Artificial neural network approach to buckling coefficients of laminated orthotropic rectangular plates with a centrally rectangular hole

The objective of the present study is to describe the results of research that has been conducted on the buckling behavior of rectangular laminated orthotropic plates that have a rectangular hole. As a result of using some geometrical holes which cause stress concentrations on laminated orthotropic plates, the analysis about the buckling coefficient of the elements become very important. This work deals with buckling analysis of laminated orthotropic plates with a central rectangular hole under in-plane static loading (uniaxial compression). Initially, the critical buckling coefficients of the laminated plates are obtained by finite elements method. However, as a new study, an other numerical method is applied to this work which is called “artificial neural networks” in order to obtain those buckling coefficients. A PASCAL computer program is used for training and testing procedure of neural networks, and finally good results are achieved.