Tehnički vjesnik, Vol. 31 No. 1, 2024.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20230314000438
Predicting Concrete Slump using Fly Ash and Stone Powder in Central Vietnam
Le Thang Vuong
; Faculty of Civil engineering, University of Science and Technology, University of Danang, Postal address 54 Nguyen Luong Bang Street, Lien Chieu District, Danang City, Vietnam
*
Cung Le
; Faculty of Transportation Mechanical Engineering, University of Science and Technology, University of Danang, Postal address 54 Nguyen Luong Bang Street, Lien Chieu District, Danang City, Vietnam
Dinh Son Nguyen
; Faculty of Transportation Mechanical Engineering, University of Science and Technology, University of Danang, Postal address 54 Nguyen Luong Bang Street, Lien Chieu District, Danang City, Vietnam
* Dopisni autor.
Sažetak
Fly ash and stone powder, which are abundant wastes in Central Vietnam, are viable alternatives to cement and sand in concrete production. However, this replacement may worsen the compressive strength and slump of concrete. This study deals with the prediction of the slump and compressive strength of concrete using fly ash and stone powder in Central Vietnam as cement and sand substitute materials, respectively. First, the Ishikawa diagram was used to analyze the factors affecting the concrete workability and compressive strength, in combination with the method of design of experiment to determine the required number of testing specimens. A total of 72 concrete mixtures with slump of 3 - 12 cm and compressive strengths 10 MPa - 60 MPa were designed. Subsequently, regression and artificial neural network methods were used to predict the concrete slump and compressive strength. The results demonstrated the high accuracy of the artificial neural network model. In addition, the above models allowed us to determine the proportion of concrete ingredients that met the slump and compressive strength requirements.
Ključne riječi
artificial neural network; concrete; design of experiment; fly ash; multivariable linear regression; slump; stone powder
Hrčak ID:
312886
URI
Datum izdavanja:
31.12.2023.
Posjeta: 901 *