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  • Other Sources  (4)
  • METALLIC MATERIALS  (3)
  • Computer Programming and Software  (1)
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  • 1
    Publication Date: 2011-08-18
    Description: (Previously announced in STAR as N81-19276)
    Keywords: METALLIC MATERIALS
    Type: Metallurgical Transactions A - Physical Metallurgy and Materials Science; 14A; Feb. 198
    Format: text
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  • 2
    Publication Date: 2019-06-28
    Description: Corrosion of SAE 310 stainless steel in H2-H2O-H2S gas mixtures was studied at a constant temperature of 1150 K. Reactive gas mixtures were chosen to yield a constant oxygen potential of approximately 6 x 10 to the minus 13th power/cu Nm and sulfur potentials ranging from 0.19 x 10 to the minus 2nd power/cu Nm to 33 x 10 to the minus 2nd power/cu Nm. The kinetics of corrosion were determined using a thermobalance, and the scales were analyzed using metallography, scanning electron microscopy, and energy dispersive X-ray analysis. Two corrosion regimes, which were dependent on sulfur potential, were identified. At high sulfur potentials (p sub S sub 2 less than or equal to 2.7 x 10 to the minus 2nd power/cu Nm) the corrosion rates were high, the kinetics obeyed a linear rate equation, and the scales consisted mainly of sulfide phases similar to those observed from pure sulfication. At low sulfur potentials (P sub S sub 2 less than or equal to 0.19 x 10 to the minus 2nd power/cu Nm) the corrosion rates were low, the kinetics obeyed a parabolic rate equation, and scales consisted mainly of oxide phases.
    Keywords: METALLIC MATERIALS
    Type: NASA-TM-81242 , A-8349
    Format: application/pdf
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  • 3
    Publication Date: 2019-06-27
    Keywords: METALLIC MATERIALS
    Type: Oxidation of Metals; 13; Feb. 197
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  • 4
    Publication Date: 2019-07-17
    Description: Existing tools for debugging performance of parallel programs either provide graphical representations of program execution or profiles of program executions. However, for performance debugging tools to be useful, such information has to be augmented with information that highlights the cause of poor program performance. Identifying the cause of poor performance necessitates the need for not only determining the significance of various performance problems on the execution time of the program, but also needs to consider the effect of interprocessor communications of individual source level data structures. In this paper, we present a suite of normalized indices which provide a convenient mechanism for focusing on a region of code with poor performance and highlights the cause of the problem in terms of processors, procedures and data structure interactions. All the indices are generated from trace files augmented with data structure information.. Further, we show with the help of examples from the NAS benchmark suite that the indices help in detecting potential cause of poor performance, based on augmented execution traces obtained by monitoring the program.
    Keywords: Computer Programming and Software
    Type: Supercomputing; Jul 11, 1994 - Jul 15, 1994; Manchester; United Kingdom
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