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Start Over Author "Ari Eko Wardoyo" Topic artificial neural network (ann)
2 results on '"Ari Eko Wardoyo"'

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

Author

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, and Rofi Budi Hamduwibawa

Subjects
bamboo-reinforced concrete (BRC), stiffness prediction, artificial neural network (ANN), Crystallography, QD901-999
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).

Published
2020
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2. The Prediction of Stiffness of Bamboo-Reinforced Concrete Beams Using Experiment Data and Artificial Neural Networks (ANNs)

Author

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, and Syarif Hidayatullah

Subjects
Bamboo, Materials science, Similarity (geometry), General Chemical Engineering, 0211 other engineering and technologies, 02 engineering and technology, Deformation (meteorology), Computer Science::Robotics, Inorganic Chemistry, 021105 building & construction, Ultimate tensile strength, medicine, lcsh:QD901-999, General Materials Science, 021108 energy, Ductility, Artificial neural network, business.industry, Stiffness, artificial neural network (ANN), Structural engineering, Condensed Matter Physics, Physics::Accelerator Physics, bamboo-reinforced concrete (BRC), lcsh:Crystallography, medicine.symptom, business, stiffness prediction, Beam (structure)
Abstract

Stiffness is the main parameter of the beam&rsquo, 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, 150 mm &times, 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, 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).

Published
2020

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