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

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

Abstract

Stiffness is the main parameter of the beam&rsquo<br />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 &times<br />150 mm &times<br />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&rsquo<br />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 :
757
Database :
OpenAIRE
Journal :
Crystals
Accession number :
edsair.doi.dedup.....2a0235e1bc15e0801ba20b46de3356c8