Computer Science – Performance
Scientific paper
Jan 2002
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2002iaf..confe.469g&link_type=abstract
IAF abstracts, 34th COSPAR Scientific Assembly, The Second World Space Congress, held 10-19 October, 2002 in Houston, TX, USA.,
Computer Science
Performance
Scientific paper
Data describing long-term materials performance under exposure to space environments has accumulated gradually over the past four decades. The authors present here selected results from several previous flight experiments and operational spacecraft, and a few examples from a current flight experiment. As examples of environmental effects on materials, analysis of Gortex samples from the Passive Optical Sample Assembly II (POSA II) experiment on the MIR-Shuttle docking module will be described. Results from a previous evaluation of radiation on silverized Teflon from over ten individual satellites will be summarized. Several examples of contamination effects on materials properties will be presented. These include outgassing of solar arrays onto nearby surfaces of the POSA I experiment and contamination of certain surfaces of the Long Duration Exposure Facility (LDEF). Results from experiments with silicone contamination on satellites in geosynchronous orbit will be compared with measurements on the Solar Maximum satellite and the LDEF. A number of techniques are being attempted to extend the range of exposure conditions present on selected experiments. Use of focusing concentrators on the Effect of Space Environments on Materials (ESEM), POSA, and Materials International Space Station Experiment (MISSE) will be described. A technique for obtaining time-resolved data from a passive materials experiment will be described. The status of an on-going materials flight experiment, MISSE, will be reported. Finally, the authors will draw some conclusions about the current state of knowledge relating to materials chosen for spacecraft applications. Understanding of degradation mechanisms, state of predictive models, and the need to strengthen model inputs will be discussed.
Golden Lewis J.
Pippin Gary H.
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