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Dr. Guichen Li
china university of mining and technology

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0 Mining Engineering
0 Rock Mechanics
0 rock bolting
0 Green Mining
0 underground engineering

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Journal article
Published: 28 August 2021 in Applied Sciences
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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.

ACS Style

Yuantian Sun; Ruiyang Bi; Qingliang Chang; Reza Taherdangkoo; Junfei Zhang; Junbo Sun; Jiandong Huang; Guichen Li. Stability Analysis of Roadway Groups under Multi-Mining Disturbances. Applied Sciences 2021, 11, 7953 .

AMA Style

Yuantian Sun, Ruiyang Bi, Qingliang Chang, Reza Taherdangkoo, Junfei Zhang, Junbo Sun, Jiandong Huang, Guichen Li. Stability Analysis of Roadway Groups under Multi-Mining Disturbances. Applied Sciences. 2021; 11 (17):7953.

Chicago/Turabian Style

Yuantian Sun; Ruiyang Bi; Qingliang Chang; Reza Taherdangkoo; Junfei Zhang; Junbo Sun; Jiandong Huang; Guichen Li. 2021. "Stability Analysis of Roadway Groups under Multi-Mining Disturbances." Applied Sciences 11, no. 17: 7953.

Journal article
Published: 19 August 2021 in Sustainability
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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.

ACS Style

Yuantian Sun; Guichen Li; Junfei Zhang; Junbo Sun; Jiandong Huang; Reza Taherdangkoo. New Insights of Grouting in Coal Mass: From Small-Scale Experiments to Microstructures. Sustainability 2021, 13, 9315 .

AMA Style

Yuantian Sun, Guichen Li, Junfei Zhang, Junbo Sun, Jiandong Huang, Reza Taherdangkoo. New Insights of Grouting in Coal Mass: From Small-Scale Experiments to Microstructures. Sustainability. 2021; 13 (16):9315.

Chicago/Turabian Style

Yuantian Sun; Guichen Li; Junfei Zhang; Junbo Sun; Jiandong Huang; Reza Taherdangkoo. 2021. "New Insights of Grouting in Coal Mass: From Small-Scale Experiments to Microstructures." Sustainability 13, no. 16: 9315.

Journal article
Published: 18 July 2021 in Minerals
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The awareness of the impact of high temperatures on rock properties is essential to the design of deep geotechnical applications. The purpose of this research is to assess the influence of heating and cooling treatments on the physical and mechanical properties of Egyptian granodiorite as a degrading factor. The samples were heated to various temperatures (200, 400, 600, and 800 °C) and then cooled at different rates, either slowly cooled in the oven and air or quickly cooled in water. The porosity, water absorption, P-wave velocity, tensile strength, failure mode, and associated microstructural alterations due to thermal effect have been studied. The study revealed that the granodiorite has a slight drop in tensile strength, up to 400 °C, for slow cooling routes and that most of the physical attributes are comparable to natural rock. Despite this, granodiorite thermal deterioration is substantially higher for quick cooling than for slow cooling. Between 400:600 °C is ‘the transitional stage’, where the physical and mechanical characteristics degraded exponentially for all cooling pathways. Independent of the cooling method, the granodiorite showed a ductile failure mode associated with reduced peak tensile strengths. Additionally, the microstructure altered from predominantly intergranular cracking to more trans-granular cracking at 600 °C. The integrity of the granodiorite structure was compromised at 800 °C, the physical parameters deteriorated, and the rock tensile strength was negligible. In this research, the temperatures of 400, 600, and 800 °C were remarked to be typical of three divergent phases of granodiorite mechanical and physical properties evolution. Furthermore, 400 °C could be considered as the threshold limit for Egyptian granodiorite physical and mechanical properties for typical thermal underground applications.

ACS Style

Mohamed Gomah; Guichen Li; Salah Bader; Mohamed Elkarmoty; Mohamed Ismael. Damage Evolution of Granodiorite after Heating and Cooling Treatments. Minerals 2021, 11, 779 .

AMA Style

Mohamed Gomah, Guichen Li, Salah Bader, Mohamed Elkarmoty, Mohamed Ismael. Damage Evolution of Granodiorite after Heating and Cooling Treatments. Minerals. 2021; 11 (7):779.

Chicago/Turabian Style

Mohamed Gomah; Guichen Li; Salah Bader; Mohamed Elkarmoty; Mohamed Ismael. 2021. "Damage Evolution of Granodiorite after Heating and Cooling Treatments." Minerals 11, no. 7: 779.

Research article
Published: 20 April 2021 in Geofluids
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The micromechanism of the effects of different height/width ratios (H/W) and initial stress levels on unloading characteristics of deep rock was investigated based on PFC3D true-triaxial unloading simulation. The results show that the increase of H/W will increase the movement speed of rock particles and intensify the acoustic emission (AE) activity inside the rock. With the increase of H/W, the failure mode of rock changes from splitting failure to tensile-shear failure. With increasing initial stress level, the particle velocity and overall fragmentation degree of rock increase. However, the increase of lateral stress will limit the coalescence of microfractures and weaken AE activity in the rock. Under unloading condition, the bonds between particles generally crack along the unloading direction, and the tensile effect is more pronounced under the condition of low initial stress level and high H/W. Under unloading condition, the variable energy of rock increases with increasing H/W and initial stress level, and the kinetic energy of rock particles increases with increasing H/W. The increase of initial stress level will increase the kinetic energy of rock particles when H/W is high.

ACS Style

Haoyu Rong; Guichen Li; Jiahui Xu; Ruiyang Bi; Yuantian Sun; Yaqiao Hu; Guoliang Bai. Particle Flow Simulation of Failure Characteristics of Deep Rock Influenced by Sample Height-to-Width Ratios and Initial Stress Level under True-Triaxial Unloading. Geofluids 2021, 2021, 1 -16.

AMA Style

Haoyu Rong, Guichen Li, Jiahui Xu, Ruiyang Bi, Yuantian Sun, Yaqiao Hu, Guoliang Bai. Particle Flow Simulation of Failure Characteristics of Deep Rock Influenced by Sample Height-to-Width Ratios and Initial Stress Level under True-Triaxial Unloading. Geofluids. 2021; 2021 ():1-16.

Chicago/Turabian Style

Haoyu Rong; Guichen Li; Jiahui Xu; Ruiyang Bi; Yuantian Sun; Yaqiao Hu; Guoliang Bai. 2021. "Particle Flow Simulation of Failure Characteristics of Deep Rock Influenced by Sample Height-to-Width Ratios and Initial Stress Level under True-Triaxial Unloading." Geofluids 2021, no. : 1-16.

Research article
Published: 10 April 2021 in Advances in Civil Engineering
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The roadway deformation normally relates to time especially for underground coal roadway. The strength of soft coal is low, and therefore the deformation increases gradually under constant stress with time, which is called rheology deformation. In this study, based on a field case, the rock mass properties and deformation data of the roadway were obtained according to the field test. A 3D numerical model was then established, and the rheological deformation including horizontal and vertical deformation of the coal roadway was systematically analyzed. The results showed that the rheological deformation of horizontal sidewall accounts for almost 30% of the whole deformation, and the stable time for such roadway is around 60 days after excavation. The tendency of the roof deformation is similar to the sidewalls, and however, the floor deformation is different. Then the related suggestions for maintaining the stability of such roadway were proposed, which is useful in-field application.

ACS Style

Yuantian Sun; Guichen Li; Junfei Zhang; Bicheng Yao; Deyu Qian; Jiandong Huang. Numerical Investigation on Time-Dependent Deformation in Roadway. Advances in Civil Engineering 2021, 2021, 1 -7.

AMA Style

Yuantian Sun, Guichen Li, Junfei Zhang, Bicheng Yao, Deyu Qian, Jiandong Huang. Numerical Investigation on Time-Dependent Deformation in Roadway. Advances in Civil Engineering. 2021; 2021 ():1-7.

Chicago/Turabian Style

Yuantian Sun; Guichen Li; Junfei Zhang; Bicheng Yao; Deyu Qian; Jiandong Huang. 2021. "Numerical Investigation on Time-Dependent Deformation in Roadway." Advances in Civil Engineering 2021, no. : 1-7.

Journal article
Published: 02 March 2021 in International Journal of Rock Mechanics and Mining Sciences
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The conventional discontinuity survey process in the mining industry is known to be a time-consuming one and it is technically challenging due to the limited accessibility of fresh rock exposures. A rapid and robust rock mass property quantification system is desirable for rock structure design during mining operations. In this work we develop an image-based and fully automatic rock mass Geological Strength Index (GSI) rating system. The proposed method involves a series of novel algorithms to quantify the GSI rating based on data recovered from digital images. The proposed GSI system includes both Structure Rating (SR) and Joint Condition Digital Imaging (JCDI) to represent the bulk rock and discontinuity surface conditions of the rock mass. Local histogram equalization and self-adaptive gamma correction were introduced into the pre-processing of the rock face images. Compared to conventional histogram equalization, local histogram equalization can effectively restrain the uneven distribution of brightness often present. Self-adaptive gamma correction based on the image properties automatically enlarges the difference between discontinuity areas and intact rock. A novel algorithm combining region growing and the Hough transform is proposed for the automatic extraction of discontinuity areas. Laboratory and field tests demonstrated that the algorithm possesses an advantage over existing methods with regard to better noise suppression and that it can yield reasonable results for images taken in poor photography conditions. Discontinuities were characterized using a novel algorithm comprising area thinning, skeleton linking, spurs removal, and sampling. Using this algorithm, four parameters of the discontinuity can be quantified: length, orientation, separation width, and JRC value. The proposed approach was validated by two field-based case studies.

ACS Style

Sen Yang; Shimin Liu; Nong Zhang; Guichen Li; Jie Zhang. A fully automatic-image-based approach to quantifying the geological strength index of underground rock mass. International Journal of Rock Mechanics and Mining Sciences 2021, 140, 104585 .

AMA Style

Sen Yang, Shimin Liu, Nong Zhang, Guichen Li, Jie Zhang. A fully automatic-image-based approach to quantifying the geological strength index of underground rock mass. International Journal of Rock Mechanics and Mining Sciences. 2021; 140 ():104585.

Chicago/Turabian Style

Sen Yang; Shimin Liu; Nong Zhang; Guichen Li; Jie Zhang. 2021. "A fully automatic-image-based approach to quantifying the geological strength index of underground rock mass." International Journal of Rock Mechanics and Mining Sciences 140, no. : 104585.

Research article
Published: 09 February 2021 in International Journal of Coal Science & Technology
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The creep behaviors in deep underground engineering structures, especially in soft rocks, have a remarkable impact on the long-term stability of the excavations, which finally leads to the high risk and failure of it. Accordingly, it is essential to recognize the time-dependent deformation through the investigation of this phenomenon. In this study, the creep behaviors of soft rocks were examined to help understand the underlying mechanism of the extended time-dependent deformation. Due to the limited results about the time-dependent properties of the constituents of the rock that reveal their heterogeneity, the targeting nanoindentation technique (TNIT), was adopted to investigate the viscoelastic characteristics of kaolinite and quartz in a two-constituent mudstone sample. The TNIT consists of identifications of mineralogical ingredients in mudstone and nanoindentation experiments on each identified constituent. After conducting experiments, the unloading stages of the typical indentation curves were analyzed to calculate the hardness and elastic modulus of both elements in mudstone. Additionally, the 180 s load-holding stages with the peak load of 50 mN were transformed into the typical creep strain–time curves for fitting analysis by using the Kelvin model, the standard viscoelastic model, and the extended viscoelastic model. Fitting results show that the standard viscoelastic model not only can perfectly express the nanoindentation creep behaviors of both kaolinite and quartz but also can produce suitable constants used to measure their creep parameters. The creep parameters of kaolinite are much smaller than that of quartz, which causes the considerable time-dependent deformation of the soft mudstone. Eventually, the standard viscoelastic model was also verified on the quartz in a sandstone sample.

ACS Style

Changlun Sun; Guichen Li; Mohamed Elgharib Gomah; Jiahui Xu; Haoyu Rong. Experimental investigation on the nanoindentation viscoelastic constitutive model of quartz and kaolinite in mudstone. International Journal of Coal Science & Technology 2021, 1 -13.

AMA Style

Changlun Sun, Guichen Li, Mohamed Elgharib Gomah, Jiahui Xu, Haoyu Rong. Experimental investigation on the nanoindentation viscoelastic constitutive model of quartz and kaolinite in mudstone. International Journal of Coal Science & Technology. 2021; ():1-13.

Chicago/Turabian Style

Changlun Sun; Guichen Li; Mohamed Elgharib Gomah; Jiahui Xu; Haoyu Rong. 2021. "Experimental investigation on the nanoindentation viscoelastic constitutive model of quartz and kaolinite in mudstone." International Journal of Coal Science & Technology , no. : 1-13.

Journal article
Published: 21 November 2020 in Minerals
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Cemented paste backfill (CPB) is widely used in underground mining, and attracts more attention these years as it can reduce mining waste and avoid environmental pollution. Normally, to evaluate the functionality of CPB, the compressive strength (UCS) is necessary work, which is also time and money consuming. To address this issue, seven machine learning models were applied and evaluated in this study, in order to predict the UCS of CPB. In the laboratory, a series of tests were performed, and the dataset was constructed considering five key influencing variables, such as the tailings to cement ratio, curing time, solids to cement ratio, fine sand percentage and cement types. The results show that different variables have various effects on the strength of CPB. The optimum models for predicting the UCS of CPB are a support vector machine (SVM), decision tree (DT), random forest (RF) and back-propagation neural network (BPNN), which means that these models can be directly applied for UCS prediction in future work. Furthermore, the intelligent model reveals that the tailings to cement ratio has the most important influence on the strength of CPB. This research can boost CPB application in the field, and guide the artificial intelligence application in future mining.

ACS Style

Jiandong Liu; Guichen Li; Sen Yang; Jiandong Huang. Prediction Models for Evaluating the Strength of Cemented Paste Backfill: A Comparative Study. Minerals 2020, 10, 1041 .

AMA Style

Jiandong Liu, Guichen Li, Sen Yang, Jiandong Huang. Prediction Models for Evaluating the Strength of Cemented Paste Backfill: A Comparative Study. Minerals. 2020; 10 (11):1041.

Chicago/Turabian Style

Jiandong Liu; Guichen Li; Sen Yang; Jiandong Huang. 2020. "Prediction Models for Evaluating the Strength of Cemented Paste Backfill: A Comparative Study." Minerals 10, no. 11: 1041.

Original paper
Published: 14 October 2020 in Natural Resources Research
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As the cover depth of coalmines in China increases, large protective coal pillars are widely used to support the overlying strata during mining. After the longwall panels on both sides of the protective pillar are mined, the protective pillar becomes an island pillar. The high static and dynamic stress accumulated in a protective island pillar may cause overall rockburst hazards in the gateway between the protective island pillar and the longwall panel being mined. Based on a rockburst accident that occurred in the Longyun coalmine, Shandong province, China, this study elucidates the occurrence mechanism of this type of rockburst. Firstly, a mathematical model is proposed to evaluate static stress distribution in the protective coal pillar. The calculation results indicate that large elastic energy is accumulated in the large protective pillar and overall rockburst hazards is very likely to be induced. To reduce rockburst risk, rockburst index is defined and long-borehole de-stress measures were adopted in this study. Then, dynamic stress evolution in the protective island pillar during mining the longwall panel was analyzed using PFC2D. The results show that the peak stress in the protective pillar increased continuously from 28 to 67 MPa with the working face advancing, indicating high rockburst risk in the protective pillar. The results of the mathematical model and numerical analysis agreed well with the rockburst accident that occurred in Longyun coalmine. This study paves the way for the design of large protective pillars based on overall rockburst prevention in deep coalmines.

ACS Style

Dong Li; Junfei Zhang; Yuantian Sun; Guichen Li. Evaluation of Rockburst Hazard in Deep Coalmines with Large Protective Island Coal Pillars. Natural Resources Research 2020, 30, 1835 -1847.

AMA Style

Dong Li, Junfei Zhang, Yuantian Sun, Guichen Li. Evaluation of Rockburst Hazard in Deep Coalmines with Large Protective Island Coal Pillars. Natural Resources Research. 2020; 30 (2):1835-1847.

Chicago/Turabian Style

Dong Li; Junfei Zhang; Yuantian Sun; Guichen Li. 2020. "Evaluation of Rockburst Hazard in Deep Coalmines with Large Protective Island Coal Pillars." Natural Resources Research 30, no. 2: 1835-1847.

Journal article
Published: 18 September 2020 in International Journal of Mining Science and Technology
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In the loose and fractured coal seam with particularly low uniaxial compressive strength (UCS), driving a roadway is extremely difficult as roof falling and wall spalling occur frequently. To address this issue, the jet grouting (JG) technique (high-pressure grout mixed with coal particles) was first introduced in this study to improve the self-supporting ability of coal mass. To evaluate the strength of the jet-grouted coal-grout composite (JG composite), the UCS evolution patterns were analyzed by preparing 405 specimens combining the influential variables of grout types, curing time, and coal to grout (C/G) ratio. Furthermore, the relationships between UCS and these influencing variables were modeled using ensemble learning methods i.e. gradient boosted regression tree (GBRT) and random forest (RF) with their hyperparameters tuned by the particle swarm optimization (PSO). The results showed that the chemical grout composite has higher short-term strength, while the cement grout composite can achieve more stable strength in the long term. The PSO-GBRT and PSO-RF models can both achieve high prediction accuracy. Also, the variable importance analysis demonstrated that the grout type and curing time should be considered carefully. This study provides a robust intelligent model for predicting UCS of JG composites, which boosts JG design in the field.

ACS Style

Yuantian Sun; Guichen Li; Nong Zhang; Qingliang Chang; Jiahui Xu; Junfei Zhang. Development of ensemble learning models to evaluate the strength of coal-grout materials. International Journal of Mining Science and Technology 2020, 31, 153 -162.

AMA Style

Yuantian Sun, Guichen Li, Nong Zhang, Qingliang Chang, Jiahui Xu, Junfei Zhang. Development of ensemble learning models to evaluate the strength of coal-grout materials. International Journal of Mining Science and Technology. 2020; 31 (2):153-162.

Chicago/Turabian Style

Yuantian Sun; Guichen Li; Nong Zhang; Qingliang Chang; Jiahui Xu; Junfei Zhang. 2020. "Development of ensemble learning models to evaluate the strength of coal-grout materials." International Journal of Mining Science and Technology 31, no. 2: 153-162.

Journal article
Published: 15 August 2020 in International Journal of Mining Science and Technology
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In coal mining industry, with the depth growing of coal mines, the creep behaviours of coal and rock can extensively affect the mining safety, coalbed methane recovery and geo-sequestration. To acquire a better insight into their creep characteristics, an efficient and robust researching technique, nanoindentation, was applied to investigate the creep performances of coal and rock samples obtained from two coal mines in the east of China. Creep characteristics were reflected by evaluating the curves of creep depth versus creep time of nanoindentation tests during the load-holding period at the peak load of 30 mN. These curves can be divided into two stages: transient stage and steady stage; and the time of load-holding period of 5 s, which is the dividing point between two stages, can efficiently avoid the influence of creep displacement on the unloading curves. The exponential function can perfectly fit creep curves and Kelvin model can be used to calculate the rheological parameters of coal and rock samples. Calculated results yield values for the creep modulus and viscosity terms of coal and rock. This study also settled a particular emphasis on the selection of the positions of indentations to obtain the rheological properties of mineralogical constituents in heterogonous coal and rock samples and their elastic aftereffect.

ACS Style

Changlun Sun; Guichen Li; Mohamed Elgharib Gomah; Jiahui Xu; Yuantian Sun. Creep characteristics of coal and rock investigated by nanoindentation. International Journal of Mining Science and Technology 2020, 30, 769 -776.

AMA Style

Changlun Sun, Guichen Li, Mohamed Elgharib Gomah, Jiahui Xu, Yuantian Sun. Creep characteristics of coal and rock investigated by nanoindentation. International Journal of Mining Science and Technology. 2020; 30 (6):769-776.

Chicago/Turabian Style

Changlun Sun; Guichen Li; Mohamed Elgharib Gomah; Jiahui Xu; Yuantian Sun. 2020. "Creep characteristics of coal and rock investigated by nanoindentation." International Journal of Mining Science and Technology 30, no. 6: 769-776.

Journal article
Published: 05 August 2020 in Engineering Fracture Mechanics
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The widespread occurrence of heterogeneous mudstone poses several challenges for the stability of engineering structures. To understand the failure mechanism of argillaceous projects, and reveal the heterogeneity of mudstone, the mechanical properties of mineralogical compositions in mudstone were investigated, by using the nanoindentation technique at the meso-scale. Through “X-ray diffraction(XRD), scanning electron microscope(SEM)- energy dispersive spectrometer(EDS), and mercury intrusion porosimeter(MIP)” observations, the mineralogical compositions in mudstone can be divided into two constituents: clay matrix and silt inclusions, further, the multiscale structure model of mudstone includes three scales: macro-, meso- and micro-scale. Nanoindentation technique was adopted to investigate the meso-scale mechanical properties of mudstone by setting four peak loads ranging from 1 mN-30 mN on different positions to avoid measuring errors. A superposition of 2 Gaussian probability densities was used to represent the distributions of the mechanical parameters of the mudstone by applying a coupled mineral-mechanical approach proposed in this study. The results showed that the mean hardness and elastic modulus of clay matrix are 398.22 MPa and 11.89 GPa, which are much smaller than that of silt inclusions (1529.43 MPa and 22.08 GPa) in mudstone, inducing the soft properties of mudstone and argillaceous projects. Due to the influence of macro- and meso-scale pores and cracks in mudstone, the elastic modulus of both the clay matrix and silt inclusions in it, is larger than that of mudstone.

ACS Style

Changlun Sun; Guichen Li; Mohamed Elgharib Gomah; Jiahui Xu; Haoyu Rong. Meso-scale mechanical properties of mudstone investigated by nanoindentation. Engineering Fracture Mechanics 2020, 238, 107245 .

AMA Style

Changlun Sun, Guichen Li, Mohamed Elgharib Gomah, Jiahui Xu, Haoyu Rong. Meso-scale mechanical properties of mudstone investigated by nanoindentation. Engineering Fracture Mechanics. 2020; 238 ():107245.

Chicago/Turabian Style

Changlun Sun; Guichen Li; Mohamed Elgharib Gomah; Jiahui Xu; Haoyu Rong. 2020. "Meso-scale mechanical properties of mudstone investigated by nanoindentation." Engineering Fracture Mechanics 238, no. : 107245.

Preprint content
Published: 25 July 2020
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The creep behaviors in deep underground engineering structures, especially in soft rocks, have a remarkable impact on the long-term stability of the excavations, which finally leads to the high risk and failure of it. Accordingly, it is essential to recognize the time-dependent deformation through the investigation of this phenomenon. In this study, the creep behaviors of soft rocks have been widely examined to help understand the underlying mechanism of the extended time-dependent deformation. Due to the limited results about the time-dependent properties of the constituents of the rock that reveal their heterogeneity, the targeting nanoindentation technique (TNIT), was adopted to investigate the viscoelastic characteristics of kaolinite and quartz in a two-constituent mudstone sample. The TNIT consists of identifications of mineralogical ingredients in mudstone with nanoindentation experiments on each identified constituent. After conducting experiments, the unloading stages of the typical indentation curves were analyzed to calculate the hardness and elastic modulus of both elements in mudstone. Additionally, the 180 s load-holding stages with the peak load of 50 mN were transformed into the typical creep strain-time curves for fitting analysis by using the Kelvin model, the standard viscoelastic model, and the extended viscoelastic model. Fitting results show that the standard viscoelastic model not only can perfectly express the nanoindentation creep behaviors of both kaolinite and quartz but also can produce suitable constants used to measure their creep parameters. Furthermore, the creep parameters of kaolinite are much smaller than that of quartz, which causes the considerable time-dependent deformation of the soft mudstone. Eventually, the standard viscoelastic model was also verified on the quartz in a sandstone sample.

ACS Style

Changlun Sun; Guichen Li; Gomah Mohamed Elgharib; Jiahui Xu; Haoyu Rong. Experimental investigation on the nanoindentation viscoelastic constitutive model of quartz and kaolinite in mudstone. 2020, 1 .

AMA Style

Changlun Sun, Guichen Li, Gomah Mohamed Elgharib, Jiahui Xu, Haoyu Rong. Experimental investigation on the nanoindentation viscoelastic constitutive model of quartz and kaolinite in mudstone. . 2020; ():1.

Chicago/Turabian Style

Changlun Sun; Guichen Li; Gomah Mohamed Elgharib; Jiahui Xu; Haoyu Rong. 2020. "Experimental investigation on the nanoindentation viscoelastic constitutive model of quartz and kaolinite in mudstone." , no. : 1.

Journal article
Published: 19 July 2020 in Applied Sciences
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Investigating the micro-parameters of rock is vital for understanding the macro-properties of rock, such as the uniaxial compressive strength (UCS), Young’s modulus, failure patterns, etc. In this paper, based on the experimental results of rock material, a parallel-bond model in three-dimensional particle flow code (PFC3D) was applied to investigate the effects of the joint action of bond stiffness ratio and bond stress ratio on macro-properties of rock. The uniaxial compressive strength, stress–strain relationships, and failure characteristics, as well as underlying compression and failure mechanisms, in the process of parameter calibration, were systematically studied. The results indicated that the interaction of several micro-parameters would obviously change the response characteristics of the macro-properties of the model. The mechanism of the effects of various micro-parameters on the macro-properties of the model was further revealed. The change of the micro-parameters would change the strength and stress state of the bond between particles. The research results could promote the understanding of the failure mechanism of rock and improve the efficiency of micro-parameter calibration and the accuracy of calibration results.

ACS Style

Haoyu Rong; Guichen Li; Dongxu Liang; Changlun Sun; Suhui Zhang; Yuantian Sun. Numerical Investigation on the Evolution of Mechanical Properties of Rock Affected by Micro-Parameters. Applied Sciences 2020, 10, 4957 .

AMA Style

Haoyu Rong, Guichen Li, Dongxu Liang, Changlun Sun, Suhui Zhang, Yuantian Sun. Numerical Investigation on the Evolution of Mechanical Properties of Rock Affected by Micro-Parameters. Applied Sciences. 2020; 10 (14):4957.

Chicago/Turabian Style

Haoyu Rong; Guichen Li; Dongxu Liang; Changlun Sun; Suhui Zhang; Yuantian Sun. 2020. "Numerical Investigation on the Evolution of Mechanical Properties of Rock Affected by Micro-Parameters." Applied Sciences 10, no. 14: 4957.

Preprint content
Published: 04 June 2020
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In deep underground engineering, the creep behaviors of soft rocks have been widely investigated to help understand the mechanism of the time-dependent large deformation and failure of underground engineering structures. However, rocks were used to be regarded as homogeneous materials and there are limited studying results about the time-dependent properties of constituents in them to reveal their creep mechanism. In this context, the targeting nanoindentation technique (TNIT) was adopted to investigate the viscoelastic characteristics of kaolinite and quartz in a two-constituent mudstone sample. The TNIT consists of identifications of mineralogical constituents in mudstone and nanoindentation experiments on identified constituents. After conducting experiments, the unloading stages of the typical indentation curves were analyzed to calculate the hardness and elastic modulus of constituents in mudstone. And the 180 s load-holding stages with the maximum load of 50 mN were transformed to the typical creep strain-time curves for fitting analysis by using the Kelvin model, the standard viscoelastic model and the extended viscoelastic model. Fitting results show that the standard viscoelastic model can perfectly express the nanoindentation creep behaviors of both kaolinite and quartz and fitting constants are suitable to be used to calculate their creep parameters. The creep parameters of kaolinite are much smaller than that of quartz, which drives the time-dependent large deformation of the soft mudstone. At last, the standard viscoelastic model was verified on a sandstone sample.

ACS Style

Changlun Sun; Guichen Li; Gomah Mohamed Elgharib; Jiahui Xu; Haoyu Rong. Experimental Investigation on the Viscoelastic Properties of Constituents in Mudstone. 2020, 1 .

AMA Style

Changlun Sun, Guichen Li, Gomah Mohamed Elgharib, Jiahui Xu, Haoyu Rong. Experimental Investigation on the Viscoelastic Properties of Constituents in Mudstone. . 2020; ():1.

Chicago/Turabian Style

Changlun Sun; Guichen Li; Gomah Mohamed Elgharib; Jiahui Xu; Haoyu Rong. 2020. "Experimental Investigation on the Viscoelastic Properties of Constituents in Mudstone." , no. : 1.

Research article
Published: 16 April 2020 in Advances in Civil Engineering
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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.

ACS Style

Yuantian Sun; Guichen Li; Junfei Zhang; Junbo Sun; Jiahui Xu. Development of an Ensemble Intelligent Model for Assessing the Strength of Cemented Paste Backfill. Advances in Civil Engineering 2020, 2020, 1 -6.

AMA Style

Yuantian Sun, Guichen Li, Junfei Zhang, Junbo Sun, Jiahui Xu. Development of an Ensemble Intelligent Model for Assessing the Strength of Cemented Paste Backfill. Advances in Civil Engineering. 2020; 2020 ():1-6.

Chicago/Turabian Style

Yuantian Sun; Guichen Li; Junfei Zhang; Junbo Sun; Jiahui Xu. 2020. "Development of an Ensemble Intelligent Model for Assessing the Strength of Cemented Paste Backfill." Advances in Civil Engineering 2020, no. : 1-6.

Journal article
Published: 04 April 2020 in Sustainability
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The roadway instability in deep underground conditions has attracted constant concerns in recent years, as it seriously affects the efficiency of coal mining and the safety of personnel. The large rheological deformations normally occur in deep roadway with soft coal mass. However, the failure mechanism of such roadways is still not clear. In this study, based on a typical soft coal roadway in the field, the in-situ measurements and rock mass properties were obtained. The rheological deformation of that roadway was revealed. Then a time-dependent 3D numerical model was established and verified. Based on the verified model, the deformation properties and evolutionary failure mechanism of deep coal roadway were investigated in detail. The results showed that the deformation of the soft coal roadway demonstrated rheological behavior and the applied support structures failed completely. After roadway excavation, the maximum and minimum stresses around the roadway deteriorated gradually with the increase of time. The failure zones in soft coal mass expanded increasingly over time, which had a negative effect on roadway stability in the long-term. According to the findings, helpful suggestions were further presented to control the rheological deformation in the roadway. This research systematically reveals the instability mechanism of the deep coal roadway and provides some strategies for maintaining roadway stability, which can significantly promote the sustainability of mining in deep underground coal mines.

ACS Style

Yuantian Sun; Guichen Li; Junfei Zhang; Jiahui Xu. Failure Mechanisms of Rheological Coal Roadway. Sustainability 2020, 12, 2885 .

AMA Style

Yuantian Sun, Guichen Li, Junfei Zhang, Jiahui Xu. Failure Mechanisms of Rheological Coal Roadway. Sustainability. 2020; 12 (7):2885.

Chicago/Turabian Style

Yuantian Sun; Guichen Li; Junfei Zhang; Jiahui Xu. 2020. "Failure Mechanisms of Rheological Coal Roadway." Sustainability 12, no. 7: 2885.

Journal article
Published: 28 February 2020 in Applied Sciences
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Coal-grout composites were fabricated in this study using the jet grouting (JG) technique to enhance coal mass in underground conditions. To evaluate the mechanical properties of the created coal-grout composite, its unconfined compressive strength (UCS) needed to be tested. A mathematical model is required to elucidate the unknown nonlinear relationship between the UCS and the influencing variables. In this study, six computational intelligence techniques using machine learning (ML) algorithms were used to develop the mathematical models, which includes back-propagation neural network (BPNN), random forest (RF), decision tree (DT), support vector machine (SVM), k-nearest neighbors (KNN), and logistic regression (LR). In addition, the hyper-parameters in these typical algorithms (e.g., the hidden layers in BPNN, the gamma in SVM, and the number of neighbor samples in KNN) were tuned by the recently developed beetle antennae search algorithm (BAS). To prepare the dataset for these ML models, three types of cementitious grout and three types of chemical grout were mixed with coal powders extracted from the Guobei coalmine, Anhui Province, China to create coal-grout composites. In total, 405 coal-grout specimens in total were extracted and tested. Several variables such as grout types, coal-grout ratio, and curing time were chosen as input parameters, while UCS was the output of these models. The results show that coal-chemical grout composites had higher strength in the short-term, while the coal-cementitious grout composites could achieve stable and high strength in the long term. BPNN, DT, and SVM outperform the others in terms of predicting the UCS of the coal-grout composites. The outstanding performance of the optimum ML algorithms for strength prediction facilitates JG parameter design in practice and could be the benchmark for the wider application of ML methods in JG engineering for coal improvement.

ACS Style

Yuantian Sun; Guichen Li; Junfei Zhang. Developing Hybrid Machine Learning Models for Estimating the Unconfined Compressive Strength of Jet Grouting Composite: A Comparative Study. Applied Sciences 2020, 10, 1612 .

AMA Style

Yuantian Sun, Guichen Li, Junfei Zhang. Developing Hybrid Machine Learning Models for Estimating the Unconfined Compressive Strength of Jet Grouting Composite: A Comparative Study. Applied Sciences. 2020; 10 (5):1612.

Chicago/Turabian Style

Yuantian Sun; Guichen Li; Junfei Zhang. 2020. "Developing Hybrid Machine Learning Models for Estimating the Unconfined Compressive Strength of Jet Grouting Composite: A Comparative Study." Applied Sciences 10, no. 5: 1612.

Research article
Published: 18 February 2020 in Energy Science & Engineering
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ACS Style

Yuantian Sun; Guichen Li; Junfei Zhang. Investigation on jet grouting support strategy for controlling time‐dependent deformation in the roadway. Energy Science & Engineering 2020, 8, 2151 -2158.

AMA Style

Yuantian Sun, Guichen Li, Junfei Zhang. Investigation on jet grouting support strategy for controlling time‐dependent deformation in the roadway. Energy Science & Engineering. 2020; 8 (6):2151-2158.

Chicago/Turabian Style

Yuantian Sun; Guichen Li; Junfei Zhang. 2020. "Investigation on jet grouting support strategy for controlling time‐dependent deformation in the roadway." Energy Science & Engineering 8, no. 6: 2151-2158.

Journal article
Published: 07 January 2020 in Applied Sciences
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Ground vibration induced by blasting operations is an important undesirable effect in surface mines and has significant environmental impacts on surrounding areas. Therefore, the precise prediction of blast-induced ground vibration is a challenging task for engineers and for managers. This study explores and evaluates the use of two stochastic metaheuristic algorithms, namely biogeography-based optimization (BBO) and particle swarm optimization (PSO), as well as one deterministic optimization algorithm, namely the DIRECT method, to improve the performance of an artificial neural network (ANN) for predicting the ground vibration. It is worth mentioning this is the first time that BBO-ANN and DIRECT-ANN models have been applied to predict ground vibration. To demonstrate model reliability and effectiveness, a minimax probability machine regression (MPMR), extreme learning machine (ELM), and three well-known empirical methods were also tested. To collect the required datasets, two quarry mines in the Shur river dam region, located in the southwest of Iran, were monitored, and the values of input and output parameters were measured. Five statistical indicators, namely the percentage root mean square error (%RMSE), coefficient of determination (R2), Ratio of RMSE to the standard deviation of the observations (RSR), mean absolute error (MAE), and degree of agreement (d) were taken into account for the model assessment. According to the results, BBO-ANN provided a better generalization capability than the other predictive models. As a conclusion, BBO, as a robust evolutionary algorithm, can be successfully linked to the ANN for better performance.

ACS Style

Guichen Li; Deepak Kumar; Pijush Samui; Hima Nikafshan Rad; Bishwajit Roy; Mahdi Hasanipanah. Developing a New Computational Intelligence Approach for Approximating the Blast-Induced Ground Vibration. Applied Sciences 2020, 10, 434 .

AMA Style

Guichen Li, Deepak Kumar, Pijush Samui, Hima Nikafshan Rad, Bishwajit Roy, Mahdi Hasanipanah. Developing a New Computational Intelligence Approach for Approximating the Blast-Induced Ground Vibration. Applied Sciences. 2020; 10 (2):434.

Chicago/Turabian Style

Guichen Li; Deepak Kumar; Pijush Samui; Hima Nikafshan Rad; Bishwajit Roy; Mahdi Hasanipanah. 2020. "Developing a New Computational Intelligence Approach for Approximating the Blast-Induced Ground Vibration." Applied Sciences 10, no. 2: 434.