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

Nursaid, Nursaid (2020) (Similarity + Document) The Prediction of Stiffness of Bamboo-Reinforced Concrete Beams Using Experiment Data and Artificial Neural Networks (ANNs). MDPI, Internasional.

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Abstract

Sti�ness is the main parameter of the beam’s resistance to deformation. Based on advanced
research, the sti�ness of bamboo-reinforced concrete beams (BRC) tends to be lower than the sti�ness
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 sti�ness 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 sti�ness 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).
Keywords: bamboo-reinforced concrete (BRC); sti�ness prediction; artificial neural network (ANN)

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Item Type:	Peer Review
Subjects:	400 Language > 406 Organization & Management
Divisions:	Graduate School > Magister Management (S2)
Depositing User:	Nursaid Nursaid | nursaid@unmuhjember.ac.id
Date Deposited:	14 Nov 2023 03:36
Last Modified:	14 Nov 2023 03:36
URI:	http://repository.unmuhjember.ac.id/id/eprint/20466

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