Title:
Prediction of Shear Strength of One-Way Slabs Voided by Circular Paper Tubes using Artificial Intelligence
Author(s):
Iman Mansouri, Chang-Hwan Lee, and Paul O. Awoyera
Publication:
Symposium Paper
Volume:
350
Issue:
Appears on pages(s):
132-141
Keywords:
voided slab, one-way slab, shear strength, artificial neural network
DOI:
10.14359/51734319
Date:
11/1/2021
Abstract:
TUBEDECK, a one-way spanning voided composite slab, has been utilized in the construction field over the years to enhance the efficiency, constructability, and environmental performance of structures. TUBEDECK incorporates both cast-in-situ reinforced concrete slabs and profiled steel decks. However, there is a need to clarify the shear resistance capacity in this slab because the shear strength of the member reduces as concrete volume is eliminated to optimize flexural strength. Therefore, this study applied the artificial neural network (ANN) technique to determine the shear strength of TUBEDECK. By varying factors in the ANN features, several ANN models were developed. Out of many models developed, an optimal model was selected, having a maximum/mean relative errors of 5.1% in a dataset.
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