Ultimate strength prediction of I-core sandwich plate based on BP neural network

Abstract

Objectives In view of the incomplete evaluation of the ultimate strength of I-core sandwich panels in the past, a BP artificial neural network method is proposed to quantitatively determine the influence of relevant parameters on the ultimate strength of I-core sandwich panels. MethodsFirst, the ultimate strength of I-core sandwich panels under axial compression are investigated using the nonlinear finite element method. Second, a BP neural network is constructed to predict the ultimate strength of I-core sandwich panels with different plate slenderness ratios between longitudinal webs, plate slenderness ratios of webs and column slenderness ratio of one longitudinal web. Finally, a formula for predicting the ultimate strength of I-core sandwich panels using the artificial neural network weight and bias method is proposed. ResultsThe mean square error MSE and correlation coefficient R of ultimate strength prediction using the BP neural network method are 0.001 2 and 0.981 8 respectively. The proposed neural network model has good prediction accuracy, and the maximum error is less than 10%. ConclusionsThis study can provide references for the application of I-core sandwich panels in hull structures.

Keywords

• i-core sandwich panels
• bp neural network
• ultimate strength
• nonlinear finite element method
• prediction