Study on Flexural of Reinforced Geopolymer Concrete Beam

Amiri, Amir Mohammad; Olfati, Amin; Najjar, Shima; Beiranvand, Peyman; Fard, M.H. Naseri

doi:10.12913/22998624/62630

Cited by 14 publications

(7 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yang et al [10] examined the damage behavior of GFRP RC beams by performing the experimental and FEA and reported that the developed FEA model is accurate enough to predict the damage behavior of GFRP RC beams. Amiri et al [11] presented a FE model of reinforced geopolymer concrete flexural members using commercial software ABAQUS and found a deviation in experimental and numerical results for deflections, but the crack pattern showed good agreement. Najafgholipour et al [12] conducted the FEA of reinforced concrete exterior and interior beam-column joints by using the CDP model in ABAQUS and studied deformations, joint shear capacity, and cracks patterns with the conclusion that FEA results are in good agreement with the experimental results.…”

Section: Introductionmentioning

confidence: 99%

Numerical Investigation of Load‐Carrying Capacity of GFRP‐Reinforced Rectangular Concrete Members Using CDP Model in ABAQUS

Raza

Khan

Ahmad

2019

Advances in Civil Engineering

117

View full text Add to dashboard Cite

The present work demonstrates the nonlinear finite element analysis (NLFEA) of 13 concentrically and eccentrically loaded short rectangular concrete column specimens reinforced with GFRP and conventional steel bars. GFRP bars are lightweight having the high tensile strength and high corrosion resistance. An NLFEA model for the rectangular concrete specimens was developed using the commercial software ABAQUS Standard and calibrated for different materials and geometric parameters based on the previous experimental test results of the studied specimen. The behavior of reinforced concrete was modelled using the concrete damaged plasticity (CDP) model, the behavior of steel bars was simulated as a bilinear elastoplastic material, and the GFRP bars were considered as a linear elastic material. After the calibration of CDP parameters, the control sample was used for the further numerical parametric analysis to investigate the effect of critical parameters, i.e., the area of concrete (Ac), the compressive strength of concrete (fc′), and the ratio of longitudinal reinforcement (ρl) and transverse reinforcement (ρt) on the load-carrying capacity of columns. The results show that the selected NLFEA model can simulate the behavior of columns accurately and there was good agreement of numerical results obtained from ABAQUS Standard with the experimental results.

show abstract

Section: Introductionmentioning

confidence: 99%

Numerical Investigation of Load‐Carrying Capacity of GFRP‐Reinforced Rectangular Concrete Members Using CDP Model in ABAQUS

Raza

Khan

Ahmad

2019

Advances in Civil Engineering

117

View full text Add to dashboard Cite

show abstract

“…In order to ensure the correctness and accuracy of the finite element model, the calculation results of the finite element model were compared with the experimental results. Since the failure mode of the beam is concrete crushing, the crack distribution generated by this failure mode can be effectively recorded by DAMAGET of the finite element model [ 47 ]. The specific finite element model crack comparison is shown in Figure 13 .…”

Section: Verification Example: Evaluation Of the Bearing Capacity Of ...mentioning

confidence: 99%

Research on an Optimized Evaluation Method of the Bearing Capacity of Reinforced Concrete Beam Based on the Bayesian Theory

Wang

Xiao

et al. 2023

Materials

View full text Add to dashboard Cite

An optimized evaluation method of the bearing capacity of reinforced concrete beam based on the Bayesian theory was proposed in this paper. This evaluation method optimized the traditional Markov Chain-Monte Carlo (MCMC) sampling method, and proposed an improved Metropolis–Hastings (MH) sampling method and a transitive MCMC (TMCMC) sampling method based on the MCMC theory. These two derived sampling methods solved the problem that the traditional MCMC algorithm makes it difficult to achieve convergence when the number of modified parameters is large. Therefore, on the basis of obtaining the measured sample information and the prior information of uncertain parameters, this paper first used multiple “model components” to form a model sample, then carried out a sensitivity analysis based on the relevant response indicators and selected the key parameters that had a great impact on the bearing capacity, carried out static load tests, and extracted and analyzed the experimental data. Then, based on a large amount of analysis data, the improved MH sampling method and TMCMC sampling method were used to establish a posterior probability distribution database. Finally, multiple posterior probability distributions were used to identify and predict the bearing capacity. The results showed that the method was feasible and effective for the evaluation of the bearing capacity of reinforced concrete beam.

show abstract

“…Figure 10 shows how the damage to concrete plasticity in the simulation creates failures consistent with actual observations. There were noticeable differences between the numerical and experimental data for the mechanical properties in previous research, including flexural and cracking tensile strength [94][95][96]. The-max load in the middle and max displacement of SFRC-2 beams obtained from the numerical model, and that load was used to calculate the flexural strength according to BS EN 12390-6 (2009).…”

Section: Numerical Model 431 Numerical Analysis Of Flexural Strengthmentioning

confidence: 99%

Modelling Fibre-Reinforced Concrete for Predicting Optimal Mechanical Properties

Khalel

Khan

2023

Materials

View full text Add to dashboard Cite

Fibre-reinforced cementitious composites are highly effective for construction due to their enhanced mechanical properties. The selection of fibre material for this reinforcement is always challenging as it is mainly dominated by the properties required at the construction site. Materials like steel and plastic fibres have been rigorously used for their good mechanical properties. Academic researchers have comprehensively discussed the impact and challenges of fibre reinforcement to obtain optimal properties of resultant concrete. However, most of this research concludes its analysis without considering the collective influence of key fibre parameters such as its shape, type, length, and percentage. There is still a need for a model that can consider these key parameters as input, provide the properties of reinforced concrete as output, and facilitate the user to analyse the optimal fibre addition per the construction requirement. Thus, the current work proposes a Khan Khalel model that can predict the desirable compressive and flexural strengths for any given values of key fibre parameters. The accuracy of the numerical model in this study, the flexural strength of SFRC, had the lowest and most significant errors, and the MSE was between 0.121% and 0.926%. Statistical tools are used to develop and validate the model with numerical results. The proposed model is easy to use but predicts compressive and flexural strengths with errors under 6% and 15%, respectively. This error primarily represents the assumption made for the input of fibre material during model development. It is based on the material’s elastic modulus and hence neglects the plastic behaviour of the fibre. A possible modification in the model for considering the plastic behaviour of the fibre will be considered as future work.

show abstract

Study on Flexural of Reinforced Geopolymer Concrete Beam

Cited by 14 publications

References 4 publications

Numerical Investigation of Load‐Carrying Capacity of GFRP‐Reinforced Rectangular Concrete Members Using CDP Model in ABAQUS

Numerical Investigation of Load‐Carrying Capacity of GFRP‐Reinforced Rectangular Concrete Members Using CDP Model in ABAQUS

Research on an Optimized Evaluation Method of the Bearing Capacity of Reinforced Concrete Beam Based on the Bayesian Theory

Modelling Fibre-Reinforced Concrete for Predicting Optimal Mechanical Properties

Contact Info

Product

Resources

About