Article citationsMore>>

Nicholas, P.E., Padmanaban, K.P., Vasudevan, D. and Selvaraj, I.J. (2014) Neural Network Based Buckling Strength Prediction of Laminated Composite Plate with Central Cutout. Applied Mechanics and Materials, 592-594, 560-564.
http://dx.doi.org/10.4028/www.scientific.net/AMM.592-594.560

has been cited by the following article:

• TITLE: Application of Artificial Neural Network for Analysis of Triangular Plate with Hole Considering Different Geometrical and Loading Parameters

  AUTHORS: Saket Rusia, Krishna Kant Pathak

  KEYWORDS: Artificial Neural Networks, Finite Element Analysis, Triangular Plate, ANSYS

  JOURNAL NAME: Open Journal of Civil Engineering, Vol.6 No.1, February 29, 2016

  ABSTRACT: In this study, Artificial Neural Network has been employed for analysis of triangular plate with different geometrical and loading parameters. Plates, having different sizes of concentric holes are analyzed. Finite element analysis for 81 cases is carried out using ANSYS Workbench 15.0 software. Using these data of FEM analysis an Artificial Neural Network has been trained. The successfully trained network is further used for analysis of four new cases which are also validated by using ANSYS Workbench 15.0 software.