| Autor: |
Jinjun Guo, Xing Xia, Peng Zhang, Kun Wang |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Journal of Materials Research and Technology, Vol 27, Iss , Pp 1630-1650 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2238-7854 |
| DOI: |
10.1016/j.jmrt.2023.09.321 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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