期刊
NANOMATERIALS
卷 11, 期 10, 页码 -出版社
MDPI
DOI: 10.3390/nano11102631
关键词
carbon fibers; composites; nanoindentation; impact behavior; interphase; artificial intelligence; neural networks; deep learning
类别
资金
- EU H2020 Project Modified Cost Effective Fibre Based Structures With Improved Multi-Functionality And Performance (MODCOMP) [685844]
- EU H2020 Project Smart By Design And Intelligent By Architecture For Turbine Blade Fan And Structural Components Systems (SMARTFAN) [760779]
This study investigated the exposure of carbon-fiber-reinforced polymers (CFRPs) to open-field conditions and demonstrated the modification effects on carbon-fiber interfaces and impact resistance. Nanomechanical properties mapping and Weibull analysis connected the weathering effect to the statistically representative behavior of the produced composites. Artificial intelligence for anomaly detection and deep-learning neural networks were used to model the resistance to plastic deformation based on nanoindentation parameters, providing new assessment insights in composite engineering and quality assurance.
The exposure of carbon-fiber-reinforced polymers (CFRPs) to open-field conditions was investigated. Establishment of structure-property relations with nanoindentation enabled the observation of modification effects on carbon-fiber interfaces, and impact resistance. Mapping of nanomechanical properties was performed using expectation-maximization optimization of Gaussian fitting for each CFRPs microstructure (matrix, interface, carbon fiber), while Weibull analysis connected the weathering effect to the statistically representative behavior of the produced composites. Plasma modification demonstrated reduced defect density and improved nanomechanical properties after weathering. Artificial intelligence for anomaly detection provided insights on condition monitoring of CFRPs. Deep-learning neural networks with three hidden layers were used to model the resistance to plastic deformation based on nanoindentation parameters. This study provides new assessment insights in composite engineering and quality assurance, especially during exposure under service conditions.
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