4.7 Article

Assessment of RC exterior beam-column Joints based on artificial neural networks and other methods

Journal

ENGINEERING STRUCTURES
Volume 144, Issue -, Pages 1-18

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.engstruct.2017.04.048

Keywords

Artificial neural networks; Codes of practice; Design; External beam-column joints; Reinforced concrete

Funding

  1. HORIZON Marie Sklodowska-Curie Research Fellowship Programme titled: ANALYSIS OF RC STRUCTURES EMPLOYING NEURAL NETWORKS (ARCSENN) [H2020-660545]

Ask authors/readers for more resources

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. (C) 2017 Published by Elsevier Ltd.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available