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Going to Extremes: Meeting the Emerging Demand for Durable Polymer Matrix Composites (2005)

Chapter: Appendix B Frequently Used Abbreviations

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Suggested Citation:"Appendix B Frequently Used Abbreviations." National Research Council. 2005. Going to Extremes: Meeting the Emerging Demand for Durable Polymer Matrix Composites. Washington, DC: The National Academies Press. doi: 10.17226/11424.
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Appendix B
Frequently Used Abbreviations


CAI

Composite Affordability Initiative

CFRP

carbon-fiber-reinforced polymers

CMC

ceramic matrix composite


DOD

Department of Defense


EMI

electromagnetic interference


FAA

Federal Aviation Administration

FEA

finite element analysis

FRP

fiber-reinforced polymers


GFRP

glass-fiber-reinforced polymers


HSR

high-speed research


ITAR

International Trade and Arms Regulations


MIL-HDBK

the former military handbook


NASA

National Aeronautics and Space Administration


PMC

polymer matrix composite


RF

radio frequency

Page 50 Cite
Suggested Citation:"Appendix B Frequently Used Abbreviations." National Research Council. 2005. Going to Extremes: Meeting the Emerging Demand for Durable Polymer Matrix Composites. Washington, DC: The National Academies Press. doi: 10.17226/11424.
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Going to Extremes: Meeting the Emerging Demand for Durable Polymer Matrix Composites
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Advanced polymer matrix composites (PMC) have many advantages such as light weight and high specific strength that make them useful for many aerospace applications. Enormous uncertainty exists, however, in predicting long-term changes in properties of PMCs under extreme environmental conditions, which has limited their use. To help address this issue, the Department of Defense requested a study from the NRC to identify the barriers and limitations to the use of PMCs in extreme environments. The study was to focus on issues surrounding methodologies for predicting long-term performance. This report provides a review of the challenges facing application of PMCs in extreme environments, the current understanding of PMC properties and behavior, an analysis of the importance of data in developing effective models, and recommendations for improving long-term predictive methodologies.

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