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The Prediction of Stiffness of Bamboo-Reinforced Concrete Beams Using Experiment Data and Artificial Neural Networks (ANNs)
- 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).
- 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)
Subjects
Details
- Language :
- English
- ISSN :
- 20734352
- Volume :
- 10
- Issue :
- 757
- Database :
- OpenAIRE
- Journal :
- Crystals
- Accession number :
- edsair.doi.dedup.....2a0235e1bc15e0801ba20b46de3356c8