Open Access
ARTICLE
Development of Wet Shotcrete with Solid Waste as Aggregate: Strength Optimization and Mix Proportion Design
Yafei Hu1,2, Keqing Li1,2, Bo Zhang1,2, Bin Han1,2,*
1
School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing, 100083, China
2
Key Laboratory of Ministry of Education of China for Efficient Mining and Safety of Metal Mines, University of Science and
Technology Beijing, Beijing, 100083, China
* Corresponding Author: Bin Han. Email:
Journal of Renewable Materials 2023, 11(9), 3463-3484. https://doi.org/10.32604/jrm.2023.027532
Received 03 November 2022; Accepted 09 December 2022; Issue published 20 July 2023
Abstract
The super-fine particle size of tailings is its drawback as a recycled resource, which is reflected in the low strength
of the new construction and industrial materials formed when it is mixed with cement and other cementitious
materials. Therefore, it is crucial to study the effect of tailings particle size and cementitious material on the
strength of tailings wet shotcrete (TWSC) and to investigate the optimal mix proportion. In this paper, a multivariate nonlinear response model was constructed by conducting central composite experiments to investigate the
effect of different factors on the strength of TWSC. The strength prediction and mix proportion optimization of
TWSC are carried out by machine learning techniques. The results show that the response model has R
2 >
0.94 and
P < 0.01, which indicates that the model has high reliability. Moreover, the strength of TWSC increases
with the increase of tailings fineness modulus and decrease of water-binder ratio, while it also increases and then
decreases with the increase of replacement rate of slag powder to cement (SRC rate). The extreme learning
machine (ELM) constructed in this paper predicts the strength of TWSC with an accuracy of more than 98%
and achieves rapid prediction under multi-factor conditions. It is worth mentioning that the ELM combined with
the genetic algorithm (ELM-GA) collaboratively solved to obtain the mix proportion for C15 and C20 strength
grades of TWSC and the maximum error is verified by experiments to be less than 2%.
Keywords
Cite This Article
APA Style
Hu, Y., Li, K., Zhang, B., Han, B. (2023). Development of wet shotcrete with solid waste as aggregate: strength optimization and mix proportion design. Journal of Renewable Materials, 11(9), 3463-3484. https://doi.org/10.32604/jrm.2023.027532
Vancouver Style
Hu Y, Li K, Zhang B, Han B. Development of wet shotcrete with solid waste as aggregate: strength optimization and mix proportion design. J Renew Mater. 2023;11(9):3463-3484 https://doi.org/10.32604/jrm.2023.027532
IEEE Style
Y. Hu, K. Li, B. Zhang, and B. Han "Development of Wet Shotcrete with Solid Waste as Aggregate: Strength Optimization and Mix Proportion Design," J. Renew. Mater., vol. 11, no. 9, pp. 3463-3484. 2023. https://doi.org/10.32604/jrm.2023.027532