Computational AI prediction models for residual tensile strength of GFRP bars aged in the alkaline concrete environment

Iqbal, Mudassir; Zhang, Daxu; Jalal, Fazal E.; Javed, Muhammad Faisal

doi:10.1016/j.oceaneng.2021.109134

Cited by 94 publications

(47 citation statements)

References 87 publications

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“…The paradigm shift in regression models using machine learning significantly contributes to solving engineering problems [ 67 , 68 , 69 , 70 , 71 ]. The current study investigated the effect of changing dosages of NGPs on the mechanical characteristics of concrete.…”

Section: Discussionmentioning

confidence: 99%

Performance Evaluation of Cementitious Composites Incorporating Nano Graphite Platelets as Additive Carbon Material

et al. 2021

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Nano graphite platelets (NGPs) belong to the carbon family and have a huge impact on the construction industry. NGPs are used as multi-functional fillers and have the potential to develop reinforcing within cementitious composites. In this paper, NGPs were incorporated in cementitious composites to investigate the effects of NGPs on the fresh, mechanical, durability, and microstructural properties of concrete. Five mixes were prepared with intrusion of NGPs (0%, 0.5%, 1.5%, 3%, and 5% by weight of cement). The properties studied involved workability, air content, hardened density, compressive strength, tensile strength, flexural strength, sorptivity, ultrasonic pulse velocity (UPV), water absorption, and external sulfate attack. The workability and percent air content decrease by 22.5% and 33.8%, respectively, for concrete with 5% NGPs compared to the control mix. The specimens containing 5% of NGPs revealed the hardened density, compressive, tensile, and flexural strength to increase by 11.4%, 38.5%, 31.6%, and 44.34%, respectively, compared to the control mix. The results revealed that the incorporation of 5%NGPs in cementitious composites reduces the sorptivity and water absorption by 32.2% and 73.9%, respectively, whereas, it increases the UPV value by 7.5% compared to the control mix. Furthermore, the incorporation of NGPs provided better resistance against external sulfate attacks. SEM–EDX spectroscopy was carried out to investigate its microstructural analysis.

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Section: Discussionmentioning

confidence: 99%

Performance Evaluation of Cementitious Composites Incorporating Nano Graphite Platelets as Additive Carbon Material

et al. 2021

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“…Artificial intelligence models can simulate highly non-linear associations between numerous input and output parameters and can therefore provide more accurate predictions than those obtained using simple and multiple regression analysis [13][14][15]. During the last decade numerous artificial intelligence models techniques, including artificial neural network (ANN) [16], adaptive neuro-fuzzy inference system (ANFIS) [17], gene and multi expression programming [18][19][20], ensemble framework techniques (for instance, bagging, rotation forest, and random subspace (RSS)) [21], decision tree (DT) [22], and support vector machine (SVM) [23], have been used in engineering and numerous other disciplines [13,24]. Hybrid ensemble strategies including bagging, RSS, and boosting with ensemble pruning are particularly suitable for extracting deep features from multivariate data [25].…”

Section: Introductionmentioning

confidence: 99%

On Random Subspace Optimization-Based Hybrid Computing Models Predicting the California Bearing Ratio of Soils

et al. 2021

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The California Bearing Ratio (CBR) is an important index for evaluating the bearing capacity of pavement subgrade materials. In this research, random subspace optimization-based hybrid computing models were trained and developed for the prediction of the CBR of soil. Three models were developed, namely reduced error pruning trees (REPTs), random subsurface-based REPT (RSS-REPT), and RSS-based extra tree (RSS-ET). An experimental database was compiled from a total of 214 soil samples, which were classified according to AASHTO M 145, and included 26 samples of A-2-6 (clayey gravel and sand soil), 3 samples of A-4 (silty soil), 89 samples of A-6 (clayey soil), and 96 samples of A-7-6 (clayey soil). All CBR tests were performed in soaked conditions. The input parameters of the models included the particle size distribution, gravel content (G), coarse sand content (CS), fine sand content (FS), silt clay content (SC), organic content (O), liquid limit (LL), plastic limit (PL), plasticity index (PI), optimum moisture content (OMC), and maximum dry density (MDD). The accuracy of the developed models was assessed using numerous performance indexes, such as the coefficient of determination, relative error, MAE, and RMSE. The results show that the highest prediction accuracy was obtained using the RSS-based extra tree optimization technique.

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“…Additionally, the use of plastic aggregate is recommended to be used in marine conditions owing to its non-absorption capacity, which resists the ingress of hazardous chemicals such as chloride and sulphate, etc. The conventional steel and fiber-reinforced polymer (FRP) rebars in PCA-incorporated concrete are expected to perform better under an alkaline environment; however, more insights regarding the durability of FRPs in PCA-incorporated concrete shall be investigated first from the relevant literature [ 59 , 60 ]. In addition, machine learning techniques are widely used for investigating material properties [ 61 , 62 , 63 , 64 , 65 , 66 , 67 ] and general engineering problems [ 68 , 69 ].…”

Section: Discussionmentioning

confidence: 99%

Performance Evaluation of Plastic Concrete Modified with E-Waste Plastic as a Partial Replacement of Coarse Aggregate

et al. 2021

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Plastic electronic waste (E-waste) is constantly growing around the world owing to the rapid increase in industrialization, urbanization, and population. The current annual production rate of E-waste is 3–4% in the world and is expected to increase to 55 million tons per year by 2025. To reduce the detrimental impact on the environment and save natural resources, one of the best solutions is to incorporate waste plastic in the construction industry to produce green concrete. This study examines the use of manufactured plastic coarse aggregate (PCA) obtained from E-waste as a partial replacement of natural coarse aggregate (NCA) in concrete. Six types of concrete mix with 10%, 20%, 30%, 40%, and 50% substitution of NCA (by volume) with PCA are prepared and tested. This study investigates the effect of manufactured PCA on the fresh and hardened characteristics of concrete. The properties of recycled plastic aggregate concrete (RPAC) studied include workability, fresh density, dry density, compressive strength (CS), splitting tensile strength (STS), flexural strength (FS), sorptivity coefficient, abrasion resistance, ultrasonic pulse velocity (UPV), and alternate wetting and drying (W–D). The results indicate that the CS, STS, and FS of RPAC declined in the range of 9.9–52.7%, 7.8–47.5%, and 11–39.4%, respectively, for substitution ratios of 10–50%. However, the results also indicate that the incorporation of PCA (10–50%) improved the workability and durability characteristics of concrete. A significant decrement in the sorptivity coefficient, abrasion loss, and UPV value was observed with an increasing amount of PCA. Furthermore, RPAC containing different percentages of PCA revealed better results against alternate W–D cycles with respect to ordinary concrete.

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Computational AI prediction models for residual tensile strength of GFRP bars aged in the alkaline concrete environment

Cited by 94 publications

References 87 publications

Performance Evaluation of Cementitious Composites Incorporating Nano Graphite Platelets as Additive Carbon Material

Performance Evaluation of Cementitious Composites Incorporating Nano Graphite Platelets as Additive Carbon Material

On Random Subspace Optimization-Based Hybrid Computing Models Predicting the California Bearing Ratio of Soils

Performance Evaluation of Plastic Concrete Modified with E-Waste Plastic as a Partial Replacement of Coarse Aggregate

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