A hybrid Kelvin-Voigt viscoelastic and stabilized neural ODE model, identified from DMA and DSC experiments, predicts composite prepreg deformation in robotic 3D printing and generalizes beyond training temperatures.
Polymer43(3), 731–735 Ghnatios and Fayazbakhsh Page 30 of 30 (2002)
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Hybrid Machine Learning and Physical Modeling of Feedstock Deformation During Robotic 3D Printing of Continuous Fiber Thermoplastic Composites
A hybrid Kelvin-Voigt viscoelastic and stabilized neural ODE model, identified from DMA and DSC experiments, predicts composite prepreg deformation in robotic 3D printing and generalizes beyond training temperatures.