Buckling designs of CFRP symmetric laminated plates by a neural network

The fiber orientation angle has an important effect on flexural rigidities and buckling values of CFRP symmetric laminated plates, and this angle is one of the design variables of CFRP. However, it is hard to determine its correct value in the case of designing CFRP symmetric laminated plates having a specific buckling value. This decision becomes, so to speak, an inverse problem. This paper presents an application of a neural network to the buckling design of CFRP symmetric laminated plates, and gives the solution to this inverse problem by use of a neural network.