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Composite cure simulation scheme fully integrating internal strain measurement
Affiliation:1. State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology, 122 Luoshi Road, Wuhan 430070, Hubei, China;2. China Ship Development and Design Center, Wuhan 430064, Hubei, China;1. Electronic Engineering Institute, China Academy of Engineering Physics, Mianyang, China;2. School of Materials Science and Engineering, Wuhan University of Technology, Wuhan, China;3. Institute of Advanced Materials and Manufacturing Technology, Wuhan University of Technology, Wuhan, China;4. State Key Laboratory of Materials Synthesis and Processing, Wuhan University of Technology, Wuhan, China;1. School of Mechanical Engineering, Chung-Ang University (CAU), 221, Huksuk-Dong, Dongjak-Gu, Seoul 156-756, Republic of Korea;2. Korea Photonics Technology Institute Lighting Solution R&BD Center, Gwangju, Republic of Korea
Abstract:This study proposes a new approach to determine key material parameters for stress/strain calculation of curing composite laminates and validate the simulation. Specifically, fiber Bragg grating (FBG) strain sensors are embedded in a composite laminate and the two key parameters for simulation, composite shrinkage strain and stiffness change during curing, are simultaneously determined from in-situ measurements by the embedded sensors. Furthermore, the simulation is validated using internal strain change during curing. This paper begins by presenting an overview of the proposed simulation scheme and by comparing it with previous approaches to highlight its advantages. Material parameter determination using a shear-lag effect at the edge of the embedded sensors is then described and the practical procedure to obtain the key parameters is demonstrated using a carbon/epoxy laminate. Finally, cure simulation is conducted for validation. Further extension to more general cases including thermoplastic composites is also discussed.
Keywords:B  Cure behavior  B  Residual/internal stress  C  Process simulation  D  Process monitoring
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