Abstract:Objectives Due to the limitations of traditional continuum mechanics and fracture mechanics,it is challenging to accurately reveal the spatial structural characteristics of deep surrounding rock,particu-larly under three-dimensional stress states and complex geological conditions.Methods Based on the dimen-sionless conditions derived from quai-resonance and pendulum wave phenomena,a"characteristic energy factor"was derived to reflect the energy evolution of deep rock masses.This factor describes the energy-bearing properties of deep surrounding rock from a statistical physics perspective.Statistical analysis of field monitoring and model test data revealed the spatial variation of the characteristic energy factor during zonal disintegration.Results Comparative analysis with Shemyakin's empirical formula for the farthest frac-ture zone radius and measurement data from the 3213 working face in an underground mine validated the scaling evolution relationship between the spatial structure of zonal disintegration and the characteristic en-ergy factor.This indicates that the evolution of the characteristic energy factor can reflect the spatial struc-tural characteristics of zonal disintegration.Conclusions The proposed model has a minimal number of pa-rameters,is easy to measure,and demonstrates strong practicality and applicability,making it well-suited for predictive analysis and support design in deep tunnel construction.Additionally,this model significantly simplifies calculations and provides a novel approach to improving safety in deep underground engineering.It holds considerable potential for future planning of deep tunnel construction and the development of sur-rounding rock support strategies.

Abstract:Objectives This study aims to evaluate the leaching characteristics of solidified heavy metal-contaminated soil under an open-unidirectional freezing condition in the shallow groundwater environment of seasonally frozen regions.Methods Active magnesium oxide(MgO)and fly ash were used to solidify/sta-bilize Pb-Cd composite contaminated soil.Freeze-thaw cycle tests and leaching toxicity tests were con-ducted under two unidirectional freezing conditions:open(with external water replenishment)and closed(without external water replenishment).Scanning electron microscopy(SEM)was employed to investigate the deterioration mechanism of freeze-thaw cycles on the leaching characteristics of the solidified/stabilized Pb-Cd contaminated soil.Results The results showed that under different freezing conditions,the frost heave and the leaching concentrations of Pb and Cd followed the same trend:open-unidirectional freez-ing>closed unidirectional freezing>constant temperature freezing.After 11 freeze-thaw cycles,compared with the open-unidirectional freezing group without stabilizer,the frost heave of the closed unidirectional freezing group and the open-unidirectional freezing group with stabilizer decreased by 38%and 83%,re-spectively.The leaching concentrations of Pb and Cd in the open-unidirectional freezing group with stabi-lizer were 5.62 mg/L and 1.09 mg/L,which were 1.99 and 1.58 times those of the closed unidirectional freezing group,and 5.21 and 2.53 times those of the constant temperature freezing group,exceeding the limits specified in the national soil quality standards.Conclusions Freeze-thaw cycles reduced the content of hydration products and increased internal pore development within the solidified soil,thereby signifi-cantly weakening the immobilization effect of MgO-fly ash on Pb and Cd.The deterioration effect was more pronounced under the open-unidirectional freezing condition.These findings provide references for improv-ing the design of solidification/stabilization processes and evaluating the long-term stability of contaminated soil in shallow groundwater environments of seasonally frozen regions.

Abstract:Objectives To illustrate the characteristics of longitudinal guided wave in resin bolts,the eigen-function expansion method was used to solve the longitudinal guided wave dispersion equations of a resin bolt.Methods The resin anchor bolt was considered as a typical double-layer cylindrical viscoelastic struc-ture.Based on the Hysteretic viscoelastic model,considering continuity boundary conditions,the acoustic field displacements were represented in the Legendre polynomial series form.Then the problem of solving the complex wave control partial differential equation system was transformed into the problem of eigen-value calculation through matrix transformation.The eigenvalue was the wave number,and the eigenvector was the displacement field distribution,the longitudinal guided wave dispersion relationship was estab-lished,and the analytical solution of the transcendental dispersion equation was obtained.Then the group velocity dispersion curve and attenuation curve could be plotted.The correctness of the presented method was verified by comparing the obtained group velocity and attenuation results of a free bolt with those of ex-isting literature.Based on the COMSOL software,the longitudinal guided waves in various resin bolts were simulated to illustrate the influences of resin layer thickness and bond length on the guided wave character-istics.Results The results showed that:(1)The thickness of the resin layer had a significant effect on the longitudinal guided waves.With the increase of layer thickness,the wave packet dispersion and waveform distortion of the recovered signal increased.The group velocity and amplitude ratio of guided waves de-crease with the increase of layer thickness,but the attenuation increased.(2)With the increase of bond length,the group velocity of guided waves in the resin bolt decreased,the amplitude ratio decreased,and the guided wave attenuation increased.Conclusions The group velocity of guided wave was approximately linear with the bond length,and quantitative judgment of the length of the resin bolt bond section can be made through changes in guided wave group velocity.

Abstract:Objectives To investigate the effect of high-temperature history on the compressive strength of desert sand concrete(DSC),compressive strength tests of DSC after exposure to high temperatures were conducted by considering the effects of desert sand replacement rate(DSRR),temperature,heating rate,and resting time.Methods X-ray diffraction(XRD)and scanning electron microscopy(SEM)were em-ployed to analyze the changes in the microstructure and phase composition of DSC after high-temperature exposure.Based on the back-propagation(BP)algorithm,an artificial neural network(ANN)for predict-ing the compressive strength of DSC after high temperature was developed by integrating particle swarm op-timization(PSO)and genetic algorithm(GA).The model was validated using ten-fold cross-validation.Re-sults The results indicated that the compressive strength of DSC decreased with increasing temperature,ac-companied by significant decomposition of hydration products and progressive propagation and interconnec-tion of microcracks.Longer resting time led to higher compressive strength,while higher heating rates ac-celerated the damage of DSC.The compressive strength reached its maximum when the DSRR was 20%.The mean absolute percentage errors(MAPE)of the three predictive models were all within 8%.A higher degree of model optimization resulted in smaller prediction errors.The hybrid PSO-GA neural network model achieved the highest prediction accuracy,with a root mean square error(RMSE)of 1.127 2,MAPE of 3.98%,and a determination coefficient(R2)of 0.987 8 for the 28-day compressive strength.Conclu-sions The proposed method significantly improves the prediction accuracy of the mechanical properties of DSC after exposure to high temperature.

Abstract:Objectives When adjacent foundation pits are excavated simultaneously,the deformations of fi-nite soil between the pits on both sides influence the distribution of earth pressure.A rational analysis and determination of the characteristics of finite soil pressure have become crucial issues in engineering.Meth-ods To characterize the soil pressure of finite soil under the condition of adjacent foundation pit excavation,the deformation patterns of finite soil during simultaneous excavation of adjacent pits and the mechanisms by which excavation affects soil pressure development were analyzed using the discrete element method.By conducting stress analysis on soil elements in different regions,an analysis model for active soil pressure of finite soil during excavation of adjacent foundation pits was constructed,and the characteristics of soil pres-sure under varying retaining wall displacements were evaluated.Results The results show that the displace-ment field and slip mode of finite soil differ from those under unilateral foundation pit excavation.Com-pared with unilateral excavation,the earth pressure on retaining walls under simultaneous excavation of ad-jacent pits is smaller.The difference in earth pressure between the two cases is influenced by the aspect ra-tio of the finite soil and the displacement of the retaining wall,the smaller the aspect ratio,the greater the pressure difference.As the retaining wall displacement increases,the pressure difference first increases and then decreases.When the wall displacement reaches half of the displacement required for the overall active limit state of the soil,the pressure difference reaches its maximum.Conclusions The proposed method can effectively characterize the distribution of earth pressure under simultaneous excavation of adja-cent foundation pits,providing theoretical support for calculating active earth pressure of finite soil under the influence of displacements of retaining walls on both sides.

Abstract:Objectives The dynamic response and anti-interference performance of the permanent magnet synchronous motor(PMSM)control system need to be further enhanced.Methods A double closed-loop pre-dictive control scheme based on grey prediction model and reduced-order Luenberger observer was pro-posed.Firstly,in order to predict the d,q axis reference current of PMSM more accurately through the his-torical current data,the grey prediction model was introduced into the current inner loop to improve the dy-namic current response performance based on double closed-loop MPC system.Secondly,a reduced-order Luenberger observer was designed in the speed outer loop to observe the load torque and make compensa-tion control,which reduced the dynamic response time and the recovery time after interference.Finally,the proposed strategy was verified by simulation and experiment respectively.Results When the motor ad-opted the MPC+DPC scheme,the speed rise time of the PMSM was about 0.3 s when it started no-load;when the load torque of 6 N ⋅ m was abruptly added to the motor,the motor speed dropped,the maximum speed fluctuation was 100 r,the speed recovery time was 0.4 s,and then the A-phase current THD was 27.59%.When the motor adopted the proposed scheme,the no-load start of the PMSM speed rise time was about 0.18 s,when the load of 6 N ⋅ m was suddenly added to the motor,the motor speed dropped,the maximum speed fluctuation was 65 r/min,the speed recovery time was 0.2 s,after stable operation,the A-phase current THD was 19.35%.Conclusions The results showed that the no-load start time of PMSM was shorter when the improved double closed-loop predictive control scheme was adopted in this paper.When the load was suddenly applied,the speed fluctuation was smaller and the speed recovery speed was faster.With less current disturbance,it had faster dynamic response performance,stronger anti-disturbance abil-ity and better current control performance.

Abstract:Objectives The surface deformation during metro operation and maintenance has become one of the most challenging issues for the current urban construction,planning and management departments,se-verely constraining healthy and sustainable urban development.Monitoring surface deformation along the metro corridors in Zhengzhou and characterizing its subsidence patterns and governing laws are of practical significance for mitigating potential risks during operation and maintenance,and for safeguarding public safety.Methods The main urban area of Zhengzhou is adopted as the study area,with 88 Sentinel-1A as-cending orbit images(February 2016-January 2022)utilized.An MT-InSAR deformation inversion frame-work is employed to retrieve the time-series deformation fields and linear deformation-rate fields,and the spatiotemporal evolution of surface deformation within buffer zones along the metro lines is investigated.The subsidence curves for the representative Shamen station were denoised,using a Bayesian estimation algo-rithm grounded in probabilistic modeling.Measurement noise was removed and the subsidence-rate charac-teristics and sinking mechanism of the station were analyzed.Results The results indicate that the signifi-cant subsidence zones are mainly concentrated in the eastern,northwestern,and southwestern regions of the main urban area.Among them,Huiji District in the northwest(Line 2)and Jinshui District(Lines 1 and 5)in the east exhibit the most pronounced subsidence,with maximum rates of 16 mm/a and 12 mm/a re-spectively The Shamen Station,located at the intersection of Lines 2 and 4,exhibits a subsidence-trough apex whose subsidence rate over the initial,active,and recession phases conforms to a logistic time-function curve.The primary cause for the surface double subsidence funnels above Shamen station within re-stricted mining areas is groundwater drainage during metro operation and maintenance.The twin subsidence funnels at the surface observed above the station are primarily attributed to groundwater drainage during metro operation and maintenance.Conclusions The findings elucidate the mechanisms of surface subsid-ence and provide a theoretical basis and technical reference for the prevention and mitigation of surface de-formation hazards in urban metro corridor zones.

Abstract:Objectives The Loess Plateau is an important part of China's ecological security.Understanding the spatiotemporal dynamics of vegetation and its climate controls provides a robust theoretical basis for eco-logical protection and restoration.Methods The kernel-based Normalized Difference Vegetation Index(kNDVI)was employed in this study to characterize vegetation cover across the Loess Plateau of China from 2000 to 2022.Spatialtemporal patterns were examined using trend analysis,stability analysis,and Hurst exponent-based prediction.In addition,meteorological observations were leveraged,and partial-derivative-based attribution was applied to quantify the respective contribution of climate change and anthro-pogenic activities to interannual kNDVI changes.Results showed that:(1)Over the past 23 years,the veg-etation cover increased at a rate of 0.0057/a,and slope-driven spatiotemporal heterogeneity in vegetation cover was significant;(2)The Hurst-based projections indicate that in the mining areas,the vegetation growth shows an upward trendency across 79.04%of the region,while 3.74%exhibits a downward ten-dency.(3)The results of attribution show that the average contributions of precipitation and temperature to kNDVI changes in the Loess Plateau were 0.000 81/a and 0.001 31/a,respectively.Anthropogenic activi-ties dominated,accounting for a 62.33%relative contribution to kNDVI change,compared with 37.67%from climate variability.(4)Land-use dynamics featured expansion of forest area,scaled ecological affores-tation projects and vegetation cover.On the contrary,urbanization exerted an adverse effect on vegetation growth.Conclusions This study provides theoretical and technical support for ecological restoration and en-vironmental quality improvement.

Abstract:Objectives To explore the relationships among the causes of tailings dam failures,examine the evolution paths of different factors,analyze the driving-dependence relationships,identify the factors with high driving force and high dependence,and propose corresponding strategies.Methods The AISM-MICMAC Model was employed to systematically analyze the hierarchical relationships and categorical distri-bution of influencing factors.Results Based on accident case analysis,69 potential factors contributing to tailings dam failures were identified and classified into 10 levels,including direct,intermediate,and root causes.Factors at the bottom of the structure were defined as root causes,while those at the top were di-rect causes.The driving force and dependence values of the factors were calculated,and a driving-dependence diagram was constructed.Conclusions The diagram revealed the hierarchical levels of the fac-tors,their evolutionary relationships,and the mutual transmission of influences.Root causes exhibited high driving force and low dependence,while direct causes showed low driving force and high dependence.The four-quadrant diagram effectively visualized the driving-dependence relationships,helping to identify key factors and propose targeted prevention and control measures.

Abstract:Objectives Floods are a critical factor affecting the safety of tailings dams.Clarifying the risk transmission pathways of floods in tailings dams helps identify key risk factors and optimize preventive mea-sures.Methods Bibliometric analysis and expert judgment were used to select important flood risk indica-tors.The hierarchical structure of these indicators was determined using Interpretative Structural Modeling(ISM).Disaster evolution pathways were further analyzed through Fault Tree Analysis(FTA),and corre-sponding preventive measures were proposed.Results(1)A total of 24 flood risk factors were identified through bibliometric analysis,from which 10 key factors were determined based on average weight values and expert experience.(2)ISM revealed the interrelationships among the 10 factors and flood risks,identi-fying direct,indirect,and fundamental influencing factors.(3)A fault tree model for flood disasters in tailings dams was constructed by integrating ISM with accident cases.Boolean algebraic operations yielded 18 disaster-causing paths and 9 prevention paths.(4)Structural importance analysis indicated that insuffi-cient drainage capacity,high peak flood flow,and shallow initial phreatic line are the most critical events influencing flood risks.Conclusions The proposed methodology,which integrates bibliometric analysis,ISM,and FTA,achieves the fusion of objective indicator screening and system modeling,and provides theoretical support for transforming flood prevention in tailings dams from passive response to active pre-vention.

Abstract:Objectives To address the issue of surrounding rock instability in gob-side entry retaining during thin coal seam mining,a roof cutting and pressure relief technique using coordinated deep and shallow hole blasting was developed.Methods Taking the 11031 working face of Mengjin Coal Mine as the engineer-ing background,the roof caving characteristics of gob-side entry retaining in thin coal seams were analyzed through theoretical research.A blasting technique combining deep and shallow holes was proposed.Numeri-cal simulations were conducted to compare the stress and displacement distributions under three roof-cutting schemes:shallow-hole pre-splitting,deep-hole pre-splitting,and coordinated deep and shallow hole blasting.The effectiveness of the coordinated blasting method was validated.Meanwhile,the parameters of advanced and lagging support systems for the No.2 coal seam were optimized,and an industrial test was carried out in the belt roadway of the 11031 working face.Results The simulation results indicated that the proposed method could promote complete caving of the overlying strata in the goaf,effectively block stress transmission between strata,and improve the stress environment of the roadway roof.Field monitoring con-firmed that coordinated deep and shallow hole blasting,combined with optimized support design,signifi-cantly reduced roadway deformation and ensured the stability of gob-side entry retaining.Conclusions The proposed technique effectively solves the problem of surrounding rock instability in gob-side entry retaining during thin coal seam mining.

Abstract:Objectives The influence of solids mass fraction on the consolidation behavior of unclassified,high-concentration tailings is investigated.Evolutionary patterns of pore water pressure and matric suction are revealed,and optimized engineering control strategies are proposed to enhance the stability of tailings dams.Methods Laboratory experiments were conducted to systematically examine the consolidation dynam-ics of high-concentration tailings with solids mass fractions of 60%～70%.Moisture sensors were used to track the three-stage spatiotemporal evolution of volumetric water content(VWC).Dynamic measurements of pore water pressure and matric suction were analyzed to assess seepage characteristics and consolidation processes across different Cs levels.Based on the experimental data,the coupling between particle-skeleton formation and water migration was examined,and engineering optimization strategies were proposed.Re-sults The solids mass fraction significantly affected the consolidation dynamics.Higher-Cs systems,due to stronger interparticle interactions,formed more stable particle skeletons,reduced seepage efficiency,and prolonged the dissipation time of excess pore water pressure.Pronounced spatial gradients in volumetric wa-ter content were observed,with a 6%difference between the upper and lower layers in the Cs=70%speci-mens.)Pore water pressure dissipation rates correlated positively with mass fraction,while the maximum matrix suction increased non-linearly from 59.12 kPa(Cs=60%)to 254.34 kPa(Cs=70%).The multistage consolidation response revealed the evolution of moisture-migration mechanisms,and the final VWC showed a significant negative correlation with the initial Cs.The solids mass fraction non-linearly regulates the consolidation behavior of high solids tailings by modulating seepage dynamics and unsaturated character-istics.Conclusions This study provides a theoretical basis for parameter optimization of high concentration discharge processes in tailings storage facilities(TSFs).Through the integration of intelligent monitoring systems with dynamic control strategies,the structural performance of the tailings dam can be effectively enhanced,thereby meeting the safety-management requirements of modern TSFs.

Abstract:Objectives To investigate the mining-induced failure characteristics of the floor aquifuge and en-sure safe working face extraction,a study on the failure patterns of the floor aquifuge based on microseis-mic monitoring was conducted.Methods With the 16001 working face in Zhaogu No.1 Mine as the research background,microseismic monitoring and numerical simulation were employed to analyze the failure charac-teristics of the floor aquifuge during coal mining.Results The floor aquifuge exhibited distinct stratified fail-ure characteristics in the vertical direction:the 0～10 m interval beneath the floor was identified as a"full mining-induced damage zone"dominated by advance failure;the 10～15 m interval corresponded to a"par-tial mining-induced damage zone""dominated by delayed failure;and depths beyond 15 m formed a"spo-radic mining-induced damage zone"influenced mainly by geological structures.Kernel density analysis of microseismic energy indicated that the floor failure depth in the 16001 working face ranged from 15 to 20 m,with maximum damage occurring in the central mining area.The key water-resistant stratum was identified as the siltstone underlying the L9 limestone.Numerical simulation results showed good agreement with mi-croseismic monitoring data regarding floor failure depth.Conclusions The findings reveal the mining-induced floor failure patterns in large mining-height working faces above confined aquifers,providing theo-retical support for the prevention and control of mine floor water inrush.

Abstract:Objectives This study investigates the stability of upstream tailings dams in the Poyang Lake re-gion under frequent heavy rainfall and prolonged rainfall conditions,focusing on the evolution of seepage fields and dam stability under different rainfall scenarios.Methods An upstream tailings dam in the Poyang Lake region was selected as a case study.Fluid-solid coupling simulations were conducted using the Seep/W and Slope/W modules of the finite element software GeoStudio.Results Under extreme rainfall condi-tions,rainfall infiltration reduced dam stability,and the rate of decrease in the safety factor was positively correlated with rainfall intensity.At rainfall intensities of 500 mm/d and 700 mm/d,the tailings dam rap-idly reached saturation,with safety factors falling below the minimum allowable value at 36 h and 24 h,re-spectively,indicating instability.Under prolonged rainfall conditions,the safety factor gradually de-creased;However,under moderate(25 mm/d)and heavy rainfall(50 mm/d),the dam remained stable af-ter 70 days of continuous rainfall.Conclusions Under heavy rainfall conditions,increased water content and saturation of surface tailings in certain areas readily induced shallow sliding instability,the main cause of localized stability reduction.Under prolonged rainfall conditions,differences in permeability across tail-ings layers caused localized increases in pore water pressure and unit weight within the dam,potentially triggering deep sliding instability and thereby contributing to overall stability reduction.To quantitatively characterize the rise of the seepage field,an infiltration coefficient was proposed to represent the magnitude and rate of the rise.The findings provide a reference for stability analysis of upstream tailings dams in the Poyang Lake region under complex rainfall conditions.

Abstract:Objectives The study aimed to solve the key problems of task offloading and resource allocation in the Internet of vehicles with imperfect channel,and reduce the computational cost.Methods Combined the imperfect channel characteristics to abstract the basic vehicle-connected task offload environment,jointly optimized the task offload ratio,power selection and server resource allocation,and established a long-term average cost minimization problem model for all users.Using a dynamic offloading optimization scheme based on deep reinforcement learning,and considering the continuity of solution variables,SP-DDPG(deep deterministic policy gradient with importance sampling and prioritized experience replay)algo-rithm was proposed to solve the problem model.Compared with some existing deep reinforcement learning methods,the performance of SP-DDPG algorithm under the influence of a single variable was studied,and two important indicators of average offloading cost and task discard number were calculated respectively.Results Compared with the complete task offloading algorithm F-DDPG and DDQN,the average task offloading cost was reduced by about 36.13%and 44.02%,and the number of dropped tasks was reduced by at least 4.38%and 9.76%respectively.Compared with the partial offloading algorithm DDPG,the aver-age offloading cost and the number of dropped tasks decreased by 13.34%and 3.17%.The experimental re-sults were averaged after multiple runs(tradeoff factor of delay and energy consumption ω=0.5,channel es-timation accuracy ρ=0.95),which had good reliability.Conclusions Compared with some conventional deep reinforcement learning algorithms,the proposed optimized deep deterministic policy gradient algo-rithm SP-DDPG had lower computational cost and better performance in the environment of vehicle network-ing with unstable and complex changes.

Abstract:Objectives To analyze the effects of water saturation,anisotropy,and pore structure on the com-plex electrical resistivity of coal and its dispersion characteristics,an experimental study on the complex re-sistivity anisotropy and dispersion characteristics of coal with different water saturations was carried out.Methods Anthracite samples from Zhaoguer Mine were selected to investigate their electrical properties.The complex impedance magnitude Z(representing actual energy dissipation)and the imaginary component X(representing energy storage capacity within the medium)were measured along different directions and under varying water saturation conditions.Corresponding complex resistivity spectrum were derived and an-isotropy coefficients were employed to quantify the influence of water saturation and porosity on the anisot-ropy behavior of the coal samples.Results The results show that the complex resistivity of water-saturated coal exhibits frequency dispersion i.e.the magnitude varies with frequency.Specifically,the absolute val-ues of Z and X decrease with the increasing water saturation,and the imaginary component X shows a sig-nificant shift.As water saturation increases,the interfacial critical frequency shifts towards higher frequen-cies.The complex resistivity of coal exhibits pronounced anisotropy across different water saturation levels.The anisotropy coefficient increases with increasing water saturation and also rises with higher porosity,a behavior primarily attributed to the pore structure and its spatial distribution of the coal.Conclusions This study demonstrates a close linkage between water saturation,pore structure,and the anisotropy and frequency-dispersion characteristics of complex resistivity in coal.It provides experimental and theoretical basis for leveraging complex electrical properties to evaluate coal-seam pore structure,development state,and mineral composition and it offers practical implications for the prevention and control of coal-mine gas hazards.

Abstract:Objectives In order to optimize the coal loading performance and production efficiency of shearer working in complex coal seam,the floor climbing shearer's spiral drum was studied based on the discrete element method,sensitivity analysis theory,and structural evolution algorithm.Methods The physical model of the spiral drum and the gangue coal rock was jointly established.The Hertz model was used to construct the coupling model between roller and gangue coal rock.Based on the physical characteristics pa-rameters and the movement parameters of the drum and the gangue coal rock,the coal-loading performance of the shearer was simulated and analyzed,and the loading rate of the spiral drum of the climbing floor shearer was obtained by regional statistics.A discrete element coupling model for different geometric param-eters and motion parameters of the drum was established.The data obtained from the simulation of discrete element coupling model was fitted,and the multi-objective design function of spiral drum was obtained based on the multi-objective optimization design weighting algorithm.Based on the stress-strength interfer-ence theory,the state evaluation function of the coal loading performance of the shearer screw drum was constructed.Combined with the sensitivity design theory,the influence law of screw drum design variables on the coal loading performance of shearer was obtained.Using structural evolution algorithm,the optimal solution of shearer spiral drum design variables was obtained.Results The results showed that the coal-loading rate of the optimized spiral drum was increased from 61.35%to 64.17%,the optimal design of spi-ral drum was achieved.The sensitivity of the design variable was reduced and the coal-loading performance of the spiral drum was improved,it showed that the overall performance of the optimized drum loading rate tended to be stable.Conclusions Combining discrete element technology,sensitivity design theory and struc-tural evolution algorithm,an effective technical route for designing spiral drum with efficient cutting perfor-mance under the condition of occurrence of coal seam containing gangue was provided.

Abstract:Objectives It is needed to attenuate the adverse effects caused by unknown actuator nonlineari-ties,actuator faults,and bounded disturbances,and to achieve fast and high-precision tracking of the de-sired trajectory of manipulator.Methods A fixed-time parameter-varying sliding fault tolerant synchronous control(FPS-FTSC)strategy was proposed based on the sum-of-squares(SOS)theory for a class of uncertain manipulator systems.Firstly,a unified mathematical model of actuators with unknown nonlinearity and faults was established.Secondly,a synchronous error control term was introduced to ensure the coordina-tion between the various axes of manipulators,and it was combined with the prescribed performance func-tion(PPF)to complete error transformation.With the parameter-varying terminal sliding framework,it was demonstrated that synchronous error and position tracking error could converge to the range limited by PPF within a fixed time based on Lyapunov stability theory.Then,while solving for the gain of parameter-varying controller,the conditions for the existence of global optimal H∞ disturbance suppression perfor-mance of the system were given.Results In simulation and experiment,the FPS-FTSC strategy enabled both position tracking error and synchronization error to quickly converge to a small neighborhood of zero under ideal conditions without actuator faults and nonlinearity;In the presence of various actuator faults and nonlinearity,the proposed strategy could still achieve fast and stable tracking of the desired trajectory,and had better control performance than existing algorithms.Conclusions Simulation and experimental re-sults showed that the proposed control strategy could achieve good transient and steady-state performance of the system under multiple constraints,demonstrating good robustness and fault tolerance.

Abstract:Objectives Urban hierarchy classification levels is closely related to urban planning and sustain-able development.This study aims to evaluate the applicability of machine learning classification methods for urban hierarchy classification and analyze the robustness of nighttime light remote sensing features.Methods Based on the 2021 NPP-VIIRS(National Polar-orbiting Partnership-Visible Infrared Imaging Radi-ometer)nighttime light remote sensing imagery,12 statistical features were extracted from 297 cities in China.Machine learning methods were employed for urban hierarchy recognition and classification,and the SHAP(Shapley Additive exPlaneations)method was used for the model interpretation and robust feature identification.Results The results show that all machine learning methods achieved AUC values above 0.90 under ROC(Receiver Operating Characteristic)curves,demonstrating excellent classification performance.Among them,random forest exhibited the best performance.with an accuracy of 0.75 and an F1 value of 0.764 6.The recognition ability of machine learning methods varied across different city tiers:The classifi-cation accuracy for third-tier and fourth-tier cities was significantly lower than that of first-tier,second-tier,and fifth-tier cities.Classification accuracy for third-and fourth-tier cities was significantly lower than for first-,second-,and fifth-tier cities.The ensemble model combining XGBoost and random forest achieved an overall accuracy of 0.783 3,with an F1 value of 0.805 1.While feature importance varied across differ-ent models,the robust nighttime light features remained consistent.Conclusions This study demonstrates that machine learning classification methods based on nighttime light remote sensing imagery can effectively identify urban hierarchies.The identification of robust nighttime light feature variables reduces the complex-ity of urban hierarchy classification and improves classification efficiency.This approach provides a scien-tific basis for urban classification.

Abstract:Objectives This study aims to elucidate the correlation mechanism between the bleeding charac-teristics of backfill slurry and mesoscopic water migration,and to reveal the influence of macro-meso struc-tural evolution on the bleeding process.Methods An orthogonal experimental design was conducted to test fluidity,bleeding rate,and settling rate.Range analysis and efficacy coefficient calculations were com-bined with a Matlab-based 3D visualization multi-factor coupling model to determine the optimal mix ratio.Nuclear magnetic resonance(NMR)was used to analyze the mesoscopic water migration characteristics of the optimal slurry at standing times of 5,30,60,90,120,and 180 minutes.Results The optimal mix ra-tio was identified as a cement-tailings ratio of 1:8,a mass concentration of 74%,and a water-reducer dos-age of 1%.The significance order of factors affecting bleeding rate was:mass concentration>cement-tailings ratio>water-reducer dosage.NMR results indicated that in high-solid-concentration backfill slurry,adsorbed water was the dominant form;pore water acted as a dynamic transitional state,with fluctuating peak areas reflecting the balance between adsorbed water release and interfacial re-adsorption;and free wa-ter increased with prolonged standing time.Conclusions The bleeding process of backfill slurry can be di-vided into four distinct stages:induction period,acceleration period,constant period,and stabilization pe-riod.Water migration follows the pathway of adsorbed water→pore water→free water.The migration rate is slowest during the induction period,peaks in the acceleration period as adsorbed water rapidly converts to free water,remains rapid in the constant period,and becomes restrained in the stabilization period,result-ing in a steady bleeding state.This study provides insight into the mechanism linking bleeding characteris-tics to mesoscopic water migration and provides a theoretical basis for optimizing backfill parameters in deep mining.