This study investigates the time-dependent rheological behavior of cemented paste backfill (CPB) that contains alkali-activated slag (AAS) as a binder. Rheological measurements with the controlled shear strain method have been conducted on various AAS-CPB samples with different binder contents, silicate modulus (Ms: SiO2/Na2O molar ratio), fineness of slag and curing temperatures. The Bingham model afforded a good fit to all of the CPB mixtures. The results show that AAS-CPB samples with high binder content demonstrate a more rapid rate of gain in yield stress and plastic viscosity. AAS-CPB also shows better rheological behavior than CPB samples made up of ordinary Portland cement (OPC) at identical binder contents. It is found that increasing Ms yields lower yield stress and plastic viscosity and the rate of gain in these parameters. Increases in the fineness of slag has an adverse effect on rheological behavior of AAS-CPB. The rheological behavior of both OPC- and AAS-CPB samples is also strongly enhanced at higher temperatures. AAS-CPB samples are found to be more sensitive to the variation in curing temperatures than OPC-CPB samples with respect to the rate of gain in yield stress and plastic viscosity. As a result, the findings of this study will contribute to well understand the flow and transport features of fresh CPB mixtures under various conditions and their changes with time.
A reasonable arrangement of filling pipelines can solve the problems of low line magnification, a high flow rate, large pipe pressure, etc., in deep well filling slurry transportation. The transportation pressure loss value of filling slurry is the main parameter for the layout design of filling pipelines. At present, pressure loss data are mainly obtained through the loop pipe experiment, which has problems such as a large amount of labor, high cost, low efficiency, and a limited amount of experimental data. In this paper, combined with a new generation of artificial intelligence technology, the random forest machine learning algorithm is used to analyze and model the experimental data of a loop pipe to predict the pressure loss of slurry transportation. The degree of precision reaches 0.9747, which meets the design accuracy requirements, and it can replace the loop pipe experiment to assist with the filling design.
With the increase in environmental awareness worldwide, the filling mining method has attracted extensive attention because this method can realize safe and green mining in underground metal mines. Recycling waste tailings in stopes to control underground rock movement, and surface settlement can reduce waste environmental pollution while ensuring mining safety. Although many test data are required to support the formulation of the mine backfill scheme, the advanced management tool of backfill test data is insufficient. In this study, a new data management method that is suitable for backfill experiments is proposed. First, this study analyses the main system requirements, including experimental business process modeling, experimental process combing, and a multidimensional query of experimental data. Then, the backfill test business flow and data flow are summarized to establish the backfill test business model and experimental index system. Then, many system functions are designed, including backfill experiment management, experimental data query, backfill knowledge maintenance, and system management. Finally, a backfill test data management system is developed based on B/S architecture. Developing a data interface, having a built-in test formula and customizing a multidimensional data analysis enable the system to solve the problems in data collection, data accounting, and data analysis. After being put into use in the Backfilling Engineering Laboratory of a group in Shandong, this system improved the data-sharing rate and utilization rate and provided a convenient data management tool for the laboratory.
To explore the hydration characteristics and early strength evolution of classified fine tailings cemented backfill (CFTCB), a nuclear magnetic resonance (NMR) analysis and a volume resistivity test were performed on classified fine tailings filling slurry (CFTFS). The early hydration products of CFTCB were studied by scanning electron microscopy (SEM) and X-ray diffraction (XRD) phase analysis. Uniaxial compressive strength (UCS) test was carried out, and the microscopic characteristics and strength rules of the hydration reaction of CFTCB were analyzed. Based on the experiment, we found the law of water content change and porosity evolution. The early hydration reaction can be divided into the dissolution, setting, and hardening stages. The volume resistivity test results show that the volume resistance of filling slurry increases slowly at first then decreases, and finally increases rapidly. The variation trend of volume resistivity is related to the degree of hydration reaction. When combined with the hydration characteristics of backfill materials, the hydration reaction rate determines the growth rate of early strength of backfill, and the formation of hydration products is the reason for the early strength increase in backfill. The research conclusion has an important theoretical guiding value and engineering significance in mine filling production organization and filling ratio parameter optimization.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.