Abstract

This study analyses the interior-two-flange (ITF) web crippling strength of roll-formed aluminum alloy lipped channels (RA channels) with web holes employing experimental testing, numerical modeling, and deep neural network (i.e., Deep belief Network, DBN). A total of 30 experimental tests on web crippling behavior were carried out, with the results utilized to validate a finite element (FE) model, developed in this study. The experimental results were compared to the data produced by the validated FE model, which was then used to train the DBN model. The results of the DBN prediction were shown to be around 5% more conservative than the FE results. In order to evaluate the effects of associated factors on the ITF web crippling strength of RA channels, a comprehensive parametric study was conducted using the DBN. The design guidelines that are currently available in the American Iron and Steel Institute (AISI 2016), the Australian and New Zealand Standards (AS/NZS 1997; AS/NZS (2018)), and the Eurocode (CEN 2007) were found to be unreliable while determining the ITF web crippling strength of RA channels. The DBN's predictions developed new formulae for calculating the web crippling strength reduction factors. After conducting a reliability study, it was found that the developed strength reduction factor equations are reliable when calculating the ITF web crippling strength of such perforated roll-formed aluminium alloy channels.

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