Numerical and machine learning modeling of GFRP confined concrete-steel hollow elliptical columns.

This article investigates the behavior of hybrid FRP Concrete-Steel columns with an elliptical cross section. The investigation was carried out by gathering information through literature and conducting a parametric study, which resulted in 116 data points. Moreover, multiple machine learning predictive models were developed to accurately estimate the confined ultimate strain and the ultimate load of confined concrete at the rupture of FRP tube. Decision Tree (DT), Random Forest (RF), Adaptive Boosting (ADAB), Categorical Boosting (CATB), and eXtreme Gradient Boosting (XGB) machine learning techniques were utilized for the proposed models. Finally, these models were visually and quantitatively verified and evaluated. It was concluded that the CATB and XGB are standout models, offering high accuracy and strong generalization capabilities. The CATB model is slightly superior due to its consistently lower error rates during testing, indicating it is the best model for this dataset when considering both accuracy and robustness against overfitting.

Investigation the effect of nanocarbon tube prepared from tea waste on microstructure and properties of cement mortar.

Environmental contamination and the massive high cost of waste disposal have been a huge concern for scholars throughout the globe, prompting them to alternatives of recycling waste materials in various implementation fields. The rising expenditure on disposal and the shortage of naturally main resources such as aggregate have increased interest in reusing recycled waste materials to manufacture concrete and mortar. The annual consumption of a country's population of hundreds of tons of black tea results in considerable numbers of discarded teabags. These huge quantities are disposed in landfills without being recycled or otherwise used. Moreover, such landfills are considered one of the country's biggest global issues. Therefore, the aim of this experimental work is to investigate the influence of nanocarbon tube produced from tea waste as cement replacement materials in mortar mixtures. Cement mortar mixes contain four replacement levels (1%, 2%, 3%, and 4%) of cement with nanocarbon tube produced from tea waste. The compressive strength, ultrasonic pulse velocity, and water absorption were tested to demonstrate the effect of the nanocarbon tube made from recycled tea waste on the mechanical properties of the mortar mix. The fresh properties such as flow rate were evaluated in accordance to specific standards. Scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDX) analyses were performed to demonstrate the microstructure of the mixtures. The results show that the fresh properties (flowability) of mortar containing nanocarbon tubes from tea waste were improved with the increase of the replacement ratio. In addition, the compressive strength was improved by substitution of up to 2%. For the other levels of substitution, it decreased with an increasing replacement percentage. In contrast, the density had increased with the increase of substitution levels of the tea waste. Based on the results of the experiments, it seems that the suggested biomixture could increase the compressive strength of the material by up to 2% of the replacement at 28 days of curing.