Comprehensive utilization of solid waste resources: Development of wet shotcrete for mines

Abstract

The development of solid waste resources as constituent materials for wet shotcrete has significant economic and environmental advantages. In this study, the concept of using tailings as aggregate and fly ash and slag powder as auxiliary cementitious material is proposed and experiments are carried out by response surface methodology (RSM). Multivariate nonlinear response models are constructed to investigate the effect of factors on the uniaxial compressive strength (UCS) of tailings wet shotcrete (TWSC). The UCS of TWSC is predicted and optimized by constructing Gaussian process regression (GPR) and genetic algorithm (GA). The UCS of TWSC is gradually enhanced with the increase of slag powder dosage and fineness modulus, and it is enhanced first and then decreased with the increase of fly ash dosage. The microstructure of TWSC has the highest gray value and the highest UCS when the fly ash dosage is about 120 kg·m⁻³. The GPR–GA model constructed in this study achieves high accuracy prediction and optimization of the UCS of TWSC under multi-factor conditions.

Keywords

tailings / solid waste / wet shotcrete / machine learning / mix proportion

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