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Monte Carlo Computational Modeling of Atomic Oxygen InteractionsComputational modeling of the erosion of polymers caused by atomic oxygen in low Earth orbit (LEO) is useful for determining areas of concern for spacecraft environment durability. Successful modeling requires that the characteristics of the environment such as atomic oxygen energy distribution, flux, and angular distribution be properly represented in the model. Thus whether the atomic oxygen is arriving normal to or inclined to a surface and whether it arrives in a consistent direction or is sweeping across the surface such as in the case of polymeric solar array blankets is important to determine durability. When atomic oxygen impacts a polymer surface it can react removing a certain volume per incident atom (called the erosion yield), recombine, or be ejected as an active oxygen atom to potentially either react with other polymer atoms or exit into space. Scattered atoms can also have a lower energy as a result of partial or total thermal accommodation. Many solutions to polymer durability in LEO involve protective thin films of metal oxides such as SiO2 to prevent atomic oxygen erosion. Such protective films also have their own interaction characteristics. A Monte Carlo computational model has been developed which takes into account the various types of atomic oxygen arrival and how it reacts with a representative polymer (polyimide Kapton H) and how it reacts at defect sites in an oxide protective coating, such as SiO2 on that polymer. Although this model was initially intended to determine atomic oxygen erosion behavior at defect sites for the International Space Station solar arrays, it has been used to predict atomic oxygen erosion or oxidation behavior on many other spacecraft components including erosion of polymeric joints, durability of solar array blanket box covers, and scattering of atomic oxygen into telescopes and microwave cavities where oxidation of critical component surfaces can take place. The computational model is a two dimensional model which has the capability to tune the interactions of how the atomic oxygen reacts, scatters, or recombines on polymer or nonreactive surfaces. In addition to the specification of atomic oxygen arrival details, a total of 15 atomic oxygen interaction parameters have been identified as necessary to properly simulate observed interactions and resulting polymer erosion that have been observed in LEO. The tuning of the Monte Carlo model has been accomplished by adjusting interaction parameters so the erosion patterns produced by the model match those from several actual LEO space experiments. Surface texturing in LEO can also be predicted by the model. Such comparison of space tests with ground laboratory experiments have enabled confidence in ground laboratory lifetime prediction of protected polymers. Results of Monte Carlo tuning, examples of surface texturing and undercutting erosion prediction, and several examples of how the model can be used to predict other LEO and Mars orbital space results are presented.
Document ID
20170006849
Acquisition Source
Glenn Research Center
Document Type
Conference Paper
Authors
Banks, Bruce A.
(Science Applications International Corp. Huntsville, AL, United States)
Stueber, Thomas J.
(NASA Glenn Research Center Cleveland, OH United States)
Miller, Sharon K.
(NASA Glenn Research Center Cleveland, OH United States)
De Groh, Kim K.
(NASA Glenn Research Center Cleveland, OH United States)
Date Acquired
July 19, 2017
Publication Date
May 15, 2017
Subject Category
Atomic And Molecular Physics
Statistics And Probability
Report/Patent Number
GRC-E-DAA-TN41765
Meeting Information
Meeting: Applied Space Environments Conference (ASCE 2017): Measurements, Models, Testing, and Tools
Location: Huntsville, AL
Country: United States
Start Date: May 15, 2017
End Date: May 19, 2017
Sponsors: NASA Headquarters, Universities Space Research Association
Funding Number(s)
WBS: WBS 199008.02.03
CONTRACT_GRANT: NNC12BA01B
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
Atomic Oxygen
Monte Carlo Modeling
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