James R. Gaier and John Siamidis

Glenn Research Center, Cleveland, Ohio

Elizabeth M.G. Larkin

Case Western Reserve University, Cleveland, Ohio 

Extraction of Thermal Performance Values From 

Samples in the Lunar Dust Adhesion Bell Jar

NASA/TM—2010-216828

October 2010
NASA STI Program . . . in Profi le

Since its founding, NASA has been dedicated to the 

advancement of aeronautics and space science. The 

NASA Scientifi c and Technical Information (STI) 

program plays a key part in helping NASA maintain 

this important role.

The NASA STI Program operates under the auspices 

of the Agency Chief Information Offi cer. It collects, 

organizes, provides for archiving, and disseminates 

NASA’s STI. The NASA STI program provides access 

to the NASA Aeronautics and Space Database and 

its public interface, the NASA Technical Reports 

Server, thus providing one of the largest collections 

of aeronautical and space science STI in the world. 

Results are published in both non-NASA channels 

and by NASA in the NASA STI Report Series, which 

includes the following report types:

• TECHNICAL PUBLICATION. Reports of 

completed research or a major signifi cant phase 

of research that present the results of NASA 

programs and include extensive data or theoretical 

analysis. Includes compilations of signifi cant 

scientifi c and technical data and information 

deemed to be of continuing reference value. 

NASA counterpart of peer-reviewed formal 

professional papers but has less stringent 

limitations on manuscript length and extent of 

graphic presentations.

• TECHNICAL MEMORANDUM. Scientifi c 

and technical fi ndings that are preliminary or 

of specialized interest, e.g., quick release 

reports, working papers, and bibliographies that 

contain minimal annotation. Does not contain 

extensive analysis.

• CONTRACTOR REPORT. Scientifi c and 

technical fi ndings by NASA-sponsored 

contractors and grantees.

• CONFERENCE PUBLICATION. Collected 

papers from scientifi c and technical 

conferences, symposia, seminars, or other 

meetings sponsored or cosponsored by NASA.

• SPECIAL PUBLICATION. Scientifi c, 

technical, or historical information from 

NASA programs, projects, and missions, often 

concerned with subjects having substantial 

public interest.

• TECHNICAL TRANSLATION. Englishlanguage translations of foreign scientifi c and 

technical material pertinent to NASA’s mission.

Specialized services also include creating custom 

thesauri, building customized databases, organizing 

and publishing research results.

For more information about the NASA STI 

program, see the following:

• Access the NASA STI program home page at 

http://www.sti.nasa.gov

• E-mail your question via the Internet to help@

sti.nasa.gov

• Fax your question to the NASA STI Help Desk 

at 443–757–5803

• Telephone the NASA STI Help Desk at

 443–757–5802

• Write to:

 NASA Center for AeroSpace Information (CASI)

 7115 Standard Drive

 Hanover, MD 21076–1320
James R. Gaier and John Siamidis

Glenn Research Center, Cleveland, Ohio

Elizabeth M.G. Larkin

Case Western Reserve University, Cleveland, Ohio 

Extraction of Thermal Performance Values From 

Samples in the Lunar Dust Adhesion Bell Jar

NASA/TM—2010-216828

October 2010

National Aeronautics and

Space Administration

Glenn Research Center

Cleveland, Ohio 44135

Prepared for the

25th Space Simulation Conference

cosponsored by the IEST, NASA, AIAA, ASTM, CSA, and JHU/APL

Annapolis, Maryland, October 20–23, 2008
Acknowledgments

This work was supported by the NASA Exploration Technology Development Program through the Dust Mitigation Project 

(JRG), the Advanced Thermal Control Project (JRG), and the Fission Surface Power Project (JS).

Available from

NASA Center for Aerospace Information

7115 Standard Drive

Hanover, MD 21076–1320

National Technical Information Service

5301 Shawnee Road

Alexandria, VA 22312

Available electronically at http://gltrs.grc.nasa.gov

Trade names and trademarks are used in this report for identifi cation 

only. Their usage does not constitute an offi cial endorsement, 

either expressed or implied, by the National Aeronautics and 

Space Administration.

Level of Review: This material has been technically reviewed by technical management. 
NASA/TM—2010-216828 1 

Extraction of Thermal Performance Values From Samples 

in the Lunar Dust Adhesion Bell Jar 

James R. Gaier and John Siamidis 

National Aeronuatics and Space Administration 

Glenn Research Center 

Cleveland, Ohio 44135 

Elizabeth M.G. Larkin 

Case Western Reserve University 

Cleveland, Ohio 44106 

Abstract 

A simulation chamber has been developed to test the performance of thermal control surfaces under 

dusty lunar conditions. The lunar dust adhesion bell jar (LDAB) is a diffusion pumped vacuum chamber 

(10–8 Torr) built to test material samples less than about 7 cm in diameter. The LDAB has the following 

lunar dust simulant processing capabilities: heating and cooling while stirring in order to degas and 

remove adsorbed water; RF air-plasma for activating the dust and for organic contaminant removal; RF 

H/He-plasma to simulate solar wind; dust sieving system for controlling particle sizes; and a controlled 

means of introducing the activated dust to the samples under study. The LDAB is also fitted with an in 

situ Xe arc lamp solar simulator, and a cold box that can reach 30 K. Samples of thermal control surfaces 

(2.5 cm diameter) are introduced into the chamber for calorimetric evaluation using thermocouple 

instrumentation. The object of this paper is to present a thermal model of the samples under test 

conditions and to outline the procedure to extract the absorptance, emittance, and thermal efficiency from 

the pristine and sub-monolayer dust covered samples. 

Introduction 

On January 14, 2004, President George W. Bush outlined the Vision for Space Exploration which, 

among other goals, called for a “human return to the Moon by the year 2020” (Ref. 1). The Vision for 

Space Exploration has since been formalized by Congressional legislation as the revised US Space Policy. 

This was fleshed out in more detail in the Exploration Systems Architecture Study (Ref. 2), which calls 

for the first lunar landing to be in the year 2018. This is an ambitious schedule given that none of the 

launch or space vehicles called for by the study presently exist and there are budgetary constraints under 

which the program must be carried out. If the program is to be successful, it must build on the lessons 

learned during the first human lunar missions, those of the Apollo program. 

One of the lessons learned during the Apollo program was that dust on the lunar surface posed a 

surprisingly broad array of difficulties (Ref. 3). There were problems to varying degrees with vision 

obscuration, equipment clogging, dust coating and abrading, radiator performance degradation, seals 

failing, and dust inhalation. Apollo 17 astronaut Harrison Schmitt remarked at a lunar simulation 

workshop in 2005 that, “Dust is the number one environmental problem on the Moon” (Ref. 4). These 

effects were a major concern even though the Apollo landers were on the lunar surface for no more than 

about three days. The early phases of the Exploration program envision missions of seven to fourteen 

days, with the eventual establishment of a permanent lunar base. Clearly the next human lunar surface 

missions must be better equipped to deal with dust. 

A specific task has been set up under the Exploration program to develop technologies to mitigate the 

effects of lunar dust on surface missions. An important aspect of this technology development will be to 

test possible dust mitigation solutions in a simulated lunar environment on Earth. One of the lessons of 

Apollo is that these must be high fidelity tests. Dust mitigation technologies that were tested in simulation 
NASA/TM—2010-216828 2 

for Apollo did not always work on the Moon. For example, it was thought that using a nylon brush would 

be an effective way to remove lunar dust from the lunar roving vehicle (LRV) radiator surfaces (Ref. 5). 

However, under lunar conditions the brush did not remove the very fine particles, and as a result the 

thermal performance of the radiator surfaces was degraded significantly in spite of brushing (Refs. 6, 7, 

and 8). 

Three strategies can be employed to mitigate the effects of dust on surface system components. First, 

components can be designed so that they can better tolerate the effects of dust. An example might be a 

space suit fabric that has better resistance to abrasion by lunar dust. Second, components can be designed 

such that less dust attaches to them. For example, a space suit fabric can have a smooth outer layer so that 

dust cannot so easily work its way between the fibers, so there is less dust on the fabric to abrade it. Third, 

techniques can be developed to clean dust from surfaces. Perhaps an air shower can be built into the 

airlock to blow the dust off of the fabric, so it does not abrade the suits. In all likelihood all three 

strategies will be used in concert. But since the nature of the surfaces of both the dust and spacecraft 

surfaces are different in the lunar environment than they are in the ambient terrestrial environment, these 

technologies must be verified in a high fidelity lunar environment simulation chamber. 

The lunar dust adhesion bell jar (LDAB) has been built at the NASA Glenn Research Center to 

provide a high fidelity simulation of the lunar surface environment. Although the principal mission of 

LDAB is to study the adhesion of lunar dust to spacecraft surfaces, it has been designed with the 

flexibility to study the effects of lunar dust on the functional properties of candidate materials and 

surfaces as well. A cut-away drawing of the LDAB is illustrated in Figure 1. A thorough discussion of the 

LDAB subsystems has been undertaken elsewhere (Ref. 9). 

The first series of experiments carried out in the LDAB were designed to determine the extent to 

which lunar dust will degrade the performance of thermal control surfaces. In essence, a plot must be 

developed with the percent dust coverage on the ordinate, and the degradation of thermal performance on 

the abscissa. In practice, neither of the quantities to be plotted were straightforward. It is the object of this 

paper to describe the difficulties in determining the percent dust coverage and the thermal degradation, 

and how they were overcome. It is hoped that lessons learned in this application might be fruitfully 

applied to others. 

Percent Dust Coverage Determination 

The samples tested utilized either a white thermal control paint (AZ-93) or a second surface mirror 

(Ag coated FEP Teflon (DuPont)) as the thermal control surface. The thermal control surface was applied 

either to 2.54 cm (1 in.) diameter aluminum substrates, or to identically fabricated composite samples. 

The composites, which were fabricated in-house, contained a surface layer of K-1100 high thermal 

conductivity graphite fibers and enough layers of PAN-based structural carbon fibers to give a thickness 

of 6.4 mm (0.25 in.) in a matrix of RS-3 isocyanate resin. This is the same composite structure used by 

the thermal control group for composite radiators within the ETDP’s Fission Surface Power project. The 

laminate was laid up as a single sheet and then the round disks were machined from that sheet. The AZ-93 

paint was applied by AZ Technology (Huntsville). The AgFEP samples were fabricated by Sheldahl 

(Northfield, MN) from 12.7 m (5 mil) thick FEP Teflon which was coated with a few tens of nm of 

silver and a few tens of nm of inconel as a sealing layer to prevent oxidation. They were hand-applied to 

the samples using adhesive. 
NASA/TM—2010-216828 3 

Figure 1.—Cutaway drawing of the lunar dust adhesion bell jar (LDAB) showing the location of the major subsystems. 

Lunar dust proved to be much more cohesive and adhesive than similar dust on Earth. This is thought 

to be because the surface of lunar dust is free of water molecules, and probably chemically activated as 

well. Without the surface layer of water, the particles can come into closer contact which enhances 

cohesion and adhesion. These “clean body” effects have been well-characterized with other materials 

subjected to ultrahigh vacuum and indeed on returned lunar samples as well (Ref. 10). The LDAB is 

designed to produce these same effects on lunar simulant materials for high fidelity materials testing. 

Lunar simulant dust is loaded into a bowl within the LDAB where it is conditioned so that it might be 

more lunar like. This conditioning starts by pumping on the chamber with a mechanical roughing pump 

while intermittently stirring the dust until the vacuum reaches 10–1 Torr. At this point a radio frequency 

air plasma is ignited which generates oxygen ions and ultraviolet light which cleans organic contaminants 

off of the dust for at least 1 hr. This is followed by heating the dust to 200 C and the chamber to 60 C 

over night while pumping on the chamber with an oil diffusion pump equipped with a liquid nitrogen cold 

trap to remove adsorbed water. After cooling, a vacuum of 710–8 Torr is typically attained. The samples 

are moved into position under a well-collimated, unfiltered Xe arc lamp to mimic solar radiation in the 

near ultraviolet, visible, and infrared portions of the spectrum. The lamp is located inside the chamber to 

avoid losses in the ultraviolet region due to absorption by window material. The temperatures of the 

samples were monitored using type K thermocouples mounted to their back sides and after exposure for 

15 min or until the temperature reached 200 C. The lamp is then turned off and the sample is moved 

into an absorbent-lined copper cold box that is maintained at about 30 K with a recirculating helium 
NASA/TM—2010-216828 4 

refrigerator. The temperature is monitored until the sample reaches equilibrium. The samples are then 

pulled out of the cold box and allowed to come to room temperature. 

The pressure is increased back to 10–1 Torr by backfilling with a non-flammable hydrogen-helium 

mixture and a second plasma is ignited for 1 hr. This chemically reduces the surface of the dust and 

implants some hydrogen into the dust as well. After the plasma treatment, the vacuum is re-established 

and typically drops to about 210–7 Torr. In situ, the dust is dumped from the bowl into a standard 7.6 cm 

(3 in.) screen of 25 or 32 m size. The samples are positioned underneath the sieve, and dust is deposited 

on them by mechanically shaking the sieve. This is to limit the size of the dust deposited onto the samples 

to the fine fraction. 

If successfully treated, the cohesion and adhesion of the dust should be enhanced significantly. 

Unfortunately, the dust is so cohesive it does not sieve well. It proved surprisingly difficult to apply an 

even coating of dust on thermal control surface samples. It was thought that a simple sinusoidal motion 

of the sieve would deposit the dust evenly and reproducibly. This has proven not to be the case. Varieties 

of jarring and vibrating motions were also employed, but did not give consistently even coatings. To 

complicate the problem further, once the dust has been treated in vacuo it behaved differently than it did 

in the tests that were conducted in air. Schemes that would work on one run would not work on the next. 

Time that the dust was sifted onto the sample correlated very poorly with the amount of dust deposited. 

That is, more dust may be deposited in a 60 sec run than on a 600 sec run. Typical results are shown in 

Figure 2. It can be readily seen that the left sample has much more dust deposited on it than the right 

sample. 

The characterization of fractional coverage by dust is complicated by the fact that all particles 

deposited on the samples are smaller than 32 m, because of the sieve. Thus, although the right hand 

sample in Figure 2 appears to be clean, microscopic investigation reveals that about 5 percent of its 

surface is covered with dust, and indeed its absorptance is increased. 

Determining the fractional occultation of the thermal control surface by a sub-monolayer of sub25 m particles is not straightforward. The sample disks have an area of 5108 m2

, and the largest 

particles 500 m2

. In order to count such small particles, magnification of at least 100 is required. At 

100 the area imaged by our microscope is 968726 m, so there are 641 non-overlapping frames that 

are completely filled with sample disk. Frames that were partially filled with the disk were ignored. This 

is permissible because the pattern of the dust distribution is larger than the sample, so we are in a sense 

only sampling already from a larger distribution. Rather than count the particles in all 641 frames for each 

of 17 samples (nearly 11,000 photos) it was decided to analyze a statistically significant random sample 

of the frames. 

Figure 2.—Photograph of two AZ-93Al-1 samples that were 

dusted at the same time in the configuration shown. The left 

hand sample, particularly on its left half, was coated much 

more heavily than the right hand sample. 
NASA/TM—2010-216828 5 

Figure 3.—Photomicrographs of the AZ-93 sample (left) and AgFEP sample (right) that were used in the analysis 

of fractional dust coverage. The area covers in each photomicrograph is about 1 mm2

. 

In order to take rigorously random samples, a computer controlled x-y- stage was installed on the 

microscope. Each sample was mounted on the stage with a specific orientation (i.e., the thermocouple 

holes aligned in the  = 0 direction). The random number generator in Microsoft Excel (Microsoft 

Corporation) was used to set the  value for each sample in order to account for systematic angular 

consistencies that might be present in the dust distribution pattern. The percentage of dust coverage on 

each sample was estimated by superimposing a grid onto each sample dividing the sample into 641 nonoverlapping frames of equal size. Frames on each sample were then randomly chosen using the random 

number generator and each selected field was located and digitally photographed. The dust appears dark 

on the AZ-93 coating, but light on the AgFEP coatings, as can be seen in Figure 3. The largest particles 

are <25 m in size. Image-Pro (company name) software was used to determine the proportion of black 

(128 to 256 on the grey scale) to white pixels (0 to 128 on the grey scale) in each photograph. The 

percentage of black pixels represents the overall dust coverage of the tested field on AZ-93, and the 

percentage of white pixels represents the overall dust coverage of the tested field on AgFEP. 

A 95 percent confidence interval (CI) was also calculated around each mean to determine the 

precision of the estimated mean using Equation (1): 

 

n

p p CI n z   1 (1) 

where z is the critical value from the normal distribution (1.96 for a 95 percent CI), p is the sample 

proportion (percentage of pixels occulted by dust), and n is the sample size (number of frames examined) 

(Ref. 11). Because this formula assumes a functionally infinite population, an assumption not met when 

over 5 percent of the population is being sampled, the finite population correction was applied to adjust 

the confidence interval calculation:

  



 



  

  

N

n

n

p p CI n z 1

1

1 (2) 

where N is the population size (total number of frames in a sample). This provides a more accurate 

estimate by taking into account the high percentage (>5 percent) of samples being measured, thereby 

reducing the standard error. 
NASA/TM—2010-216828 6 

There is a trade-off in number of frames examined between the amount of effort and the precision 

which the measurement is known. The mean, standard deviation, and confidence interval as a function of 

frames examined for a typical sample are plotted in Figure 4. It can be seen that the 95 percent confidence 

interval flattens out, and measuring beyond 50 frames would have limited returns. Thus, 50 frames were 

measured for each sample. 

The result of the calculations for dusted, AZ-93 painted aluminum is shown in Figure 5. Notice that 

the 95 percent confidence interval is fairly large, between 9 and 13 percent in this case, despite the fact 

that the mean, shown in Figure 4, seems to vary little. This was true for all four materials tested. It can be 

seen in equation 1 that greater numbers of measurements are required for the same confidence interval if 

the mean coverage is near 50 percent, than if it is near 0 or 100 percent. 

Figure 4.—Statistical parameters as a function of frames examined for dusted 

sample. 

Figure 5.—Plot of /pristine as a function of fractional dust coverage for the AZ-93Al 

samples. The () are mean percent for each experiment and the horizontal lines 

bound the coverage at the 95 percent confidence interval. The () are the dust 

coverage estimates from single frame measurements, combined with a simple 

linear model to calculate . 
NASA/TM—2010-216828 7 

Thermal Performance Degradation Determination 

The thermal modeling was done using Thermal Desktop (Cullimore & Ring Technologies), a PCbased design environment for generating thermal models of electronics and vehicles. Thermal Desktop 

incorporates both parameter based finite difference surfaces with finite elements and CAD technology to 

model thermal problems. Thermal Desktop develops the capacitance and conductance network for input 

to SINDA/Fluint which is a comprehensive finite-difference, lumped parameter (circuit or network 

analogy) tool for heat transfer design analysis and fluid flow analysis in complex systems. Thermal 

Desktop 5.1 Patch 3 was used to generate the thermal model, which consists of 743 nodes and 1840 linear 

conductors. A visualization of the model and the material parameters used in it are shown in Figure 6. 

Any thermal model has to be constrained. In this study, the AZ-93 coated aluminum samples were 

considered to be the baseline. There are many characteristics that could vary over the course of the 

experiment such as the intensity of the heating lamp, the translational and angular positions of the sample, 

and the temperature of the cold box. It was decided to hold all those variables constant, and to sweep all 

errors into the absorptivity () and the emissivity (ε) of the samples. The method for goodness of fit 

between the model and the data was to minimize the differences between the area under the temperature 

as a function of time plot, i.e., the weighted average difference. In most cases, the calculations iterated 

until that difference was less than 1 percent. 

One important unknown was the radiant power of the heating lamp. An independent calibration 

swamped out the detector, which established that the intensity of the lamp was greater than 10 suns. The 

experienced technician who did the testing estimated that it might be as high as 20 suns. When it was 

assumed from examining the literature that the ε of the AZ-93 coated aluminum sample was 0.895, and 

the  was 0.172, the intensity of the lamp was found to be 29.1 kW/m2

, or about 21.5 suns. This was the 

value that was used for the lamp intensity for all subsequent calculations. 

For the pristine samples during heating, the  and ε of the coated sample are set to their initial values. 

Subsequently, the  was varied for each test run until there was less than 1 percent difference in the 

weighted average temperatures between each test run and each analysis run. During cooling, the ε was 

varied for each test run until there was less that 1 percent difference in the weighted average temperatures 

between each test run and each analysis run. 

For the dusted samples during heating, and for the same lamp power established previously, the 

was varied for each test run until there was less that one percent difference in the weighted average 

temperatures between each test run and each analysis run. During cooling, the ε was varied for each test 

run until there was less that 1 percent difference in the weighted average temperatures between each test 

run and each analysis run. 

Figure 6.—Picture of the thermal model and parameters used in its construction. 
NASA/TM—2010-216828 8 

Results 

A full discussion of the results is available elsewhere (Ref. 12), and will only be summarized here. 

Table I shows the resulting values for the average of 4-7 data runs on each of the four materials tested. 

Note that the  drops and the  rises when composite substrates are used, so / rises as well. 

By combining the statistical techniques to measure the percent dust coverage with the thermal 

degradation, /, a plot of the thermal degradation was obtained (Fig. 7). Interestingly, the degradation 

values seem to rise monotonically with dust coverage regardless of the thermal control coating or 

substrate. A least squares line (without the outlier with a 3.68 /) has an R2

 of 0.72, and extrapolates to a 

value of degradation of a factor 3 at full coverage by dust. 

In most studies the  of radiators has been assumed not to change in a significant way when they 

accumulate dust because the  of the dust itself is so high. However, sub-monolayers of dust on AZ-93 

paint lowered the  so much that a full monolayer would have degraded the surface to 80 percent of its 

clean value. In contrast, sub-monolayers of dust on AgFEP surfaces raised the  such that a full 

monolayer would have enhanced the  by 20 percent. This is particularly important if the thermal control 

surface is in a well shaded area. 

The overall degradation of the thermal control surface depends on both the  and . When the relative 

/ was plotted as a function of dust coverage, an interesting relationship was seen. As can be seen in 

Figure 7, all of the data taken together seem to rise monotonically. A least squares fit to this data has an 

R2

 of 0.72, and crosses the 100 percent dust coverage line at about 3. This implies that no matter which 

surface or substrate is used, a monolayer of dust on it will raise its / by a factor of 3. Or put another 

way, thermal control surfaces must be made 3 times larger if they are expected to be covered with dust 

than if they would remain clean. 

TABLE I.—OPTICAL PROPERTIES OF MATERIALS USED IN THIS STUDY 

Pristine material Emissivity 

() 

Absorptivity 

() 

/

AZ-93 on Al 0.886 ± 0.024 0.173 ± 0.029 0.195 

AZ-93 on composite 0.833 ± 0.027 0.196 ± 0.006 0.235 

AgFEP on Al 0.719 ± 0.041 0.073 ± 0.006 0.102 

AgFEP on composite 0.648 ± 0.038 0.101 ± 0.025 0.156 

Figure 7.—The total change in / as a function of dust coverage. 
NASA/TM—2010-216828 9 

Conclusions 

Challenges associated with determining the percent coverage of dust applied to samples in the LDAB 

have been described and a statistical method to overcome them proposed. A thermal model is described 

that is capable of reproducing the experimental data within 1 percent. Even though it is difficult to narrow 

the range of the confidence interval without taking an extraordinary number of measurements, and the /

values contain all other sources of error in the time temperature plots, the trends are clear nonetheless. 

Even sub-monolayers of lunar dust will have a significant impact on the performance of thermal control 

surfaces. This study suggests that full monolayer coverage will raise the / values by a factor of 3 over a 

clean thermal control surface. Clearly, dust mitigation techniques must be developed to protect these 

surfaces during lunar exploration. 

References 

1. G.W. Bush, “A Renewed Spirit of Discovery: The President’s Vision for U.S. Space Exploration,” 

(2004). 

2. “NASA’s Exploration Systems Architecture Study,” NASA/TM—2005-214062. 

3. J.R. Gaier, “The Effects of Lunar Dust on EVA Systems During the Apollo Missions,” NASA/TM—

2005-213610. 

4. H. Schmitt, “The Apollo Experience/Problems Encountered with Lunar Dust,” Biological Effects of 

Lunar Dust Workshop, Sunnyvale, CA (2005). 

5. Jacobs, S., Durkee, R.E., and Harris, R.S., “Lunar Dust Deposition Effects on the Solar Absorptance 

of Thermal Control Materials,” AIAA Paper 71–479 presented at the AIAA 6th Thermophysics 

Conference, Tullahoma, TN, April 1971. 

6. McKay, G.H., Chairman, “Saturn V Launch Vehicle Flight Evaluation Report-AS-510, Apollo 15 

Mission,” Saturn V Flight Evaluation Working Group, 1971. 

7. McKay, G.H., Chairman, “Saturn V Launch Vehicle Flight Evaluation Report-AS-511, Apollo 16 

Mission,” Saturn V Flight Evaluation Working Group, 1972. 

8. McKay, G.H., Chairman, “Saturn V Launch Vehicle Flight Evaluation Report-AS-512, Apollo 17 

Mission,” Saturn V Flight Evaluation Working Group, 1973. 

9. James R. Gaier and Edward A. Sechkar, “Lunar Simulation in the Lunar Dust Adhesion Bell Jar,” 

Proceedings of the 45th AIAA Aerospace Sciences Meeting (2007). Also, NASA/TM—2007-214704 

(2007). 

10. Grossman, J.J., et al., Microchemical, Microphysical, and Adhesive Properties of Lunar Material, 

Proceedings of the Apollo 11 Lunar Science Conference, Vol. 3 (1970) pp. 2171–2181. 

11. Moore, David S. and McCabe, George P., Introduction to the Practice of Statistics, 2nd ed ., W.H. 

Freeman and Company, New York, 1993, pp. 576–577. 

12. Gaier, J.R., et al., The Effect of Simulated Lunar Dust on the Absorptance, Emittance, and Operating 

Temperature on AZ-93 and Ag/FEP Thermal Control Surfaces, manuscript in review (2008). 
REPORT DOCUMENTATION PAGE Form Approved 

OMB No. 0704-0188 

The public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the 

data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this 

burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. 

Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB 

control number. 

PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 

1. REPORT DATE (DD-MM-YYYY)

01-10-2010 

2. REPORT TYPE

Technical Memorandum 

3. DATES COVERED (From - To)

4. TITLE AND SUBTITLE

Extraction of Thermal Performance Values From Samples in the Lunar Dust Adhesion Bell 

Jar 

5a. CONTRACT NUMBER

5b. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

6. AUTHOR(S)

Gaier, James, R.; Siamidis, John; Larkin, Elizabeth, M.G. 

5d. PROJECT NUMBER

5e. TASK NUMBER

5f. WORK UNIT NUMBER

WBS 936374.04.08.03 

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

National Aeronautics and Space Administration 

John H. Glenn Research Center at Lewis Field 

Cleveland, Ohio 44135-3191 

8. PERFORMING ORGANIZATION

 REPORT NUMBER

E-16670-1 

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)

National Aeronautics and Space Administration 

Washington, DC 20546-0001 

10. SPONSORING/MONITOR'S

 ACRONYM(S)

NASA 

11. SPONSORING/MONITORING

 REPORT NUMBER

NASA/TM-2010-216828 

12. DISTRIBUTION/AVAILABILITY STATEMENT

Unclassified-Unlimited 

Subject Category: 91 

Available electronically at http://gltrs.grc.nasa.gov 

This publication is available from the NASA Center for AeroSpace Information, 443-757-5802

13. SUPPLEMENTARY NOTES

14. ABSTRACT

A simulation chamber has been developed to test the performance of thermal control surfaces under dusty lunar conditions. The lunar dust 

adhesion bell jar (LDAB) is a diffusion pumped vacuum chamber (10-8 Torr) built to test material samples less than about 7 cm in diameter. 

The LDAB has the following lunar dust simulant processing capabilities: heating and cooling while stirring in order to degas and remove 

adsorbed water; RF air-plasma for activating the dust and for organic contaminant removal; RF H/He-plasma to simulate solar wind; dust 

sieving system for controlling particle sizes; and a controlled means of introducing the activated dust to the samples under study. The LDAB 

is also fitted with an in situ Xe arc lamp solar simulator, and a cold box that can reach 30 K. Samples of thermal control surfaces (2.5 cm 

diameter) are introduced into the chamber for calorimetric evaluation using thermocouple instrumentation. The object of this paper is to 

present a thermal model of the samples under test conditions and to outline the procedure to extract the absorptance, emittance, and thermal 

efficiency from the pristine and sub-monolayer dust covered samples. 

15. SUBJECT TERMS

Lunar soil; Lunar dust; Thermal control coatings 

16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

 ABSTRACT

UU 

18. NUMBER

 OF 

 PAGES

15 

19a. NAME OF RESPONSIBLE PERSON

STI Help Desk (email:help@sti.nasa.gov) 

a. REPORT

U 

b. ABSTRACT

U 

c. THIS 

PAGE

U 

19b. TELEPHONE NUMBER (include area code)

443-757-5802 

Standard Form 298 (Rev. 8-98)

Prescribed by ANSI Std. Z39-18