations for any observed effects on gas 

exchange? Attempts will be made to make distinctions at the 

crop canopy level between metabolic and physical possibilities. 

4. Are there interactive effects of partial pressures of oxygen and carbon 

dioxide on gas exchange rates, i.e. is net photosynthesis a function of the 

7-7 

po2/pco2 ratio? 
EXPERIMENTAL PROTOCOLS 

Baseline Conditions 

Baseline environmental condi reports experiments in plant growth chambe 

the VPGC for maintaining reduced atmospheric pressure (Table 2). capabilities of 

TABLE 2.- BASELINE CONDITIONS FOR CROP PRODUCTION 

TESTS IN VPGC. 

Environmental 

Condition Lettuce wheat 

Pressure (psi)a 10.2 

Oxygen (psilb 2.1 

Carbon dioxide @mol/mol) 1200 

Temperature (C) 23 

Dewpoint temperature (C)C 17.5 

Photoperiod (lighddark) 18/6 

PPF (pmol/m2/s) 400 

10.2 

2.1 

1200 

23 

17.5 

20/4 

1500 

aPressure given is for first growout of each crop; the second growout will 

bpartial pressure of 02 given is for first growout with the second growout 

CA dewpoint temperature was selected to give a relative humidity of 70%. 

use 14.7 psi as the baseline. 

to be set at 3.1 psi. 

The following sections are the categories of experiments and types of data to be 

compiled for the two growouts of lettuce and wheat. 

Diurnal Routines 

Each day, measurements of net photosynthesis (Ps), dark respiration (DR), and 

evapotranspiration (Et) will be ma& and continued throughout growth and development. 

Sensitive measurements of rates of Co;! uptake will probably not be possible until 

following the completion of the germination process (several days after planting). Since 

there will be lighddark cycles used and no attempt at CQ removal will be made, the DR 

measurement will be obtained from the slope of the liar increase in Cq2 concentration 

that occurs following lamp shutdown. It is assumed that DR is constant over the range of 

C02 concentrations that develop. After the lights are turned on the Co;! will decrease 

linearly until the setpoint value of 1200 ppm is achieved. This is referred to as the diurnal 

rawdown. While the Ps drawdown method of measurement is not steady 

e concentration of 1200 pmol/mol is close to saturation of Ps at the 

SYn 

the 

7-8 
specified light intensity, is linear, and is therefore a reliable daily rate meas 

(unpublished data). A supplementary method for measuring the photosyn 

achieved for the complete light period by tracking the absolute quantity of C02 injected to 

maintain the setpoint. This is equivalent to the amount of C@ used in Ps plus the quantity 

leaked from the chamber during the time of measurement. The numbers obtained are 

referred to as GO2 mass flow measurements and are considered a steady state method of 

measurement. Leakage tests performed prior to and following each crop test will be used 

to apply corrections to calculations made for any long term meaurements (Le. those 

exceeding a couple hours). It is anticipated that the leak rate, particularly at the subambient 

pressures, will be small enough (i.e. < 5 %/day) to assume a negligible loss for short term 

(e1 hour) rate calculations. Oxygen concentration during the light phase will be maintained 

at the established setpoint and quantities tracked by continual scrubbing with a molecular 

sieve. Accounting of the oxygen removed during the photoperiod by the molecular sieve 

will also serve as a supplementary method of Ps rate measurement and will be compared 

with the C@ mass flow data. It may be possible to use the two measurements to calculate 

an assimilation quotient for Ps (C02 uptak402 evolved). 

Daily measurements of water flux will also be made for both light and dark 

components of the daily cycle. The light measurement actually represents a combined 

evapotranspiration (Et) value. It will not be possible to separate the two components 

precisely since the energy budgets differ and a finite, but perhaps small stomatal 

conductance can be measured during the dark period. An estimate of evaporation will be 

obtained in the pretest checkouts by running the system at test conditions without plants. 

Pt Transients 

Since the baseline pressure used is 10.2 psi, it will be necessary to compare 

measurements of gas exchange rates with those conducted at ambient pressure (see 

objectives A.2 and B. 1). The constraint of one experimental unit and limited replications in 

time pose an interpretive challenge. Therefore, short-term rate measurements at several 

stages of development will be made. For the first growout of each crop, the pressure 

transients will be ambient pressure and for the second growout of each crop where the 

baseline atmospheric pressure is ambient, the pressure transients will be conducted at 10.2 

psi. It will also be necessary to vary the partial pressure of 02 during the pressure transient 

experiments. Both the reduced and normal sea level ambient partial pressures of 02 will be 

used. These short term experiments will be used as an aid to interpretation of biomass 

production results and for establishing the extent to which overall rates of plant metabolism 

can be altered by Pt and pe. Pure N2 and 02 will be injected to establish increased partial 

pressures and total atmospheric pressures. The vacuum pumps and a method for 

removal (molecular sieve) will be used to reduce levels back to baseline or to change 02 

(for variable 02 experiments). The pressure transients may be summarized as follows: 

Growout I (baseline Pt=10.2 psi) - Pt=14.7 psi, p02=3.1 psi and Pt=14.7 psi, p02=2.1, 

and Growout II (baseline Pt=14.7 psi) - Pt=10.2 psi, p02=2.1 psi and Pt=10.2 psi, 

pO2=3. lpsi. 

Variable 

Crucial to defining the optimum atmospheric environment for plant growth is the 

7-9 
detemination of partial pressures of 02 that will maximize Ps and minimize background 

respiration OR). An experiment with variable partial pressure of 02 will be conducted 

over the range of 1.1 psi to 3.1 psi using 5 levels for the light period measurements. Due 

to the constraint of a short dark period, only 2 levels of pa will be used during the dark 

period. Within each experiment, the appropriate ambient pressure treatments (like those 

mentioned in the Pt transients section) will be used as internal controls. A sample protocol 

for the Ps measurements is illustrated in Figure 2; the exact order of the 8 separate 

measurement periods randomized for each run of the same experiment. ?he zero-slope 

portions of the figure represent the quasi-steady state measurements of C@ mass flow 

injections. A fifteen-minute period for total and partial pressure changes is shown and is 

close to the time limit constraint for changes necessary to complete the set of treatments. 

Mass flow of C02 will be tracked at intervals no greater than 5 minutes in order to establish 

sufficient time segments for strong statistical estimates of rates. For the dark period 

experiment, C02 will increase and then the starting value of 1200 ppm reestablished using 

a C@ removal system (LiOH) or a photosynthetic drawdown prior to beginning the next 

treatment. A sample protocol and example of a hypothetical result are shown in Figure 3 to 

4 

3 

2 

1 

Oxygen Partial Pressure 

Total Pressure 

-...--...-. 

0 

0 120 240 360 480 600 

Time (min) 

15 

14 

13 

z 

U 

12 ; 

L 

11 

2 

10 e - 

ca 9- 

8 

7 

6 

Figure 2.- Example of treatment protocol for the variable oxygen experiments in 

the VPGC during the light period. 

7- 10 
a 

x 

0 

z 

5 

0 

1: 

0 

I 

€ 

€ 

W 

1300 

Carbon Dioxide 5 ...I............. 

1180 

f! 

8 1160 

0 100 200 300 400 

Time (min) 

3.2 

3.0 5 

v 

n 

2.8 2 

2.6 $ 

a. 

=I 

cn 

2.4 3 .- 

Y 

L 

2.2 nm 

c 

a, 2.0 9 

5 1.8 

1.6 

Figure 3.- Sample protocol and example of hypothetical results to illustrate experiments for 

illustrate the treatment sequence and possible effects. Also, tracking of water flux for both 

light and dark experiments would be desirable to determine if the treatments influence 

evapotranspiration. Given that water vapor pressure deficit is held constant, any treatment 

effects on Et will likely be attributable to effects on stomatal conductance. 

measuring dark respiration during application of different treatment atmospheres. 

po2/pco2 Ratio 

Possible p02 effects on the rate of Ps may actually be attributable to the ratio of 

oxygen to carbon dioxide. This experiment will enable the generation of photosynthetic 

response functions to C@ concentration at two levels of p02 (2.1 and 3.1 psi). Control of 

C@ will be disabled and the C02 allowed to decrease (photosynthetic drawdown). 

Drawdowns to the C@ compensation point, while desirable for generating a complete 

function, can take several hours and may result in a substantial decrease in the free 

carbohydrate pool. The latter effect may influence how the crop canopy is in turn affected 

7-1 1 
by a subsequent change in the p02. The photosynthetic response curve can be 

.characterized down to about 200 ppm C02 fairly quickly (Le. 60-90 minutes) without a 

major change in the free carbohydrate pool. The method just described is nonseady state 

and may not be representative of the internal conditions and time necessary for true 

photosynthetic steady state to be achieved. Stomatal conductance is strongly dependent on 

C@ concentration and the VPGC has a rather tight configuration (Le. volume to area ratio 

= 2.4). Therefore, a steady state experiment will be conducted and mas flow 

measurements used to calculate the rate of Ps at different C02 concentration setpoints. If 

the two methods do not provide consistent results, then a more time-consuming steady state 

method (Co;! setpoints and mass flow measurements) will be used. 

Light Intensity Response Function 

A routine experiment in constructing gas exchange databases for plants is to 

determine the photosynthetic response to light intensity (PPF) in the photosynthetically 

active radiation (PAR) waveband (400 - 700 nm). For lettuce, a reduced baseline light 

intensity is necessary to minimize the risk of tipburn, a condition exacerbated by controlled 

environment growth using solution culture or nutrient film techniques. However, given the 

potential responses to low pressure and decreased partial pressure of oxygen and the 

potential for accelerating generation or C@ removal, it will be of interest to determine 

the photosynthetic response to light intensity for differing atmospheric conditions. This 

can be achieved by conducting an experiment using at least 2 light intensities (baseline and 

a higher value) in combination with the 2 Pt levels and 2 pO2 levels as described in the 

protocol for the variable oxygen experiments. Some exploratory work will be necessary to 

determine appropriate PPF values to use in combination with the atmospheric treatment 

variables. The procedure will involve short duration (30 min) drawdowns of C02 and 

calculation of the rate of Ps from the slopes of the line segments (10). For wheat, a 

photosynthetic response is anticipated throughout the light range capability of up to 1500 

pmol/m2-s. This response function will be generated by dimming the lamps to achieve 

PPF values in the range of 250 to 1500 pmol/m2-s in steps of approximately 250. The 

light compensation point will be calculated as the x-intercept from the fitted function. As 

with the lettuce, an experiment will be conducted to determine if light saturation varies with 

growth cycle at which they will occur are summarized in Tables 3 and 4. 

pt and Po2. 

A schedule of experimental events for each crop and the estimated times in the 

TEST REQUIREMENTS 

The conduct of experiments outlined and discussed in this report require changes in 

total pressure and in partial pressures of individual gases in the atmosphere. The required 

changes must be accomplished in certain time periods in order to impose all necessary 

atmospheric treatment regimes. The types of changes, methods of implementing the 

changes, and method capabilities are summarized in Table 5. 

Leak Rate Tests 

Experiments outlined in this report involve the determination of steady-state and 

7- 12 
nonsteady-state rates of consumption and evolution of metabolic g 

environment. These measurements are based upon changes in con 

upon quantities injected to maintain a constant concentration. For tune mc 

than a couple hours or for measurements integrated over days, calculations will 

knowledge of the rate of leakage of the gas of interest from or into the system. Leakage 

rates of C02 and C2H4 from the VPGC will be determined with the chamber in full test 

mode with the exception of plants. Individual gases will be injected and samples taken 

from the inside air and the external ambient atmosphere to determine the concentration 

gradient. The leak rate may be calculated from the formula, 

where L is the leak rate in %/day, t is time, C1 is the concentration of the gas at t2, C1 the 

concentration of the gas at ti, and camb the concentration of the gas in the ambient 

atmosphere (30). In conducting the test, sufficient time should be allowed after injecting 

C@ and C2H4 for equilibration with the chamber environment as the gases will dissolve 

in water, the seals, and perhaps other materials. 

REFERENCES 

1. Andre, M., and D. Massimino. 1992. Growth of plants at reduced pressures: 

experiments in wheat-technological advantages and constraints. Adv. Space Res. 

2. Acock, B., V.R. Reddy, H.F. Hodges, D.N. Baker, J.M. McKinion. 1985. 

Photosynthetic response of soybean canopies to full-season carbon dioxide 

enrichment. Agron. J. 77: 942-947. 

3. Barta, D.J., J.S. Dominick, and M. Kallberg. 1995. Early human testing of advanced 

life support systems, phase I. Society of Automotive Engineers Tech. Paper 95- 

4. Barta, D.J. and D.L. Henninger. 1995. Johnson Space Center's regenerative life 

support systems test bed. Adv. Space Res. (In press). 

5. Bugbee, B.G. 1990. Exploring the limits of crop productivity: a model to evaluate 

progress. Pages 1-23 in R.D. MacElroy, ed. Controlled Ecological Life Support 

Systems: CELSS '89 Workshop. NASA technical memorandum 102277, Moffett 

Field, CA. 

6. Bugbee, B.G. and F.B. Salisbury. 1988. Exploring the limits of crop productivity. 

7. Chun, C. and T. Takakura. 1993. Control of root environment for hydroponic lettuce 

production - rate of root respiration under various dissolved oxygen concentrations. 

American Society of Agricultural Engineering Paper No. 934040. 

8. Corey, K.A., M,E. Bates, and S.L. Adams. 1995. Carbon dioxide exchange of lettuce 

plants under hypobaric conditions. Adv. Space Res. (In press). 

9. Corey, KA. 1994. Carbon dioxide exchange of lettuce in decreased pressure 

atmospheres and different diluent gases. NASAlASEE Summer Faculty Fellowship Final Report. 

12: 97-106. 

1490, July 10-14, 1995. 

Plant Physi0l.88: 869-878. 

7-13 
10. Corey, KA. and R.M. Wheeler. 1992. Gas exchange in NASA's biomass 

production chamber: A preprototype closed human life support system. Bioscience 

11. Daunicht, H.J. and H.J. Brinkjans. 1992. Gas exchange and growth of plants under 

reduced air pressure. Adv. Space Res. 12: 107-1 14. 

12. Ehleringer, J.R. 1979. Photosynthesis and photorespiration: Biochemistry, 

physiology, and ecological implications. HortScience 14 2 17-222. 

13. Gale, J. 1972. Availability of carbon dioxide for photosynthesis at high altitudes: 

theoretical considerations. Ecology 53: 494-497. 

14. Gale, J. 1973. Experimental evidence for the effect of barometric pressure on 

photosynthesis and transpiration. In: Plant Respnses to Climatic Factors, 

Proceedings of the Uppsala Symposium, UNESCO, Paris, pp. 289-294. 

15. Gerbaud, A. and M. Andre. 1989. Photosynthesis and photorespiration,in whole 

plants of wheat. Plant Physiol. 89: 61-68. 

16. Govindjee, ed., 1983. Photosynthesis, VoZ 11: Development, Carbon Metabolism and 

Plant Productivity. Academic Press, Inc., New York. 

17. Musgrave, M.E., W.A. Gerth, H.W. Scheld, and B.R. Strain. 1988. Growth and 

mitochondrial respiration of mungbeans (PhcrseoZus aureus Roxb.) germinated at 

low pressure. Plant Physiol. 86: 19-22. 

18. Musgrave, M.E. and B.R. Strain. 1988. Response of two wheat cultivars to C@ 

enrichment under subambient oxygen conditions. Plant Physiol. 87: 346-350. 

19. Ohta, H., E. Goto, T. Takakura, F. Takagi, Y. Hirosawa, and K. Takagi. 1993. 

Measurement of photosynthetic and transpiration rates under low total pressures. 

American Society of Agricultural Engineering Pdper No. 934009. 

20. Parkinson, K.J., H.L. Penman, and E.B. Tregunna. 1974. Growth of plants in 

different oxygen concentrations. J. Expt. Bot. 25: 135-145. 

2 1. Poskuta, J. 1968. Photosynthesis, photorespiration, and respiration of detached 

spruce twigs as influenced by oxygen concentration and light intensity. Physiol. 

22. Prince, R.P., and W.M. Knott, J.C. Sager, and S.E. Hilding. 1987. Design and 

performance of the KSC Biomass Production Chamber, Society of Automotive 

Engineers Technical Paper Series No. 87 1437, Warrendale, PA. 

23. Rule, D.E. and G.L. Staby. 1981. Growth of tomato seedlings at sub-atmospheric 

pressures. HortScience 16: 33 1-332. 

24. Salisbury, F.B., and B.G. Bugbee. 1988. Plant productivity in controlled 

environments. HortScience 23: 293-299. 

25. Siegel, S.M. 1961. Effects of reduced oxygen tension on vascular plants. Physiol. 

Plant. 14 554-557. 

26. Taylor, D.L. 1942. Influence of oxygen tension on respiration, fermentation and 

growth in wheat and rice. her. J. Bot. 29:721-738. 

27. Thimann, K.V. 1954. The physiology of growth in plant tissues. Am. Scientist 

28. Thornley, J.H.M. 1970. Respiration, growth and maintenance in plants. Nature 227: 

29. Wheeler, R.M. 1992. Gas exchange measurements using a large, closed plant growth 

chamber. HortScience 27:777-780. 

30. Wheeler, R.M., J.H. Drese, and J.C. Sager. 1991. Atmospheric leakage and 

condensate production in NASA's Biomass Production Chamber. Effect of diurnal 

42 503-509. 

Plant. 21: 1129-1136. 

42589-606. 

304-305. 

7- 14 
Science 33: 161-168, 

32. Wheeler, RM., C.L. Mackowiak, J.C. 

33. Wieland, P.O. 1994. Desig 

Environmental Control 

CELSS 

W02) 

DcH2Ov) 

DR 

Et 

Hb 

Pr 

Ps 

pt 

KO2 

PN2 

m 

PPF 

Ts 

VPD 

VPGC 

ACRONYMS, ABBREVIATIONS, & SYMBOLS 

Controlled Ecological Life Support Systems 

Diffusion coefficient of carbon dioxide 

Diffusion coefficient of water vapor 

Dark Respiration 

Evapotranspiration 

Hypobaric 

Photorespiration 

Photosynthesis (net) 

total pressure of atmosphere 

partial pressure of carbon dioxide 

partial pressure of nitrogen 

partial pressure of oxygen 

photosynthetic photon flux 

Transpiration 

vapor pressure deficit 

Variable Pressure Growth Chamber 

7-15 
Test Day ActivitiedExperiments 

1-8 

9 Gas exchange measurementsb 

10- 14 Stand estabIishment/Daily routinesc 

1s 

16 Pressure transient experiment (light) 

17 Variabfe p@ experiment 

Germination and seedling establishmenddark respiration measurementsa 

Daily routines/Pressure transient experiment (dark) 

18 Ps response to C02 at 2 p02 (drawdowns) or p@:pC02 ratio experiment 

19 PPF experiment at 2 p@ 

20-2 1 

22 

23 

24 

25 

26 

27 

28 

Daily routine 

Daily routines/Pressure transient experiment (dark) 

Pressure transient experiment (light) 

Variable p@ experiment 

Ps response to C02 at 2 p02 (drawdowns) or p@:pCO2 ratio experiment 

PPF experiment at 2 POI;! 

Daily routine 

Daily routine/Return to ambient Pt .. measure ratedHarvestd 

aRes@ation rate measurements duxing germination will be possible by about day 2 or 3. 

bEsQmate of day for obtaining reliable Ps and Et measurements. 

cDaily routine includes measurements of Ps, DR, and Et at baseline conditions. 

dDay of harvest is estimate. 

7- 16 
TEST ACTIvlTIES FO 

Test Day Ac t 

1- 4 

5 

6- 14 

15 

16 

17 

18 

19 

20-21 

22 

23 

24 

25 

26 

27-35 

36-40 

41-42 

43-47 

48-64 

Gemination and seedling estabkhment/Dark respiration measurementsa 

Gas exchange measurement& 

Stand establishment/Daily routinesc 

Daily routines/Pressure transient experiment (dark) 

Pressure transient experkent (light) 

Variable pq2 experiment 

Ps response to C02 at 2 p02 (drawdowns) or p@:pCO2 ratio experiment 

PPF experiment at 2 PO;! 

Daily routines 

Daily routines/Pressure transient experiment (dark) 

Pressure transient experiment (light) 

Variable PO;! experiment 

Ps response to C02 at 2 p02 (drawdowns) or pQ:pCO2 ratio experiment 

PPF experiment at 2 PO;! 

Daily routinesd 

Repeat of experiments conducted days 15-19 and days 22-26 

Daily routines 

Repeat of experiments conducted days 36-40 

Daily routinae/Retwn to ambient Pt - measure rates/Harvestf 

aRespiration rate measurements during germination will be possible by about day 2 or 3. 

bEstimate of day for obtaining reliable Ps and Et measurements. 

7- 17 
CDaily routine include 

growth and development which 111 

bay of harvest is estimate. 

TABLE 5.- TEST REQUIREMENTS TO IMPLEME 

IN THE VPGC DURING PLANT GROWTH 

PHEHC CHANGES 

Atmospheric Direction Chanve Method 

Change ofchange Minimum Maximum Method Capability 

pt increase 4.5 psi 4.5 psi injection a1OOO ltmin 

decrease 4.5 psi 4.5 psi vacuum b2000 lts 

Po;! increase 0.5 psi 2.0 psi injection a1000 ltmin 

decrease 0.5 'psi 0.5 psi Rs variable 

vacuum& b2()01ts 

injection a1000 ltmin 

maintenance molecular sieve C2 ltmin 

increase o - 10 ppm 1000 ppm injection d 3 - 30ooo 

cm31min go;! 

decrease 0-100ppm 1OOOppm Ps variable 

LiOH e?4 mmoltmin 

inCRaSe 0.5 psi 4.5 psi injection a1000 ltmin PN2 

decrease 0.5 psi 4.5 psi vacuum b2000 us 

PH20V increase maintenance mist injection 

decrease maintenance heat exchanger 

cold H20 coils 
' Investigation of Two-Phase Flows in Piping Bends and Elbows 

. FinalReport 

NASNMEE Suqner Faculty Fellowship Prograin - 1995 

Johnson Space Center 

Prepared By: Allen B. Duncan, PbD., Assistant Professor 

Vincent M. Sciascia, Graduate Research Assistant 

Universitjl and Department: .Universii of Illinois at Chicago 

Department of Mechanical Engineering 

..WC 251, Room 2039 ERF 

842 W. Taylor St. . 

Chicago, IL 60607-7022 

NASMJSC 

Directorate: 

Division: 

Branch: 

JSC Colleague: 

Date Submitted: 

Contract Number: 

Engineering 

Crew and Thermal Systems 

EC3 

Kathryn LM. Hurlbert 

. August9,1995 

NGT-44-001300 

8-1 
Abstract 

An &perimentd investigation of the hydrodynamic charactwistics of two-phase R-113 

,flow has been cgried out.' Straight tube pressure drop data, as a hnction of mass flow 

. rate (mass flux) and flow quality has been obtained using the Two-Phase Flow Test 

Facility located h the Advanced Therd-L;;boratories of the Crew and Thermal Systems 

Division at .the Lyndon k. Johnson Space Center. Additionally, after successllly 

obtaining the straight rube pressure drop data, the test facilty was m'bdified in order to 

obtain pressure drop data for the flow of two-phase R-113 through 180" piphg bends. 

Inherent instabilities of the test facility prevented the successfiil acquisition of pressure 

drop data through the piping bends. 

The experimental str&ght tub data will be presented and compared with existing 

predictive conelationi in aa attempt to gain iasight into the utiiity of such correlations as 

the basis for developing design criteria. A discussion of the htab%ties which rendered 

suaessfbl aquisition of the piping bend data win be presented and suggestions will be 

made for eliminating these system tendencies. Finally, recommeDdatons for he 

investigations, based on successfiri reconfiguration of the test facility, WElt be made. 

8 -2 
Introduction 

Power requirements for spacecraft and satellites continue to increase, necessitating similar 

increases in the effeGtiveness and efficiencies of sjia&cr& thermal management systems. 

Aciive two-phase cooling loops have been identified as systems.which may satisfy the 

requirments of fbture spaceflight themat control qstenk; . However, archivai literature 

documenting both experimental and analytical Snvestigations- of the pressure gradient 

characteristics of two-phas6 Bow through piping bends and elbotvs, -such as those which 

wiU be inchxkd ki realistic system designs, is virtually- non-ezdstent. The current 

investigation wilt obtain baseline data far the two-phase flow test facility developed by the 

Crew and "hemal Systems Division. Additionally, the investigation will obtain data 

which wiu help characterize the pressure drop characteristics of two-phase flows through 

180" piping bends. This iwestigation will compliment and support the TEEM flisht 

experimrent !tche&td for laamch;in-1997. 

During the sumzlper pelid an experimental investigation of the hydrodynamic 

chcterhtics of two-pb flows similar to those which would occv11: in the twephase 

active thermal control systems (ATCS) of a-space vehicle was undertaken. This 

investigation represents the &st step of 8 10% term effort which will develop 

mahmatid dels and experimental data for the prediction of the pressure drops which 

my be expected fbr two-phase flow through realistic systems which inchrde piping 

efbows, expanding and ccmmcmg * flow scetim, and cornmoe utilized devices such as 

quick- fdngs. 

Experiments! kvcstigstion 

charactedaion of the curred imdgation is illusbated f Ftg; 1. The R-113 entd the 

positive displacement pump as Singtccphase liquid. The singla-phase liquid was pumped 

through the evaporator section which consisted &a circulation heater where heat input 

could induce partial vaporization of the Bowing R-113. The liquid or two-phase mixture 

which exited the evaporator don could be obmed in the flow visualization section in 

order to JlaraGterize the -of the two-phase or &+phase flow. Downstream of 

the visvatization section, the'fhid passed tbrmgh the pressure drop test section. Tbis 

ptessure drop test section atlowed the operata to choose citber a low raqIEe @ara;tron) or 

aigh range (v~~) pressure tnrnsduca fbr the meammma of tht pFessure drop in the 

test section. The panmeten which were direcdy varied in the investigation 

were those'ofpump power input (controhg mass flow rate or mass bc) and evaporator 

input power (CmtrOEng flow quality). In this manner, the pFessute drop in the straighttube seaion -was measured as a fitnction of both mass flow rate (mass &rx) and flow 

quality. The two-phase test facitity was used in conjunction with a PC based data 

acquisition system for the recording and procasing of each measured value obtained from 

system insmunentation. 

Strtight Tube fwestigadoa 

A Of the tw0-m flaw test fhcility utitized'fbt.the sbaigfib-tube flow 

8-3 
. - Fig.'l Schematic-of Test Facility 

Figure 2 illustrates the measured pressure drop in the straight tube Section for single phase 

R-113 liquid. while the measured values of pressure drop Consistently exceed those 

which are predicted using the Blasius Solution' , the trend exhiifled was quite uniform, 

with the mean of the measure vaIues exceeding the prediction by approximately 0.075 kPa 

for virtuaUy the entire range offlow rates. Possible reasons for this steady state error are 

the presence of roughness in the tubes or a pressure drop due to the fittings present at 

each pressure tap and each end of the tube. This data indicated that for single phase flow, 

the measured values obtained from the test facility were aweptably accurate and 

repeatabie. 

8-4 
1.4 T 

Pressurqr‘Drop Vs. Mass Flow Rate, Single Phase Liquid , 

5 25 

Fig. 2 ‘ Sin@ Phase Straight ”ube Pressure Drop, Data and Predictive Correlations 

’ Figure 3 illustrates the measured presaue drop in-the straight tube seaion fir two-phase 

R-113 flow iubjected to evapomor input levels which produced a flow quality of 2po/,. 

The data was compared with four predictive correlations, each of these empirically 

developed. ”be first of these was tbat of Lockbrt ad Martin&2, utilizing the fretion 

fictor associated with the ~lasius solution’. %comityj the prediction of Lockhart and 

mew2 was used with their recommended Hcstion actor. The third predictive 

Gonelation UtiEiZed fbr comparisoa was that of Tromd and Uibrkh3. FW, the 

predictive wrrMon O~BUOZCY* was utiiizd While the trend oftbe observed data was 

rates, each of the three correlatons predicted pressure drop vahres which were greater 

than those which were measured. 

consistent with those of the predictive correlations the IWlgGOf masS flow 

8-5 
Straight Tube Pressure Drop Vs Mass Fiow Rate, Quality = 20% 

- LOCkhWt8MartinsUi-8bEiur 

~&~ 

Tmnlrwr#&Ubfldl 

-I 

mmm 

0 Damsaltt 

Q wasdm 

8 13 23 28 

Fig. 3 Straight Tube Pressure Drop Vs. Mass FIow Rate, Qt;;lfity = 20% 

Figure 4 illustrates the measured pressure drop in the straight tube section fin: two-phase 

R- 1 13 flow subjected to evaporator input levels which produced a flow quality of 30?! as 

well as the corresponding predictive wrreiations. As obd in Fig. 3, each of the 

corrciations produced a prediction of pressure dmp which was grerrter than tha! observed 

-. The most sigdkant diffkrence between Fs 4 and Fig. 3 is that the 

predictive cmehticm which utifized the Bbius S** *don hor with the 

prediction of Lockhatt and Martin&* demonstrated a Sipifhut "Enyp" at the transition 

to turbulent flow of the K-113 liquid in the two-phase flow. The predictive correlation of 

Troniewski and Ulbrich3 yielded the closest agreemeat with the measured values 

Figure 5 illustrates the measured and predicted pressure drop dues for two-phase flow 

having a Quality of 40%. white two of the conelations, that of Troniwski and Ubrich3 

and that of Lockhart and Martinesli2 match both the trends and values of the m=ed 

data, this my have been simply because it is at this quality vatue that the ftuctuation in 

measured mass flow rate became quite significant. At this quality due, ffuctuations in the 

measured value of the mass flow rate were as great 8s f 15%. While this fluctuation 

ocuxrred in the measured value, the trends of the! data d-4 in Fig. 4 indicate that 

there was little effect on the measured pressure drop vdues lying within the "high end" of 

8-6. 
zhe range of data. However, for the measured pressure drop values lying within the low 

end of the data ( < 8 Wa), the uncertain fluctuation in mass flow rate appeared to be 

accompanied by an unce@n fluctuation in the measured pressure drop value. 

Pressure Drop YS Mass Flow Rate, 1036 Quality 

Fig. 5 Straight Tube Pressure Drop Vs. Mass Flow Rate, Quality = 40% 

8-7 
Figures 6 9 illustrate the measwed and predicted pr&que.drop vdues for two-phase 

flows having qualities of SO%, 60%, 70%, and 80%, res. 

that -as flow qudity 

dues which were si 

which was that of the predictive conefations yielding pressure 

measuredexperimentany. 

4 

Tube Pressure hop Vs. Mass Flow Rate, Quality = 50% 

8-8 
.. Straight Tube Pressu fop Vs Mass Flow Rate, Quality 18 T 

16 - 

14 

4 

- %==Y 

10 12 14 16 .18 20 P 

- 2/ 0. 

-8 

h Mt (@8) 

0 8- 

I 

24 

Fig. 7 ! Straight Tube Pressure Drop Vs. Mass Flow Rate, Quatity = #A 

Straight Tube Pressura Drop YS Mass Flow Rat% Qualii = 70% 

18 T 

-B;rmcy 

18 28 22 24 0 

12 14 16 IO 

'1 

8 

M8UFkwR.htgh) 

Fig. 8 Straight Tube Pressure Drop Vs. Mass Flow Rate, Quality = 70% 

8-9 
10 

14 

'iii 12 

4, 

E '* 

f". 

4 

.- 

&e : - 

Straight TubePressure-Drop vs Mass FI 

8 

Fig. 9 Straight Tube Pressure Drop Vs. Mass Flow Rate, Quality = 88% 

Investigation of Two-Phase Flow Through Piping Beads 

The test faciIity was modified in an attempt to obtain presnp drop idormation for flow 

through 180' bends,- as iliustrated in Fig. 10. Ur6omuately, this attempt was not 

successll. The lack of success is primarily due to two.different system design 

characteristics. Fii, it was concluded that fluctuations mass flow (and therefore quality) 

due to percolation in the evaporator section produced random changes in system pressure 

which were greater in magnihrde than those measured across the tubing bend. Second, the 

configuration of pressure transducers prescn'bed for &e system did not ailow for 

accurately and repatably obtaiaing pressure drop data across the tubingbend. 

- 

8-10 

flux values should eliminate the occurrence of percolation. Additionally9 replacing the 

current flat plate orifice flow meter with a rotor-type flow meter may reduce the noise 

level associated with the signal delivered to the data acquisition system. 

Beyond reconfiguration ef€oks for the two-phase test faCLity, several investigations should 

be undertaken. Certainly, the first of these should be to complete a comprehensive 

investigation of the pressure drop characteristics of two-phase flows through the 186'' 

bends of -the modified f%@ity. Investigations lltilizing various refrigerants, mass flux 

values, and tubq diameters should be bndertaken. AdditionaUy, investigations of the 

pressure drops measured through quickdisconnects and other fittings, as well as tubiig 

expansions, contractions, and manifolds should follow. Each of tbis experimental 

investigatons should be coupled with rigorous analysis of the obwed phenomnena. 

8-12 
References 

1. Blaiius, H., “Grenzschichten in Fliissigkeiten mit kleiner Reibung,” Z. Mafh. -Phy.s., 

Vol. 56, 1908, p. 1; also NACA TM 1256. 

‘2. Lockhart; R. C., and Martinelli, R. W., .“Proposed ‘Correlation of Data for 

Isothermal Two-Phase Two Component Flow in Pipes,’? Cheh. .Eng. Prog, Vol. 45, No. 

- 1, pp. 39 - 48, 1949. - .- 

3. 

Channels,” Chem. Etigr. Sci., Vol. 39, No. 4, pp. 751-765. 

Troniewski, L., and uibrich, R., ‘Two-Phase Gas Liquid Flow in Rectangular 

4. 

fig=. Prog. Ser., Voi 64, pp. 232-219: - 

Baroczy, C. J., “A Systematic Correlation for Two-Phase Pressure Drop,” Chem. 

’. 

5. Chisolm, B., “Brief Communications - Two-Phase Row in Bends,” Znt. .I. 

Midtiphe FlmU, VO~. 6,August, 1980, pp. 363-367. 

8-12 
A VELOCITY DIS UTION MODEL 

FOR STEADY STATE HEAT TRANSER 

Final Report 

NASNASEE Summer Faculty Fellowship Program-1995 

Johnson Space Center 

Prepared By: 

Academic Rank: 

College and Department: 

NASNJSC 

Directorate: 

Division: 

Branch: 

JSC Colleague: 

Date Submitted: 

Contract Number: 

Eric B. Hall, Ph.D. 

Assistant Professor 

Southern Methodist University 

Dept. of Electrical Engineering 

Ddas, Texas 75275 

Space Biomedical Research Institute 

Medical Sciences Division 

Space and Life Sciences 

Alan €3. Feiveson, Ph.D. 

August 4,1995 

NGT-44-001-800 

9- I 
random time and at some location (x, y, 2). ETo = TI, then U, Y, and Fare 

mtually independent and Gaussian, each with mean zero and variance RTo, 

where R is the gas constant. When To f the velocity components are not 

independent and are not Gaussian. Our objective is to characterize the joint 

distribution of the velocity components U, V, and Was a function ofy, and, in 

particular, to characterize the distribution of Vgiven y. It is hoped that this 

research will lead to an increased physical understanding of the nature of 

turbulence. 

9-2 
THE SIMULATION 

Consider a box that is filled with an ideal gas and that is aligned along Cartesian coordinates (x, 3 z) having until length in the “y“ direction and unspecified length in the ‘Y’ and 

‘Y7 directions. Heat is applied dormly over the c6h~t77 end of the box (y = 1) and is removed uniformly over the ‘‘~01d~~ end O-, = 0) at a constant rate such that the ends of the box are maintained 

at temperatures aty = 0 and T, aty= 1. Let U, V, 

and W denote the respective velocity components of a 

molecule inside the box selected at some random time 

and at some location (x, yt 2). (See Figure 1 .) Our concern in this project is to characterize these velocity 

components. In this regard, we will first consider the 

probIem of simdating the molecular motion inside the Figure 1 

box so as to obtain simulated velocities. This siulation will be based on the direct sirnulation Monte Carlo code presented in [Bird, 19941. 

For the simulation, we will consider (as indicated by Figure 2) a thin slice of the box 

that effectively ignores the z spatial component. The z component is not entirely neglected 

however since the molecule velocities are considered three dimensional even though the 

molecule positions are taken to be only two dimensional. This two dimensional slice is divided into cells and subcells as indicated by Figure 3. As Bird describes the problem in [Bird, 

1994, p. 2151, subcells were introduced because it “was feared that coincidental collisions 

between molecules at opposite sides of the cells, coupled with the immediate migration of 

these molecules to the next cell, might cause false disturbances to propagate with speed 

Y 

Tp 

-...___ 

Figure 2 

equal to the ratio of the cell 

size to the time step.” 

In order to explain the 

operation of the simulation 

program, we will consider the 

input file dsmc2 .dat that 

contains the data used to produce a particular simulation 

run. Any line in the data file 

beginning with ‘#I’ is treated 

as a comment and is ignored 

___* 

by the program. The line numbers mentioned below refier to the copy of this file that is 

reproduced at the end of this report. 

9-3 
The first item in the file ones 6-9) determines whether or not an output file dsmc2 . out 

is produced. This file corresponds to the only output provided by the original program 

dsmc2. for from [Bird, 19941. 

When the program begins, it first asks whether a new calculation is desired or an old 

calculation should be restarted. This latter option is only possible when line 19 of the data file 

has been set to 0 in an earlier run in order to produce arestart file. The restart file dsmc2 . res 

contains a snapshot of the current state 

of the sirnulation and can be used to restart the program at that point should 

any sort ofintemption occur. (Note that 

the size of this restart file can be as large 

as 20 Meg.) For long shulations, it is 

suggested that the values in lines 19-20 

be chosen so that a restart file is produced approximately once each hour. 

subcells 

Producing the file more fiequently may 

greatly reduce the speed of the simulation. 

Figure 3 

A second output option is the production of a log file dsmc2. log that contains velocity and temperature idonnation for cells along a partidary location. This file is produced 

when line 26 of the data file is set to zero. The value for y is specified by lime 150 of the input 

file. In addition, this log file contains information regarding the number of molecules per cell 

that may be usefiil is choosing a proper value of CMI: which is considered below. A sample 

of this output file is given near the end of this report. Note that the averages given by this 

option are not cumulative but are instead based only on the number of molecules occupying 

cells along the giveny location at the time the file is updated. 

The next output option determines whether or not a chart of velocity moments is produced during the simulation. When this option is selected by setting line 3 1 of the data file to 

zero, a chart as given later in this report is periodically written to the screen and to the file 

dsmc2. cht. The statistics in this chart are cumulative over the run of the simulation. The 

third column indicates the total number of molecules that have been used to obtain the sample 

moments found in the final three columns. The row numbers that are used to produce the 

chart are determined by lines 163-182 of the data tile. Note that it is possible to produce this 

data for every row in the box simply by setting line 167 in the data file equal to the total 

number of rows in the box. 

A third output option makes it possible to track the position of a molecule initially 

located along some specified row. A file called dsmc2. mol containing the (x, y) coordinates of a molecule in the specified row is produced when line 36 of the data file is set to 

zero. The initial molecule row number is specified by line 154 of the data file. Since the 

molecules generally move only slightly between successive time steps, the step size provided 

9-4 
S = CWRP'lg9, then the 0.~~06 

width of the cell in Row i is 

given by F3-1(l-S)/(l-Pm) 

where W is the total width o.oOol 

of the box in they direction. 

Note that here we have as- O-Ooo3 

of rows in they direction is 

200. This value can be 0.0001- 

changed if the code is 

recompiled. Generally, the 

11.0005 

sumed that the total number 0.0002 

Qratio CWRY should be the -o.ooo,~ 

square root of the ratio of 0.0057 0.00572 0.00574 0.00576 0.0057I 0.0058 Q.QOS82 0.00584 0.00586 8.00588 0.0059 0.00591 

- 

- 

- 

- 

the temperatures at the two ends of the boxes. A graph showing the number of molecules in 

each row for a particular simulation is given near the end of this report. 

The initial temperature of the gas is determined by FW, which we have chosen to be 

the geometric mean of the two surface temperatures. This value is given in line 44 of the data 

file. The initial number density FND is in molecules per square meter. This value is specified 

in line 48 of the data file. 

In the DSMC method, a side simulated molecule represents FNUMactual molecules. 

This value is given in line 52 of the data file and must be chosen so that the total number of 

simulated molecules is not greater 

than the maximum allowed number of molecules, which in this case 

CB['2] _._ _.._.. 

is 40000. (This value can be 

changed ifthe code is recompiled.) 

The actual number of simulated 

molecules used by the program is 

given by (FNDflNUt4) multiplied 

by the area of the box. 

The value Dl34 in line 56 of 

the data file is the time step of the 

simulation, and it should be chosen so that the molecular motion and the collisions are uncoupled. In particular, it should be much less than the local mean collision time. The DSMC 

Boundary 

cq13 .__._....: 

Boundary 1 

CWI 

.Figure 4 

~ 

Boundary 3 

cw31 

9-5 
method becomes increasingly more accurate as the cell size and the time step tend to zero, 

‘(See [Bird, 1994, p. 2151.) 

The values CB[i] for i = 1,2,3, and 4, are specified in lies 69-81 of the data file and 

Column 20 

Column 1 

/\ Surfixe 2 lies along 

Row 200 lower boundary of 

/ 

Surface 1 lies along 

lower boundary of 

Row 1 Row 202 

Figure 5 

determine the dimensions of the box as indicated by Figure 4. Two 

planar surCaces (Surface 

1 and Surface 2) at possibly different temperatures may be placed anywhere within the box. 

The reflection at these 

surfaces is diffirse, which 

means that the return velocity of a colliding molecule is determined by 

the temperature of the 

wall instead of by the incident velocity. At the walls (or boundaries) of the box, the reflection 

is specular, which means that the appropriate velocity component before the collision is 

simply reversed to obtain the velocity Component after the collision. 

Surface 1 is specified by the parameters in lines 92-110 of the data file. The value 

ISURI;Il] specifies the direction of a line normal to the Surface and pointing toward the gas. 

For specular reflection, it is this velocity component that is reversed upon reflection. (The 

velocity components parallel to the surface are not changed.) For example, in Figure 5, such 

a normal is in the positivey direction, which corresponds to a value of 1 for ISUml]. The 

negative y direction corresponds to a value of 2, the positive x direction corresponds to a 

value of 3, and the negative x direction corresponds to a value of 4. The values ofLLM[l][i] 

spe* the location of Surface 1 as indicated by Figure 5 and the descriptions in lines 96-1 06 

of the data file. The value TSU.11 is the temperature of Surface 1. Surface 2 is similarly 

specified by the parameters in lines 112-130. 

The values in lines 132-146 determine the rate of output and the duration of the simulation. Their use is illustrated by the flow chart near the end of this report. Note that the 

sampling does not begin until NPS output cycles have occurred. The moment chart is not 

produced until this same point is reached. 

FlJTuRE DIRECTIONS 

The ultimate goal of this work is to characterize the conditional distribution of the y 

component of the velocity &en a particular location y. Since this problem appears to be 

9-6 
analytically intractable, any practical investigation of the distribution will involve data obtained either emp~cally or via a simulation such as the one that we have considered here. 

One immediate item for fbture consideration involves the effect of the random number 

generator on the simulation results. We, as did Bird, have used the algorithm by Knuth that 

is found in [Press et aZ., 1992, p. 2831. In perrenberg et al., 19921, it was shown that subtle 

numerical errors can occur in Monte Carlo simulations when many supposedly ‘good’ random number generators are used. Since our simulation requires a lqe number of random 

numbers, it would be helpfbl to repeat and compare these simulations with a variety of 

different random number algorithms. 

A second item for fbture consideration involves an investigation of the boundary conditions at the two surfaces. The ment code assumes that the distribution of the velocity 

component that is nod to the surface has the form of a zero mean Gaussian distribution 

taken to the right of the origin and renormalized. This is the distribution that would correspond to molecules crossing the surfkce &om some external stationary equilibrium gas. (See 

[Bird, 1994, p. 2591.) An alternate model that provides a better fit with the simulated data is 

a distribution obtained by taking the absolute value of the difference of two independent 

gamma random variables. 

REFERENCES 

Bird, G. A., Molecular Gas l?ynumics and the Direct Simulation of Gas Flows, 

Clarendon Press, Odord, 1994. 

Chapman, S., and T. G. Cowling, me Mathematical &ory of Non-Unijorm Gases, Third 

edition, Cambridge University Press, Cambridge, 1970. 

Ferrenberg, A. M., D. P. Landau, and Y. Joanna Wong, “Monte Carlo Simulations: Hidden 

Errors from ‘Good’ Random Number Generators,” PhysimZ Review Letters, Vol. 

69, NO. 23, DW. 7,1992, pp. 3382-3384. 

Meyer, R. E., Introdkction to Mathematical Fluid Dynamics, Dover Publications, New 

York, 1971. 

Press, W., S. A. Teukolsky, W. T. Vetterling, B. P. Flamery, NumericaZIecipes in C: lihe 

Art of Scient@c Computing, Second edition, Cambridge University Press, 1992. 

Prigogine, I., “Evolution Criteria, Variatonal Properties, and Fluctuations,” 

Nonequilibrium &mudynamics: Viiriatioml Techniques and Stabiliq, University of Chicago Press, Chicago, 1966, pp. 3-16. 

9-7 
10000- 

5000 

0 

-5000 

-1 0000 

20 

Scatter plot ofy velocity component in meters/seCond for approximately 16000 molecules 

selected at random from the box &er approximately 268 million collisions have occurred. 

The temperature at row 1 is 300 and at row 200 is 30000. 

9-8 
A plot of the root mean square value of they velocity component for each row in the box. 

Again, the values were obtained for a box that had experienced approximately 268 million 

simulated collisions. The temperature at row 1 is 300 and at row 200 is 30000. 

9-9 
A plot of the number of molecules present in each row of a box that has experienced approximately 268 million simulated collisions. The cell width at row 200 is ten times the cell width 

at row 200. 

9- 10 
Reii Sample 

no 

Have we completed 

4 

Sanlple the Box IncremcnSI 

Is I =. NIS? 

I 

+ 

IncrematJ 

Is J =- 

I 

NSP? 

9- 11 
Percentage of n ells = 99% 

Data for cells 

Total number of 

Average Temperature of Cells = 2932.75 

Average U velocity component = 0.04133742 km/s 

Average V velocity component = 0.002432757 km/s 

Average W velocity component = -0.002770768 kids 

Average Squared U vel compt = 0.5711446 

Average Squared V vel compt = 0.719397 

Average Squared W vel compt = 0.6397187 

Average U-3 velocity compt = 0.101235 

Average V"3 velocity compt = 0.01372038 

Average WA3 velocity compt = -0.04497306 

Average U"4 velocity compt = 0.9689213 

Average V"4 velocity compt = 1.44099 

Average WA4 velocity compt = 1.14349 

Average X Component of Mol = -0.0002265342 

Average Y Component of Mol = 0.005869242 

Sample of dsmc2. log 

Molecules = 37538 

Collisions = 145790602 

Start Time = 1.16e-06 

End Time = 0.00055648 

DTM = 2e-09 

FNUM = 1.3e+14 

CWRY = 10 

FTMP = 3000 

FND =o 

Surf 1 Temp = 300 

Surf 2 Temp = 30000 

ROW 

20 

40 

50 

60 

80 

100 

120 

140 

160 

180 

Y Midpoint 

0.00055534 

0.00127118 

0.00169623 

0.00217341 

0.00331058 

0.00474384 

0.00655029 

0.00882712 

0.01169679 

0.01531368 

Mol Count 

2874478 

2260561 

2158229 

2103919 

2086605 

2146617 

2246682 

2378198 

2527745 

2695610 

2nd Moment 

0.7194 

1.1495 

1.3561 

1.5588 

1.9812 

2.4251 

2.9223 

3.4810 

4.1265 

4.8761 

3rd Moment 4th Moment 

-0.2035 1.7523 

-0.3343 4.3424 

-0.3945 6.0186 

-0.4584 7.9019 

-0.5631 12.6606 

-0.7288 18.9076 

-0.8890 27 -4045 

-1.0843 38.6212 

-1.3110 53.6066 

-1.5899 73.5440 

9- 12 
1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

54 

55 

56 

57 

58 
110 

111 

112 

113 

114 

115 

300 
14 1 

142 

143 

14 4 

145 

146 

147 

I 

9- 15 
TRABECULAR BONE MECHANICAL PROPERTIES AND FRACTAL DIlMENSION 

Final Report 

NASMASEE Summer Faculty Fellowship Program--1995 

Johnson Space Center 

Prepared By: 

Academic Rank: 

University & Department 

NASAIJSC 

Directorate: 

Division: 

Branch: 

JSC Colleague: 

Date Submitted: ' 

Contract Number: 

Harry A. Hogan, PbD. 

Associate Professor 

Texas A&M University 

Department of Mechanical Engineering 

College Station, Texas 77843-3 123 

Space and Life Sciences 

Medical Sciences 

Space Biomedical Research Institute 

Linda 6. Shackelford, M.D. 

August 7,1995 

NGT-44-00 1-800 

10-1 
ABSTRACT 

Countermeasures for reducing bone loss and muscle atrophy due to extended 

exposure to the microgravity environment of space are continuing to be developed and 

improved. An important component of this effort is bite element modeling of the lower 

extremity and spinal column. These models will permit analysis and evaluation specific to 

each individual and thereby provide more efficient and effective exercise protocols. Inflight countermeasures and post-flight rehabilitation can then be customized and targeted 

on a case-by-case basis. Recent Summer Faculty Fellowship participants have focused 

upon finite element mesh generation, muscle force estimation, and fractal calculations of 

trabecular bone microstructure. Methods have been developed for generating the threedimensional geometry of the femur from serial section magnetic resonance images (MRI). 

The use of MRI as an imaging modality avoids excessive exposure to radiation associated 

with X-ray based methods. These images can also detect trabecular bone microstructure 

and architecture. The goal of the current research is to determine the degree to which the 

fiactal dimension of trabecular architecture can be used to predict the mechanical 

properties of trabecular bone tissue. The elastic modulus and the ultimate strength (or 

strain) can then be estimated fiom non-invasive, non-radiating imaging and incorporated 

into the finite element models to more accurately represent the bone tissue of each 

individual of interest. Trabecular bone specimens fiom the proximal tibia are being 

studied in this first phase of the work. Detailed protocols and procedures have been 

developed for carrying test specimens through all of the steps of a multi-faceted test 

program. The test program begins with MRI and X-ray imaging of the whole bones 

before excising a smaller workpiece from the proximal tibia region. High resolution MRI 

scans are then made and the piece firther cut into slabs (roughly 1 cm thick). The slabs 

are X-rayed again and also scanned using dual-energy X-ray absorptiometry (DEXA). 

Cube specimens are then cut from the slabs and tested mechanically in compression. 

Correlations between mechanical properties and fiactal dimension will then be examined 

to assess and quantifj the predictive capabiity of the fiactal calculations. 

10-2 
INTRODUCTION 

As plans and progress continue toward establishing a permanent space station, and 

ultimately resuming spaceflight beyond the earth's orbit, coping with the physical and 

psychological demands placed upon the astronauts continues to pose a sigdcant 

challenge. The musculoskeletal system in particular can undergo dramatic changes fiom 

extended exposure to the weightless environment associated with long duration 

spaceflight. In addressig these issues, efforts centered at the Space Biomedical Research 

Institute of the Johnson Space Center are continuing to focus on developing improved 

techniques for monitoring musculoskeletal condition and applying effkctive 

countermeasures to minimize losses and maintain adequate function. An important 

component of this broad-based effort is aimed specifically at developing computer models 

that can be customized to individuals on a case-by-case basis. Much of the initial work 

deals primarily with the lower liib because of its prominence in overall skeletal fbnction. 

Recent Summer Faculty Fellowship participants have devised methods for non-invasively 

determining the size and shape of the main load-bearing bones, such as the femur & tibia 

(Todd, 1994), and also estimating muscle forces and joint kinematics during exercise 

(Figueroa, 1995). The bone dimensions and geometry are derived from magnetic 

resonance images (MRI) since this avoids exposure to ionizing radiation as is customary 

with X-ray and similar methods. Finite element models of the femur can be constructed 

from the geometry data and the applied loads derived tiom physiological muscle force 

data. The goal is to use such models to predict the stresses and strains within the bone, 

and from them identi@ and assess regions of weakness and potential fracture risk. This 

detailed and quantitative insight will allow individualized evaluation of skeletal condition 

(pre-, post-, and in-flight) and prescription of exercise protocols for in-flight countermeasures as well as post-flight rehabiiitation. The next major step in developing this 

capability is to determine the material properties of the bone tissue within the bones. With 

methods available to generate the geometry and loads, a complete and more accurate 

model also requires information on the material properties of the bone or bones of interest. 

A major challenge at this point is to devise a way to estimate these properties fiom MRI 

data, which is a process essentially unexplored to date. The goal of the current research is 

therefore to evaluate the usefilness of estimating mechanical properties of trabecular bone 

tissue tiom MRI data. The study is limited to trabecular bone (as opposed to cortical 

bone) because MRI signals do not detect cortical bone, but this is not a severe limitation 

since trabecular bone is much more adaptive to changes in loading and is also more 

susceptible to fiacture risk. The specific parameter being used to quant@ trabecular bone 

microstructure is the fiactal dimension. This quantity is calculated from the MRI 

following the methods developed by Acharya (1995), another recent Summer Faculty 

Fellowship program participant. Thus, the specific aim of the current research is to 

correlate mechanical properties of trabecular bone tissue with fiactal dimension. The 

properties are measured fiom a series of mechanical tests on in vitro specimens taken from 

bones that have first been scanned with the MRI. This will allow direct correlation of the 

properties and fiactd dimension fiom the same specific sample of tissue. 

10-3 
PROTOCOLANDPROCEDURES 

Overview 

Much of the time and effort during the summer research period has been spent 

formulating and refining the detailed research plan. Protocol details and various test 

procedure options for executing the research have been evaluated. The research involves 

collaboration between several different laboratories and personnel so extensive 

coordination is essential. Identifjling all of the necessary tasks and the appropriate order 

and procedures has been a major focus. The main steps in the overall process are: 

1. Acquire human tibia specimens and prepare for "whole bone" MRI scanning. 

(at University of Texas Medical School, Orthopedics Biomechanics Laboratory) 

2. MRI scan proximal portion of whole tibia using clinically available resolution. 

(at Baylor College of MedicineMethodist Hospital, Medical Physics) 

3. Cut section beneath tibial plateau (3-4 cm long) and prepare for "high-resolution" MIU. 

(at University of Texas Medical School, Orthopedics Biomechanics Laboratory) 

4. MRI scan excised piece of proximal tibia to image trabecular architecture. 

(at Baylor College of Medicine Methodist Hospital, Medical Physics) 

5. Slice proximal tibia piece into slabs approximately 1 cm thick. 

(at University of Texas Medical School, Orthopedics Biomechanics Laboratory) 

6. Scan slabs for bone mineral density using dual energy X-ray absorptiometry (DEXA). 

(at Baylor College of Medicine Methodist Hospital, Medical Physics) 

7. X-ray slabs to provide alternate images of trabecular architecture. 

(at University of Texas Medical School, Orthopedics Biomechanics Laboratory) 

8. Cut slabs into cubes for mechanical testing. 

(at UT Med School and/or Texas A&M University) 

9. Conduct mechanical tests and calculate mechanical properties of interest. 

(at UT Med School and/or Texas A&M University) 

10. Determine wet and dry densities and ash weights. 

(at UT Med School and/or Texas A&M University) 

1 1. Calculate fiactal dimension fiom MRI and X-ray images. 

(at State University of New York at Buffalo, Biomedical Imaging Group) 

10-4 
Once the experimental tests are completed and the data analyzed, correlations will 

be examined between mechanical properties and other parameters. The mechanical 

properties of interest are the elastic moduli (in all 3 orthogonal directions) and the ultimate 

stress, ultimate strain, and energy absorbed along the primary axis of in vivo loading (i.e. 

the superior-inferor direction). The elastic moduli are measures of material stiffhess while 

the other quantities are measures of strength or "ductility". The main microstructural 

parameter is the fractal dimension of the trabecular architecture. The hctal dimension is 

a novel quantity not commonly used for such purposes but recent studies have shown it to 

be a unique measure in distinguishing between normal and osteoporotic bone (Ruttimann 

et ul., 1992; Majumdar et al., 1993; Weinstein and Majumdar, 1994). This suggests that 

the fractal dimension may likewise be a promising parameter for predicting mechanical 

properties. Addressing this question is therefore a major goal of the current research. For 

completeness and reference with other studies, additional microstructural measures to be 

included in correlation studies are the wet and dry densities and the ash weights. 

As mentioned previously and indicated in the above outline, the research is being 

carried out at several different laboratories. The Orthopedic Biomechanics Laboratory at 

the University of Texas Medical School is under the direction of Dr. Timothy Harrigan 

and also staffed by Dr. Catherine Ambrose and Ms. Frances Biegler. This facility provides 

the source for fresh human bones and also is equipped for specimen cutting and 

mechanical testing. A recently finded collaborative research project between the UT 

Medical School, the Space Biomedical Research Institute at NASA Johnson Space Center, 

and the Baylor College of Medicine provides the focal point and programmatic fi-amework 

for the current research. Drs. Linda Shackelford and Laurie Webster oversee the NASA 

participation providing guidance and direction on scientific issues as well as maintaining 

the relevance of the work to NASA programs and mission. Drs. Adrian LeBlanc, Harlan 

Evans, and Chen Lin of the Baylor College of Medicine are responsible for all MEU 

scanning and image preparation. Fractal analysis is being conducted by Dr. Raj Acharya 

of the Biomedical Imaging Group at the State University of New York at Buffalo. As a 

result of participation in the Summer Faculty Fellowship program the tasks associated 

with specimen preparation, mechanical testing, and post-test measurement of physical 

properties will likely be shared between the UT Medical School and facilities at Texas 

A&M University. 

More detailed descriptions of the research activities are outlined below. The 

overall project can be roughly divided into four phases based upon the size and nature of 

the bone specimens being examined. The first phase involves acquisition, preparation, and 

imaging of whole bone -human tibia specimens. The second phase deals with preparation 

and imaging of a 3-4 cm section excised from the proximal tibia just beneath the tibial 

plateau. The third phase involves firther cutting the specimen into slabs roughly 1 cm 

thick and imaging each slab. The fourth and final phase involves cutting the slabs into 1 

cm cubes, mechanically testing the cubes, and analyzing the physical properties of the 

tissue in each cube specimen. 

10-5 
Phase I - whole Tibia Procedures 

Whole tibia bones are acquired through the University of Texas Medical School 

and prepared for imaging in the Orthopedic Biomechanics Laboratory. Each tibia is 

cleaned of so& tissue and stored frozen. The bone is first X-rayed to ensure that it is fkee 

of disease or otherwise not suitable to be included in the study. For proper MRI scanning, 

each bone must be mounted in a container such that the bone is immersed in 'doped' water. 

A container for this purpose was fabricated at NASMJSC from 1/4" thick plexiglass plate 

material. The box assembly with a tibia mounted is depicted in Figure 1. The plexiglass 

box is 4.5" wide, 4" tall, 16.5" long, and open at the top. A lid was made to cover the box 

to minimize splashing or leakage of the fluid during handling. An insert piece was also 

made to actually hold the bone. This permits easy placement and removal of the bone 

from the box. It was also intended to provide easy removal of the bone after it is 

embedded in plastic subsequent to MlU scanning. The insert was constructed fiom 1/8" 

plexiglass and made to fit just inside the walls of the box like a thin liner. Holes (1/4" 

diameter) were drilled in the long sides of the insert for holding rods inserted transversely 

through the bone. Two transverse holes were drilled diametrally through the bone near 

the proximal and distal bounds of the diaphysis region. The holes are 1/4" in diameter and 

lie in the mediavlateral plane. Plexiglass rods were inserted through these holes and then 

mounted in the holes in the insert liner. 

Ee~vable TOP VIEW 

16.5" 4 

SIDE VIEW 

Figure 1 .- Schematic drawing of container for whole bone MRI scanning. 

10-6 
The final preparation for imaging is to mark the boundaries of the proximal section 

fiom which mechanical testing specimens will be cut. This section should typically be 

roughly 3 to 4 cm long and located just beneath the tibial plateau. Landmarks must also 

be created to provide reference marks for locating tissue regions within the plane of each 

image slice. Four shallow "grooves" in the outer surfhce will be made for this purpose. 

These grooves will run axially along the length of the bone and wilI be cut with a Dremel 

tool to a depth of 1 to 2 mm. The grooves will be located along the medial, lateral, 

anterior, and posterior aspects of the periosteal surface of the bone cortex. The grooves 

will appear as notches in each planar transverse image. The intersection of lines drawn 

connecting the mediavlateral notches and the anterior/posterior notches will thereby form 

a systematically defined origin for Coordinate locations within the plane of each image. 

After the bone is properly marked and mounted in its container it is transferred to 

the Baylor College of Medicine for MRI scanring. The whole bone scans are made using 

a knee resonator coil, which has an inside diameter of 20.5 cm and an axial length of 26.5 

crn. Axial scans (i.e. transverse to the bone axis) were made of the 3 to 4 cm region 

identified in the proximal portion with no gap between adjacent scans and with a scan 

thickness of 2 mm. These scans actually required multiple images to permit the 

determination of more detailed parameters such as T1, T2, and T2* in addition to the 

more routine spin-echo signals. The in-plane resolution of these images is approximately 

0.5 mm. Additional spin-echo scans are made at 2 to 3 cm intervals moving proximally 

into the diaphysis region of the bone. These will be used for hrther studies on 

constructing finite element models fiom MRI data. In addition, five roughly evenly spaced 

coronal scans (Le. parallel to the bone axis in the mediavlateral plane) were also made in 

order to register the axial position of the axial scans. 

Following the MRI scanning, the container was emptied of water and returned 

with the bone still mounted to the UT Medical School. The container was then filled with 

polyester resin to completely embed the bone in plastic. A plastic sheet liner was placed in 

the container first to facilitate removal after the plastic hardened. The embedding 

procedure was intended to provide orthogonal reference surfaces for the whole assembly 

to guide subsequent cutting operations and also for defining common coordinate systems 

for locating positions within images and within the physical bone slab specimens. This 

particular procedure is currently being reviewed in lieu of using the "grooves0 described 

above for the same purpose. Further preliminary studies are underway to address this. 

Phase 2 - Proximal Tibia Section Procedures 

In order to obtain images with high enough resolution to depict the microstructural 

architecture within trabecular bone tissue the size of the bone sample to be imaged must 

be reduced. The MRI facilities at Baylor College of Medicine are again used for this 

imaging. An orbit coil is used for high resolution MRI but its chamber is only 8 cm in 

10-7 
diameter. Thus, a smaller section fiom the proximal portion of the tibia was cut using a 

band saw at the UT Medical School. This piece was roughly 3.5 cm long with the first cut 

1-2 cm below the tibial plateau (see Fig, 2). Before making these cuts, care must be taken 

to document the axial location of the cuts relative to a landmark that can be identified in 

the MRI. Two choices are apparent: the proximal-most tip of the articular surface, or the 

location of the proximal transverse rod upon which the bone is mounted. The first tibia 

that was used in preliminary tests was rather large and had to be trimmed significantly on 

the medial and lateral aspects as well in order to fit within the orbit coil. This also meant 

cutting away essentially all of the surrounding plastic in which the bone had been 

embedded. The large size of the bone also permitted cutting an additional 3.5 cm section 

below (or distal to) the first. This piece was small enough to fit within the orbit coil 

without firther trimming. The in-plane resolution of the orbit coil is 0.125 microns for a 

scan thickness of 3 mm. Axial scans were made for the entire length of the piece with no 

gap between successive scans. Similarly, coronal scans were made of the same piece with 

no gap between scans. These scans were initially made on both pieces with the specimens 

simply wrapped with par& sheets. Upon reviewing the images, however, artifacts due 

to air pockets were observed, particularly in the central portions of the pieces where the 

porosity is high. Thus, the protocol has been revised to have the pieces fblly hydrated 

before scanning and placed in a container of water during scanning. Placing the specimens 

in water will also ensure that the reference notches on the external surface of the cortical 

wall are clearly imaged. 

3-4 cm 

I I 

band sawcuts I n 

1 position coordinates I 

Figure 2.- Region cut fiom proximal tibia. 

10-8 
Phase 3 -- Transverse Slab Procedures 

The next phase begins with cutting the 3 to 4 cm pieces into slabs roughly 1 cm 

thick or slightly thicker. The goal is to get 3 slabs from each piece. A band saw at the 

University of Texas Medical School was used for cutting the preliminary pieces examined 

thus far. Using a band saw makes it difficult to maintain precisely straight, flat, and 

parallel cutting surfaces and this must be considered in subsequent cutting operations for 

making cube specimens. Proper marking and/or measuring must be included at this stage 

in order to maintain the axial position of the cut faces relative to coordinate landmarks. 

The width of material removed by the saw must also be accounted for in this process. The 

next two steps involve imaging each separate slab and the order in which they are carried 

out is not critical. An X-ray image of each slab will be made by contact radiography at the 

UT Medical School. These X-rays will produce detailed images of the trabecular 

structure from which alternate calculations of fractal parameters can be made. This will 

provide a direct comparison of the image quality and fractal parameters between images 

derived f?om X-ray and those from MRI. The slabs will also be imaged using dual-energy 

X-ray absorptiometry (DEXA) scanning techniques at the Baylor College of Medicine. 

DEXA scans are available clinically and give measures of bone mineral density 0) and 

bone mineral content (BMC). The BMD and BMC values can be determined for regions 

of interest defined graphically on the image. Thus, with proper documentation of 

coordinates, BMD and BMC can be calculated for the same specific tissue regions from 

which the cube specimens for mechanical testing were ultimately cut. 

Phase 4 - Cube Specimen Procedures 

The final phase of the protocol begins with cutting each slab into a series of 

roughly cube shaped specimens for mechanical testing. Considerable time and effort has 

been spent in developing and refining these procedures but only the highlights will be 

summarized here. First, each slab must be marked in some manner to ident% which flat 

surfaces are proximal (or superior) and/or distal (or inferior) and which reference notches 

are mediavlateral and anterior/posterior. These markings should preserve these 

identifications to the degree possible throughout the process of being cut into the cube 

specimens. A Buehler Isomet low speed diamond blade wafering saw is used for this 

cutting. The saw used dwing the summer research period was located at the University of 

Texas Medical School, but one is also available at Texas A&M University. A series of 

parallel cuts are made to cut the slab first into "bars" as indicated by the long-dashed lines 

in Figure 3. Two blades were gang-mounted approximately 1 cm apart to create two 

parallel cuts with each cutting operation. A custom gripper was made to hold the slab 

during this process to allow 3 or 4 such bars to be cut without re-gripping the workpiece. 

The precision of these cuts will routinely produce surfaces parallel to well within required 

tolerances for opposite Exes of the cube specimens. The surfhces of the bars formed from 

the band saw will not be parallel enough, however, so each bar must be rotated 90 degrees 

10-9 
and cut to face off one of the two surfaces cut with the 

transverse to its long axis to yield a set of 

short-dashed lines in Fig. 3). Each spe 

orientation and coordinate location within the slab crossthe current work is the need to cut slabs before making cross-cuts to produce cubes. This 

is necessary to allow DEXA and X-ray imaging as described previously and thereby 

precludes using a milling machine with blade cutters (as used by Ciarelli et al., 1991, for 

example). The detailed steps and procedures in the cutting process have been developed 

with the assistance of a volunteer undergraduate research assistance and are outlined in a 

separate document resulting fiom that work (Brandt, 1995). 

-u 

first cut into "bars" 

next cut 

into cubes 

Note that the arrows indicate the medial/lateral 

and anteriodposterior reference markers 

Figure 4.- Cutting slabs into cube specimens. 

Cube specimens will be stored wet and .frozen until time for mechanical testing. 

Mechanical tests will be conducted in compression under displacement control at a rate of 

0.01s". Each test specimen will be loaded between two flat platens lubricated to eliminate 

lateral constraint due to fiction. One of the platens will be articulated to self-align and 

reduce non-dorm loading fiom imperfectly parallel specimen surfaces. A shallow (1 -2 

mm deep) recessed area will be machined in the platens to fbcilitate placement of the 

specimens centered along the machine lodig axis. Each specimen will be tested 

nondestructively along each of its 3 orthogonal axes (i.e., superior/inferior, medial/lateral, 

10-10 
anterior/posterior) following procedures similar to those of Goulet et al. (1994), Keller 

- (1994), and Lmde et al. (1992). This will permit calculation of elastic moduli for each 

direction. A final destructive test to Mure will then be conducted along the primary 

anatomical axis of loading (superior/inferior for proximal tibial bone). Quantities such as 

the ultimate strength, ultimate strain, and energy absorbed to failure can then be calculated 

for this direction of loading. Additional details to be determined through preliminary 

testing and further study include whether to use preconditioning cyclic loading, which 

particular testing machine to use, and whether to use extensometers for surface strain 

measurement. Using extensometers will likely require more elaborate design of the 

platens in order to provide adequate clearance to prevent the extensometers fiom 

interfering with the platens during testing. Numerous studies have addressed the issue of 

end effects (Allard & Ashman, 1991; Aspden, 1990; Harrigan et al., 1988; Keaveny et al., 

1993; Lmde et al., 1992; Simmons & Hipp, 1995; Zhu et al., 1994), but no simple 

solution has been developed to date, including using extensometers. Thus, applying an 

extensometer will definitely provide more insight into the details of each test, but it will 

not totally mitigate the problems assoceated with end effects. Testing machines are 

available at the University of Texas Medical School and also at Texas A&M University. 

Facilities are also available at Texas A&M for determining the wet and dry densities and 

ash weights. The wet density is simply the wet weight of the specimen (in g), which can 

be measured before or after testing, divided by the volume of the specimen (in cm3) as 

calculated fiom caliper measurements of physical dimensions. The dry density is the 

weight of the specimen (in g) taken after drying in an oven at 100°C for 24 hours. The 

specimen is then ashed in an oven at 500°C for 48 hours and weighed. The ratio of ash 

weight (in g) to dry weight (in g) is commonly expressed as a percentage and termed the 

"ash weight percent", or sometimes even just "ash weight". An ash density can also be 

calculated by dividing the ash weight (in g) by the volume (in cm3). 

Much progress has been made during the summer research period in defining the 

relevant requirements, evaluating available options, and establishing detailed procedures 

for conducting the tests and analyses required for this complg multi-disciplinary, multiinstitution collaborative research effort. Extensive study of the literature has been 

combined with preliminary tests as needed to address the major issues encountered. Four 

tibia (2 sets of paired) have been acquired and mounted in the removable insert pieces for 

whole bone MRI scanning. One has already been scanned and used for the preli&nary 

studies. As the preliminary work progressed through mechanical testing the images from 

the MRI scans are being reviewed and analyzed by Dr. Acharya. When all details of the 

protocol are approved and agreed upon by all investigators, the other three tibia will be 

tested. Correlation studies will then be conducted to establish the relationships between 

the measured mechanical properties and the various independent variables (fractal 

dimension, wet/dry/ash densities, BMD/ BMC, T2*, etc.). 

10-1 1 
REFERENCES 

Acharya, R. S., LeBlanc, A., Shackelford, L. C., Swamarkar, V., Krishnamurthy, R, 

Hausman, E., and Lin, C. (1995) Fractal analysis of bone structure with applications 

to osteoporosis and microgravity effects. (manuscript submitted). 

Allard, R. N. and hhman, R. B. (1991) A comparison between cancellous bone 

compressive moduli determined from surface strain and total specimen deflection. 

Trans. Orthop. Res. Society 3 7th Annual Mtg., 1 5 1. 

Aspden, R. M. (1990) The effect of boundary conditions on the results of mechanical 

tests. J. Biomechanics 23, 623. 

Brandt, S. (1995) Procedures for cutting cube specimens of trabecular bone from the 

proximal tibia. Unpublished Research Report. 

Ciarelli, M. J., Goldstein, S. A., Kuhn, J. L., Cody, D. D., and Brown, M. B. (1991) 

Evaluation of orthogonal medchanical properties and density of human trabecular 

bone fiom the major metaphyseal regions with materials tesing and computed 

tomography. J. Orthop. Res. 9,674-682. 

Figueroa, F. (1995) Methodologies to determine forces on bones and muscles of body 

segments during exercise, employing compact sensors suitable for use in crowded 

space vehicles. FinaZ Report NASNASEE Summer Faculty Fellowship Program. 

Goulet, R. W., Goldstein, S. A., Ciare&, M. J., Kubn, J. L., Brown, M. B., and Feldkamp, 

L. A. (1994) The relationship between the structural and orthogonal compressive 

properties of trabecular bone. J. Biomechanics 27,375-389. 

Hanigan, T. P., Jasty, M. Mann, R. W., and Harris, W. H. (1988) Limitations of the 

continuum assumption in cancellous bone. J. Biomechanics 21,269-275. 

Keaveny, T. M., Borchers, R. E., Gibson, L. J., and Hayes, W. C. (1993) Trabecular bone 

modulus and strength can depend on specimen geometry. J. Biomechanics 26, 991- 

1000. 

Keller, T. S. (1994) Predicting the compressive mechanical behavior of bone. J. 

Biomechanics 27, 1 159- 1 168. 

Linde, F., Hvid, I., and Madsen, F. (1992) The effect of specimen geometry on the 

mechanical behaviour of trabecular bone specimens. J. Biomechanics 25,359-368. 

10-12 
Majumdar, S., Weinstein, R. S., and Prasad, R. R. (1993) Application of fid geometry 

techniques to the study of trabecular bone. Med Phys. 20, 161 1-1619. 

Ruttiman, U. E., Webber, R. L., and Hazelrig, J. B. (1992) Fractal dimension fiom 

radiographs of peridental alveolar bone. oral Surg.0raZ MedOraZ PathoZ. 74, 98- 

110. 

Simmons, C. A. and Hipp, J. A. (1995) A new method for the mechanical testing of 

trabecular bone. Proc. 1995 ASME Bioengineering Con$, BED-Vol. 29,355-356. 

Todd, B. A. (1994) Finite element modeling of the lower extremities. Final Report 

NASNASEE Summer Faculty Fellowship Program. 

Weinstein, R. S. and Majumdar, S. (1994) Fractal geometry and vertebral compression 

fractures. J. Bone Mia Res. 9, 1797-1802. 

Zhu, M., Keller, T. S., and Spengler, D. M. (1994) Effects of specimen load-bearing and 

fiee surface layers on the compressive mechanical properties of cellular materials. J. 

Biomechanics 27, 57-66. 

10-13 
Prepared By: 

Academic Rank: 

CONSTRAINTS IN GENETIC PROGRAMMING 

NASA/ASEE Su 

University & Department: 

NASA/JSC 

Directorate: 

Division: 

Branch: 

JSC Colleague: 

Date Submitted: 

Contract Number: 

Cesary Z. Janikow, Ph.D. 

Assistant Professor 

University of Missouri - St. Louis 

Department of Mathematics and 

St. Louis, MO 63121 

Computer Science 

Engineering 

Automation, Robotics and Simulation 

Intelligent Systems 

Dennis Lawler 

July 20, 1995 

NGT-44001-800 

11 - 1 
ABSTFLACT 

Genetic programming refers to a class of genetic algorithms utilizing generic representation in the form of program trees. For a particular application, one needs to provide 

the set of functions, whose compositions determine the space of program structures being 

evolved, and the set of terminals, which determine the space of specific instances of those 

programs. The algorithm searches the space for the best program for a given problem, 

applying evolutionary mechanisms borrowed from nature. 

Genetic algorithms have shown great capabilities in approximately solving optimization 

problems which could not be approximated or solved with other methods. Genetic programming extends their capabilities to deal with a broader variety of problems. However, 

it also extends the size of the search space, which often becomes too large to be effectively 

searched even by evolutionary methods. Therefore, our objective is to utilize problem constraints, if such can be identified, to restrict this space. In this publication, we propose 

a generic constraint specification language, powerful enough for a broad class of problem 

constraints. This language has two elements - one reduces only the number of program 

instances, the other reduces both the space of program structures as well as their instances. 

With this language, we define the minimal set of complete constraints, and a set of oper* 

tors guaranteeing offspring validity from valid parents. We also show that these operators 

are not less efficient than the standard genetic programming operators if one preprocesses 

the constraints - the necessary mechanisms are identified. 

11 - 2 
INTRODUCTION 

Evolutionary problem solving simulates nature to search for a solution. First, rep 

tation for potential solutions must be defined, along with an evaluation function to q 

different solutions. A number of solutions are simultaneously processed in a simulated pop 

dation. Individual solutions undergo simulated evolution: Darwinian selective pressure is 

used for survival determination, mutation is used to alter individual solutions, and crossover 

is used for information inheritance from usually two parents to one or two offspring. 

Genetic programming (GP) [5, 61 is one of the most recent evolutionary methods. It 

differs from others, such as the well-known genetic algorithms (GAS) [2, 31, by its representation - an individual solution is a high level program, structured as a tree representing 

the dynamic program structure. This allows, for example, for the learning of analytical 

functional descriptions [5] - which can not be accomplished with GAS. 

A GP application requires specification of the primitive function set and the terminals, 

which can be used in any combination (the closure property) [5]. However, by providing 

the primitive functions (along with procedural interpretations), one explicitly determines 

the set of plausible expressions that can be evolved. For example, suppose we need to learn 

the (unknown) function y = sin (z) - cos (z + 2). If we don’t know the function, we do not 

know that the solution will involve trigonometric functions. Therefore, we may decide to 

use the following function set {+, -, *, /). This will prevent the exact solution from being 

discovered (the suficiency principle states that one assumes that the function set includes 

all needed functions). The evolved solution would have to be fairly complex for a satisfactory approximation (if possible at all, especially given size constraints imposed on GP 

programs). On the otha hand, if we allow many functions to participate in the primitive 

set, we explode the search space beyond manageability. Therefore, the GP approach is very 

sensitive to the user’s insights (in addition to being very sensitive to its own parameters). 

This will hopefully change when methods are developed to constrain the space, to incorporate heuristics, to a.utomatically select/prune the set of primitives, to automatically update 

the sensitive parameters, etc. 

An important issue for any problem solving method is that of handling constraints, 

which are often present. If disregarded, they may lead to infeasible solutions. On the other 

hand, when properly handled they can reduce the amount of searching required. Constraints 

can be handled by evolutionary algorithms, especially by genetic algorithms, where most 

constraint-related research has been done. However, a common problem is that of generality 

of any approach. Many GA approaches create specified representations and/or operators, 

which prohibit invalid solutions from occurring. Examples are a mat. representation for 

the transportation problem and a permutation sequence for the traveling salesman problem. 

Even though these approaches are very nicely crafted and are efficient, they are also handtailored for the specific problems and must be redone for a new problem, a class of problems, 

or a specific instance of a problem with different constraints. To avoid that, one needs to 

provide a more general approach. One such approach has been studied in GAS - penahe 

solutions which violate the constraints [SI. But this method is not perfect either. Even 

though it is generic and only requires modification of the evaluation function, it is much 

less efficient as it still allows explorations of infeasible problem subspaces, wasting resources 

there. In addition, too relaxed a penalty can still allow generation of infeasible solutions. 

11 - 3 
Too rigid a penalty may prohibit good solutions from being discovered [7]. 

The most desirable approach is to provide a constraint-specification language, and then 

provide built-in mechanisms to handle those constraints, preferably by moving the search 

into feasible subspaces only. The language should be powerful enough to express a broad 

range of specific constraints that a particular problem may have. This has been done with 

GAS for the class of linear constraints over a parameter space [?I. 

GP offers much greater capabilities than GAS by its variable length parameterized rep 

resentation. However, as mentioned, it must advance in many directions to enjoy more 

practical applications. And constraints are an important aspect of such advancement. In 

this paper, we propose a constraint handling methodology, which is based on the idea of a 

constraint specification language. This language is presented and enforcement mechanisms 

are provided. The language is not capable of expressing "any" constraint. However, it is 

applicable to a broad range of problem constraints. Moreover, we show that the enforcement mechanisms do not reduce the efficiency of the GP algorithm. In fact, the. actual 

search efficiency is greatly improved since the search is now conducted only in the feasible 

subspace . The idea is based on restricting both the space of program structures, and on reducing 

the number of program instances for any particular program structure. In this paper, we 

overview the various methods for processing constraints in genetic algorithms. Then, we 

propose a constraint specification language for GP, which is easy to use. Afterwards, we 

present transformations aimed at reducing the set of constraint specifications to a minimal 

yet sufficient set, which is easy to enforce. Subsequently, we define mutation and crossover 

to be "closed" in the program subspace specified by the specifications. That is, given valid 

parents these operators generate only valid offspring. We also provide a method to initialize 

the population of programs with only valid instances to ensure that the evolution will be 

closed in the feasible subspace. Finally, we show that one may implement these operators 

with the same level of efficiency as the standard operators in unconstrained GP. 

CONSTRAINTS IN GP AND GAS 

Genetic programming is a special case (or a generalization, depending on the exact definition) of genetic algorithms. Given a problem, a set of constants for the problem (e.g., 

program variables or actions) is specified, and a set of primitive functions is defined. Eventual program data can be included in the terminal set, or it can be hidden in interpretations 

of functions. Compositions of functions determine the space of programs which can be expressed this way. What is sought is one of such programs, the one which solves the problem 

the best way (given some criteria). 

Discovery, or rather creation, of the best program is accomplished by evolution. A 

population of initial programs (possibly random) is set, which then evolve by simulating 

nature. In this simulation, current programs are evaluated (given problem criteria) and an 

evaluation-based pressure is used to promote survival of better programs. Programs also 

undergo mutation, and create offspring by means of cros8over. 

An obvious problem that GP tries to address is that of searching the infinite space of 

possible programs. This is done by limiting this space as explained below. Our objective is 

to further limit this space by additional constraints. 

11 -4 
Current State of the Art in Constraint Processing in GP 

Except for ADFs (automatic function definitions) and a few tailored applications, there 

is very little reported work on constraints and methods for handling them in GP [4,5, 61. 

In ADFs, constraints relate to differentiating among different functions and the program 

being evolved. This has few implications for our objectives. The tailored applications are 

not more helpful, since they aim at satisfying constraints of very specific functions (usually 

a single constraint). 

In general, the only other constraint used in GP relate to managing the complexity 

of the evolution. This is done by imposing restrictions on program size. Program size is 

defined in one of two ways: either by the depth of the tree (proportional to maximum 

number of nested function calls) or by the total size of the tree (proportional to the total 

number of function calls). Either case is always handled in one of two different ways: 

0 abandon the violating program, and keep creating new ones until one that satisfies 

the constraint is generated (method 1 below), 

0 use the parent program instead of the violating offspring (method 2 below). 

These methods are fine if violations are rare. With the size constraint, this is indeed 

the case. However, with new constraints, this is unlikely to be true and new methods will 

have to be investigated. 

Various Methods for Handling Constraints 

In any evolutionary method (such as GP, but especially in GA), constraints have been, 

or at least can be, handled in a number of ways. Difficulties come in implementing some of 

the ways, and in prior determination of which way might be the best for a given problem 

(or a class of problems). Unfortunately, there is no "silver bullet". 

Genetic algorithms enjoy richer methodologies to deal with problem constraints. In 

addition to those two methods listed for dealing with size constraints in GP, GA researchers 

have used approaches such as modifications of the interpretation of a particular solution 

(called phenotype), repair algorithms, and penalty functions to penalize indid solutions. 

A recently emerging approach is to provide "smart" operators, called closed, which are 

intended to produce only valid offspring from valid parents. Such operators have been 

proposed for GA parameter optimization with linear constraints [7]. 

Objectives and Methods 

Because possible constraints are endless, it is impossible to provide constraint handling 

methods for specific constraints ahead of time. On the other hand, we want to avoid 

having to provide such methods separately for each problem, whenever a constraint appears. 

Therefore, our objective is to design a constraint specification language able to express 

constraints encountered in a broad range of applications. Then, we could have generic 

mechanisms processing those constraints so that 

0 only valid programs are evolved, 

0 the space of valid programs is constrained to reduce the effective search space. 

11 - 5 
EXPLORATION OF CONSTRAINT SPECIFICATIONS 

Search Space in GP 

GP's problem space is defined by terminals T and functions F, where each fi E F has 

a fixed arity a;. Function compositions determine the space of possible program structures. 

Because the space is infinite, it is normally restricted by the aforementioned two methods 

- restrict the number of nodes or restrict the maximal depth of a program. Terminals 

are values which can appear in terminal nodes. They have no implications for program 

structures. Instead, given a specific program structure, which serves as a template, terminals 

determine the space of possible program instances. This space, for a particular program 

structure, can again be infinite if infinite sets are allowed (such as real numbers). Therefore, 

the space of all programs is determined by both F and T, and this space can be infinite in 

two dimensions. One of these possibly infinite dimensions , the space of program structures, 

is normally restricted by the size constraints. The other dimension, program instances of 

a program structure, is restricted by the finite accuracy of computer representations. It is 

assumed that this space contains the sought program. This assumption is the basis for GP 

problem solving - the suficiency assumption. 

2'- and 8'- Constraint Specifications 

We use two different kinds of constraint specifications, but, as we will see, they are not 

completely independent. These are syntactic T-specifications and semantic F-specifications. 

Moreover, we will show that not all of them are really needed - after certain transformations, 

only a few are sufficient to express exactly the same constraints. However, it will generally 

be much easier to express problem constraints with the full specification language, while it 

will be much easier to devise mechanisms for the minimal set. 

T-specifications are based on domains for function arguments and on function ranges. 

Definition 1 Let us define + to stand for domain compatibility. That is, X 3 Y means 

that X can replace Y , where both X and Y stand for sets of values (3nite or infinite) allowed 

for domains or returned as function ranges. 

Definition 2 Define the following T-specifications (syntactic constraints): 

1. T- - the set of values allowed at the Root, or the set of values allowed to be returned 

by the evolved program, that is by functions appearing at the Root. T- actually 

specifies both a domain (for the root node) and a range Mor the program]. 

2. T, - Ti is the range of fi, that is the set of values returned by the function f;. 

3. T: - Tj is the domain for the jth aqument of fi, that is the set of values allowed 

4. T, =$ T,* - compatibilities between ranges and domains 

5. T, =$ Tbt - compatibilities between function ranges and the program mnge 

there (which may be returned by functions used as this aqument). 

where 'P' indicates that the compatibility can be straight or it can be negated. 

11-6 
T-specifications reduce both the space of program structures and the space of instances of 

those structures. Therefore, they are very powerful constraints. GP uses only one t 

set - any due from that set may appear in any leaf of a program tree. Obvio 

true in actual programs - different functions take different arguments. Texpressing such differences, thus allowing reduction in the space of program instances per 

program structure. Moreover, some T-specifiations also implicitly restrict what function 

can call other functions, effectively reducing the space of possible program structures. For 

example, if the domain for a function argument is fixed, then the value for that argument 

may not be obtained from a function with an incompatible range. Therefore, some Tspecifications can be seen analogous to function prototypes available in high level languages. 

However, syntactic fit does not necessarily mean that a function should call another 

function. One needs additional specifications based on program semantics. These are 

provided by means of F-specifications, which further restrict the space of program structures 

(but not program instances). 

Definition 3 Define the following F-spe&fications (semantic constraints): 

6. FROot - the set of functions disallowed at the Root. 

7. F, - F; is the set of functions disallowed as direct callers to fi (genemlly, a function 

is unaware of the caller; however, GP constructs a prqmm tree, which represents the 

dynamic structure of the program). 

8. F,' - 5' is the set of fvnctions disallowed as argj to fi. 

Example 1 Assume a function (if argl arg2 arg3), interpreted as: if argl evaluates to 

true, return the evaluation of argz, else return the evaluation of arg3 (assume both of 

which evaluate to real numbers). One needs to specify that argl could only be terminals 

which are boolean values, or only functions which return boolean values. Assuming that 

T = R1 U {T, F), one may specify Tjf = (T, F). Because R1 is not compatible with { T , F ) , 

only elements of the latter can be placed there. 

Proposition 1 X =+ Y H X E Y. 

:: X j Y means that in places whem values from Y are valid one may place any value from 

XI or any function returning a value jkm X. To guarantee that no out-of-domain values 

a= used for the original Y , X may not contain values not found in Y. Therefore, it must - 

be a subset of Y, or it must equal Y. 

Using known properties of E, domain compatibilities could be automatically computed 

(giving compatibility T-specifications #4 & #5), as long as these are restricted to syntactic 

constraints. 

Example 2 Assume two sets: Ti = (1,2,3) representing masses of physical objects in 

Mogmms, and Tz = (1,2) representing times in seconds. Thus one may conclude that 

Tz 3 TI since (1,2) C {1,2,3}. But by observing the interpktatim of these objects, an 

obvious conclusion is that Tz j4 TI, but this is based on interpretation of these setsI which 

is left to F-specifications. 

11 - 7 
Rules on T- and F-specifications 

Given the above T-specifications and F-specijkations, which can be used to express 

problem constraints, an obvious issue is that of possible redundancies, or that of existence 

of sufficiently minimal specifications. We answer these questions in this section. Surprisingly, after certain static transformations, only a subset of T- and F-specifications will turn 

out to be sufficient to express all T- and F-specijication constraints. This observation is extremely important, as it will allow efficient constraint enforcement mechanisms after initial 

preprocessing. The sufficient minimal set is thus important for efficient constraint processing, but not for constraint specifications - specifications are more easily expressed with the 

original T-specijkations and F-specihtions. This is why we need both, along with the 

necessary transformations. 

The first step is is to extend F-specifications. 

Definition 4 Define %omplete' T-specifiations as those that list all elements of Definition 

2] including ranges and domains for all finctions and their arguments and compatibilities 

between all pairs mne-domain and range-pmgrarn range. 

Proposition 2 The following F-specification constraints are implied by complete T-specifications: 

vfk,F(Tk is Tj + fk E e) 

vfkeF(Tk Tht + fk f F-) 

:: If fk returns a range which is not compatible with the domain for a specific function 

argument, then fk cannot be used to provide values for the argument. The same applies to 

values returned from the program. 

Proposition 2 is very important because the compatibility T-specijkations (#4 & #5) 

can be automatically generated from other T-specifications, and according to the rule, they 

can be automatically translated to F-spectjications. The latter, as we will see, are easier to 

handle. 

Note that the opposite of these implications is not true since some F-specifiations are 

based solely on interpretations. In other words, it is not true that fk E qJ + Tk j4 Tj. 

Note that the following is not true either: 'tlf&7(Tk =% Tj 3 fk # Fj) (see Example 2). 

Fortunately, the first implication is sufficient for us as it tells us that properly extended F,* 

and F- specifications subsume the T, + T,* and T, + T- T-specifications. 

Example 3 Suppose f = (f1, fa}, u1 = l,u2 = 1. ALSO suppose f1 return ml-ualued 

numbers (TI = R1), and fa takes boolean aqmments (Ti = (F,T}). Because TI j4 Tzl we 

may conclude that f1 cannot be placed as the argument to fa: f1 E Pi. 

Definition 5 If F-specijbtions explicitly satisfy Proposition 2 then call them 'T-extensive' 

F-specifiations. If F-specijkations do not ezplicitLy satisfy Proposition 2 for any function 

fk E F, then call them 'T-intensive' F-specijications. 

In other words, T-intensive F-specijkations list only some additional constraints - which 

cannot be derived from T-specijkations. T-extensive F-specifications, on the other hand, 

are those semantics-based constraints extended by syntactic constraints on function calls. 

For now, we will look at redundancies among F-specifiations. 

11 - 8 
Proposition 3 Suppose fk E F and F-specijications are T-extensive. Then 

:: If a function f; cannot call fk, then fk will never be called by f;. Also, if fk is never 

called from f;, it must not be called from any of f; 's arguments. 

With Proposition 3 one may wonder whether we need both F: and F, constraints - 

they seem equivalent. The next rule says they are not. 

Proposition 4 Suppose fk E F and F-specifiations are T-extensive. Then 

The implication is true only when Proposition 3 applies. 

:: If fk cannot be called from f; by its juI argument, it may possibly be allowed as another 

aqument (unkss, according to Proposition 3, it cannot be called fnmr any of the aryuments). 

Even though they are not equivalent, both are not needed either. It turns out that F: 

F-specifications are stronger. 

Definition 6 If F-specifications explicitly satisfy Proposition 3, call them 'F-eztensive' Fspecificcrtions. If F-specifications do not include any F, constraints, call them 'F-intensive ' 

F-specifi&ions. 

Proposition 5 F-intensive F-specijkations are suficient to ezpress all possible F-specifications. 

:: According to Proposition 3, fk E F; can be deduced when f; is excluded fnmr all aguments of fk. According to Proposition 4, it can happen only when Proposition 3 applies. 

Therefore, F-intensive F-specifications provide sufficient information to produce F-extensive 

F-specifi&ions. 

We now return to the question of T-specificationsvs. F-specifications. We have seen that 

T-intensive F-specifications provide restrictions on function calls based on interpretations, 

and that they can be extended to T-extensive F-specificartions, which also take syntax 

into account. One question that comes to mind is: do we still need T-specijications after 

they have been used to produce T-extensive F-spedjicaticms? In other words, is there any 

constraint in T-speci&ations which is not expressed with T-extensive F-speci$cations? The 

answer is 'no' for certain T-speczfiations. 

Proposition €3 T-extensive F-specifications are sufiient to express Constraints imposed 

by compatibility (#4 d #5) and T, (#2) T-specijhtions. 

:I Let us look at compatibilities of the form Tk 4 Tj. Proposition 2 says that the negated 

forms (#) are all expressed in T-extensive F-specifications. However, the stmight form 

(a) can be superseded by F-specifications, which provide additional constraints based on 

interpretations. Thus, if fk E CJ, then the comsptnading T-specification is irrelevant. On 

the other hand, if fk (in the T-intensive fm), then we have two cases: 

11-9 
e if Tk 

e if Tk =3 T., then we have no mason to extend F-specifications- thus, fk # 53 

qj, then according to Proposition 2 we put fk into e: fk E <j in T-ewive 

forms 

The same can be argved for Tk =$ T-. As to T, T-specifications , they are sets of values 

returned by functions. Therefore, they place restrictions on function calls. But, F-extensive 

F-specifications express all possible restrictions on function calls. Said differently, T, is 

only used for other specifications. 

Definition 7 Define T-extensive F-intensive F-speci&ations as the hormal' form. 

Theorem 1 (Fundamentals of T - and F-specificrrtion constmints) Even if the user provides 

only T-F-intensive F-specifications, T-F-extensive F-specifications can be computed, and 

along with domains and the progmm mnge they are sufficient to express all T- and Fspecification constmints. Moreover, just the normal F-specifications along with domains 

and the progmm mnge are suficient as well. 

:: It follows fmm Propositions 5 and.6. 

Based on Theorem 1, we may now restrict our discussion to F-speci,ficartions only, assuming that these are in the normal form. To make sure they are, a simple preprocessing 

mechanism suffices. 

EXPLORATION OF CONSTRAINT HANDLING METHODS 

We propose to implement the specified constraints into "smart" operators. To do so, 

we must define operators "closed" in the valid program structure - from valid parents 

always generate valid offspring. This will also require an initialization procedure with valid 

programs. 

Definition 8 In the progmm tree, we call 'function nodes' all nodes which correspond to a 

function. In this case, we say that the function labels the node. All other nodes are called 

'terminal nodes'. 

Definition 9 Define TN to be the set of values which can replace node N. That is, TN is 

the set of values that the node can assume without invalidating, w/respect to T-sgeci,ficcrtions 

and F-specijkations , the progntm tree containing that node. 

Definition 10 Define 3N to be the set of functions which can replace node N. That iS, 

3N is the set of functions which can label that node without invalidating, w/respect to Tspecifications and F-specifiations , the pmgmm tree containing that node. 

For terminal nodes, we cannot determine what other possible dues can it contain by 

just looking at the node. We must look at the parent of the node (unless it is the Root). 

For function nodes, we could either use the set of dues returned by the function labeling 

that node (Ti for fi). However, after replacing the function node with a terminal node, we 

11 - 10 
would anyway have to look at the context where the node appears. Therefore, we decided 

to use the context information even for function nodes. 

As the subsequent rules state, the above sets not only can be efficiently computed, but 

some can also be guaranteed to be non-empty under certain conditions, which hold for GP. 

Moreover, in the next section we will see that these sets can be precomputed for all possible 

node types, and that functions to extract random elements of these sets can be precomputed 

as well. This will lead to a very efficient enforcement of these constraints. 

Proposition 7 Assume a node N is the jth ayument off; and F-specifications are normal. 

Then, 

TN = T/ 

3N = {fkl(fk E F) A (fk e e)) 

:: Any value that does not invalidate the domain T! is OK. Any function that is not ezplicitly 

excluded from <3 is OK. This is so because iff; E Fk, that is iff; cannot be accepted as a 

caller to fk, then acconiing to Proposition 3 fk E 

Proposition 8 Assume a node N is the Root and F-specifitions are normal. Then, 

but it is not. 

FN = (fkl(fk E F) A (fk e F-)} 

:: Arguments ape analogous to those for Proposition 7, ezcept that the Root provides the 

constmints. 

Proposition 9 TN # 0 for any terminal node in any valid pmgmm. 

:: The valid progmm does not change when the terminal node is replaced with itself. 

Proposition 10 As long as any function returns a value (as it is in GP), TN # 0 for any 

function node in any valid program. 

:: If the function node is labeled with f;, then it can be replaced with any terminal ft..m T;. 

This set is not empty as long as each function returns at least one value. 

Proposition 11 For any function node N of any valid progmm, 3N # 0. 

:: If the node is labeled With f;, then f; E 3~. 

Note that 3' is not guaranteed to be non-empty for terminal nodes. That is, some 

terminals may only be used for computations, but will never be computed. 

Example 4 Suppose F = {fun>, and fo returns the closest integer to its madvalued argument. Then, To = I, Ti = R1, and T- = I. Also, (fo E Fi) A (fa E Fo) (in the 

T-F-extensive form), but only (fo E Fi) is sufficient (in the normal fm). 

For the program (fo 3.27), the terminal node 3.27 has 7 = I and 3 = 0. 

We can now define closed operators. We assume that all random numbers are taken 

from a uniform distribution. For any node N, denote 

11 - 11 
0 r$ to be a random element from TN 

0 r$ to be a random element from 3N (assuming that it is non-empty) 

For any terminal node N, denote 

0 VN to be the current value from that node 

Mutation 

Assume that node N is chosen for mutation. This selection can be based on a fixed 

probability of mutating any allele in all chromosomes (often called post mutation in GP), 

or on selecting a random allele in a given selected parent (normal mutation in GP). 

Operator 1 (mutation) If a node N is selected for mutation, then replace it with r$ with 

probability pk, or with r$ with 1 - pk. If r; is used, then recursively repeat exactly the 

same Opemtor 1 on all aquments of the selected function. 

If r$ is needed for the node N and the 3N set is empty, try another mndom node fnmr the 

same parent (in normal mutation) or abandon the opemtion (in post mutation). If 4 is 

needed for any descendent of N and the 3N set is empty, use rg instead. 

Proposition 12 For any valid parent program, mutation Opemtor 1 is guamnteed to take 

place as long as pk > 0. For a function node, Opemtor 1 is guaranteed to take place immediately. Moreover, all T- and F-specifiation constmints are guamnteed to be preserved. 

:: The parent is valid. According to Propositions 9 and 10, the set TN is never empty. 

Therefore, as long as this set is allowed in mutation (pk > O), mutation will eventually take 

place on any node. However, if N is a function node, then according to Propositions 10 and 

11 both TN and 3N are non-empty, so mutation will immediately take phce regardless of 

pk. The mutation sets are computed bed on normal F-specijktions, which are suficient 

according to Theorem 1. 

Crossover 

Because crossover with two offspring can be accomplished with two crossover operations, 

each with one offspring, we will define crossover with one offspring. In unconstrained GP, 

there are no specific constraints. Therefore, crossover is reduced to finding two random 

crossover points. In constrained "smart" crossover, the choices of plausible crossover points 

can be highly reduced. Requiring that two offspring can be generated from the same two 

crossover points further reduces chances of finding such points, but can be done if necessary. 

Definition 11 Define SN,, to &e the set of nodes fnmr parent, which can replace a given 

node N selected for crossover. 

Proposition 13 For crossover at node N1 in parentl, and another parenh, 

VN~ + TN, if NZ is a terminal node in parent2 

11 - 12 
:: Crossover may be seen analagous to mutation - jivm parent2 select those crossover nodes 

. which are also allowed in mutation for N1. And TN and 3~ are terminals and functkms 

that the node N1 can mutate into. If N1 = Root then TN, and 3N, are terminals and 

functions that the node Root1 can mutate into. 

Operator 2 (crossover) If parent1 and parent2 are two crossover parents, select a random 

crossover point NI in parentl, except that internal nodes have collective probability of pi 

and leaves have collective probability 1 - p: (following standard GP pnrctice of directing 

crossover into internal nodes). Based on whether N1 is the Root, apply Proposition 13 to 

compute sN1,2. If the set is not empty, then select a random node N2 (leaves and internal 

nodes may be given distinct probabilities with p:), and replace the subtree starting with N1 

with that staring with Nz . If the set is empty, try another crossover point N1 frvm parentl. 

Proposition 14 For any two valid parents, Operator 2 is guaranteed to find valid crossover, 

and the operation will satisfy T- and F-specifications. 

:: Both parents are valid. Therefore, replacing them wholly dl produce a valid oflspring. 

Moreover, the offspring is created by replacing a subtree with another subtree from a set 

computed according to T- and F-specijkations. Therefore, any oflspring will satisfy these 

wnstmints. 

Feasible Initialization Procedure 

Operator 3 (initialization) Initialize the population by growing chromosomes starting each 

with a mndom terminal node N such that VN E T&, and then applying Operator 1 to that 

node. 

Proposition 15 The above initialization routine Operator 3 will only generate individuals 

which are valid with respect T- and F-specification constraints. 

I: Operator 1 guarantees a valid oflsp-ng fnmr a valid parent (Propositions 7, 8). And the 

initial terminal node is valid os the Root. 

IMPLEMENTATION 

Constraint preprocessing 

We do not need terminals T to be explicitly given as in GP - T,, T:, and T- will 

determine individual sets. The preprocessing needed to ensure that F-specifications are 

normal and that our operators can apply can be described as follows: 

1. Read T-, T, ranges for functions of F and T: domains for their arguments 

2. Read T-specification compatibility constraints of the form T, T,* and T, 3 TROOt 

(not necessary if computed automatically) 

3. Read (at least T-intensive F-intensive) F-specificatwns 

11 - 13 
4. Compute normal F-specifications 

5. Produce functions for rr and fl for all necessary sets. 

Given this preprocessing mechanism, the'defined operators can be used in any GP. 

Implementation 

Proposition 16 rr and ? can be precomputed, as part of the preprocessing mechanism, 

into functions returning mndom elements of those sets. 

:: For mutation, we directly need rz and r5. For any mutation, it is detemined in one 

step which of the two is needed. Based on whether N is the Root or not, Proposition 8 or 7 

gives us exactly the sets jbm which the random element is selected. There is a jixed number 

of these sets: there are exactly 1 4- nnEk (aJ of each 7 and 3 sets. All F sets are always 

finite with up to I FI elements, and 7 is either finite, or infinite when domains such 05 mab 

are used. Moreover, these sets never change as GP operates. For the 3 sets, the elements 

can be enumemted and rF can be compiled into a function returning a mndom function f.om 

each enumerated set. For the 7 sets which are infinite, rr can be precompiled to =turning 

a mndom entry jbm the domain. For finite setsl the elements can be enumemted again and 

rr can be compikd into a function returning a mndom element fi.om each enumemted set. 

For sets which are unions of finite or infinite subsets, one may first detemaine which class 

of subsets to choose ftom (assuming that we provide some measures comparing cardinalities 

of finite and infinite sets, or the user provides such information), and then apply one of the 

two above techniques. 

For crossover, we need to use the SN,, sets. However, at each time we know whether 

the node No is a terminal or a finction node, at which moment the problem reduces to the 

same as in mutation - selecting random entries ftom the appropriate 7 or 3 set. Moreover, 

if P: is used, the elements may be divided into two groups fnmr which to select the mndom 

entry - p: would determine which group to we. 

Theorem 2 (Implementation theorem for GP) The defined mutation and crossover OFtions not observing size constraints are as efficient as the standard operators in GP, when 

implemented with the preprocessing mechanism. 

:: In GP, mutation generates a random function from F or a random element of T. 

Crossover selects a random subtree. It follows directly fnnn Ptvposition 16 that in our 

approach any mutation or crossover can be accomplished by selecting a random entry jivm 

a fied set, even though the sets are more plentifd. However, for any node it is deterministic, in a fied time, which set should be wed. 

Conjecture 1 Provided T-specifiations and F-specifications are the maximal constraints 

that can be implemented into a generic constrain pmeessing methodology in GP without 

invalidating Theorem 2. 

:: Other Constraints will require information about a node position in a tree - pmcessing 

complexity would be a function of tree depth. 

11 - 14 
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[4] Kenneth E. Kinnear, Jr. (ed.) Advances in Genetic Prqmmming. The MIT Press, 

1994. 

[5] John R. Koza. Genetic Pmgmmming. The MIT Press, 1992. 

[SI John R. Koza. Genetic Programming II. The MIT Press, 1994. 

[7] Zbigniew Michalewicz & Cezary Z. Janikow. "GENOCOP: A Genetic Algorithm for 

Numerical Optimization Problems utith Linear Constraints". To appear in Communications of the ACM. 

[8] J.T. Richardson, M.R. Palmer, G. Liepins & M. Hilliard. "Some Guidelines for Genetic Algorithms with Penalty Functions". In Proceedings of the Third International 

Conference on Genetic Algorithms. Morgan Kaufmann, 1989. 

11 - 15 
ORBITER FLIGHT DECK REDESIGN 

(A PHYSICAL LAYOUT FOR A FUTURISTIC FLIGHT DECK) 

Final Report 

NASNASEE Summer Faculty Fellowship Program--1995 

Johnson Space Center 

Prepared By: 

Academic Rank: 

University & Department: 

NASNJSC 

Directorate: 

Division: 

Branch: 

JSC Colleague: 

Date Submitted: 

Contract Number: 

Mehrzad Khorsandi 

Assistant Lecturer 

Texas A&M University 

Civil Engineering Dept. 

Engineering Design Graphics 

College Station, TX. 77843 

Space and Life Sciences 

Flight Crew Support 

Graphic Research and Analysis 

Facility (GRAF) 

James Maida 

October 30,1995 

NGT-44-00 1-800 

12-1 
ABSTRACT 

The purpose of this summer project was to develop a set of schematic drawings for 

resdesign of the Space Shuttle flight deck from which a three dimensional computer 

drawings can be built and viewed in a virtual environment. In order to achieve this goal, 

first recommendations for overall redesign of Space Shuttle previously made by experts in 

the field were reviewed and relevant information were extracted and delineated. Original 

drawings of the Space Shuttle made by Rockwell were obtained and carellly examined. 

In order to implement and assess any modifications in terms of space saving parameters, it 

was determined that the drawings alone could not achieve this objective. As a complement, 

physical measurements of the mockup of Space Shuttle flight deck were made and the 

information was categorized and properly labeled on the original drawings. Then, spacesaving redesign ideas, as motivated by expert recommendations on such things as 

information display panel upgrade by technologically advanced flat display units, were 

implemented. Next, the redesign ideas were executed on the Forward flight deck, Overhead 

Console, Right and Left Console, and Center Console. A new 3-D computer drawing of this 

was developed by modifying the existing drawing on the in-house developed software 

(PLAID). Finally, the drawing was transported to a Virtual Environment and observed. 

12-2 
INTRODUCTION 

Background: 

In order to keep Space Shuttle operating smoothly in the hture, the current cabin, 

its equipments, and its operation should be redesigned. The new futuristic cabin which 

includes the latest and the most advanced technological equipments should help operate 

the Space Shuttle in a more suitable, reliable, economical, and safe manner. The Orbiter 

Advanced Cabin Design has been under consideration for many years and many studies 

have been done to satis@ this need. Some of the major issues in this relation are: 

1) The cabin equipments and flight crew's use of them are archaic; 

2) The cost of operation and maintenance through the use of the current obsolete 

3) Use of new, more advanced, and lighter weight equipment could help achieve cabin 

4) Use of more advanced information systems could result in crew size reduction; and 

5) The expected one billion dollar budget cut in the Space Shuttle program for 1996 

equipment are considerably high; 

weight reduction allowing for higher payload to be hauled to the orbit; 

fiscal year makes cost cutting measures more imperative. 

The archaic equipment currently used in the Space Shuttle are heavy and 

occupied large volume as compared to the most advanced technological equipments. 

For example, the bulky Cathode Ray Tubes (CRT) used as display in the Forward flight 

deck can be replaced with modem light weight and flat display units. The focus of this 

Summer project was to redesign the interior of the flight deck to increase space and 

decrease weight, taking advantage of these technological advancements. 

Objectives: 

The first objective of this project was the preliminary design of the flight deck 

based on the recommendations previously made by the experts in the aeronautic and 

avionic field. The second objective was to prepare a computer model of the proposed 

changes to the flight deck which could be viewed in virtual environment for review and 

possible modifications. 

EXPERTS RECOMMENDATIONS 

To become familiar with the background of the flight deck redesign and arrive at 

the objectives of this project many NASA memos were provided which were mostly cost 

saving recommendations of the experts of the field for the space shuttle. Also many 

more articles and books were recommended as references. Even though some of them 

were very hard to find in short period of time but they were all very useful to the design 

process. 

12-3 
There were two types of expert recommendations provided along with the project 

description, to reduce the operating and maintenance cost of the Space Shuttle. The first 

type were general recommendations for a futuristic Space Shuttle as a whole. The 

second type were specific recommendations for a futuristic flight deck. A summary of 

these follows. 

General Recommendations 

These recommendations were made based on the goal of 50% reduction in the 

Space Shuttle maintenance and operating cost. 

1) Use of integrated navigation system 

2) Use of electronic integrated orbiter. 

3) Use of Multifunction Electronics Display Subsystem. 

4) Use of Fiber-Optics. 

5) Use of Star Tracker Cameras 

6) Use of Solid State Data Recorders. 

7) Use of &-Board Automation. 

8) Use of Electronic Voice Communication. 

9) Crew size reduction. 

Expert Recommendations Specifically for Flight Deck 

1) Removal of the Center Console. 

2) Removal of the two Side Consoles. 

3) Removal of the Over Head Console. 

4) Reduction of window acreage. 

5) Flattening of the Forward Station (based on the use of the most advanced and less 

space taking equipment). 

6) Flattening the AFT Station. 

7) Cockpit Redesign / Flightcrew Escape. 

THE DESIGN PROCESS 

The design process consisted of two phases. The first phase was to incorporate 

the expert recommendations for the redesign of the flight deck and present them in the 

form of sketch. This phase took the major part of the summer work. The second phase 

consisted of taking only the space saving ideas for the Forward flight deck from the first 

phase and implementing and incorporating them in an existing 3D drawing of flight 

deck. 

12-4 
First Phase of Design 

The first phase needed much of the data gathering and data organization, physical 

measurement of the mockup, and study of the original drawings of the flight deck to 

clearly understand the space we were to work with and design. These drawings were 

prepared nearly thirty years ago by Rockwell and they are currently used on an every day 

basis for any alteration or maintenance to the Space Shuttle. The last part of this phase 

included sketching of the redesign ideas. 

Data Gathering- Several references in form of NASA memos were provided, 

along with the problem statement. These were studied along with other relevant books, 

articles, and memos. Although the acquisition of data and documents was sometimes 

difficult and time consuming, partly due to sensitive nature of some of them, the overall 

process was a beneficial learning experience. This was an essential stage in the design 

process for becoming familiar with the space and area one has to work with. It also 

helped to set the stage for the next step of design which was the actual mockup 

measurement. 

Studv of the Original Drawings of the Flight Deck- In order to understand the 

working space (space to be redesigned) within the flight deck the original drawings of the 

flight deck by Rockwell were obtained. These drawing were specially useful in 

providing information about the hidden spaces, which are commonly located under the 

panels that are to be replaced with more advanced equipment. However, the fact that 

some of the drawing are very hard to locate, their sizes are not practical for this kind of 

overall redesign. In order to read original flight deck's drawing one must become 

familiar with zero base origin for X, Y, and Z coordinates used throughout the Rockwell 

drawings for flight deck, and at all time take those into account (See Figure 1). Still the 

exact or even the approximate sizes of the working space (space to redesign) within 

flight deck could not be easily obtained from the origural drawings. While dimensions 

for some of the individual pieces were given on separate drawings but the overall 

drawings (Isometrics, sections, and complete views of flight deck such as Forward and 

Aft) lacked dimensions and specifications. Therefore, after the study of these drawings it 

was concluded that it would be more efficient to do an actual measurement of the 

mockup as describe below. 

Phvsical Measurement of the Mockup. The physical measurement of the mockup 

and identification of its panels started by visiting the building (building 9B) where most 

mockups are located and video taping the flight deck, mid deck and other relevant areas. 

The video tape was viewed in order to determine the significant areas to be measured. 

The actual measurements and part identification of the flight deck took place for a few 

days on regular basis with the help of some of the engineers on sight. In addition to 

resolving some of the obscure points in the original drawings, physical measurement of 

the mockup was very useful in gaining better understanding and becoming more familiar 

with the redesign of the spaces under study. 

12-5 
m.00 

x, 374 

xo -7 

Baseline Floor Plan of the Flight Deck 

Baseline Section of the Flight Deck 

Figure I. Base Line Drawings (X, Y, and 2 Coordinates) of the Flight Deck and Their 

origin (Measurements Reference), Rockwell Drawings. 

12-6 
Figures 2 through 5 show the results of physical measurements of the mockup. 

. Each figure is followed by an identical figure on which the location of permanent panels 

are identified and labeled. Unmarked panels are mission-specific. Some of the 

permanent panels are subject to future replacement by more advanced equipment saving 

weight and space and., as a result, cost. 

Redesign Recommendations- The following recommendations along with quick 

sketches were made at the end of this phase of the design. 

1) Flattening the Forward flight deck. The use of flat display panels to replace the 

existing bulky CRTs. The current dept of the Forward flight deck would be modified 

to a less space taking panels. This gained space could allow for the pilot and 

commander seats to be moved further to the front. (See Figure 6) 

2) Flattening of the AFT flight deck could be another way to save more usable space 

because the flight deck is at its highest around the AFT station. (See Figure 6) 

3) Removal of the Right and Lefi Console could provide a better movement space for 

the pilot and the commander while seating but not much space is gained in the height 

direction. (See Figure 6) 

4) Removal of the center console could provide for one additional seat in front for the 

mission specialist but it really would take away from the easy communication 

between the commander and the pilot. It can be heightened and converted to a 

separate work space for mission specialist. (See Figure 6) 

5) Removal of the overhead console could be the most usefid height-saving idea. It 

allows for gain in height and opens up the overhead space for more scape panels. 

(See Figure 6) 

6) Adding escape panels to the overhead area right above the pilot and the commander 

seat (converting all seats to ejectable and repositionable by 90 degree seats). These 

panels would function just like the current overhead window providing additional 

height. (See Figure 6) 

7) Design and develop new space saving ejectable seats that can be folded in the floor 

of the flight deck. This idea requires raising of the flooring of the flight deck which 

becomes possible after the height gained with the creation of the overhead escape 

openings. The ejectable seat when not in use should fold in the floor. This would 

provide for more space for specific missions that need them and for easier movement 

of the crew members. 

Second Phase of Design 

The second phase of design concentrated on the space saving ideas for the 

Forward flight deck (flattening it), Right and Left Console (removing them), and 

Overhead Console (removing it). (See Figures 7). Most of the redesign ideas in this 

phase are short-term modifications that do not require any changes to the main body of 

the flight deck. Therefore, they are interior space saving ideas. These ideas are mostly 

taken fiom the previous phase and were given scale and coordinates to 

12-7 
Flight Station Forward Console Dimensions 

Flight Deck Forward Console Panel Identification 

Fimwe 2. Flight Station Forward Console's Dimensions and Panel Identification. 

12-8 
Flight Deck Center Console Panel Identification 

Fiewe 3. Flight Station Center Console's Dimensions and Panel Identification. 

12-9 
-1 

Flight Station AFT Station's Dimensions 

Flight Deck AFT Station Panel Identification 

Figure 4. Flight Deck AFT Station's Dimensions and Panel Identification. 

12-10 
Flight Deck Floor Plan (Existing Arrangement) 

Flight Deck in Section (Dimensions) 

Figure 5. Flight Deck Existing Floor Arrangements and Dimensions. 

12-1 1 
Flight Deck in Section (Redesigned Arrangement) 

Figure 6. Flight Deck's Proposed Space Saving Floor Pian Arrangement. 

12-12 
Flight Deck Existing Arrangement 

Flight Deck Proposed New Arrangement 

Figure 7. Flight Deck Forward, Side Consoles, Overhead, and Center Console 

Arrangements. 

12-13 
be incorporated on a 3D existing computer drawing of the flight deck. The existing 3D 

computer drawing were originally created through the use of an in-house developed 

software called PLAID. This of the GRAPH Lab 

staff. After modification of em redesign ideas, 

the revised 3D drawing was viewe 

helpful tool in getting the feel of the newly created space without having to build a 

physical model. It can also be used for future modification by a virtual experience of the 

actual spaces. The 111 potential of this tool is yet to be realized. 

CONCLUSIONS AND FUTURE RECOMMENDATIONS 

Redesign of the Space Shuttle flight deck is a process that requires coming 

together of many different components. In this project we focused on defining and 

testing some steps for implementation of this task with particular attention to spacesaving concepts . Expert recommendation for overall redesign of Space Shuttle were 

reviewed and relevant information were extracted and delineated. Original drawings of 

the Space Shuttle made by Rockwell were obtained and careklly examined. In order to 

implement and assess any modifications in terms of space saving parameters, it was 

determined that the drawings alone could not achieve this objective. As a complement, 

physical measurements of the mockxp of Space Shuttle flight deck were made and the 

information was categorized and properly labeled on the original drawings. Then, spacesaving redesign ideas, as motivated by expert recommendations on such things as 

information display panel upgrade by technologically advanced flat display units, were 

implemented. Next, the redesign ideas were executed on the forward flight deck, 

overhead console, right and left console, and center console. A new 3-D computer 

drawing of this was developed by modifying the existing drawing on the in-house 

developed software (PLAID). Finally, the drawing was transported to a Virtual 

Environment and observed 

In order to perform the complete process of redesigning the flight deck exactly, a 

complete detailed electronic 3-D computer model of the entire current base-line Shuttle 

flight deck (FWD and AFT) is needed. Such a model could be used for the redesign and 

mer analysis of the Space Shuttle Flight Deck. It should have a data base that would 

allow the user to be able or remove or attach any part(s) within the 3-D model and 

accurately asses the amount of space (e.g., in cubic feet) and weight (e.g., in pounds) 

gained or lost. Then redesign idea could be applied much more easily and the changes 

would be estimated more precisely. 

12-14 
REFERENCES 

(1) "Advanced Trends in Avionics," Jim Curran, Iowa State University Press, 1992. 

(2) Shuttle Avionics Upgrade Investigations, date 7/26/93, Naval Air Warfare Center, 

Aircraft Division, Indianapolis, IN. 

(3) Clementine: "An Experiment to Flgith Quality Lightweight Space Technologies," 

Pedro L. Rustan. 

(4) JSC memo ACS-90-49, date 1 1/28/90, "Orbiter Advance Displays". 

(5) JSC memo ACS-94-02, dated 1/10/94, "What Is Obsolete Around Here?" 

(6) JSC memo ACS-93-28, dated 9/2 1/93, "What Ligquid Oxygen/Hydrogen 

Explosion Explosion Tests Are Telling Us" 

(6) "Access to Space-Option 1," Final Presentation to Arnold Aldrich, 8/24/93. 

12-15 
FLUID DYNAMIC VERIFICATION EXPERIMENTS ON STS-70 

Final Report 

NASNASEE Summer Faculty Fellowship Program- 1995 

Johnson Space Center 

Prepared By: 

Academic Rank: Associate Professor 

Stanley J. Kleis, Ph.D. 

University and Department: 

NASNJSC 

Directorate: 

Division: 

Branch: 

JSC Colleague: 

Date Submitted: 

Contract Number: 

University of Houston 

Department of Mechanical 

Engineering 

Houston, TX 77204-4792 

Space and Life Sciences 

Medical Sciences 

Biomedical Operations 

and Research 

Neal R. Pellis, Ph.D. 

August 9, 1995 

NGT-44-001-800 

13-1 
ABSTRACT 

Fluid dynamic experiments were flown on STS-70 as phase two 

of the engineering evaluation of the first bioreactor Engineering 

Development Unit (EDU#l). The phase one experiments were 

comparative cell cultures in identical units on earth and onboard 

STS-70. In phase two, two types of fluid dynamic experiments were 

performed. Qualitative comparisons of the basic flow patterns were 

evaluated with the use -of "dye" streaklines formed from alternate 

injections of either a mild acid or base solution into the external 

flow loop that was then perfused into the vessel. The presence of 

Bromothymol Blue in the fluid then caused color changes from yellow 

to blue or vice versa, indicating the basic fluid motions. This 

reversible change could be repeated as desired. In the absence of 

significant density differences in the fluid, the flow patterns in 

space should be the same as on earth. Video tape records of the flow 

patterns for a wide range of operating conditions were obtained. 

The second type of fluid dynamic experiment was the 

quantitative evaluation of the trajectories of solid beads of various 

densities and sizes. The beads were introduced into the vessel and 

the paths recorded on video tape, with the vessel operated at various 

rotation rates and flow perfusion rates. Because of space 

limitations, the video camera was placed as close as possible to the 

vessel, resulting in significant optical distortion. 

This report describes the analysis methods to obtain 

comparisons between the in-flight fluid dynamics and numerical 

models of the flow field. The methods include optical corrections to 

the video images and calculation of the bead trajectories for given 

operating conditions and initial bead locations. 

13-2 
INTRODUCTION 

The bioreactor development team at NASNJSC is responsible 

for the development of a complete cell cultivation system capable of 

growing and maintaining anchorage dependent cells in a microgravity 

environment for extended periods of time. The bioreactor system 

provides control of many parameters required for the successful cell 

culture while suspending the cells in a fluid environment that 

allows three dimensional assembly. The present report will address 

only the fluid dynamics within the culture vessel. 

Space flight experiments in STS-70 were scheduled for June, 

1995, for the bioreactor developed at NASNJSC. Unfortunately, the 

flight was delayed by schedule conflicts with STS-71 and technical 

problems due to woodpecker damage of the external tank insulation. 

Two sets of experiments were scheduled; cell growth experiments 

and fluid dynamic verification experiments. 

The current bioreactor vessel design is based in part on the 

viscous pump reactor vessel developed jointly by NASNJSC and Dr. 

S. Kleis of the Turbulent Shear Flow Laboratory (TSFL), University of 

Houston [l]. The basic elements of the vessel are shown in Figure 1. 

A three dimensional flow field is established by rotating the outer 

cylinder and spin filter at different rates. Fluid enters the vessel 

from the external flow loop, in the gap between the left vessel end 

and the disc. It then circulates within the vessel before being 

extracted through the porous spin filter. 

disc 1 outer cylinder 

flow 

f ilt er 

exit 

Figure 1 .- EDU#1 Bioreactor Flow Fields Elements. 

13-3 
As part of the development of the current vessel design, a 

numerical model of the flow field within the vessel has been 

developed. The model has previously been verified under a wide 

range of operating conditions in a unit gravity environment by 

extensive measurements of the velocity fields and flow 

visualizations at TSFL. The purpose of the fluid dynamics phase of 

the flight experiments was to verify the model under microgravity 

conditions. 

An accurate model of the fluid flow field is required to be able 

to predict mass transport within the vessel to be able to separate 

effects of changes in cell hydrodynamic environment from 

microgravity effects on cells. In the presence of body forces, 

density differences between the cells attached to micro carriers and 

the fluid medium cause relative motions, resulting in both 

mechanical shear and increased mass transport. In the microgravity 

environment, buoyancy effects are greatly reduced; the normal earth 

gravity is replaced by centripetal acceleration as the dominant body 

force. For a typical rotation rate of 2 rev/min in a 5 cm diameter 

vessel, the magnitude of the body force is reduced to approximately 

0.001 m/s2 compared with gravitational acceleration of 10 m/s2 on 

earth. In the absence of other factors, cells would go from a 

convection dominated mass transport regime on earth to a diffusion 

dominated regime in microgravity. However, the viscous pump 

bioreactor vessel has been designed to provide a steady three 

dimensional flow field with controllable rates of shear. This allows 

the establishment of local velocity gradients. The local shear flow 

about the cells can provide control over the mass transfer rates. It 

is expected that, for most cell types, the shear rates required for 

adequate mass transport is well below the shear rates that causes 

damage to the cells by mechanical stress. In fact, it is expected 

that the shear rates for good mass transport are much lower than 

the stresses due to cells on micro carriers falling at terminal 

velocity in earth's gravity. If these characteristics are 

demonstrated, the bioreactor can be used to study the effects of 

controlled stress levels on cell function as well as a low stress 

environment for studies of direct gravity effects on cells. 

The objectives of the fluid dynamic experiments conducted on 

STS-70 are two fold. First, flow visualizations of flow fields 

established under a wide range of operating conditions will be 

compared with similar tests previously performed at TSFL. Since 

13-4 
these tests are performed with nearly uniform density, the results 

can be compared directly with ground based experiments. The 

second set of fluid dynamic experiments records the positions of 

beads with diameters of from 1 to 3 mm moving within the 

bioreactor vessel. The trajectories of these particles were video 

taped for several different inner and outer wall rotation rates and 

for several perfusion rates. Unlike the flow visualization tests, 

these experiments will produce results that can not be obtained on 

earth. The results of these experiments will also be compared with 

the numerical model. Differences in the predicted and measured 

results will provide guidance for modifications to the numerical 

model. 

OPTICAL DISTORTIONS 

Conducting experiments on the mid-deck of a shuttle imposes 

additional constraints on the experiment design. Weight and volume 

limitations require careful consideration of available supplies and 

often change procedures. For the fluid dynamic experiments, space 

considerations meant mounting the video camera as close as 

possible to the vessel to minimize interference with the crew and 

other hardware (such as the main hatch, located just to the right of 

the EDU locker). This required the use of a 3X macro lens, which 

introduced additional optical distortion (the 'fish eye' effect) into 

the images. in addition, the bioreactor vessel itself is made of a 

clear polycarbonate and is filled with a cell culture medium with a 

refractive index near that of water. The refraction of light by the 

vessel acts as a cylindrical lens, distorting the apparent positions 

of cells and beads in the vessel. This effect was greatly reduced by 

placing an optical correction lens made of polycarbonate between 

the vessel and camera. The lens had a cylindrical surface slightly 

larger than the vessel on one side and a flat surface on the camera 

side as shown in figure 2. 

The macro lens distortion can be removed from the position 

data if the type of distortion is known. If the lens is a simple lens, 

then the distortion can be approximated as a simple spherical 

distortion resulting from objects being different distances from the 

center of the lens. 

13-5 
I 1 

optical 

correct ion 

Figure 2.- Optical configure for EDU#I videos. 

For a simple 'thin' lens, the object plane distance Q and the 

image plane distance I, are related to the lens focal length F by the 

relation, 

111 

F-5 I 

-- + -. 

The height of an object in the image plane is the related to the 

height in the object plane by a similar relation, since 

- yo =a* 

01 

Assuming that points on a spherical object plane are imaged on a 

flat image plane, a point at a location (x, y) on a flat object a 

perpendicular distance 0 from the lens would have a position (x', y') 

in the image plane, given by, 

x'= .+ 

Q2 + x2 + y 

and 

13-6 
3- 
POSITION ESTIMATES 

As discussed above, the relative motion bet en the fluid and 

the cells on microcarriers can have a dramatic e t on the amount 

of mass transport to and from the cells. In the absence of gravity or 

other body forces to drive convection currents, mass transport in a 

fluid without shear relies on diffusion. A solid sphere in a viscous 

flow field with shear will have a region of fluid that surrounds and 

moves with the sphere (a closed stream surface). When shear is 

present, the distance over which diffusion takes place is reduced 

and concentration gradients that drive the diffusion are increased. 

In a rotating vessel, the shear and relative motion caused by density 

differences in the centripetal acceleration field will 

non uniform flow field is {2], 

13-8 
m A=mf----l dV. Du, d 

dt Dt dt m, -{Vi - ui - &a2V2ui} - 6mp{Vi - ui} + m3pV2ui 

Where mp is the mass of the particle, mf is the mass of fluid 

displaced by the sphere, a is the sphere radius, Vi is the i th sphere 

velocity component, Ui is the corresponding fluid velocity component 

evaluated at the current position and time, and p is the fluid 

viscosity. Note: The Basset history integral term, which accounts 

for the transient decay of the initial conditions, has been neglected 

in this equation. 

When performing a force balance in cylindrical coordinates, 

the proper equations relating the net force to time rates of change 

of position are: 

d2 z and F, =m - 

dt! dtdt dt! ‘ 

Normalizing, the resulting component equations are: 

(l+ $E)( rdae + 2 ““1 = 

at? drdt 

and 

13-9 
Ro=2 cm, Z0=2.2 cm 

2.5 

2 

1.5 

1 

0.5 

0 

0.3 0.65 1 

1, 1 

-1 0 1 

Ro=2.2 cm, Z0=3 cm Ro=2.3 cm, Z0=3 cm 

2.5 

2 

1.5 

1 

0.5 

0 

3 0.65 1 

1 1 

0.5 0.5 

0 0 

-0.5 -0.5 

-1 -1 

-1 0 1 -1 0 1 

Figure 5.- Particle Trajectories for three initial particle positions 

(shown above figures) for case of disc rotation rate = 11 rpm, 

linder rotation rate 0.5 rpm, perfusion = 0 ccfmin, bead 

diameter = 3.175 mm, ps/pf = 1.045. Total time = 5 min. 

13-1 0 
Ro=2 cm, Z0=2 cm 

0.5 

0. 

-0.5 

0.3 0.65 1 

- 

* 

Ro=2.3 cm, &=3 cm 

0.3 0.65 1 

1, 

0.5 0.5 

0 0 

-0.5 -0.5 

-1 -1 

-1 0 1 -1 0 I 

Ro=l ,875 cm, &=I .875 cm 

0.3 0.65 

lr 1 

-1 

-1 

- 

0 1 

Figure 6.- Heavier particle trajectories for three initial particle 

positions (shown above figures) for the case of disc rotation rate = 

11 rpm, outer cylinder rotation rate = 0.5 rpm, perfusion = 0 cc/min, 

bead diameter = 3.175 mm, pslpf = 1.18. Total time = 5 min. 

13-1 1 
Ro=2 cm, Z0=3.75 cm Ro=1.8 cm, Zo=l .5 cm Ro=2 cm, &=2 cm 

0.5 

0. 

-0.5 

0.3 0.65 1 

. 0.5 . 0.5 . 

0. 0. 

. -0.5 . -0.5 . 

0.3 0.65 1 

11 i 

- I 

0.3 0.65 1 

11 1 

-1 0 1 -1 0 1 -1 0 1 

Figure 7.- Heavier particle trajectories for three initial particle 

positions for the case of disc rotation rate = 6 rpm, outer cylinder 

rotation rate 3: 1.0 rpm, perfusion = 10 cc/min, bead diameter = 

3.175 mm, ps/pf = 1.18. Total time = 10 min. 

13-1 2 
-1 -1 

Figure 8.- Heavier particle trajectory for initial particle position 

(1.8 cm, 0, 1.5 em) for the case of disc rotation rate = 6 rpm, outer 

cylinder rotation rate = 1.0 rpm, perfusion = 10 cc/min, bead 

diameter = 3.175 mm, ps/pf = 1.18. Total time = 10 min. 

In these equations the fluid and sphere velocities have been 

normalized by the characteristic velocity, U, the larger of the tip 

velocity of the disc or outer cylinder, and the length scale used was 

r2, the radius of the outer cylinder of the bioreactor (2.5 cm for the 

current design). The subscripts s and f refer to the sphere or fluid, 

respectively. 

These equations were solved using a forth order Runga-Kutta 

method for the position coordinates as functions of time using the 

fluid velocities computed by a previous numerical model for steady 

fluid motion. Figures 5, 6, and 7 show the bead trajectories in side 

13-13 
views, (r, z) planes, in the top figures and top views, (r, 9) planes, in 

the lower figures. In each figure, three initial bead positions are 

shown. Figure 5 represents the conditions used for the cell 

experiments on STS-70, with a bead density ratio near that of cells 

on microcarriers. Figure 6 is for the same operating conditions, but 

for a bead whose density ratio and size match the bead used in the 

fluid dynamic experiments of STS-70. Figure 7 is for a lower 

rotation rate, typical of future cell studies. In all cases, the bead is 

suspended in the fluid (stays off the outer wall) with significant 

axial and radial motions. Figure 8 shows a perspective view of the 

three dimensional bead motion. 

It is interesting to note that the equations of motion show 

that neutrally buoyant larger beads in a general three dimensional 

flow field will not follow the streamlines. The terms including the 

Laplacian of the fluid velocity do not approach zero as the bead 

density approaches that of the fluid. Thus, a zero relative velocity 

is not a solution for neutrally buoyant bead. These terms do 

approach zero in the limit of small bead size. This is a reflection of 

the differences between a rigid sphere and a deformable fluid 

element. 

Several test cases have been used to verify the accuracy of the 

bead position calculations. These include flow fields for solid body 

rotation and simple Couette flow with infinitely long cylinders. The 

results agreed as expected. Unfortunately, there is no known exact 

solution which has all three velocity components. The predictions 

do, however, behave properly (follow streamlines) for the case of 

small beads in a computed three dimensional flow. 

CONCLUSONS 

It has been shown that a simple spherical optical correction 

for the macro lens is adequate for processing bead position data. 

Estimates of the out-of-plane coordinate will be necessary to 

process the bead position results from STS-70. 

Bead position predictions based upon previous numerical 

models of the flow field and force balances on the beads have been 

developed for comparison with the flight experiments. The flight 

experiment video tapes have just become available. However, 

preliminary results indicate that the predicted trajectories look 

qualitatively similar to the bead trajectories observed in the down 

13-1 4 
linked videos from the flight experiments. More quantitative 

comparisons are being made. 

REFERENCES 

1. "A Viscous Pump Bioreactor," S. Kleis, S. Schreck, and R. 

Nerem, Biotechnoloav and Bioenaineering, Vol. 36, pp. 771 -777 

(1 990). 

2. "Equation of Motion for a Small Rigid Sphere in a Nonuniform 

Flow," M. R. Maxey and J. J. Riley, Phvs. Fluids, 26, pp. 883-889, 

(1 983). 

13-15 
LCTV HOLOGRAPHIC IMAGING 

Final Report 

NASA/ASEE Summer Faculty Fellowship Program - 1995 

Johnson Space Center 

Prepared By: 

Academic Rank: 

Jerome Knopp, Ph.D. 

Associate Professor 

University & Department: The University of Missouri-Columbia/Kansas City 

CEP Electrical and Computer Engineering Dept. 

Kansas City, Missouri 641 10 

NASA/JSC 

Directorate: 

Division: 

Branch: 

JSC Colleague: 

Date Submitted: 

Contract Number: 

Engineering 

Avionic Systems 

Electromagnetic Systems and Navigational Sensors 

Richard D. Juday 

October 26, 1995 

NGT-44-001-800 

14-1 
ABSTRACT 

Astronauts are required to interface with complex systems that require 

sophisticated displays to communicate effectively. Lightweight, head-mounted 

real-time displays that present holographic images for comfortable viewing may 

be the ideal solution. We describe an implementation of a liquid crystal 

television (LCTV) as a spatial light modulator (SLM) for the display of 

holograms. The implementation required the solution of a complex set of 

problems. These include field calculations, determination of the LCTV-SLM 

complex transmittance characteristics and a precise knowledge of the signal 

mapping between the LCTV and framegrabbing board that controls it. Realizing 

the hologram is further complicated by the coupling that occurs between the 

phase and amplitude in the LCTV transmittance. A single drive signal (a gray 

level signal from a framegrabber) determines both amplitude and phase. Since 

they are not independently controllable (as is true in the ideal SLM) one must 

deal with the problem of optimizing (in some sense) the hologram based on this 

constraint. Solutions for the above problems have been found. An algorithm 

has been for field calculations that uses an efficient outer product formulation. 

Juday's MEDOF (Minimum Euclidean Distance Optimal Filter) algorithm used 

for originally for filter calculations has been successfully adapted to handle 

metrics appropriate for holography. This has solved the problem of optimizing 

the hologram to the constraints imposed by coupling. Two laboratory methods 

have been developed for determining an accurate mapping of framegrabber 

pixels to LCTV pixels. A friendly software system has been developed that 

integrates the hologram calculation and realization process using a simple set 

of instructions. The computer code and all the laboratory measurement 

techniques determining SLM parameters have been proven with the production 

of a high quality test image. 
LCTV HOLOGRAPHIC IMAGING 

Astronauts are required to interface with complex systems that require 

sophisticated displays to communicate effectively. Display systems that can 

render 3-D objects offer significant advantages over 2-0 displays for certain 

types of information. Holographic images with true parallax provides a high 

quality image that can be observed for long periods of time without the 

discomfort that sometimes occurs in conventional stereograms. Furthermore, 

a single hologram can replace a complex optical system and can reduce the 

weight and the number of optical components. Compact lightweight optical 

systems are the key to building practical head-mounted display systems that 

are attractive for astronaut use. Holographic displays can simultaneously 

incorporate the optics and the imaging device in a single element. The ideal 

holographic display is a high resolution spatial light modulator (SLM) with realtime imaging capability. One particular attractive and economic SLM that has 

real-time capability is liquid crystal television (LCTV). We describe here an 

implementation of an LCTV for the display of holograms. This implementation 

required the solution of a complex set of problems. These include field 

calculations, determination of the LCTV-SLM complex transmittance 

characteristics and a precise knowledge of the signal mapping between the 

LCTV and framegrabbing board that controls it. Realizing the hologram is 

further complicated by the coupling that occurs between the phase and 

amplitude of the LCTV. A single drive signal (a gray level signal from the 

framegrabber) determines both amplitude and phase. Since they are not 

independently controllable one must deal with the issue of optimizing (in some 

sense) the hologram based on this constraint. The solutions for these problems 

is discussed below. 

MEASUREMENT OF THE LCTV COUPLING CURVE 

Before the LCTV can be used as an SLM the amplitude and phase 

characteristics of its complex transmittance must be determined by laboratory 

measurement. The LCTV screen is operated between two polarizers; the angles 

of the polarizers determine the SLM characteristics. Each combination of 

polarizer angles determines a unique SLM operating curve. The gamut of 

operating curves varies considerably and includes highly coupled, phase-mostly 

and amplitude-mostly curves. But in all cases the phase and amplitude are not 

independent; they are controlled by a single signal, a gray level value from a 

framegrabber board. In order to assure high light throughput and a bright 

image, the polarizers were set for phase-mostly operation. This was not 

necessarily the best choice of SLM curve in terms of image quality but it did 

assure that the image would be easy to locate. The polarizer angles for phasemostly operation were determined by previous experiences with other LCTV 

cells ’. 

14-3 
SLM Measurements 

The determination of the SLM curve was based on separate measurements of 

the amplitude and phase characteristics as a function of gray level value. The 

amplitude transmittance was determined from intensity transmittance 

measurements of a helium-neon laser beam passing through the LCTV. The 

relative phase transmittance was inferred from fringe shifts measurements 

made with a grating interferometer. This approach is described in detail 

elsewhere ' . The shift measurements were made from framegrabbed images 

of fringes. In the past, ad-hoc techniques requiring a mix of computer analysis 

and human intervention were used to determine the shifts by examining null 

positions in the pattern. Because the patterns are noisy and are not uniform in 

amplitude variation across the fringe image the null positions can be difficult to 

define. This required determining null neighborhoods by eye an then using the 

computer to fine tune the search process. A new approach was tested that 

avoided the search process. 

Algorithms for Fringe and Phase Analysis 

A first attempt was made at developing software that carried out the fringe 

analysis completely without human intervention. The fringe periodicity and the 

shift were determined using correlation. The correlations produced fairly 

smooth curves with clearly defined maxima and minima. The fringe pattern 

with the greatest contrast was. used as a base on which to correlate other 

shifted patterns. The proper scale relation between fringe shift and phase shift 

was determined by an accurate measurement on the periodicity of fringe 

patterns. The average periodicity from the autocorrelations of all the fringe 

patterns gave a good estimate of the period. This was done using the Matlab 

m-file SM0OTH.M. The shift in the peak (global maxima) of the. crosscorrelation of all the patterns with the reference fringe pattern determined the 

relative phase shift. The technique worked well with noisy fringe data with 

only one caveat. The non-uniformity in the fringe contrast sometimes results 

in large jumps of nearly one period in the peak position due to small differences 

in local maxima. This was fixed by linearly interpolating phase shifts where 

large jumps occurred. The m-file FRlNGE4.M calculated the cross-correlations 

and the peak shifts. The program has only been used on one data set and 

needs further testing. But it ran without any problems and produced data that 

appeared consistent with the observed fringe shift measurement estimated by 

ruler and eye. 

CALCULATION OF A REALIZABLE HOLOGRAM 

Most of the past work in calculating fields for computer enerated holograms 

is associated with farfield or Fourier transform holograms$43. This is primarily 

due to the low resolution of SLMs available and the low resolution requirements 

14-4 
of Fourier transform holograms. There is not a significant corresponding body 

of work on nearfield computer generated holograms. The general problem for 

calculating the nearfield for an arbitrary object source is not too difficult for 

planar objects where the problem can be posed as a linear filter problem '. ln 

this case the solution can be implemented on computer where the efficiencies 

inherent in the fast Fourier transform can be exploited. For three dimensional 

objects it is often more efficient to define the object as a collection of elemental 

objects such as points, lines, rectangular apertures, etc. and use the 

superposition of elemental fields to find the object field. We have chosen this 

approach, but have exploited approximations that lead to separability of 

mathematical operations in the x and y directions. This separability is inherent. 

in field calculations for rectangular apertures and point objects modeled with 

quadratic approximations. This results in an efficient outer product 

formulations that are easy to implement in Matlab. 

The Outer Product Formulations 

Calculations were made for two letter "F" objects. One defined as a collection 

of. rectangular apertures, the other as a set of point sources. The superposed 

fields for the elemental objects (rectangular apertures or point sources) 

determines the total field for each F. 

Rectangular Apertures 

In the case of rectangular objects the fields for the rectangles were estimated 

using small angle (quadratic) approximations and formulated in terms of 

separable Fresnel integrals. The phasor field for a single rectangular aperture 

assumed to be transilluminated by a plane wave (or self-luminous with a 

uniform field across the aperture) is 5: 

Here xo,yo are the coordinates of point at which the field is desired, A is a 

constant, z is the distance to from the observation point from the plane of the 

rectangular aperture, and A is the wavelength and k is the propagation constant 

2nlA. The limits of the integrals. xlC,ylc, and xuc,yuc. are the coordinate pairs 

of the lower left corner and the upper right corner of the rectangular aperture. 

The integrals in Eq. (1) can be redefined in terms of Z;fi with a change of 

variables defined by the following relations: 

14-5 
This gives: 

The integrals in Eq. (2) are the complex form of the tabulated Fresnel integrals. 

Pade approximations to the Fresnel integrals are known. We used the 

approximation by Hastings in the m-file FRES4.M to estimate the integrals and 

to calculate the fields. FRES4.M is called by the m-file FRESNEL.M which is 

called with the upper and lower corner coordinates of an elemental rectangular 

aperture as arguments. The superposition of the elemental fields (arranged to 

form a letter F) is given in the m-file F-F1ELD.M. The first calculations from this 

approach produced a field intensity that showed a diffracted and blurred 

projection of the letter F with fringing at the edges of the letter F. The pattern 

produced looked very much like the in-line holograms produced originally by 

Gabor '. It was decided that using this particular type of hologram might be 

a problem as an initial test object. Since one would observe the virtual image 

of the F looking through a hologram that itself resembled an F, the possibility 

of confusion between the image in the hologram and the virtual image exists. 

It was decided to use a diffusive representation of the letter F instead. The 

diffusive virtual image consisted of a set of randomly phased point sources 

arranged to form an F. The use of random phasing guaranteed a specular field 

intensity in the hologram plane in which the underlying structure of the F was 

completely hidden from the eye. 

Point Sources 

Holograms resulting from point sources can be efficiently calculated using a 

quadratic approximation to each point source. The quadratic approximation 

leads to the same x-y separability that was exploited in the rectangular aperture 

calculations. Given a point source at of strength A located at (xl,yl) the 

phasor field can be represented Up is given by 5: 

14-6 
If we assume that the point source is located near the z-axis and that the point 

observation makes small angles with respect to the z-axis then the field may 

be approximated as 5: 

As in the previous case, the separability of the quadratic approximation implies 

that an outer product formulation is possible. The Matlab code for these 

calculations is in the m-file POINTH0L.M. 

Optimization of the Hologram: HOLOMED 

Once a hologram has been calculated, its field must be optimally fitted to the 

SLM characteristics of the LCTV. The fitting process was carried out by 

optimizing the ratio of the light throughput of the hologram to the square error 

in the Euclidean distance in the complex plane between the desired complex 

transmittance and the realizable transmittance of the LCTV. This optimization 

was carried out using an adaptation of the filter pro ram MEDOF (Minimum 

His adaptation of 

MEDOF dubbed HOLOMED will be described in a future paper ’. The output of 

the HOLOMED program is a 220(rows) X 320 array of gray level values ranging 

from 0 to 255. These gray level values must be written to the LCTV via a 

framegrabber. 

Euclidean Distance Optimal Filter) developed Juday B . 

THE LCTV - FRAMEGRABBER AFFINE MAP 

It would be convenient if the gray level values could be written to the LCTV 

with a framegrabber that mapped gray level values one to one from 

framegrabber pixels to LCTV pixels. This is unfortunately not case. The 

Matrox PIP framegrabber used for writing to the LCTV requires a 51 2 X 512 

array of gray level values from which a video signal is synthesized for the 

LCTV. Only a portion of the PIP array values are mapped to the LCTV. Rows 

in the PIP are converted to a standard video lines that are written to the LCTV. 

Odd rows and even rows separately determine the two fields that determine the 

interlaced image in a conventional television frame. The LCTV has only 220 
rows of pixels. It overwrites the two fields on top each other: it does not 

interlace. Therefore 440 rows of PIP pixels are mapped to the 220 rows of the 

LCTV. Determining which rows in the framegrabber mapped to which lines in 

the LCTV was easily determined by consecutively writing "lines of pixels" (All 

pixels in a line set to a gray level of 255, remaining pixels to 0) from the PIP. 

to the LCTV and observing which PIP row first turned on the top row of pixels 

on the LCTV. This completely defined the row to row map. It does not define 

the details of the pixel mapping. Determining how pixels within a given PIP 

row mapped to pixels within an LCTV row was more difficult. The problem is 

to determine precisely where in a given line video signal from the PIP starts and 

stops writing to LCTV row. The start and stop points are arbitrary and there 

locations depend on the details of the timing circuits in the PIP and the LCTV 

drive electronics. This requires a measurement with subpixel accuracy. This 

measurement was done in two steps. 

First, a rough measurement was made that resolved the start and stop positions 

in the framegrabber to within a framegrabber pixel. by consecutively "turning 

on" (Le. set one pixel to 255, the rest to 0 ) single pixels in a framegrabber 

row. The effect on the LCTV screen pixels were then observed through a 

television microscope system. A change in the first pixel of the LCTV line. 

indicated the start position of PIP line writes while a change in the last LCTV 

pixel on the line determined the stop position for line writes. This produced a 

rough estimate of the. mapping ratio of PIP pixels to LCTV pixels. Two other 

methods were then used to fine tune the mapping between framegrabber and 

LCTV pixels and achieve subpixel resolution. 

The first method, developed by Juday8, was based on writing a pattern of 

sinusoids of varying frequencies and phase shifts to the LCTV screen. The 

patterns were changed until a sinusoid was found that produced a uniform 

intensity across the LCTV of two pixels on and two pixels off. A slight error 

in either phase or frequency produced an easily discernable gross patten nonuniformity that was easy to see when the LCTV screen was magnified. 

A second method, developed by Knopp 8, was based on observing a moire. 

frequency of a created by a bar pattern with a 6 pixel period. (3 pixels on, 3 

pixels off) that beat with between the LCTV screen periodic pixel pattern. A 

low frequency beat of a few cycles across the LCTV screen was observed due 

to a low frequency beat in the 3rd harmonic of the periodic pattern with the 

LCTV pixel pitch. This permitted a fairly good measurement of the ratio of the 

PIP pixels to LCTV pixels. The measured ratio agreed well with the value 

determined by Juday's method. Although it was not done because of time 

constraints, it is also possible to measure phase shift by this approach by 

measuring the beat position. Screen uniformity can be checked by looking for 

any bowing in the moire beat. 

14-8 
The mapping experiments yielded the following affine (line) relation between 

PIP pixel coordinates and LCTV coordinates: 

t = 1.522~ + 21.621 

where t and u are PIP and LCTV pixel coordinates respectively. The equation 

assumes that the first pixels in a row are at 0. It can be used to remap the 

array coordinates of the output from HOLOMED. to pixel coordinates in the 

PIP. Once this inverse mapping of the desired LCTV values is determined, it is 

easy to determine the corresponding gray levels at pixei coordinates within the 

PIP. These remapped coordinates are typically "virtual" since only integer 

coordinate values can be realized within the framegrabber. This requires that 

the remapped values be interpolated using to get the actual values written to 

the PIP. This was done using the Matlab's cubic spline fit function. The m-file 

for calculating the inverse mapping and performing the interpolation is 

LCTVF1T.M. This subprogram is called under the m-file TVP1P.M which takes 

the file output from HOLOMED as an argument and produces a file that can be 

written directly to the PIP provided the Matlab header is stripped. 

OBSERVATION OF THE VIRTUAL IMAGE 

The true test of all the laboratory measurements and the methodologies used 

to calculate fields and optimally realize them on the LCTV was the quality of 

the resulting image observed on the LCTV. The virtual image on the LCTV was 

calculated to be an F that was 6 mm high and one meter behind the LCTV. It 

was assumed that the hologram would be illuminated with a collimated beam 

from a helium-neon laser (A = ,6328 microns). A 50 cm lens was placed about 

4.5" from the LCTV and used to reimage the F on a CCD television camera. 

An highly astigmatic image appeared about 32 inches from the lens. The 

calculated distance was about 35 inches. Multiple images of the F were 

observed, due to the discrete grating structure of the LCTV. The error in the 

image location and the astigmatism were eventually led to the discovery of an 

error in the computer code. The pixel pitches in the x and y directions had 

been entered in reverse order. This error leads to severe astigmatism and errors 

in the image position. After correcting the coding error the astigmatism was 

gone. The high quality image shown in Fig. 1 was produced. Note that the 

point sources that make up the 'F' are clearly separated and can be used to 

estimate the resolution of the hologram. 

SUMMARY AND CONCLUSIONS 

Methods of calculating and optimally realizing a hologram have been developed 

and proven in the laboratory. The following has been accomplished: 

1 4-9 
(1 ) Efficient code that uses an outer 

product formulation for calculating 

fields for objects consisting of 

elemental points and rectangular 

apertures has been developed. 

(2) The MEDOF algorithm used for 

filter calculations has been 

successfully adapted to handle 

metrics appropriate for holography. 

(3) Two laboratory methods have 

been developed for determining an 

accurate mapping of framegrabber 

pixels to LCTV pixels. hologram of the letter F. 

(4) A friendly software system has been developed that integrates the hologram 

calculation and realization process. 

(5) The code and all the laboratory measurements on the SLM parameters has 

been proven with a test image. 

FUTURE RESEARCH 

A good deal of work is needed to completely exploit the hologram production 

system that has been developed. A possible (but far from exhaustive list) 

includes testing of 

variations in mapping parameters 

various coupling curves and their effects on images 

of different hologram metrics 

new SLMs 

3-D images 

dynamic imagery 

REFERENCES 

1. C. Soutar,. S. E. Monroe, Jr. and. J. Knopp, "Measurement of the complex 

transmittance of the Epson liquid crystal television", Optical Engineering, 33, 

1061 -1068 (1 994). 

2. W. H. Lee, "Sampled Fourier Transform Hologram Generated by Computer", 

Appl. Opt., 9, 639 (1970). 

3. A. W. Lohman and D.P. Paris,"Computer Generated Spatial Filters for 

14-10 
Coherent Data Processing", Appl. Opt., 7, 651 (1968). 

4. D. Gabor, "A New Microscopic Principle", Nature, 161, 777, (1 948). 

5. J. W. Goodman, lntroduction to Fourier Optics, McGraw-Hill, New York 

(1968). 

6. M. Abramowitz and I. Stegun (editors), Handbook of Mathematical 

Formulas, US. Department of Commerce, 7th Printing, page 300, May (1 968). 

7. R. D. Juday,"Optimal realizable filter minimum Euclidean distance principle", 

~ppl. opt., 32, 5100, (1993). 

8. Details of this approach will be reported later in a paper by R.D. Juday and 

J. Knopp et. al. to be submitted to the SPE. conference in April, Orlando, FI. 

(1 9961 and eventually offered to Optical Engineering. 

9. Matrox Inc., 1055 Regis Blvd., Dorval, Quebec, Canada, H9P2T4. 

14-11 
INTELLIGENT PLANNING AND SCHEDULING FOR 

CONTROLLED LIFE SUPPORT SYSTEMS 

Final Report 

NASNASEE Summer Faculty Fellowship Program 1995 

Johnson Space Center 

Prepared by: 

Academic Rank. 

university & Depament 

NASNJSC 

Directorate: 

Division: 

Branch: 

JSC Colleague 

Date Submitted 

Contract Number 

V. Jorge Leon, Ph.D. 

Assistant Profasor 

Texas A&hirl University 

En@t!ering Technology and 

IndustrklEngineering 

College Stasion, TX 77843 

Fin@eering 

Automation, Robotics & Simulation 

Intelligent systems 

MariataMcCamy 

August 11, 1995 

NGT-1-800 

15-1 
ABSTRACT 

Planning in Controlled Ecological 

special lookahead capabilities due to the 

biological systems. This project ch 

requirements of intelligent planni 

of the planning task into short-term and long-term planning, and studies the crop 

scheduling problem as an initial approach to long-term planning. 

CELSS is studied in the realm of Chaos. The amount of biomass in the system 

is modeled using a bounded quadratic iterator. The results suggests that closed 

ecological systems can exhibit periodic behavior when imposed external 

control. 

The main characteristics of CELSS from the planning and schednling 

perspective are discussed and requirements for planning systems are given. Crop 

scheduling problem is identified as an important component of the required long-term 

lookahd capabilities of a CELSS planna. The main characte&ics of crop 

scheduling are described and a model is proposed to represent the problem. A 

surrogate measure of the probability of survival is developed. The measure reflects 

the absolute deviation of the vital reservoir levels from their nominal values. The 

solution space is generated using a probability distribution which captuns both 

knowledge about the system and the current state of affaits at each decision epoch. 

This probability distribution is used in the context of an evolution paradigm. 

The concepts developed me as the basis for the development of a simple crop 

scheduling tool which is used to demons&& its usefulness in the design and operation 

of CELSS. 

15-2 
INTRODUCTION 

Significant automation will be required for the operation of Controlled 

Ecological Life Support Systems (CELSS) in order to enable the crew to spend more 

time carrying out science and mission related activities rather than routine, but 

indispensable, life support related activities. The successful control of a CELSS will 

depend to a great extent on our ability to predict the behavior of highly restrained 

biological systems and to maintain stable balance between the crew, biological, 

mechanical and physico-chemical systems. 

For instance, the sole decision of planting a givea crop today must be associated with 

a Series of activities and events which will both produce and consume vital resources 

for a period of time measurable in months or years. More over, the appropriateness 

of a planting decision depends on what the current state of affaifi is - Le., what other 

crops are currently in growth, what are the 0, ,602, and food storage levels, energy 

status, etc. Managing and controlling this type of system present a formidable task 

which may be impossible to deal with manually. 

This project studies issues assoCiated with intdigait planning and scheduling as 

means to aid in the design, operation and behavior prediction of GELSS. This report 

will present the planning and scheduling models and methodologies developed during 

the summer program. The implementation of a crop scheduling tool using these 

concepts is presented in a separated report in this volume (Whitaker and Leon, 1995). 

Given a set of goals, a set of allowable actions, and an a description of an initial 

state of affairs, planning is dew as the task of finding a se~ueaoe of actions that 

will bring about a stateof affairs in which all the desired goals are satisfied (Kautz 

and Pednault, 1988). SChedJing is defined here a~e the resolution of time conflicts 

generated by actions competing for scarce resources, It must be mted that, planning 

can also assign resources to actions; however, time conflicts on the usage of resources 

is only partially specified in the form of precedence relations between actions. On the 

other side, scheduling assumes that the sequence of actions required to accomplish a 

given goal is given in advance and only deals with the appropriat~ timing between 

these actions. It is well known that most practical cases of planning and scheduling 

problems are very complex problems proven to be mathematically intractable from the 

optimization or satisficing point of view. Fii 1 illustrates a sample plan generated 

to accomplish the goal “harvest wheat at time 1 and plant lettuce at time 2.” The 

plan will also specify resource assignment to action. For instance, “crew person 

N0.2” is assigned to perform the action “select seeds.” 

Long-term dynamic and non-linear behavior characterize ecological systems. 

15-3 
Figure 1. A typical plan 

CHAXACTERIS"XCS OF CELSS 

From the planning, scheduling and control perspective, the inclusion of 

biological systems is what xnakes CELSS unique when compared to most systems 

studied in the litmature. Species in biological systems adapt to changes in the 

enyiFonments using their intemal mechanisms of control. In fact, it has been 

chances of survival (Colombano, 1981). Thus, it may not be appropriate to equate 

stability with survival. Another complicating fact is that, biological systems can be 

controlled through the careful manipulation of external environmental variables; 

however, the relation between the control action and the systems's response can be 

very indmt, subject to extensive filtering and occasional reinterpretation (MacEihy, 

1981). Simple CELSS modeas have been used to demonstrate that it is possible that 

failures can occur at times long after the cause of the perturbation has been removed 

(Auslander, 1981). For instance, it is possible that the percent of edible biomass 

obtained from a given crop can be severely decmsed if at some pint during growth 

the plants where subjected to long periods of darhess. In this example, the time 

elapsed between the disturbance (Le., darhess) and the effect (Le., harvest) can be in 

the order of months or several weeks. 

The above characteristics make the design and operation of CELSS a formidable 

challenge which we are only starting to understand. Among the unanswered questions 

there are those related to the amount of local versus global control required, the 

quantification of the probabiity of survival, the sizing of vital element reservoirs, and 

suggested that species may adopt the sbrategy of instability in order to enhance their 

15-4 
others. New paradigms may be necessary to model and analyze this systems. In this 

project, we explored two of a number of possible paradigms. Specifically, Chaos was 

used to model the non-linear and dynamic behavior of the system, and Evolution is 

used as a paradigm to generate a space of crop schedules. 

CELSS - A Perspective From Chaos 

A main diEference between "natural" or "free" biological systems and CELSS 

resides in the latter's imposition of external bounds on the system's response. In this 

section we describe how Chaos theory can be used to study the response biological 

systems (i.e., amount of biomass) when bounded extemally. A simple experiment 

demonstrates that an unstable "free" biological system may have a periodic behavior 

when *constIStined" externally. 

Chaos theory has been recently used to model population dynamics and the 

behavior of biological and other natural systems (May, 1976). Chaotic behavior can 

be represented by simple mathematical modefs - however, the resulting behavior may 

be unpredictable. Chaos can be used to model the behavior of systems that are nonhear and dthe on initial conditions. Non-linearity implies that what occurs now 

significantly affects future.events. As with biological behavior, chaotic behavior is a 

collection of many orderly behaviors, none of which dominates each other under 

ordinary circumstances. The explicit consideration of this apparent instabiity in 

systems behavior may enable the developmeat of better models for the analysis and 

synthesis of controlled system. For instance, chaotic systems have been controlled by 

perturbing them in the right way so they will be forced to follow a diffesent behavior. 

Furthermore, this controllers have proved to be more efficient than their traditional 

counterparts. 

in the experiments. This function can be expressed as follows: 

x(n+l)=a x(n) (1 - x(n)) 

Where, x(n) is the normalized size of the population of a specie at time n, and a is a 

proportionality constant. This function has intensting characteristics, such as: 

1. The size of the population at any time depend of the initial condition (~(0)). 

2. Stable? periodic or unstable behavior can be represented with the appropriate 

choice of the parameter a. 

3, It can portray abrupt changes in behavior from order to chaos - i.e., perioddoubling bifurcations. 

4. It can portray long-term stability through "attracting" states. 

5. It exhibits "universal" behavior observed in many natural systems. 

predictable to some extent. The important result is that this predictability allows for 

the control of chaotic systems; in fact, there is evidence that control using Chaos can 

outperform traditional control (Ditto and Pecora, 1993). 

Figure 2 (a), @) and (c) show plots of the same function for different values of 

a resulting in stable, periodic and unstable behavior, respectively. 

The quadratic iterator known as the Logistic Function (Vefhurst, 1984) is used 

These characteristics make the apparently random behavior of the systems is 

15-5 
We model a CELSS using the logistic function; where, x(n) represents the 

amount of plant biomass in the system. Clearly, in a CELSS this amount cannot 

maximum amount of biomass at any point in time. "he function used in the 

experiment is modified as follows: 

. grow unbounded. In order to model this, an upper bound, U, is imposed limiting the 

x(ntl)=a x(n) (1 - x(n)) 

ifx(n+l) > U, then setx(n+l) = U. 

The value of a=4.0 applied to the original "free" system yields the unstable behavior 

depicted in Figure 2@). However, the behavior of the "bounded" system became 

periodic as illustrated in Figure 3. 

I* . ..,. t 

J 

I 

(a) Extintion, stable and periodic (c) Unstable, a= 4.0 

Fmre 2 .The Logistic Function 

r I 

I I I I I 

1 

Figure 3. A bounded Logistic function With a = 4.0, U=O.9 

15-6 
This interesting result using a simple experiment suggests that the 

implementation of a CELSS may be possible. Further, it suggests that the system will 

have alternating periods of time in which the biological system is mostly controlled 

using the plant's internal control mechanisms and period during which artificial 

control will be needed. For instance, incineration or other recycling process may be 

required whenever the amount of food produced is excessive. 

using the Chaos paradigm may be valuable for the understanding of CELSS. 

This simple experiment also suggests that more formal and thorough studies 

CELSS PLANNERS - REQThe long duration of CELSS operations and the complex dynamics induced by 

the biological systems, mechanical reliability and information uIIcebtalu1 tymakeit 

necessary for a CELSS planner to have the following special requirements: 

of several months) inherent to biological systems. This implies the need of lookahead 

capabilities not present in traditional planners. The lookahead should ensure longterm system stability and strategic management of resources. Only vital resoumust be considered and time granuhity should be in the order of days. 

2. Detail resource scheduling and minute-tO-minute planning should be done 

using a planning horizon in the order of hours to days. It is important that detailed 

plans are consistent with the long-term lookahead analysis. 

3. Plannexs must exploit the intelligence and flexibility of humans. This 

implies that planners should: (a) enable the incorporation of user input before and 

during plan generation, (b) provide with plan explanation and (c) provide with "what1. Planners must explicitly consider the long-term dynamics (i.e., in the order 

if" analysis capabilities. 

4. Planners must be adaptable to unforeseen changes in operating conditions. 

CELSS may need to operate in isolation from terrestd feedback for months. The 

planner must be able to acmmmadate to unknown or unforeseen conditions during the 

design of the system. Planners must allow the incorporation of experience for 

adaptation to new conditions and improvement in performance. 

PLANNING PROBLEM DECOMKlSI'ITON 

The requirements described above suggest the decomposition of the planning 

problem into two subproblem: Long-Term Planning (LTP) and Short-Term Planning 

(STP). Figure 4 depicts the proposed problem decomposition. STP is much like 

most planning problems in the literatwe; Le., is well described by the definition of 

planning in the begiMing of this report. Although very important, this will not be 

discussed further in this report. 

The LTP can be described as the problem of scheduling strategic resources. 

Strategic resources may include crew, crops, main elements (02, CO,, H20, etc.), 

food, storage space and others. Figure 4 shows how only the initial portion of a 

long-term plan is broken down into further detail in the sh~fi-t~~~t~ plan. Further, it 

15-7 
also suggests that the immediate actions prescribed by LTP ensure the adequate levels 

in the long run. It must be noted that LTP gives the planning tool with predictive 

capabilities which make it also useful as a "what-if" tool for design and situation 

diagnosis. 

Reservoir Levelr 

600 

500 

PLANNER 400 

LONG-TERM 

(Schedule strategic 300 

resources) 200 

100 

I *., 8.. . ,.,. .,..,..,I,* 

SHORT-TERM PLANNER 

Figure 4. Planning problem decomposition 

THE CROP SCHEDULING PROBL3B4 

The crew, crops and other live agents determine to a gnat extent the long-term 

behavior of a CELSS. In this project, a first look is given to the Crop Scheduling 

Problem (CSP). CSP can be formulated as follows: 

csp: 

Decision Variables: 

Objective: 

Constraints: 

What, how much and when to plant. 

Maximize the probability of survival. 

Conservation and transformation of mass 

Crew availability 

Space availability (planting, process, storage) 

Energy and other operational constraints 

15-8 
This scheduling problem is unique for a number of reasons which make it 

specially challenging when compared with more traditional scheduling problems. The 

first distinction is related to the time characteristics of plants as illustrated in Figure 

5. Once a decision of planting is made, this triggers a several events in the near 

(same day) and far (months later) future. Although some precedence exists between 

these events, some partial sequences may occur simultaneously and may require of the 

same scarce resources. The management of such a system becomes too complicated 

to deal with manually, specially if different types of crops are considered. For 

instance in Figure 5, at the time of planting one must consider how will this affect the 

0, and C02 resewoirs during its growth and how will it impact the food storage 

space, crew loading 

non-linearity of the 

decisions will have to be made while the events triggered by the decision of planting 

are still taking place. 

processing about 3 months later (e.g., wheat). The 

. becomes evib€ when observing that other planting 

Figure5 Aplantmodel 

A CROP SCHEDULING MODEL 

In this section a model for CSP is proposed. First, a surrogate measure of the 

probability of survival is proposed as an objective function. Second, a solution space 

that is geaerated using an evolution paradigm is described. Finally, the search and 

ideas to deal with the size of the solution space will be discussed. 

Objective Function 

The quantiiication of the probability of suMvd is not a trivial issue. This 

problem is similar to the one in safety analysis but in CELSS is complicated by the 

long-term dynamics inherent to such systems as growing plants (Auslander, 1981). 

Here, the probability of survival is represented using a surrogate measure, 2, which 

reflects the absolute deviations of the each vital reservoir’s level fiom the 

corresponding nominal value. 

15-9 
Let d, be some normalized indicator (Le., between 0 and 1) of the average 

deviation of reservoir's r level from its nominal value. 2 can be defi 

where, R is the total number of vital reservoirs and f(.) is an appropriate real valued 

function. 

=Z f(d1, dz, - - .dR, 

Solution Space 

of empty trays and reservoir levels. Other important information are the time at 

which the state is described, crew profile, human model, plant models and physical 

system models. 

plant. Decision epochs are prompted by significant events. These events can be 

classified into (i) biological evmts, (ii) user spe&ed events and (is) stochastic 

events. 

The solution space can be represented as a tree where the nodes are decision 

points and the branches are different paths resulting from different scheduling 

decisions. A path in this tree will represent one possible schedule. A schedule which 

satisfies all the operating constraints is tenned an admissible plan. The scheduling 

problem can be stated as the problem of finding the admissible plan which minimizes 

2. 

Considering all possible alternatives a& each decision epoch would be 

Rathex, we suggest the gdm of dternatives using hemstxs which impractical. 

capture both knowledge about the problem, as well as, the cxurc~~t state of affairs. 

Inspired by evolution processes, a fitness probability distribution is determined at each 

decision epoch. The random variable is the crop type, and the correspnding 

probability reflects the marginal effect that planting the eonespondur gcrapwillhave 

on the vital reservoirs. This probabilities can be computed using arguments similar to 

the ones used in the determination of the objective function. Knowledge about the 

process is captured through the use of the system's models to predict the impact that 

each crop would have if planted. The current state of affairs is captured since the 

reservoir levels at the decision epoch must be co11sideffd. It must be noted that this 

probability distribution must be computed at each decisiorr epoch to reflect the 

updated "desirability" of each crop. Thus the tenn desirabi&ypmbabiZify. 

There are several different ways that this probability can be used to generate the 

solution space. The most efficieat way of using it is still a matter of Mer research. 

One way to implement this generation strategy is illustrated in Figure 6. Given a 

number of empty trays, one can randomly sample from the desirabiity distribution 

until all empty trays are filled - noted that, plant-norhng is considered as one possible 

crop. Figure 6 illustrate how a single path (schedule) can be generated. 

Search and Dealing With Complexity 

Clearly, generating the space using local information will unavoidably lead to 

the necessity of backtracking when non-admissible situations are encountered. Too 

The state of the system is defined by the status of the in-growth crops, number 

At a decision epoch, a decision is made as for what, how much and when to 

.. 

15-10 
much backtracking may render the approach impractical. In the case of CELSS, 

however, too much backtracking may suggest that the system is not robust enough; 

Le., there are only a few paths leading to mission completion. If this is the case, a 

system redesign will be more recommendable than a more sophisticated scheduler. 

Clearly, too much backtracking may also suggest a poor space generation scheme. 

cannot be resolved automatically. Hence, the importance of schedule explanation tu 

aid the user in suggesting conflict resolution. 

Most existing search strategies may be applied to deal with the size of the 

solution space. The determination of the most appropriate search strategy is still an 

open research issue. 

For CESS it would be desirable to allow for user intervention if conflicts 

Fwm 6. An evolution approach 

AN EXAlMPLE IMPLEMENTATION OF TRE A SCHEDULER 

A simple crop scheduler was implemented to illustrate its potential use in 

planning as well as design of CELSS. A detailed description of this implementation 

is contained in a separate report (Whitdcer and Leon, 1995). Figure 7 illustrate the 

main components of the Intelligent Crop Scheduler. (IC$) developed during this 

summer project. ICs has two main components: a Schedule Generator (SG) and a 

15-1 1 
Schedule Simulator (SS). SG is based on the concepts described above. SS contains 

detail human metabolic simulator and two plant models (Le., wheat and lettuce). It 

also contains a simplified physical system model as illustrated in Figure 8. For 

simplicity, only O,, C02 , edible wheat and edible lettuce reservoirs are considered. 

The main systems considered are the crew, plants and a generic waste processing 

system. 

A sample planting schedule is illustrated in Figure 9. Figure 10 illustrates the 

reservoir levels for the schedule, as well as, its performance. A variety a scenarios 

were run illustrating how the output can be used to aid in sizing the gas tanks, food 

storage space, growing area, crew profile, planting strategy, growing parameters, and 

others. See Whitaket and Leon (1995) for a discussion of the example cases. 

FIiguce 7. Intelligent Crop Schedukr 

15-12 
Fmre 8. A simplified CELSS model 

I 1 

+ 

0 

20 0 0 

0 

80 

-+ 

0 

Fwre 9. Sample crop schedule 

15-13 
Deviations from Nominal 

Reservoir Levels 

Lelluc + - 1.--0 

Wheat 

c02 

Fvre 10. Sample reservoir level output 

15-14 
REFERENCES 

Ditto, W.L. and L.M. Pecora (1993) "Mastering Chaos," Scientijk American, August 

1993. 

Gelick, J. (1987) Chaos - Making a New Science, Viking. 

Kautz, H.A. and E.P.D. Pednault (1988) "Planning and Plan Recognition," AT&T 

Technical Jounzcrl, 67, 25-40. 

May, R.M. (1976) "Simple Mathematical Models With Very Complicated 

Dynamics," Nahcre, 261,459-467. 

The articles for ref- to MacElroy (1981), Auslander (1981) and Colombano 

(1981) are in NASA Publication 2247: "Controlled Ecological We Support System - 

First principal Investigators Meeting," Pmceedings of a NAscf Meeting, University of 

New Hampshire, Durham, NH, May 34,1981- 

Peitgen, H.-O., H. Jurgens and D. Saupe (1992), chaos and Fractals - Nav 

Fromtiers of Science, Springer-VErlag, New York, 1992. 

Volk, T. and J.D. Rummel(l987) "Mass Balances for a Biological Life Support 

System SimuWon Model," Adv. $'e Res., 7 (4), 141-148. 

.Whitaker, L.O. and V.J. Leon (1995) "An Intelligeat Crop Scheduling Tool for 

CEJSS," 1995 NASNASEE Summer Faculty Fellowship Program, NASA - Johnson 

Space Center, Houston, Texas. 

15-15 
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