Determining of Load Bearing Capacity of Rectangular Concrete Columns Reinforced with Longitudinal Spirals Using FEM and ANN Methods

Document Type : Original Article

Authors

1 Department of Civil Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Iran

2 Student of Faculty of Engineering, Department of Civil Engineering, Shahid Chamran University of Ahvaz

Abstract

Concrete rectangular columns reinforced with longitudinal spirals are new types of RC columns which their behavior has been investigated by researchers in recent years. These researches are limited to some experimental studies which investigate the effect of different configurations and layouts of the spirals within the cross-section of these columns on the bearing capacity and ductility. In this study, for the first time, the behavior of these columns has been simulated using numerical approaches. Finite Element (FE) models of these columns were developed using ABAQUS/CAE/Explicit v.2016 and then verified against available valid experiments in literature. Subsequently, by performing several sensitivity analyses using verified EF model, the effective parameters on bearing capacity of this kind of columns were detected. By changing the value of these parameters in rational ranges, a comprehensive parametric analysis was done after that using FE models in order to produce necessary input data for training an Artificial Neural Network (ANN). This parametric study was performed because of the lake of sufficient available experimental data. The developed ANN was verified against some experimental data. Finally, in addition to ANN, a regression analysis was performed to obtain a polynomial function can predict the bearing capacity of these type of columns. Obtained results demonstrate that the combination of FE and ANN is an effective method to predict the load bearing capacity of RC columns with longitudinal spiral reinforcements and have a good agreement with the results of regression analysis.

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References

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Journal of Structural and Construction Engineering
Volume 6, Issue 2 - Serial Number 24
August 2019
Pages 157-176

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History

  • Receive Date: 22 October 2017
  • Revise Date: 07 January 2018
  • Accept Date: 05 February 2018

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