Abstract

Continuous fiber reinforced thermoplastics (cFRTP) are one of the most promising lightweight materials. For their use in structural components, reproducible and comparable material values have to be evaluated, especially at high strain rates. Due to their high stiffness and outstanding strength properties, the evaluation of the material behavior at high strain rates is complex. In the presented work, a new tensile specimen geometry for strain rate testing is virtually optimized using a metamodel approach with an artificial neural network. The final specimen design is experimentally validated and compared with rectangular specimen results for a carbon fiber reinforced polycarbonate (CF-PC). The optimized specimen geometry leads to 100% valid test results in experimental validation of cross-ply laminates and reaches 9% higher tensile strength values than the rectangle geometry with applied end tabs at a strain rate of 40 s−1. Through the optimization, comparable material parameters can be efficiently generated for a successful cFRTP strain rate characterization.

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