(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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Official URL: https://www.mdpi.com/2073-4352/10/9/757

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)

Item Type:	Peer Review
Subjects:	400 Language > 406 Organization & Management
Divisions:	Graduate School > Magister Management (S2)
Depositing User:	Nursaid Nursaid
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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