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RISS 인기검색어
- 검색키워드
- 저자 : Alih, Sophia C. (검색결과 3 건)
- 무료
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- 유료
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Numerical investigation on the flow mixing feature inside a continuously carbonating process tank
Ali, H.,Kim, K.W.,Kwak, M.K.,Kim, J.S.,Choi, J.Y.,Park, C.W. Pergamon Press ; Elsevier Science Ltd 2016 Computers & electrical engineering Vol.51 No.-
<P>A carbonating tank is continuously operated and filled with water supplied by an immersed flow injecting nozzle. At the same time, CO2 gas is introduced from the gas tank. CO2 gas can be dissolved in water and can form carbonated water with minimum production of gas bubbles depending on various process conditions. Therefore, the flow mixing phenomenon of CO2 and water can be affected by the placement of the injecting nozzle and the flow rate in consideration of the interfacial surface. In this study, the gas-liquid flow mixing with the mass transport inside the carbonation process tank is numerically predicted. The Euler-Euler methodology is used to observe the effects of the design of the injecting nozzle, the gas bubble size, as well as the velocities of liquid and gas on the gas volume fraction, liquid velocity, gas concentration, interfacial area, and mass transfer coefficient. (C) 2015 Elsevier Ltd. All rights reserved.</P>
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Seismic behavior of RC columns internally confined by CFRP strips
Halim, Nur Hajarul Falahi Abdul,Alih, Sophia C.,Vafaei, Mohammadreza Techno-Press 2021 Advances in concrete construction Vol.12 No.3
During past decades fiber-reinforced polymer (FRP) sheets have been externally bonded to structural elements to increase their axial, shear, or bending capacity. FRP bars also have been widely used to replace the steel reinforcements in columns subjected to a harsh environment. In this study, carbon fiber-reinforced polymer (CFRP) strips were used as the transverse reinforcement for concrete columns. Although FRP bars have already been used as the transverse reinforcement in concrete columns, the efficiency and feasibility of CFRP strips have not been investigated. CFRP strips are flexible; therefore, they can be easily shaped as spirals to confine the concrete core of columns. The efficiency of CFRP strips for the confinement of the concrete core was examined through a series of quasi-static cyclic tests on four full-scale columns that had similar size and longitudinal reinforcements. One of the columns was selected as the reference, and steel spirals transversally reinforced it. CFRP strips transversally reinforced the other three columns with different widths and spacing. The obtained results showed that the number of cracks in the CFRP-confined columns was less than the reference column. The length of cracks in the CFRP-confined columns was also relatively shorter. Besides, the CFRP-confined columns had a larger ultimate load, effective yield strength, and displacement ductility ratio compared with the reference column.
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Ismail B. Mustapha,Muyideen Abdulkareem,Taha M. Jassam,Ali H. AlAteah,Khaled A. Alawi Al-Sodani,Mohammed M. H. Al-Tholaia,Hatem Nabus,Sophia C. Alih,Zainab Abdulkareem,Abideen Ganiyu 한국콘크리트학회 2024 International Journal of Concrete Structures and M Vol.18 No.3
Concrete compressive strength is usually determined 28 days after casting via crushing of samples. However, the design strength may not be achieved after this time-consuming and tedious process. While the use of machine learning (ML) and other computational intelligence methods have become increasingly common in recent years, findings from pertinent literatures show that the gradient-boosting ensemble models mostly outperform comparative methods while also allowing interpretable model. Contrary to comparison with other model types that has dominated existing studies, this study centres on a comprehensive comparative analysis of the performance of four widely used gradient-boosting ensemble implementations [namely, gradient-boosting regressor, light gradient-boosting model (LightGBM), extreme gradient boosting (XGBoost), and CatBoost] for estimation of the compressive strength of quaternary blend concrete. Given components of cement, Blast Furnace Slag (GGBS), Fly Ash, water, superplasticizer, coarse aggregate, and fine aggregate in addition to the age of each concrete mixture as input features, the performance of each model based on R2, RMSE, MAPE and MAE across varying training–test ratios generally show a decreasing trend in model performance as test partition increases. Overall, the test results showed that CatBoost outperformed the other models with R2, RMSE, MAE and MAPE values of 0.9838, 2.0709, 1.5966 and 0.0629, respectively, with further statistical analysis showing the significance of these results. Although the age of each concrete mixture was found to be the most important input feature for all four boosting models, sensitivity analysis of each model shows that the compressive strength of the mixtures does increase significantly after 100 days. Finally, a comparison of the performance with results from different ML-based methods in pertinent literature further shows the superiority of CatBoost over reported the methods.
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