Abstract
An adaptive neuro-fuzzy inference system (ANFIS) combines artificial neural networks (ANNs) with a Fuzzy Inference System (FIS) to predict the first three natural frequencies of basalt/carbon fiber (CF)-reinforced hybrid laminated composite face layers and Polyethylene Terephthalate (PET) foam-core skew sandwich plates. The ANFIS models are trained on large datasets, with accuracy validated through statistical methods. Elastic properties of the face layers and PET foam core are measured via uniaxial tensile and compression testing. Experimental modal analysis and numerical simulations in ABAQUS demonstrate that natural frequencies increase with skew angle and core thickness, but decrease with aspect ratios and fiber angles.
Published Version
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