ORCID Profile
0000-0002-9046-3492
Current Organisation
China University of Mining and Technology
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Publisher: Springer Science and Business Media LLC
Date: 11-2019
Publisher: MDPI AG
Date: 04-08-2202
DOI: 10.3390/MA15155369
Abstract: Blast furnace slag (BFS) and fly ash (FA), as mining-associated solid wastes with good pozzolanic effects, can be combined with superplasticizer to prepare concrete with less cement utilization. Considering the important influence of strength on concrete design, random forest (RF) and particle swarm optimization (PSO) methods were combined to construct a prediction model and carry out hyper-parameter tuning in this study. Principal component analysis (PCA) was used to reduce the dimension of input features. The correlation coefficient (R), the explanatory variance score (EVS), the mean absolute error (MAE) and the mean square error (MSE) were used to evaluate the performance of the model. R = 0.954, EVS = 0.901, MAE = 3.746, and MSE = 27.535 of the optimal RF-PSO model on the testing set indicated the high generalization ability. After PCA dimensionality reduction, the R value decreased from 0.954 to 0.88, which was not necessary for the current dataset. Sensitivity analysis showed that cement was the most important feature, followed by water, superplasticizer, fine aggregate, BFS, coarse aggregate and FA, which was beneficial to the design of concrete schemes in practical projects. The method proposed in this study for estimation of the compressive strength of BFS-FA-superplasticizer concrete fills the research gap and has potential engineering application value.
Publisher: Hindawi Limited
Date: 2017
DOI: 10.1155/2017/4010376
Abstract: The kinetics of fluid-solid coupling during immersion is an important topic of investigation in rock engineering. Two rock types, sandstone and mudstone, are selected in this work to study the correlation between the softening characteristics of the rocks and moisture content. This is achieved through detailed studies using scanning electron microscopy, shear tests, and evaluation of rock index properties during exposure to different moisture contents. An underground roadway excavation is simulated by dynamic finite element modeling to analyze the effect of moisture content on the stability of the roadway. The results show that moisture content has a significant effect on shear properties reduction of both sandstone and mudstone, which must thus be considered in mining or excavation processes. Specifically, it is found that the number, area, and diameter of micropores, as well as surface porosity, increase with increasing moisture content. Additionally, stress concentration is negatively correlated with moisture content, while the influenced area and vertical displacement are positively correlated with moisture content. These findings may provide useful input for the design of underground roadways.
Publisher: Elsevier BV
Date: 03-2019
Publisher: Wiley
Date: 10-01-2019
DOI: 10.1002/NAG.2891
Publisher: MDPI AG
Date: 19-08-2021
DOI: 10.3390/SU13169315
Abstract: Pre-grouting as an effective means for improving the stability of roadways can reduce maintenance costs and maintain safety in complex mining conditions. In the Guobei coal mine in China, a cement pre-grouting technique was adopted to enhance the overall strength of soft coal mass and provide sufficient support for the roadway. However, there are very limited studies about the effect of grouting on the overall strength of coal in the laboratory. In this paper, based on the field observation of a coal-grout structure after grouting, a series of direct shear tests were conducted on coal and grouted coal specimens to quantitatively evaluate the quality improvement of grouted coal mass. The results showed that the peak and residual shear strength, cohesion, friction angle and the shear stiffness of grouted coal were significantly improved with the increase of the diameter of grout column. Linear regression models were established for predicting these mechanical parameters. In addition, three failure models associated with coal and grouted coal specimens were revealed. According to microstructure and macroscopic failure performance of specimens, the application of the proposed models and some methods for further improving the stability of grouted coal mass were suggested. The research can provide the basic evaluation and guideline for the parametric design of cement pre-grouting applications in soft coal mass.
Publisher: MDPI AG
Date: 28-08-2021
DOI: 10.3390/APP11177953
Abstract: The roadway stability has been regarded as the main challenging issue for safety and productivity of deep underground coal mines, particularly where roadways are affected by coal mining activities. This study investigates the −740 m main roadway in the Jining No. 2 Coal Mine to provide a theoretical basis for the stability control of the main deep roadway affected by disturbances of adjacent working activities. Field surveys, theoretical analyses, and numerical simulations are used to reveal mechanisms of the coal mining disturbance. The field survey shows that the deformation of roadway increases when the work face advances near the roadway group. Long working face mining causes the key strata to collapse based on the key strata theory and then disturbs the adjacent roadway group. When the working face is 100 m away from the stop-mining line, the roadway group is affected by the mining face, and the width roadway protection coal pillar is determined to be about 100 m. Flac3D simulations prove the accuracy of the theoretical result. Through reinforcement and support measures for the main roadway, the overall strength of the surrounding rock is enhanced, the stability of the surrounding rock of the roadway is guaranteed, and the safe production of the mine is maintained.
Publisher: Hindawi Limited
Date: 16-04-2020
DOI: 10.1155/2020/1643529
Abstract: Cemented paste backfill (CPB) is an eco-friendly composite containing mine waste or tailings and has been widely used as construction materials in underground stopes. In the field, the uniaxial compressive strength (UCS) of CPB is critical as it is closely related to the stability of stopes. Predicting the UCS of CPB using traditional mathematical models is far from being satisfactory due to the highly nonlinear relationships between the UCS and a large number of influencing variables. To solve this problem, this study uses a support vector machine (SVM) to predict the UCS of CPB. The hyperparameters of the SVM model are tuned using the beetle antennae search (BAS) algorithm then, the model is called BSVM. The BSVM is then trained on a dataset collected from the experimental results. To explain the importance of each input variable on the UCS of CPB, the variable importance is obtained using a sensitivity study with the BSVM as the objective function. The results show that the proposed BSVM has high prediction accuracy on the test set with a high correlation coefficient (0.97) and low root-mean-square error (0.27 MPa). The proposed model can guide the design of CPB during mining.
No related grants have been discovered for LI Guichen.