| Autor: |
k., Ramya, Malathy, R. |
| Předmět: |
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| Zdroj: |
Turkish Online Journal of Qualitative Inquiry; 2021, Vol. 12 Issue 3, p2184-2196, 13p |
| Abstrakt: |
Self-compacting concrete originated from Japan in the late 80's. because it does not require the vibrator to be consolidated. it was mostly used from 2000.Since there is no specific code for the mix design. The application of ANN will help to predict exactly the mix design of SCC. The application of artificial neural networks in self-compacting concrete began from the year of 2001.From the beginning the study shows that the ANN is a reliable method to predict the optimum admixture in a fast manner. When compared to do experimentally which is costlier and time consuming. ANN is programmed with the two modulus that is the output of the first ANN program will be the input of the second program are mostly used. Self-compacting concrete has been produced using the different types of mineral and chemical admixtures in order to reduce the material wastage and time. Glass powder is an excellent admixture. Using glass powder will increase the strength of SCC by 15 % and it also reduces the absorption of carbon dioxide. There should be application of ANN in SCC made with admixture of glass powder will help to develop an eco-friendly concrete. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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