Buckling load optimization of sandwich plates with trapezoidal corrugated core and elliptical cutout using vibration correlation techniques and artificial neural network; experimental and numerical analysis

The present research was carried out in order to estimate the buckling load of a sandwich plate with a trapezoidal corrugated core with cut-out using three vibration correlation techniques (VCT). The structure investigated in this research is a sandwich plate with a trapezoidal core and an oval cut-out, which is made of thermoplastic polymer using a 3D printer. By using artificial neural network (ANN) and genetic algorithm (GA), the specific critical buckling load (pcr) which is defined as the ratio of critical buckling load (Pcr) to plate weight (gr) has been minimized and the optimal dimensions for cut-out parameters including the ratio of the large diameter of the ellipse (z = 20mm) to the small diameter of the ellipse (b) and oval angles with the horizontal axis (a degrees) are obtained. Using the method of equivalent properties, the trapezoidal core is transformed into an equivalent orthotropic core and finally the desired structure is transformed into a three-layer sandwich plate including homogeneous upper and lower layers and an orthotropic middle layer. By using the meshless method based on radial and polynomial functions and with the help of the finite element method, the numerical simulation of buckling and free vibration of the sandwich plate has been done. The results showed that the estimation of the buckling load with the vibration correlation technique (VCT) corresponds to the actual condition of the structure, so that due to the high quality of sandwich plate construction and its integrity, the results obtained from the first, second, and third methods of the VCT show the effectiveness of this method for predicting of the buckling load of the structure.