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Keywords = bamboo-reinforced concrete (BRC)

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27 pages, 8199 KiB  
Article
The Prediction of Stiffness Reduction Non-Linear Phase in Bamboo Reinforced Concrete Beam Using the Finite Element Method (FEM) and Artificial Neural Networks (ANNs)
by Muhtar
Forests 2020, 11(12), 1313; https://doi.org/10.3390/f11121313 - 10 Dec 2020
Cited by 6 | Viewed by 2882
Abstract
This paper discusses the reduction of the stiffness of bamboo reinforced concrete (BRC) beams to support the use of bamboo as an environmentally friendly building material. Calculation of cross-section stiffness in numerical analysis is very important, especially in the non-linear phase. After the [...] Read more.
This paper discusses the reduction of the stiffness of bamboo reinforced concrete (BRC) beams to support the use of bamboo as an environmentally friendly building material. Calculation of cross-section stiffness in numerical analysis is very important, especially in the non-linear phase. After the initial crack occurs, the stiffness of the cross-section will decrease with increasing load and crack propagation. The calculation of the stiffness in the cross-section of the concrete beam in the non-linear phase is usually approximated by giving a reduction in stiffness. ACI 318-14 provides an alternative, reducing the stiffness of the plastic post-linear beam section through the moment of inertia (I) of the beam section for elastic analysis between 0.50Ig–0.25Ig. This study aims to predict the value of the reduction in the stiffness of the BRC beam section in the non-linear phase through the load-displacement relationship of experimental results validated by the Finite Element Method (FEM) and the Artificial Neural Networks (ANN) method. The experiment used 8 BRC beams and one steel-reinforced concrete (SRC) beam of singly reinforced with a size of 75 mm × 150 mm × 1100 mm. The beams were tested using a four-point loading method. The analysis results showed that the value of the stiffness reduction in the beam cross-sectional in the non-linear phase ranged from 0.5Ig–0.05Ig for BRC beams, and 0.75Ig–0.40Ig for SRC beams. Full article
(This article belongs to the Special Issue Timber and Construction Structure)
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25 pages, 26364 KiB  
Article
Precast Bridges of Bamboo Reinforced Concrete in Disadvantaged Village Areas in Indonesia
by Muhtar
Appl. Sci. 2020, 10(20), 7158; https://doi.org/10.3390/app10207158 - 14 Oct 2020
Cited by 12 | Viewed by 5048
Abstract
Bamboo is an inexpensive, environmentally friendly, and renewable building material that thrives in Indonesia. Bamboo has a high tensile strength but also has weaknesses, namely, it is easily attacked by insects and has high water absorption. Utilization of bamboo as a precast concrete [...] Read more.
Bamboo is an inexpensive, environmentally friendly, and renewable building material that thrives in Indonesia. Bamboo has a high tensile strength but also has weaknesses, namely, it is easily attacked by insects and has high water absorption. Utilization of bamboo as a precast concrete bridge reinforcement must be treated first through soaking, drying, and giving a waterproof coating and sand. This research aimed to obtain a precast bamboo reinforced concrete bridge technology with good integrity, with measuring parameters of deformation and deflection according to AASHTO standards. The dimensions of the bridge were a span of 320 cm, a width of 224 cm, and a height of 115 cm. Two bridge frames were connected by four bridge beams. The bridge plate was made of a 10-cm-thick concrete plate. The bridge support of the reinforced concrete is assumed to be the hinge support and the rubber bearing is assumed to be the roller support. The bamboo reinforced concrete frame bridge test was carried out directly with a load of a minibus-type vehicle. The test results show that the precast bamboo reinforced concrete frame bridges have sufficiently good integrity; that is, they can distribute loads with deflection and deformation that do not exceed their permits. The maximum displacement occurs in the bridge frame of 0.25 mm, meeting the requirements based on the AASTHO and RSNI T-12-2004 standards, which is not more than Δmax = L/800 = 3.75 mm. The maximum deformation occurs in the bridge beam of 0.20 mm, and the bridge frame of 0.13 mm meets the requirements based on the AASTHO and RSNI T-12-2004 standards, which is not more than δmax = L/800 = 3.75 mm. Full article
(This article belongs to the Collection Advanced Technologies in Wood Science)
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12 pages, 6615 KiB  
Article
The Prediction of Stiffness of Bamboo-Reinforced Concrete Beams Using Experiment Data and Artificial Neural Networks (ANNs)
by 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
Crystals 2020, 10(9), 757; https://doi.org/10.3390/cryst10090757 - 27 Aug 2020
Cited by 12 | Viewed by 3978
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 [...] Read more.
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). Full article
(This article belongs to the Special Issue Numerical Study of Concrete)
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