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Quantifying High Temperature Corrosion

Product Number: 51321-16805-SG
Author: Y. F. Su; P. I. M. Stack; C. J. Stephens; K. A. Kane; S. Dryepondt; R. Pillai; B. A. Pint
Publication Date: 2021
$0.00
$20.00
$20.00

Alloys designed for high temperature service can form a variety of surface oxides or scales based on the alloy composition, service temperature, gas environment, surface deposits, etc.  The most severe environments, including molten salts and liquid metals can result in significant metal loss, void formation and/or pitting. Standard and evolving practices are discussed for measuring these types of degradation including measuring oxide scale thickness, internal oxidation and/or metal loss, correlating them to mass change and reporting the results. Manual and automated methodologies to measure oxide thickness and metal loss are reviewed and compared in order to provide a summary of techniques and identify the best practices for quantifying a variety of materials and damage mechanisms and producing statistically meaningful results.  Such techniques create datasets useful for improved understanding of corrosion degradation mechanisms, potentially better predictive
models and enhanced data analytics.

Alloys designed for high temperature service can form a variety of surface oxides or scales based on the alloy composition, service temperature, gas environment, surface deposits, etc.  The most severe environments, including molten salts and liquid metals can result in significant metal loss, void formation and/or pitting. Standard and evolving practices are discussed for measuring these types of degradation including measuring oxide scale thickness, internal oxidation and/or metal loss, correlating them to mass change and reporting the results. Manual and automated methodologies to measure oxide thickness and metal loss are reviewed and compared in order to provide a summary of techniques and identify the best practices for quantifying a variety of materials and damage mechanisms and producing statistically meaningful results.  Such techniques create datasets useful for improved understanding of corrosion degradation mechanisms, potentially better predictive
models and enhanced data analytics.

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