Reinforcement mechanism of nano-SiO2 and polypropylene fibers on concrete abrasion resistance subject to dynamic sandy water
Abrasion resistance of concrete is essential for the safety assessment of hydraulic structures subject to sandy water scouring. In this study, ten types of concrete specimens were designed to investigate the effect of nano-SiO2 (NS) and polypropylene fibers (PF) on the abrasion resistance and mechan...
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| Published in | Journal of materials research and technology Vol. 27; pp. 1630 - 1650 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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Elsevier B.V
01.11.2023
Elsevier |
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| Abstract | Abrasion resistance of concrete is essential for the safety assessment of hydraulic structures subject to sandy water scouring. In this study, ten types of concrete specimens were designed to investigate the effect of nano-SiO2 (NS) and polypropylene fibers (PF) on the abrasion resistance and mechanical properties of concrete. In view of the discreteness of the results, grey theory, Support vector machine (SVR) and artificial neural network (ANN) model were selected to explore the relationship between abrasion resistance and factors involving NS, PF, compressive strength, splitting tensile strength and curing age. The results revealed that the appropriate addition of NS and PF promote the hydration process and remarkably enhanced the performance of concrete. And the grey relation analysis indicated that the optimal content of NS and PF were 3 % and 0.9 kg/m3, respectively. Compared with GM (1, N) and SVR, ANN model benefited from more comprehensive consideration of the effects of various factors to predict abrasion resistance more reliably. The results of grey relation analysis and ANN model showed that there was a close correlation between the mechanical properties, admixtures and the abrasion resistance. |
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| AbstractList | Abrasion resistance of concrete is essential for the safety assessment of hydraulic structures subject to sandy water scouring. In this study, ten types of concrete specimens were designed to investigate the effect of nano-SiO2 (NS) and polypropylene fibers (PF) on the abrasion resistance and mechanical properties of concrete. In view of the discreteness of the results, grey theory, Support vector machine (SVR) and artificial neural network (ANN) model were selected to explore the relationship between abrasion resistance and factors involving NS, PF, compressive strength, splitting tensile strength and curing age. The results revealed that the appropriate addition of NS and PF promote the hydration process and remarkably enhanced the performance of concrete. And the grey relation analysis indicated that the optimal content of NS and PF were 3 % and 0.9 kg/m3, respectively. Compared with GM (1, N) and SVR, ANN model benefited from more comprehensive consideration of the effects of various factors to predict abrasion resistance more reliably. The results of grey relation analysis and ANN model showed that there was a close correlation between the mechanical properties, admixtures and the abrasion resistance. |
| Author | Xia, Xing Zhang, Peng Wang, Kun Guo, Jinjun |
| Author_xml | – sequence: 1 givenname: Jinjun orcidid: 0000-0002-9408-8482 surname: Guo fullname: Guo, Jinjun organization: School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China – sequence: 2 givenname: Xing surname: Xia fullname: Xia, Xing email: zzuxx2021@gs.zzu.edu.cn organization: School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China – sequence: 3 givenname: Peng surname: Zhang fullname: Zhang, Peng organization: School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China – sequence: 4 givenname: Kun orcidid: 0000-0002-5792-1068 surname: Wang fullname: Wang, Kun organization: School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou 450001, China |
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| Keywords | Polypropylene fiber reinforced nano-SiO2 concrete Machine learning algorithms Abrasion resistance Grey theory |
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| Title | Reinforcement mechanism of nano-SiO2 and polypropylene fibers on concrete abrasion resistance subject to dynamic sandy water |
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