Experimental methods to characterize the woven composite prepreg behavior during the preforming process Article Swipe
This paper reports several characterization methods of the properties of the uncured woven prepreg during the preforming process. The uniaxial tension, bias-extension, and bending tests are conducted to measure the in-plane properties of the material. The friction tests utilized to reveal the prepreg-prepreg and prepreg-forming tool interactions. All these tests are performed within the temperature range of the real manufacturing process. The results serve as the inputs to the numerical simulation for the product prediction and preforming process parameter optimization.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://www.osti.gov/biblio/1431017
- OA Status
- green
- Cited By
- 7
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W2625550687
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2625550687Canonical identifier for this work in OpenAlex
- Title
-
Experimental methods to characterize the woven composite prepreg behavior during the preforming processWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2016Year of publication
- Publication date
-
2016-01-01Full publication date if available
- Authors
-
Weizhao Zhang, JiList of authors in order
- Landing page
-
https://www.osti.gov/biblio/1431017Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.osti.gov/biblio/1431017Direct OA link when available
- Concepts
-
Tension (geology), Bending, Composite material, Materials science, Composite number, Process (computing), Forming processes, Characterization (materials science), Woven fabric, Structural engineering, Compression (physics), Engineering, Computer science, Nanotechnology, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 2, 2020: 1, 2019: 1, 2018: 3Per-year citation counts (last 5 years)
- Related works (count)
-
20Other works algorithmically related by OpenAlex
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