Coal Moisture Variations in Response to Rainfall Event in Mines and Coal-Fired Power Plant Stockpiles—Part 1: Runoff, Infiltration, and Drainage

Excessive coal moisture leads to a lower heating value and power plant efficiency, and increased transportation costs. Therefore, coal stockpile management and moisture control are particularly important in regions with heavy precipitation. This paper and Part 2 address factors influencing moisture retention and migration in coal stockpiles. Part 1 of this paper series simulates phenomena of runoff, infiltration, and drainage in a stockpile after a rainfall event. Part 2 reports the effect of coal particle size and climate conditions on the rate and depth of moisture evaporation process within a coal stockpile. To perform this study, two coal samples were collected from the Witbank mine in South Africa. The results of the present study showed that smaller interparticulate void spaces because of the compaction or fines particles (−0.5 mm fraction) inhibited infiltration, leading to increased runoff volume. An increase stockpile slope increased the amount of runoff due to coal–water contact time reduction. The ability of heavy rainfall to destroy near-surface structures (erosion) happened more readily at stockpiles with high slopes and high fine content. The fine content significantly influenced the dewatering efficiency of drainage. Coals with higher ash contents had stronger moisture retention ability than that of other coals even though coals with low ash contents had a high fine content. This was ascribed to the contribution of the clay minerals, such as kaolinite, in the high ash coal. The results of this paper can be used for the effective management of coal stockpiles to prevent excessive moisture in stockpiles for the best possible utilisation of coal in power plants.

Computation of Permeability of Soil using Artificial Intelligence Approaches

The Gaussian Process Regression (GPR), Decision Tree (DT), Relevance Vector Machine (RVM), and Artificial Neural Network (ANN) AI approaches are constructed in MATLAB R2020a with different hyperparameters namely, kernel function, leaf size, backpropagation algorithms, number of neurons and hidden layers to compute the permeability of soil. The present study is carried out using 158 datasets of soil. The soil dataset consists of fine content (FC), sand content (SC), liquid limit (LL), specific gravity (SG), plasticity index (PI), maximum dry density (MDD) and optimum moisture content (OMC), permeability (K). Excluding the permeability of soil, rest of properties of soil is used as input parameters of the AI models. The best architectural and optimum performance models are identified by comparing the performance of the models. Based on the performance of the AI models, the NISEK_K_GPR, 10LF_K_DT, Poly_K_RVM, and GDANN_K_10H5 models have been identified as the best architectural AI models. The comparison of performance of the best architectural models, it is observed that the NISEK_K_GPR model outperformed the other best architectural AI models. In this study, it is also observed that GPR model is outperformed ANN models because of small dataset. The performance of NISEK_K_GPR model is compared with models available in literature and it is concluded that the GPR model has better performance and least prediction error than models available in literature study.

Study on Particle-Size Process on Internal Erosion of Grap-Graded Soil--Rock Mixtures of Different Fine Contents

Soil–rock mixtures are widely encountered in geotechnical engineering projects. The instability and failure mechanism of grap-graded soil–rock mixtures under rainfall conditions has always been the focus of geological disaster research. To deeply explore the mechanism of seepage deformation of soil–rock mixtures, an indoor physical permeability test that considers soil–rock mixtures with different fine contents was conducted, and a particle-scale numerical simulation test of the permeability evolution was carried out using the coupling model of PFC3D and ABAQUS. The test results showed that the spatial distribution of fine particle loss along the height direction could be divided into three areas: top loss, middle uniform, and bottom loss area. The “island” effect of coarse particles, which is caused by excessive fine content and makes the fine particles bear more load, was eliminated with the loss of fine particles. In this preset working condition of coarse and fine particle diameters, setting FC to 35% may be the best way to fill the voids between the coarse particles. Particle migration leads to a change in the load-bearing skeleton structure, thereby causing seepage deformation. Therefore, the particle-scale numerical test method can better reproduce the seepage deformation process of grap-graded soil–rock mixtures.

Minimum Void Ratio Model Established from Tailings and Determination of Optimal Void Ratio

Minimum void ratio of tailings and its value change with fine content and are key design parameters for tailing consolidation and seepage stability. Based on the distribution of tailing grains with the sedimentary beach, we establish a minimum void ratio model for tailing grain in binary size, which requires only two parameters ( ε and ω ). Calibrations of the model using 168 groups of tests (22 kinds of grain size ratios with 7-9 kinds of fine contents) show two parameters that are fitting for power function, and the exponent values increase with the dominant grain size expanded. Besides, the exponent values are related to the equivalent grain size ratio, dominant grain size, and shape characteristics. The minimum void ratios with fine content are predicted under the derived model. Good agreement was obtained between the predictions and measurements, and the average discrepancies are less than 10%. And optimal void ratio and optimal fine content can be predicted, and the values are in good agreement with the experimental ones. Furthermore, based on the predicted optimal void ratio, the exponential relationship between the optimal void ratio and the equivalent grain size ratio may have no influence on the derived dominant grain size and shape characteristics. For tailings, further work is needed to verify if the derived exponential relationship between the optimal void ratio and the equivalent grain size ratio is valid.

Sustainable and Stable Clay Sand Liners over Time

The washout of fine materials from liners consisting of clay–sand mixtures is expected to influence the hydraulic conductivity. Clay sand liners must be assessed for efficiency when initially subjected to flood or standing water as the wetting under a hydraulic gradient can cause fine material to move and migrate away from the mixture. During wetting and drying complex expansion and shrinkage, changes take place. These changes affect the hydraulic conductivity and are likely to go out of the design range set out for the facility. The research covers the behavior of two clay sand liners tested over an extended time. The hydraulic conductivity measured under a specific hydraulic gradient was measured continuously following the establishment of the test set-up. Self-recording sensors were used to measure the temperature during the tests. The results indicated that the hydraulic conductivity reduces after an initial period of increase and fluctuation caused by the loss of mass because of fine material migration and swelling initiated due to the high content of smectite minerals. The testing and monitoring continued for more than 400 days. The permanent reduction in the hydraulic conductivity occurs after the initial period of repeated rise and fall. The extent of the initial period for the two tested mixtures is subject to the fine content mass and the clay mineralogy. The continuous reduction in the hydraulic conductivity after the initial period is due to the rearrangement of particles and compression in the sand–clay mixture.

Experimental Investigation into Limit Void Ratio Characteristics of Calcareous Sands considering Various Factors

Relative density is an important index affecting the mechanical behaviors of calcareous sands. The dense sands present softening strength, whereas the loose sands exhibit hardening strength. Furthermore, the relative density is determined based on the maximum and minimum void ratios obtained by using the maximum and minimum dry density test. In this study, a series of tests were carried out on various mixed graded sands to explore their material properties and the relationship between the limit void ratio, considering the effects of test methods, equipment, and fine content. It is shown that a more accurate maximum void ratio can be attained by using the 1000 mL measuring cylinder with low rotation speed. In addition, in order to avoid particle breakage of calcareous sands, it is suggested that the minimum void ratio should be obtained with the 1000 mL compaction cylinder combining vibration with hit. The results also show that a linear relationship exists among the limit void ratio of various mixed graded sands. Besides, the void ratio is significantly affected by the fine content. 40% is the critical fine content corresponding to the lowest value of the limit void ratio.

Effect of Tailings Fine Content on the Properties of Cemented Paste Backfill from the Perspective Packing Density

In order to quantitatively study the influence of tailings fine content on the properties of cemented paste backfill (CPB) and further understand the mechanism of tailings fine content acting, the concept of packing density was introduced in this study. The packing density of each tailings sample was measured by the wet packing method after the samples with various fine contents were prepared. Moreover, CPBs with different tailings fine contents were tested by the mini slump test, rheological test, uniaxial compressive strength (UCS) test, and mercury intrusion porosimetry test. The results demonstrated that the flow spread and UCS both increase first and then decrease with the increase of tailings fine content, while the yield stress shows an opposite trend. The fine content of tailings affects the flowability of fresh CPB mainly through the packing density. When the fine content is high, the influence of the specific surface area of tailings cannot be ignored. The packing density is an important factor affecting the strength of CPB, and there is an obvious linear relationship between the packing density and UCS. The pore structure of CPB samples with different tailing fine contents is significantly different, and the macroscopic packing density changes the strength of CPB by affecting the microscopic pores.