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The Prediction of Stiffness of Bamboo-Reinforced Concrete Beams Using Experiment Data and Artificial Neural Networks (ANNs)

Authors :
Muhtar
Amri Gunasti
Suhardi
Nursaid
Irawati
Ilanka Cahya Dewi
Moh. Dasuki
Sofia Ariyani
Fitriana
Idris Mahmudi
Taufan Abadi
Miftahur Rahman
Syarif Hidayatullah
Agung Nilogiri
Senki Desta Galuh
Ari Eko Wardoyo
Rofi Budi Hamduwibawa
Source :
Crystals, Vol 10, Iss 9, p 757 (2020)
Publication Year :
2020
Publisher :
MDPI AG, 2020.

Abstract

Stiffness is the main parameter of the beam’s resistance to deformation. Based on advanced research, the stiffness of bamboo-reinforced concrete beams (BRC) tends to be lower than the stiffness of steel-reinforced concrete beams (SRC). However, the advantage of bamboo-reinforced concrete beams has enough good ductility according to the fundamental properties of bamboo, which have high tensile strength and high elastic properties. This study aims to predict and validate the stiffness of bamboo-reinforced concrete beams from the experimental results data using artificial neural networks (ANNs). The number of beam test specimens were 25 pieces with a size of 75 mm × 150 mm × 1100 mm. The testing method uses the four-point method with simple support. The results of the analysis showed the similarity between the stiffness of the beam’s experimental results with the artificial neural network (ANN) analysis results. The similarity rate of the two analyses is around 99% and the percentage of errors is not more than 1%, both for bamboo-reinforced concrete beams (BRC) and steel-reinforced concrete beams (SRC).

Details

Language :
English
ISSN :
20734352
Volume :
10
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Crystals
Publication Type :
Academic Journal
Accession number :
edsdoj.b6e3f494b5174de8b5148f928565ae8b
Document Type :
article
Full Text :
https://doi.org/10.3390/cryst10090757