The Role of Rheological Additives on Fresh and Hardened Properties of Cemented Paste Backfill

Previously conducted studies have established that grouting backfill in mining-induced overburden bed separation and mined-out areas with broken rocks provides an efficient strategy to control strata movement and surface subsidence caused by underground mining. Grouting backfill materials (GBMs) based on coal gangue (CG) are highly desirable in coal mining for accessibility to abundant CG and urgent demand for CG disposal. However, CG is generally employed as coarse aggregate due to rather rigid and inert properties, limiting its application in GBMs. Herein, to reduce reliance on fine aggregates, such as fly ash and clay, cemented GBM formulations using ground CG powder as a dominant component were proposed. Urea and quicklime were utilized as additives to optimize slurry transportability and compressive strength. Besides typical grinding without additives, CG powder was also prepared via grinding with urea, intending to enhance the hydrogen bonding (HB) interaction between urea and minerals contained in CG. The effect of grinding time and urea on CG particle size and phase composition was investigated. Then, the dependence of slurry transportability and compressive strength on grinding time, solid concentration, urea, and quicklime dosage were revealed. It has been experimentally proved that grinding for 30~90 min significantly decreased CG particle size and even induced crystal deformation of dolomite and kaolinite. For GBMs, urea improved slurry flowability, possibly caused by decreased water absorption on the CG surface and the release of water encapsulated in hydrated cement particles. Moreover, quicklime strengthened GBM bodies, which could be explained by an accelerated pozzolanic reaction between CG powder and additional CH supplied by quicklime hydration. G60U3-based GBM-B2 with 5% quicklime provided a stable and smooth slurry with a bleeding rate of 1.25%, a slump flow of 205 mm, and a hardened body with a seven-day UCS of 1.51 MPa.

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Experimental Study on Performance Optimization of Grouting Backfill Material Based on Mechanically Ground Coal Gangue Utilizing Urea and Quicklime

Wang

Zhang

et al. 2023

“…It was found that the addition of straw fiber increased the tensile properties of the CPB, and it was also found that this strengthening effect was weakened when the curing time was increased. The above-mentioned research demonstrated that adding substances to CPB increases its toughness [28][29][30][31][32]. However, to date, there have been few studies on the influence of rubber on the mechanical properties of backfill.…”

Section: Introductionmentioning

confidence: 99%

The Failure Mechanical Properties of Cemented Paste Backfill with Recycled Rubber

Yang

Wang

et al. 2023

Understanding the mechanical properties and failure process of cemented paste backfill with recycled rubber (RCPB) is the foundation of backfill design in underground mining. In this study, physical and mechanical tests were conducted on RCPB to obtain its mechanical property parameters, such as its uniaxial compressive strength (UCS), toughness, and peak strain. The influence of the rubber dosage on the mechanical properties of RCPB was also analyzed. In addition, the deformation behavior, fracture development, and failure process of RCPB with different rubber contents were observed using the digital image correlation (DIC) technique. The experimental results suggested that, although the UCS of RCPB is reduced as more rubber is added, its toughness and ability to absorb energy is increased. Moreover, the impact resistance of RCPB is improved by this increased toughness. With the increase in the rubber content, the deformation corresponding to the plastic yield stage of RCPB increased, which resulted in better ductility and improved impact resistance. The failure of the RCPB specimens mainly showed an “X” shape. The results of this study help us to better understand the mechanical behavior of RCPB after backfilling underground.

“…It is indicated that the yield stress of CPB decreased continuously with the increase of initial sulfate content, while the viscosity increased. Jin et al [ 31 ] analyzed the influence of polyacrylamide (PAM) and polycarboxylate superplasticizer (PCE) on CPB with varying water/solid ratios W/S and W/C. The results showed that the high W/C (1.0 and 1.2), low W/S (0.3), 0.05% PAM, and 1.0% PCE can benefit the production cost as well as the physical properties of the CPB.…”

Section: Introductionmentioning

confidence: 99%

A Novel Design Concept of Cemented Paste Backfill (CPB) Materials: Biobjective Optimization Approach by Applying an Evolved Random Forest Model

He¹,

Cheng

et al. 2022

For cemented paste backfill (CPB), uniaxial compressive strength (UCS) is the key to ensuring the safety of stope construction, and its cost is an important part of the mining cost. However, there are a lack of design methods based on UCS and cost optimization. To address such issues, this study proposes a biobjective optimization approach by applying a novel evolved random forest (RF) model. First, the evolved RF model, based on the beetle search algorithm (BAS), was constructed to predict the UCS of CPB. The consistency between the predicted value and the actual value is high, which proves that the hybrid machine learning model has a good effect on the prediction of the UCS of CPB. Then, considering the linear relationship between the costs and the components of CPB, a mathematical model of the cost is constructed. Finally, based on the weighted sum method, the biobjective optimization process of the UCS and cost of CPB is conducted; the Pareto front optimal solutions of UCS and the cost of CPB can be obtained by the sort of solution set. When the UCS or the cost of CPB is constant, the Pareto front optimal solutions can always have a lower cost or a higher UCS compared with the actual dataset, which proves that the biobjective optimization approach has a good effect.