A database on the behaviour of reinforced concrete external beam-column joint sub-assemblages established from the results of over 150 tests is developed and used for the development, training and validation of an artificial neural network (ANN) based model. The ANN model predictions on the mode of failure and load-carrying capacity of the joints, together with the predictions of widely used code methods and those of a recently proposed method, which does not require calibration through the use of test data, are compared with their counterparts stored in the database developed herein. The comparison confirms the already reported shortcomings of current code methods and demonstrates that both ANN model and the recently proposed method can provide reliable alternatives to the code methods.
|Number of pages||18|
|Early online date||4 May 2017|
|Publication status||Published - 1 Aug 2017|
- Artificial Neural Networks
- codes of practice & standards
- external beam-column joints
- reinforced concrete
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Demetrios M. Cotsovos
- School of Energy, Geoscience, Infrastructure and Society - Associate Professor
- School of Energy, Geoscience, Infrastructure and Society, Institute for Infrastructure & Environment - Associate Professor
Person: Academic (Research & Teaching)