Design and Testing
Measuring ply-wise deformation during consolidation using embedded sensors
Strip-type shape sensor method claims real-time measurement of ply-wise deformation.
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Notched testing of sandwich composites: The sandwich open-hole compression test
A new ASTM-standardized open-hole compression test method seeks to determine the notch sensitivity of sandwich composites.
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Material equivalence testing in shared composites databases
In response to traditionally proprietary polymer matrix composites (PMC) qualifications, NCAMP continues its efforts to make material property databases publicly available.
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Glass-coated magnetic microwires for nondestructive composites monitoring
Glass-coated, amorphous microwires combine nanometer to micrometer diameters, enabling embedding into composites without degrading mechanical properties.
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Composite prepreg tack testing
A recently standardized prepreg tack test method has been developed for use in material selection, quality control and adjusting cure process parameters for automated layup processes.
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Improving analyses of composite pressure vessels
Accurate geometry modeling and equivalent material property approximations captured by WoundSim will play a role in improving COPV analyses.
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Determining the equivalency of composite test methods
While time consuming and somewhat subjective, the comparative assessment approach has been proven effective toward assessing composites test method equivalence.
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Composites testing as part of a building block approach, Part 2: Upper building block levels
Testing under the upper levels of the building block approach for composites design depends on the structure’s application and complexity.
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Model-driven design and analysis for sustainable lightweight design
Fraunhofer IGCV uses graph-based design language for fast creation of design variants and simultaneous evaluation of ecological and economic performance along the entire life cycle.
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Using machine learning to accelerate composites processing simulation
A speed gain of 1,000 to 10,000 times greater than traditional FE models has been achieved using machine learning models, enabling near real-time simulation for large composite components.
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