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51314-4127-Instrumented Test Coupons for Enhanced Evaluation of Material Performance

Product Number: 51314-4127-SG
ISBN: 4127 2014 CP
Author: Mara Shedd
Publication Date: 2014
$0.00
$20.00
$20.00
The annual cost of corrosion for Air Force aircraft and missiles is estimated to be $5.4 billion with corrosion accounting for 32.2% of the maintenance budget. In large part mitigation of corrosion is achieved through materials selection based on accelerated laboratory corrosion and service environment testing. Military performance requirements for materials qualification often rely on pass/fail measurements of flat panels with scribed defects exposed in continuous salt fog tests. It is well known that these tests are only appropriate for quality assurance testing and that in operational environments corrosion protection systems and alloys may fail due to other corrosion processes associated with localized corrosion galvanic couples and mechanical loading that may not be evaluated using current practices. Although advances have been made and research continues in the development of more representative accelerated corrosion test cycles (GM 9540P ASTM G85 SAE J2334 SERDP WP-1673 WP-1674) similar advancements in test coupon design and instrumentation have not been realized. There is a need to improve coatings and materials corrosion testing by leveraging advances in sensing and instrumentation to obtain high fidelity data on corrosion performance and degradation processes. To address this issue a smart test coupon (STC) that incorporates multimodal measurements using advanced low cost sensors and monitoring techniques to improve materials evaluation in accelerated laboratory corrosion and service environment testing has been developed. The modular open architecture system design for this technology supports the continuous multimodal sensing of environmental parameters corrosion coating performance and material residual strength throughout a corrosion test. The results of the laboratory testing of the individual sensor elements for corrosion galvanic corrosion and residual strength that generated consistent data to rank coating performance will be presented. 
The annual cost of corrosion for Air Force aircraft and missiles is estimated to be $5.4 billion with corrosion accounting for 32.2% of the maintenance budget. In large part mitigation of corrosion is achieved through materials selection based on accelerated laboratory corrosion and service environment testing. Military performance requirements for materials qualification often rely on pass/fail measurements of flat panels with scribed defects exposed in continuous salt fog tests. It is well known that these tests are only appropriate for quality assurance testing and that in operational environments corrosion protection systems and alloys may fail due to other corrosion processes associated with localized corrosion galvanic couples and mechanical loading that may not be evaluated using current practices. Although advances have been made and research continues in the development of more representative accelerated corrosion test cycles (GM 9540P ASTM G85 SAE J2334 SERDP WP-1673 WP-1674) similar advancements in test coupon design and instrumentation have not been realized. There is a need to improve coatings and materials corrosion testing by leveraging advances in sensing and instrumentation to obtain high fidelity data on corrosion performance and degradation processes. To address this issue a smart test coupon (STC) that incorporates multimodal measurements using advanced low cost sensors and monitoring techniques to improve materials evaluation in accelerated laboratory corrosion and service environment testing has been developed. The modular open architecture system design for this technology supports the continuous multimodal sensing of environmental parameters corrosion coating performance and material residual strength throughout a corrosion test. The results of the laboratory testing of the individual sensor elements for corrosion galvanic corrosion and residual strength that generated consistent data to rank coating performance will be presented. 
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