Authors
Abstract
In this study, a model for predicting the ultimate strength of rectangular
concrete filled steel tube (RCFST) beam-columns under eccentric axial loads has
been developed using artificial neural networks (ANN). The available experimental
results for (111) specimens obtained from open literature were used to build the
proposed model. The predicted strengths obtained from the proposed ANN model
were compared with the experimental values and with unfactored design strengths
predicted using the design procedure specified in the AISC and Eurocode 4 for
RCFST beam-columns. Results showed that the predicted values by the proposed
ANN model were very close to the experimental values and were more accurate
than the AISC and Eurocode 4 values. As a result, ANN provided an efficient
alternative method in predicting the ultimate strength of RCFST beam-columns.
Keywords
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