Experimental and finite element studies on the structural behavior of BFRC continuous beams reinforced with BFRP bars

Abushanab, Abdelrahman; Alnahhal, Wael; Farraj, Murad

doi:10.1016/j.compstruct.2021.114982

Cited by 13 publications

(4 citation statements)

References 62 publications

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“…Subsequently, the weighting process of the observations is readjusted by assigning higher weight to the incorrectly predicted observations in the initial iteration. The weight distribution for training step t is adjusted according to Equation (11), where βt ∈ [0, 1] is the parameter related to the distribution update (Equation ( 12)), and L k is the average loss function (Equation ( 13)). A linear loss function was also used in this study to assess the performance of the base learner, as shown in Equation ( 14):…”

Section: Adaptive Boostingmentioning

confidence: 99%

“…Several research studies have explored the potential risk and countermeasures of steel corrosion on the flexural behavior of RC beams and slabs [7][8][9][10][11]. Three types of corroded specimens were considered in the previous studies; namely, specimens exposed to natural corrosive environments, specimens extracted from existing structures, and specimens corroded using the impressed current/voltage techniques with a target corrosion level (C L ).…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning-Based Flexural Capacity Prediction of Corroded RC Beams with an Efficient and User-Friendly Tool

2023

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Steel corrosion poses a serious threat to the structural performance of reinforced concrete (RC) structures. Thus, this study evaluates the flexural capacity of RC beams through machine learning (ML)-based techniques with six parameters used as input features: beam width, beam effective depth, concrete compressive strength, reinforcement ratio, reinforcement yield strength, and corrosion level. Four single and ensemble ML models are evaluated; namely, decision tree, support vector machine, adaptive boosting, and gradient boosting. Hyperparameters of each model were optimized using grid search and K-fold cross-validation with root mean squared error used as the performance index. The predictive performance of each model was assessed using four statistical performance metrics. The analysis results demonstrated that the decision tree model exhibited overfitting and limited generalization ability. The adaptive boosting model also had a slight overfitting issue. In addition, the support vector machine reported comparable accuracy to that of adaptive boosting. Conversely, the proposed gradient boosting ensemble model achieved the best performance with strong generalization ability, as indicated by its lowest mean absolute error of 2.78 kN.m, mean absolute percent error of 13.40%, and root mean squared error of 3.56 kN.m, and the highest coefficient of determination of 97.30% on the test dataset. The optimized gradient boosting model has been deployed into a graphical user interface, allowing for practical implementation of the model and enabling fast, efficient, and intelligent prediction of the flexural capacity of corroded RC beams.

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Section: Adaptive Boostingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Flexural Capacity Prediction of Corroded RC Beams with an Efficient and User-Friendly Tool

2023

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“…However, research is currently focused on the properties and application effects of flexural members and aims to enhance the ductility of concrete by introducing a specific quantity of basalt fiber, thereby reducing the hazards associated with the brittle failure of this composite structure [33,34]. And compared the bond strength degradation characteristics of BFRP bars, ordinary steel bars embedded in concrete in a single-corrosive environment coupled with high-low temperatures [35][36][37][38]. There have been few studies of circular flexure members in foundation pit and slope engineering, particularly on the relatively accurate formula to calculate the load-carrying capacity of the BFRP-reinforced concrete and the practical application of BFRP as reinforcement for support structures.…”

Section: Introduction Of Modified Bfrp Barsmentioning

confidence: 99%

Experimental Study on Flexural Behavior of RC Piles with Basalt Fiber-Reinforced Polymer Bars and Load Carrying Capacity Calculation

Chen,

Pan,

Wei

et al. 2024

Buildings

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The practical application of BFRPB (Basalt Fiber-Reinforced Polymer Bars) as a support structure in foundation pit and slope engineering is relatively under-researched. The indoor tensile test presented in this paper is carried out on the bond between BFRPB and different labelled concrete. The mechanical characteristics of BFRPB, the failure characteristics, and the load-carrying capacity were analyzed. The results of this study demonstrate that the normal section stress of concrete cylindrical components with BFRP has a good linear relationship and supports the rationality of the flat section assumption. In circular reinforced concrete BFRP structures, the failure of the pile load occurs in four phases, and the cracking load is in the range of 51% to 67% of the normal yield load. The main bars increase in strain with load but become attenuated in the compression zone. The deformation of the main bars increases with the load but becomes muted in the compression zone. Based on the method of calculating the load-carrying capacity of GFRP-reinforced RC piles and the normal limit load-carrying moment obtained from in-door tests, the bending moment correction coefficient in the calculation formula for the load-carrying capacity of BFRP-reinforced RC piles was then obtained.

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“…In this regard, studies have been carried out to improve the filament-cement matrix in the form of basalt textile cement matrix interaction that promotes strength development (Jia et al, 2021). In addition, basalt fibre in the form of BFRP sheets and rebars is utilised to strengthen structures externally and reinforce internally (High et al, 2015;Al-Hamrani et al, 2021;Abushanab et al, 2022). Another interesting use of basalt fibre is in the recycled concrete applications (Dong et al, 2017;Katkhuda and Shatarat, 2017).…”

Section: Introductionmentioning

confidence: 99%

Residual mechanical properties of basalt fibre reinforced cement mortars at elevated temperatures

Revanna

Moy

2022

JSFE

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PurposeA study on the mechanical characteristics of cementitious mortar reinforced with basalt fibres at ambient and elevated temperatures was carried out. To investigate their effect, chopped basalt fibres with varying percentages were added to the cement mortar.Design/methodology/approachAll the specimens were heated using a muffle furnace. Flexural strength and Compressive strength tests were performed, while monitoring the moisture loss to evaluate the performance of basalt fibre reinforced cementitious mortars at elevated temperatures.FindingsFrom the study, it is clear that basalt fibres can be used to reinforce mortar as the fibres remain unaffected up to 500 °C. Minimal increases in flexural strengths and compressive strengths were measured with the addition of basalt fibres at both ambient and elevated temperatures. SEM pictures revealed fibre matrix interaction/degradation at different temperatures.Originality/valueThe current study shows the potential of basalt fibre addition in mortar as a reinforcement mechanism at elevated temperatures and provides experimental quantifiable mechanical performances of different fibre percentage addition.

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Experimental and finite element studies on the structural behavior of BFRC continuous beams reinforced with BFRP bars

Cited by 13 publications

References 62 publications

Machine Learning-Based Flexural Capacity Prediction of Corroded RC Beams with an Efficient and User-Friendly Tool

Machine Learning-Based Flexural Capacity Prediction of Corroded RC Beams with an Efficient and User-Friendly Tool

Experimental Study on Flexural Behavior of RC Piles with Basalt Fiber-Reinforced Polymer Bars and Load Carrying Capacity Calculation

Residual mechanical properties of basalt fibre reinforced cement mortars at elevated temperatures

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