| Autor: |
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 |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Crystals, Vol 10, Iss 9, p 757 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2073-4352 |
| DOI: |
10.3390/cryst10090757 |
| Popis: |
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). |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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