The Prediction of Stiffness Reduction Non-Linear Phase in Bamboo Reinforced Concrete Beam Using the Finite Element Method (FEM) and Artificial Neural Networks (ANNs)

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 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.

Performance Prediction of Hybrid Bamboo-Reinforced Concrete Beams Using Gene Expression Programming for Sustainable Construction

“…The behavior of steel was simulated using an elastic-plastic modeling approach [52,53]. The properties of concrete, steel, and bamboo utilized in this study were obtained from previous research studies [8,23]. The material behavior of steel reinforcement is characterized by both elastic and plastic behaviors, with the elastic behavior described by Young's modulus and the plastic behavior defined by the post-yielding Young's modulus.…”

“…Bamboo, a forest product with significant social, economic, and ecological importance, has emerged as a promising natural and sustainable resource capable of substituting for traditional construction materials [8]. Its growing popularity signifies its potential as an alternative to replace steel reinforcement in reinforced concrete structures [9].…”

PKM Kelompok Kreatif Tukang Bangunan Desa Sukogidri Dengan Keterampilan Membuat Tulangan Beton Dari Bambu

“…Bambu kering, dibersihkan pada sisi dalam dan dipangkas dengan mesin gerinda (Muhtar, 2019) menjadi bentuk tulangan beton berukuran 15 x 15 mm². Lapisan kedap air No-drop atau Sikadur ® -752 ( (Ghavami, 2005); (Sabnani et al, 2012); (Puri et al, 2017); (Muhtar et al, 2018); (Muhtar, 2020d); (Muhtar, 2020a); (Muhtar, 2020e); (Muhtar et al, 2016); ; (Muhtar, 2020b); (Bhonde et al, 2014); (Muhtar, 2020c); ; Gunasti, 2017) diberikan pada batang bambu untuk menghindari aksi saling menyerap air dengan beton (Bhonde et al, 2014).…”

A Review on the Mechanical Behaviour of Bamboo Reinforced Concrete Beams

“…Numerous studies recommended applying excessive reinforcement or a lower workload than the strength limit of the composite [38]. Despite the lower Table 1: Selected mechanical properties of bamboo and other reinforcing materials Reinforcing material Yield strength, MPa Tensile strength, MPa MOE, GPa Bamboo [7,19] 201 309 27 Steel [19][20][21] 442 620 207 GFRP [22][23][24] 680 3100-4150 57-86 CFPR [24,25] -3500-6000 230-600 AFRP [24,26] -1540-3400 70-140 BFRP [24,27] -3000-4840 [79][80][81][82][83][84][85][86][87][88][89][90][91][92][93] Notes: GFRP-Glass Fibre Reinforced Plastic; CFPR-Carbon Fibre Reinforced Plastic; AFRP-Aramid Fibre Reinforced Plastic; BFRP-Basalt Fibre Reinforced Plastic; MOE-Modulus of Elasticity.…”

“…Muhtar [80] developed a calculation model for predicting local slip in BRC beams through the curvature moments and bond stress with 6% of uncertainty, proving the proposed model's high reliability. Muhtar [81] and Mishra et al [77] adopted FEM and ANN methods to predict stiffness reduction and deflection values for BRC beams, respectively. The validation of the proposed models constituted 85%-93% and 99% for each study, respectively.…”