The Internet of Things(IoT)has orchestrated various domains in numerous applications,contributing significantly to the growth of the smart world,even in regions with low literacy rates,boosting socio-economic developm...The Internet of Things(IoT)has orchestrated various domains in numerous applications,contributing significantly to the growth of the smart world,even in regions with low literacy rates,boosting socio-economic development.This study provides valuable insights into optimizing wireless communication,paving the way for a more connected and productive future in the mining industry.The IoT revolution is advancing across industries,but harsh geometric environments,including open-pit mines,pose unique challenges for reliable communication.The advent of IoT in the mining industry has significantly improved communication for critical operations through the use of Radio Frequency(RF)protocols such as Bluetooth,Wi-Fi,GSM/GPRS,Narrow Band(NB)-IoT,SigFox,ZigBee,and Long Range Wireless Area Network(LoRaWAN).This study addresses the optimization of network implementations by comparing two leading free-spreading IoT-based RF protocols such as ZigBee and LoRaWAN.Intensive field tests are conducted in various opencast mines to investigate coverage potential and signal attenuation.ZigBee is tested in the Tadicherla open-cast coal mine in India.Similarly,LoRaWAN field tests are conducted at one of the associated cement companies(ACC)in the limestone mine in Bargarh,India,covering both Indoor-toOutdoor(I2O)and Outdoor-to-Outdoor(O2O)environments.A robust framework of path-loss models,referred to as Free space,Egli,Okumura-Hata,Cost231-Hata and Ericsson models,combined with key performance metrics,is employed to evaluate the patterns of signal attenuation.Extensive field testing and careful data analysis revealed that the Egli model is the most consistent path-loss model for the ZigBee protocol in an I2O environment,with a coefficient of determination(R^(2))of 0.907,balanced error metrics such as Normalized Root Mean Square Error(NRMSE)of 0.030,Mean Square Error(MSE)of 4.950,Mean Absolute Percentage Error(MAPE)of 0.249 and Scatter Index(SI)of 2.723.In the O2O scenario,the Ericsson model showed superior performance,with the highest R^(2)value of 0.959,supported by strong correlation metrics:NRMSE of 0.026,MSE of 8.685,MAPE of 0.685,Mean Absolute Deviation(MAD)of 20.839 and SI of 2.194.For the LoRaWAN protocol,the Cost-231 model achieved the highest R^(2)value of 0.921 in the I2O scenario,complemented by the lowest metrics:NRMSE of 0.018,MSE of 1.324,MAPE of 0.217,MAD of 9.218 and SI of 1.238.In the O2O environment,the Okumura-Hata model achieved the highest R^(2)value of 0.978,indicating a strong fit with metrics NRMSE of 0.047,MSE of 27.807,MAPE of 27.494,MAD of 37.287 and SI of 3.927.This advancement in reliable communication networks promises to transform the opencast landscape into networked signal attenuation.These results support decision-making for mining needs and ensure reliable communications even in the face of formidable obstacles.展开更多
Despite the long-standing success of waste tailings recycling at shallower lithosphere,heat influx from the stifling environment of deep strata and ground squeezing due to aggravating deposit rheology have posed subst...Despite the long-standing success of waste tailings recycling at shallower lithosphere,heat influx from the stifling environment of deep strata and ground squeezing due to aggravating deposit rheology have posed substantial challenges to traditional mine backfilling.To explore the minefill behavior in difficult geology settings,a new thermo-poroelastic model is developed in this study for characterizing the porepressure evolution in hydrating backfill subjected to coupled thermal perturbation and mechanical deformation.By scrutinizing the undrained pressure responses to a hierarchy of thermo-mechanical loading configurations,we investigated the relative contribution of heat exchange and wall convergence to the macroscopic minefill behavior.The result suggests that the backfill response could exhibit unique rate and path-dependence upon thermal loading due to the competing processes that govern the pressure evolution.Moreover,it shows that while rapid wall convergence would always induce significant pressure,thermal straining via heat exchange might still modulate substantially the pressure distribution when the temperature catalyzes considerable water expansivity.These findings could facilitate understanding of the complex backfill behavior in difficult geology settings,and thus have significant implications for adaptive tailings management to deep mining development.展开更多
Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental con...Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental concept drift,gradually alter the behavior or structure of processes,making their detection and localization a challenging task.Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift,particularly from a control-flow perspective.The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs,with a specific emphasis on the structural evolution of control-flow semantics in processes.We propose DriftXMiner,a control-flow-aware hybrid framework that combines statistical,machine learning,and process model analysis techniques.The approach comprises three key components:(1)Cumulative Drift Scanner that tracks directional statistical deviations to detect early drift signals;(2)a Temporal Clustering and Drift-Aware Forest Ensemble(DAFE)to capture distributional and classification-level changes in process behavior;and(3)Petri net-based process model reconstruction,which enables the precise localization of structural drift using transition deviation metrics and replay fitness scores.Experimental validation on the BPI Challenge 2017 event log demonstrates that DriftXMiner effectively identifies and localizes gradual and incremental process drift over time.The framework achieves a detection accuracy of 92.5%,a localization precision of 90.3%,and an F1-score of 0.91,outperforming competitive baselines such as CUSUM+Histograms and ADWIN+Alpha Miner.Visual analyses further confirm that identified drift points align with transitions in control-flow models and behavioral cluster structures.DriftXMiner offers a novel and interpretable solution for incremental concept drift detection and localization in dynamic,process-aware systems.By integrating statistical signal accumulation,temporal behavior profiling,and structural process mining,the framework enables finegrained drift explanation and supports adaptive process intelligence in evolving environments.Its modular architecture supports extension to streaming data and real-time monitoring contexts.展开更多
The residual subsidence caused by underground mining in mountain area has a long subsidence duration time and great potential harm,which seriously threatens the safety of people's production and life in the mining...The residual subsidence caused by underground mining in mountain area has a long subsidence duration time and great potential harm,which seriously threatens the safety of people's production and life in the mining area.Therefore,it is necessary to use appropriate monitoring methods and mathematical models to effectively monitor and predict the residual subsidence caused by underground mining.Compared with traditional level survey and InSAR(Interferometric Synthetic Aperture Radar)technology,GNSS(Global Navigation Satellite System)online monitoring technology has the advantages of long-term monitoring,high precision and more flexible monitoring methods.The empirical equation method of residual subsidence in mining subsidence is effectively combined with the rock creep equation,which can not only describe the residual subsidence process from the mechanism,but also predict the residual subsidence.Therefore,based on GNSS online monitoring technology,combined with the mining subsidence model of mountain area and adding the correlation coefficient of the compaction degree of caving broken rock and the Kelvin model of rock mechanics,this paper constructs the residual subsidence time series model of arbitrary point on the ground in mountain area.Through the example,the predicted results of the model in the inversion parameter phase and the dynamic prediction phase are compared with the measured data sequence.The results show that the model can carry out effective numerical calculation according to the GNSS monitoring data of any point on the ground,and the model prediction effect is good,which provides a new method for the prediction of residual subsidence in mountain mining.展开更多
This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfac...This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfaction. It addresses a significant research gap in understanding metro passengers’ dynamics across cultural and geographical contexts. It employs questionnaires, field observations, and advanced data analysis techniques like association rule mining and neural network modeling. Key findings include a correlation between rainy weather, shorter waiting times, and higher arrival volumes. Neural network models showed high predictive accuracy, with waiting time, metro satisfaction, and weather being significant factors in Lagos Light Rail Blue Line Metro. In contrast, arrival patterns, weather, and time of day were more influential in Wuhan Metro Line 5. Results suggest that improving metro satisfaction and reducing waiting times could increase arrival volumes in Lagos Metro while adjusting schedules for weather and peak times could optimize flow in Wuhan Metro. These insights are valuable for transportation planning, passenger arrival volume management, and enhancing user experiences, potentially benefiting urban transportation sustainability and development goals.展开更多
Investigating the combined effects of mining damage and creep damage on slope stability is crucial,as it can comprehensively reveal the non-linear deformation characteristics of rock under their joint influence.This s...Investigating the combined effects of mining damage and creep damage on slope stability is crucial,as it can comprehensively reveal the non-linear deformation characteristics of rock under their joint influence.This study develops a fractional-order nonlinear creep constitutive model that incorporates the double damage effect and implements a non-linear creep subroutine for soft rock using the threedimensional finite difference method on the FLAC3D platform.Comparative analysis of the theoretical,numerical,and experimental results reveals that the fractional-order constitutive model,which incorporates the double damage effect,accurately reflects the distinct deformation stages of green mudstone during creep failure and effectively captures the non-linear deformation in the accelerated creep phase.The numerical results show a fitting accuracy exceeding 97%with the creep test curves,significantly outperforming the 61%accuracy of traditional creep models.展开更多
Gas content serves as a critical indicator for assessing the resource potential of deep coal mines and forecasting coal mine gas outburst risks.However,existing sampling technologies face challenges in maintaining the...Gas content serves as a critical indicator for assessing the resource potential of deep coal mines and forecasting coal mine gas outburst risks.However,existing sampling technologies face challenges in maintaining the integrity of gas content within samples and are often constrained by estimation errors inherent in empirical formulas,which results in inaccurate gas content measurements.This study introduces a lightweight,in-situ pressure-and gas-preserved corer designed to collect coal samples under the pressure conditions at the sampling point,effectively preventing gas loss during transfer and significantly improving measurement accuracy.Additionally,a gas migration model for deep coal mines was developed to elucidate gas migration characteristics under pressure-preserved coring conditions.The model offers valuable insights for optimizing coring parameters,demonstrating that both minimizing the coring hole diameter and reducing the pressure difference between the coring-point pressure and the original pore pressure can effectively improve the precision of gas content measurements.Coring tests conducted at an experimental base validated the performance of the corer and its effectiveness in sample collection.Furthermore,successful horizontal coring tests conducted in an underground coal mine roadway demonstrated that the measured gas content using pressure-preserved coring was 34%higher than that obtained through open sampling methods.展开更多
According to the particularity of the open pit, the main influencing factors of mining quantity about mineral resources have been summarized systematically in life cycle and the structured hierarchical relation of its...According to the particularity of the open pit, the main influencing factors of mining quantity about mineral resources have been summarized systematically in life cycle and the structured hierarchical relation of its influencing factors has been constructed. In the light of the production process of open pit, the functional relationships between investment, mining cost and mining quantity have been defined based on the process of mining and loading so that the relation of the life cycle cost and mining quantity can be set up. And what’s more, in order to obtain the maximum economic profit of mining enterprises in life cycle, the planning model of mining quantity has been established based on the life cycle cost. The rational distribution of mining quantity will have been found on the condition of obtaining optimal solution about the planning model so as to determine scientifically the production scale of mining enterprises from the point of view of the sustainable development.展开更多
In mining industries no mines are identical and each mine has its own unique set of mining conditions. In order to study thecondition of mines for efficiency, safety and economy reasons, a fuzzy model is presented bas...In mining industries no mines are identical and each mine has its own unique set of mining conditions. In order to study thecondition of mines for efficiency, safety and economy reasons, a fuzzy model is presented based on fuzzy evaluation. Relevant data fromfive mines were collected and the model was used to evaluate the mining condition of these mines. The evaluation results are in conformity with the real situation.展开更多
Shear strain energy is a pivotal physical quantity in the occurrence of earthquakes and rockbursts during deep mining operations.This research is focused on understanding the changes in shear strain energy in the cont...Shear strain energy is a pivotal physical quantity in the occurrence of earthquakes and rockbursts during deep mining operations.This research is focused on understanding the changes in shear strain energy in the context of retreating longwall mining,which is essential for the optimized design and mitigation of rockbursts and seismic events.Through the application of innovative analytical models,this study expands its analytical range to include the variations in shear strain energy caused by fault coseismic slip.An integrated methodology is utilized,taking into account the changes in coseismic and fault friction parameters as well as enhancements in mining-induced stress and existing background stresses.Our numerical investigation highlights the significance of mining location and fault characteristics as key determinants of shear strain energy modifications.The analysis demonstrates significant spatial variability in shear strain energy,especially noting that fault slip near the mining face greatly increases the likelihood of rockburst.This finding emphasizes the need to integrate fault coseismic slip dynamics into the triggering factors of rock(coal)bursts,thus broadening the theoretical foundation for addressing geological hazards in deep mining operations.The results are further corroborated by observational data from the vicinity of the F16 fault zone,introducing the concept of mining-induced fault coseismic slip as an essential element in the theoretical framework for understanding rockburst triggers.展开更多
Topic modeling is a fundamental technique of content analysis in natural language processing,widely applied in domains such as social sciences and finance.In the era of digital communication,social scientists increasi...Topic modeling is a fundamental technique of content analysis in natural language processing,widely applied in domains such as social sciences and finance.In the era of digital communication,social scientists increasingly rely on large-scale social media data to explore public discourse,collective behavior,and emerging social concerns.However,traditional models like Latent Dirichlet Allocation(LDA)and neural topic models like BERTopic struggle to capture deep semantic structures in short-text datasets,especially in complex non-English languages like Chinese.This paper presents Generative Language Model Topic(GLMTopic)a novel hybrid topic modeling framework leveraging the capabilities of large language models,designed to support social science research by uncovering coherent and interpretable themes from Chinese social media platforms.GLMTopic integrates Adaptive Community-enhanced Graph Embedding for advanced semantic representation,Uniform Manifold Approximation and Projection-based(UMAP-based)dimensionality reduction,Hierarchical Density-Based Spatial Clustering of Applications with Noise(HDBSCAN)clustering,and large language model-powered(LLM-powered)representation tuning to generate more contextually relevant and interpretable topics.By reducing dependence on extensive text preprocessing and human expert intervention in post-analysis topic label annotation,GLMTopic facilitates a fully automated and user-friendly topic extraction process.Experimental evaluations on a social media dataset sourced from Weibo demonstrate that GLMTopic outperforms Latent Dirichlet Allocation(LDA)and BERTopic in coherence score and usability with automated interpretation,providing a more scalable and semantically accurate solution for Chinese topic modeling.Future research will explore optimizing computational efficiency,integrating knowledge graphs and sentiment analysis for more complicated workflows,and extending the framework for real-time and multilingual topic modeling.展开更多
Security attributes are the premise and foundation for implementing Attribute-Based Access Control(ABAC)mechanisms.However,when dealing with massive volumes of unstructured text big data resources,the current attribut...Security attributes are the premise and foundation for implementing Attribute-Based Access Control(ABAC)mechanisms.However,when dealing with massive volumes of unstructured text big data resources,the current attribute management methods based on manual extraction face several issues,such as high costs for attribute extraction,long processing times,unstable accuracy,and poor scalability.To address these problems,this paper proposes an attribute mining technology for access control institutions based on hybrid capsule networks.This technology leverages transfer learning ideas,utilizing Bidirectional Encoder Representations from Transformers(BERT)pre-trained language models to achieve vectorization of unstructured text data resources.Furthermore,we have designed a novel end-to-end parallel hybrid network structure,where the parallel networks handle global and local information features of the text that they excel at,respectively.By employing techniques such as attention mechanisms,capsule networks,and dynamic routing,effective mining of security attributes for access control resources has been achieved.Finally,we evaluated the performance level of the proposed attribute mining method for access control institutions through experiments on the medical referral text resource dataset.The experimental results show that,compared with baseline algorithms,our method adopts a parallel network structure that can better balance global and local feature information,resulting in improved overall performance.Specifically,it achieves a comprehensive performance enhancement of 2.06%to 8.18%in the F1 score metric.Therefore,this technology can effectively provide attribute support for access control of unstructured text big data resources.展开更多
To investigate the fracture propagation characteristics and failure mechanism of anti-dip rock slope induced by underground mining,the Jiguanling landslide in Wulong,Chongqing,China is taken as the prototype,and physi...To investigate the fracture propagation characteristics and failure mechanism of anti-dip rock slope induced by underground mining,the Jiguanling landslide in Wulong,Chongqing,China is taken as the prototype,and physical model test is utilized to study the fracture evolution process,deformation characteristics and failure mechanism of anti-dip rock slope.In this study,the digital image correlation(DIC)technique and pressure acquisition system are combined to analyze the displacement and stress field of rock slope during underground mining stages.The results show that the anti-dip rock slope experiences four stages during underground coal mining:tensile fracture propagation in upper toppling zone,shallow damage in the lower shear zone,coal seam roof caving,failure of the whole slope.There is a phenomenon of local tensile and compressive stress conversion in upper toppling zone after roof caving.The appearance of coal seam roof caving increases the compressive area and pressure of the shear zone,leading to the failure of the shear blocks at the front edge,and ultimately causing failure of the whole slope.Mining with retained coal pillar before shallow failure in the shear zone can effectively block the impact of lower mining on the upper toppling zone,achieve a 16%contraction in toppling zone,and improve the stability of the slope.The failure mode of slope can be summarized as shear–slip–toppling collapse failure.This paper improves the understanding on the failure mechanism of anti-dip rock slope caused by underground mining.展开更多
Cemented tailings backfill(CTB)is a crucial support material for ensuring the long-term stability of underground goafs.A comprehensive understanding of its compressive mechanical behavior is essential for improving en...Cemented tailings backfill(CTB)is a crucial support material for ensuring the long-term stability of underground goafs.A comprehensive understanding of its compressive mechanical behavior is essential for improving engineering safety.Although extensive studies have been conducted on the uniaxial compressive properties of CTB,damage constitutive models that effectively capture its damage evolution process remain underdeveloped,and its failure mechanisms are not yet fully clarified.To address these gaps,this study conducted systematic uniaxial compression tests on CTB specimens prepared with varying cement-tailings ratios.The results revealed distinct compaction and softening phases in the stress−strain curves.A lower cement-tailings ratio significantly reduced the strength and deformation resistance of CTB,along with a decrease in elastic energy accumulation at peak stress and dissipation energy in the post peak stage.Based on these findings,a modified damage constitutive model was developed by introducing a correction factor,enabling accurate simulation of the entire uniaxial compression process of CTB with different cement-tailings ratios.Comparative analysis with classical constitutive models validated the proposed model’s accuracy and applicability in describing the compressive behavior of CTB.Furthermore,particle size distribution and acoustic emission tests were employed to investigate the influence of cement-tailings ratio on failure mechanisms.The results indicated that a lower cement-tailings ratio leads to coarser particle sizes,which intensify shear-related acoustic emission signals and ultimately result in more pronounced macroscopic shear failure.This study provides theoretical support and practical guidance for the optimal design of CTB mix ratios.展开更多
Belt conveyors are extensively utilized in mining and power industries.In a typical coal mine conveyor system,coal is transported over distances exceeding 2 km,involving more than 20000 idlers,which far exceeds a reas...Belt conveyors are extensively utilized in mining and power industries.In a typical coal mine conveyor system,coal is transported over distances exceeding 2 km,involving more than 20000 idlers,which far exceeds a reasonable manual inspection capacity.Given that idlers typically have a lifespan of 1-2 years,there is an urgent need for a rapid,cost-effective,and intelligent safety monitoring system.However,current embedded systems face prohibitive replacement costs,while conventional monitoring technologies suffer from inefficiency at low rotational speeds and lack systematic structural optimization frameworks for diverse idler types and parameters.To address these challenges,this paper introduces an integrated,on-site detachable self-powered idler condition monitoring system(ICMS).This system combines energy harvesting based on the magnetic modulation technology with wireless condition monitoring capabilities.Specifically,it develops a data-driven model integrating convolutional neural networks(CNNs) with genetic algorithms(GAs).The conventional testing results show that the data-driven model not only significantly accelerates the parameter response time,but also achieves a prediction accuracy of 92.95%.The in-situ experiments conducted in coal mines demonstrate the system's reliability and monitoring functionality under both no-load and fullload conditions.This research provides an innovative self-powered condition monitoring solution and develops an efficient data-driven model,offering feasible online monitoring approaches for smart mine construction.展开更多
In the underhand cut-and-fill mining method,a sill mat(i.e.an artificial horizontal pillar)constructed by cemented backfill is essential to prevent mine workers from being directly exposed under problematic rock roofs...In the underhand cut-and-fill mining method,a sill mat(i.e.an artificial horizontal pillar)constructed by cemented backfill is essential to prevent mine workers from being directly exposed under problematic rock roofs.A critical issue is to determine the minimum required strength of the sill mat to ensure a safe and cost-effective design.Until now,Mitchell’s analytical solution is the only available option,considering two stiff and immobile rock walls.Unavoidable rock wall closure associated with stope excavation below the sill mat was neglected.This,along with other undefined parameters,explains why Mitchell’s solution is rarely used in sill mat design.A new analytical solution for determining the minimum required strength of the sill mat accounting for wall closure is necessary.In this study,a closed-form analytical solution for estimating rock wall closure generated by stope excavation below a sill mat is developed by using Salamon’s and Flamant’s models.The proposed analytical solution does not contain any coefficients of correction or calibration.Despite several assumptions(or somewhat of oversimplifications)necessary to render a simple analytical solution possible,good agreements are obtained between the rock wall closures predicted by applying the proposed analytical solution and those obtained numerically with FLAC3D for many cases with arbitrarily chosen geometrical and material parameters.The proposed analytical solution is therefore validated and can be used to evaluate the rock wall closure generated by stope excavation below a sill mat.展开更多
Gas storage in abandoned mines is one way to reuse waste space resources.The surrounding rock of gas storage reservoirs in underground roadways undergoes damage and deformation under the cyclic loading of gas charging...Gas storage in abandoned mines is one way to reuse waste space resources.The surrounding rock of gas storage reservoirs in underground roadways undergoes damage and deformation under the cyclic loading of gas charging and discharging,which can pose a risk to the safety of the reservoirs.This study establishes a true triaxial numerical model of rock mass with the discrete element method(DEM)and explores the crack evolution of surrounding rock of underground gas storage during cyclic loading and unloading.Also,a damage evolution model in numerical analysis considering residual deformation is developed to explain the experimental results.As was revealed,cyclic loading and unloading resulted in fatigue damage in the specimen and caused strength deterioration of the specimen.During the loading process,the uniformly distributed force chains of the rock mass redistributed,evolving gradually to mostly transverse force chains.This contributed to the appearance of blank areas in the force chains when through cracks appear.The ratio of tensile cracks to shear cracks gradually decreases and finally stabilizes at 7:1.The damage evolution model considering residual strain can be mutually verified with the numerical simulation results.Based on the DEM model,it was found that there was a certain threshold of confining pressure.When the confining pressure exceeded 30 MPa,the deformation to ductility of sandstone samples began to accelerate,with a greater residual strength.This study provides a theoretical basis for analyzing the long-term mechanical behavior of surrounding rock of gas storage in abandoned mines.展开更多
This paper dwells on regression models of cash-cost and country-benefit developed to enable accounting for the cumulative impact of the determinant parameters in the prediction of cash-costs and country-benefits of go...This paper dwells on regression models of cash-cost and country-benefit developed to enable accounting for the cumulative impact of the determinant parameters in the prediction of cash-costs and country-benefits of gold mining opportunities in the justification of taxation regimes and selection of investment targets worldwide. The data used in the generation of regression models include the total cash-cost and country-benefit per ounce vs the parameters of rock-mass (type of ore body, its dip angle, strike length and thickness), mine-design (rate of gold production, type of mine, depth of mine, gold price and age of mine) and country parameters (the Fraser Institute parameters: taxation regime, infrastructure, environmental regime, political stability, labor regulations and security) were generated from 160 gold mines in the top 20 gold rich countries for a period of 7 years from 2002 to 2008. The regression models show that the determinants account for 71% and 55% of the determinants of cash-cost and country-benefit respectively. Depending on the availability of data, the regression models generated in this study could be enhanced by adding into the parameters used in the regression analysis, the unaccounted for mine and country parameters. Also, Depending on the availability of data, the Regression models generated in this study could be enhanced further by replacing the parameters of Fraser Institute ranking used in the regression analysis with the actual parameters of country effect on cash-cost and country-benefit of the gold produced. Nevertheless, the regression models generated in this study could be used to predict the cash-costs and country-benefits of gold mining opportunities in the justification of taxation regimes and selection of investment targets worldwide.展开更多
文摘The Internet of Things(IoT)has orchestrated various domains in numerous applications,contributing significantly to the growth of the smart world,even in regions with low literacy rates,boosting socio-economic development.This study provides valuable insights into optimizing wireless communication,paving the way for a more connected and productive future in the mining industry.The IoT revolution is advancing across industries,but harsh geometric environments,including open-pit mines,pose unique challenges for reliable communication.The advent of IoT in the mining industry has significantly improved communication for critical operations through the use of Radio Frequency(RF)protocols such as Bluetooth,Wi-Fi,GSM/GPRS,Narrow Band(NB)-IoT,SigFox,ZigBee,and Long Range Wireless Area Network(LoRaWAN).This study addresses the optimization of network implementations by comparing two leading free-spreading IoT-based RF protocols such as ZigBee and LoRaWAN.Intensive field tests are conducted in various opencast mines to investigate coverage potential and signal attenuation.ZigBee is tested in the Tadicherla open-cast coal mine in India.Similarly,LoRaWAN field tests are conducted at one of the associated cement companies(ACC)in the limestone mine in Bargarh,India,covering both Indoor-toOutdoor(I2O)and Outdoor-to-Outdoor(O2O)environments.A robust framework of path-loss models,referred to as Free space,Egli,Okumura-Hata,Cost231-Hata and Ericsson models,combined with key performance metrics,is employed to evaluate the patterns of signal attenuation.Extensive field testing and careful data analysis revealed that the Egli model is the most consistent path-loss model for the ZigBee protocol in an I2O environment,with a coefficient of determination(R^(2))of 0.907,balanced error metrics such as Normalized Root Mean Square Error(NRMSE)of 0.030,Mean Square Error(MSE)of 4.950,Mean Absolute Percentage Error(MAPE)of 0.249 and Scatter Index(SI)of 2.723.In the O2O scenario,the Ericsson model showed superior performance,with the highest R^(2)value of 0.959,supported by strong correlation metrics:NRMSE of 0.026,MSE of 8.685,MAPE of 0.685,Mean Absolute Deviation(MAD)of 20.839 and SI of 2.194.For the LoRaWAN protocol,the Cost-231 model achieved the highest R^(2)value of 0.921 in the I2O scenario,complemented by the lowest metrics:NRMSE of 0.018,MSE of 1.324,MAPE of 0.217,MAD of 9.218 and SI of 1.238.In the O2O environment,the Okumura-Hata model achieved the highest R^(2)value of 0.978,indicating a strong fit with metrics NRMSE of 0.047,MSE of 27.807,MAPE of 27.494,MAD of 37.287 and SI of 3.927.This advancement in reliable communication networks promises to transform the opencast landscape into networked signal attenuation.These results support decision-making for mining needs and ensure reliable communications even in the face of formidable obstacles.
基金jointly supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(Grant No.2022D01E32)Opening Fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(Chengdu University of Technology)(Grant No.SKLGP 2023K012)the National Natural Science Foundation of China(Grant No.U20A20266).
文摘Despite the long-standing success of waste tailings recycling at shallower lithosphere,heat influx from the stifling environment of deep strata and ground squeezing due to aggravating deposit rheology have posed substantial challenges to traditional mine backfilling.To explore the minefill behavior in difficult geology settings,a new thermo-poroelastic model is developed in this study for characterizing the porepressure evolution in hydrating backfill subjected to coupled thermal perturbation and mechanical deformation.By scrutinizing the undrained pressure responses to a hierarchy of thermo-mechanical loading configurations,we investigated the relative contribution of heat exchange and wall convergence to the macroscopic minefill behavior.The result suggests that the backfill response could exhibit unique rate and path-dependence upon thermal loading due to the competing processes that govern the pressure evolution.Moreover,it shows that while rapid wall convergence would always induce significant pressure,thermal straining via heat exchange might still modulate substantially the pressure distribution when the temperature catalyzes considerable water expansivity.These findings could facilitate understanding of the complex backfill behavior in difficult geology settings,and thus have significant implications for adaptive tailings management to deep mining development.
文摘Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental concept drift,gradually alter the behavior or structure of processes,making their detection and localization a challenging task.Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift,particularly from a control-flow perspective.The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs,with a specific emphasis on the structural evolution of control-flow semantics in processes.We propose DriftXMiner,a control-flow-aware hybrid framework that combines statistical,machine learning,and process model analysis techniques.The approach comprises three key components:(1)Cumulative Drift Scanner that tracks directional statistical deviations to detect early drift signals;(2)a Temporal Clustering and Drift-Aware Forest Ensemble(DAFE)to capture distributional and classification-level changes in process behavior;and(3)Petri net-based process model reconstruction,which enables the precise localization of structural drift using transition deviation metrics and replay fitness scores.Experimental validation on the BPI Challenge 2017 event log demonstrates that DriftXMiner effectively identifies and localizes gradual and incremental process drift over time.The framework achieves a detection accuracy of 92.5%,a localization precision of 90.3%,and an F1-score of 0.91,outperforming competitive baselines such as CUSUM+Histograms and ADWIN+Alpha Miner.Visual analyses further confirm that identified drift points align with transitions in control-flow models and behavioral cluster structures.DriftXMiner offers a novel and interpretable solution for incremental concept drift detection and localization in dynamic,process-aware systems.By integrating statistical signal accumulation,temporal behavior profiling,and structural process mining,the framework enables finegrained drift explanation and supports adaptive process intelligence in evolving environments.Its modular architecture supports extension to streaming data and real-time monitoring contexts.
基金supported by the Natural Science Foundation of Shanxi Province,China(202203021211153)National Natural Science Foundation of China(51704205).
文摘The residual subsidence caused by underground mining in mountain area has a long subsidence duration time and great potential harm,which seriously threatens the safety of people's production and life in the mining area.Therefore,it is necessary to use appropriate monitoring methods and mathematical models to effectively monitor and predict the residual subsidence caused by underground mining.Compared with traditional level survey and InSAR(Interferometric Synthetic Aperture Radar)technology,GNSS(Global Navigation Satellite System)online monitoring technology has the advantages of long-term monitoring,high precision and more flexible monitoring methods.The empirical equation method of residual subsidence in mining subsidence is effectively combined with the rock creep equation,which can not only describe the residual subsidence process from the mechanism,but also predict the residual subsidence.Therefore,based on GNSS online monitoring technology,combined with the mining subsidence model of mountain area and adding the correlation coefficient of the compaction degree of caving broken rock and the Kelvin model of rock mechanics,this paper constructs the residual subsidence time series model of arbitrary point on the ground in mountain area.Through the example,the predicted results of the model in the inversion parameter phase and the dynamic prediction phase are compared with the measured data sequence.The results show that the model can carry out effective numerical calculation according to the GNSS monitoring data of any point on the ground,and the model prediction effect is good,which provides a new method for the prediction of residual subsidence in mountain mining.
文摘This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfaction. It addresses a significant research gap in understanding metro passengers’ dynamics across cultural and geographical contexts. It employs questionnaires, field observations, and advanced data analysis techniques like association rule mining and neural network modeling. Key findings include a correlation between rainy weather, shorter waiting times, and higher arrival volumes. Neural network models showed high predictive accuracy, with waiting time, metro satisfaction, and weather being significant factors in Lagos Light Rail Blue Line Metro. In contrast, arrival patterns, weather, and time of day were more influential in Wuhan Metro Line 5. Results suggest that improving metro satisfaction and reducing waiting times could increase arrival volumes in Lagos Metro while adjusting schedules for weather and peak times could optimize flow in Wuhan Metro. These insights are valuable for transportation planning, passenger arrival volume management, and enhancing user experiences, potentially benefiting urban transportation sustainability and development goals.
基金support from the National Natural Science Foundation of China(No.52308316)the Scientific Research Foundation of Weifang University(Grant No.2024BS42)+2 种基金China Postdoctoral Science Foundation(No.2022M721885)the Key Laboratory of Rock Mechanics and Geohazards of Zhejiang Province(No.ZJRMG-2022-01)supported by Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering,Institute of Rock and Soil Mechanics,Chinese Academy of Sciences(NO.SKLGME023017).
文摘Investigating the combined effects of mining damage and creep damage on slope stability is crucial,as it can comprehensively reveal the non-linear deformation characteristics of rock under their joint influence.This study develops a fractional-order nonlinear creep constitutive model that incorporates the double damage effect and implements a non-linear creep subroutine for soft rock using the threedimensional finite difference method on the FLAC3D platform.Comparative analysis of the theoretical,numerical,and experimental results reveals that the fractional-order constitutive model,which incorporates the double damage effect,accurately reflects the distinct deformation stages of green mudstone during creep failure and effectively captures the non-linear deformation in the accelerated creep phase.The numerical results show a fitting accuracy exceeding 97%with the creep test curves,significantly outperforming the 61%accuracy of traditional creep models.
基金supported by the National Natural Science Foundation of China(Nos.51827901,42477191,and 52304033)the Fundamental Research Funds for the Central Universities(No.YJ202449)+1 种基金the Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering,Institute of Rock and Soil Mechanics,Chinese Academy of Sciences(No.SKLGME022009)the China Postdoctoral Science Foundation(No.2023M742446).
文摘Gas content serves as a critical indicator for assessing the resource potential of deep coal mines and forecasting coal mine gas outburst risks.However,existing sampling technologies face challenges in maintaining the integrity of gas content within samples and are often constrained by estimation errors inherent in empirical formulas,which results in inaccurate gas content measurements.This study introduces a lightweight,in-situ pressure-and gas-preserved corer designed to collect coal samples under the pressure conditions at the sampling point,effectively preventing gas loss during transfer and significantly improving measurement accuracy.Additionally,a gas migration model for deep coal mines was developed to elucidate gas migration characteristics under pressure-preserved coring conditions.The model offers valuable insights for optimizing coring parameters,demonstrating that both minimizing the coring hole diameter and reducing the pressure difference between the coring-point pressure and the original pore pressure can effectively improve the precision of gas content measurements.Coring tests conducted at an experimental base validated the performance of the corer and its effectiveness in sample collection.Furthermore,successful horizontal coring tests conducted in an underground coal mine roadway demonstrated that the measured gas content using pressure-preserved coring was 34%higher than that obtained through open sampling methods.
文摘According to the particularity of the open pit, the main influencing factors of mining quantity about mineral resources have been summarized systematically in life cycle and the structured hierarchical relation of its influencing factors has been constructed. In the light of the production process of open pit, the functional relationships between investment, mining cost and mining quantity have been defined based on the process of mining and loading so that the relation of the life cycle cost and mining quantity can be set up. And what’s more, in order to obtain the maximum economic profit of mining enterprises in life cycle, the planning model of mining quantity has been established based on the life cycle cost. The rational distribution of mining quantity will have been found on the condition of obtaining optimal solution about the planning model so as to determine scientifically the production scale of mining enterprises from the point of view of the sustainable development.
文摘In mining industries no mines are identical and each mine has its own unique set of mining conditions. In order to study thecondition of mines for efficiency, safety and economy reasons, a fuzzy model is presented based on fuzzy evaluation. Relevant data fromfive mines were collected and the model was used to evaluate the mining condition of these mines. The evaluation results are in conformity with the real situation.
文摘Shear strain energy is a pivotal physical quantity in the occurrence of earthquakes and rockbursts during deep mining operations.This research is focused on understanding the changes in shear strain energy in the context of retreating longwall mining,which is essential for the optimized design and mitigation of rockbursts and seismic events.Through the application of innovative analytical models,this study expands its analytical range to include the variations in shear strain energy caused by fault coseismic slip.An integrated methodology is utilized,taking into account the changes in coseismic and fault friction parameters as well as enhancements in mining-induced stress and existing background stresses.Our numerical investigation highlights the significance of mining location and fault characteristics as key determinants of shear strain energy modifications.The analysis demonstrates significant spatial variability in shear strain energy,especially noting that fault slip near the mining face greatly increases the likelihood of rockburst.This finding emphasizes the need to integrate fault coseismic slip dynamics into the triggering factors of rock(coal)bursts,thus broadening the theoretical foundation for addressing geological hazards in deep mining operations.The results are further corroborated by observational data from the vicinity of the F16 fault zone,introducing the concept of mining-induced fault coseismic slip as an essential element in the theoretical framework for understanding rockburst triggers.
基金funded by the Natural Science Foundation of Fujian Province,China,grant No.2022J05291.
文摘Topic modeling is a fundamental technique of content analysis in natural language processing,widely applied in domains such as social sciences and finance.In the era of digital communication,social scientists increasingly rely on large-scale social media data to explore public discourse,collective behavior,and emerging social concerns.However,traditional models like Latent Dirichlet Allocation(LDA)and neural topic models like BERTopic struggle to capture deep semantic structures in short-text datasets,especially in complex non-English languages like Chinese.This paper presents Generative Language Model Topic(GLMTopic)a novel hybrid topic modeling framework leveraging the capabilities of large language models,designed to support social science research by uncovering coherent and interpretable themes from Chinese social media platforms.GLMTopic integrates Adaptive Community-enhanced Graph Embedding for advanced semantic representation,Uniform Manifold Approximation and Projection-based(UMAP-based)dimensionality reduction,Hierarchical Density-Based Spatial Clustering of Applications with Noise(HDBSCAN)clustering,and large language model-powered(LLM-powered)representation tuning to generate more contextually relevant and interpretable topics.By reducing dependence on extensive text preprocessing and human expert intervention in post-analysis topic label annotation,GLMTopic facilitates a fully automated and user-friendly topic extraction process.Experimental evaluations on a social media dataset sourced from Weibo demonstrate that GLMTopic outperforms Latent Dirichlet Allocation(LDA)and BERTopic in coherence score and usability with automated interpretation,providing a more scalable and semantically accurate solution for Chinese topic modeling.Future research will explore optimizing computational efficiency,integrating knowledge graphs and sentiment analysis for more complicated workflows,and extending the framework for real-time and multilingual topic modeling.
基金supported by National Natural Science Foundation of China(No.62102449).
文摘Security attributes are the premise and foundation for implementing Attribute-Based Access Control(ABAC)mechanisms.However,when dealing with massive volumes of unstructured text big data resources,the current attribute management methods based on manual extraction face several issues,such as high costs for attribute extraction,long processing times,unstable accuracy,and poor scalability.To address these problems,this paper proposes an attribute mining technology for access control institutions based on hybrid capsule networks.This technology leverages transfer learning ideas,utilizing Bidirectional Encoder Representations from Transformers(BERT)pre-trained language models to achieve vectorization of unstructured text data resources.Furthermore,we have designed a novel end-to-end parallel hybrid network structure,where the parallel networks handle global and local information features of the text that they excel at,respectively.By employing techniques such as attention mechanisms,capsule networks,and dynamic routing,effective mining of security attributes for access control resources has been achieved.Finally,we evaluated the performance level of the proposed attribute mining method for access control institutions through experiments on the medical referral text resource dataset.The experimental results show that,compared with baseline algorithms,our method adopts a parallel network structure that can better balance global and local feature information,resulting in improved overall performance.Specifically,it achieves a comprehensive performance enhancement of 2.06%to 8.18%in the F1 score metric.Therefore,this technology can effectively provide attribute support for access control of unstructured text big data resources.
基金supported by the National Natural Science Foundation of China(52474092 and 52074042).
文摘To investigate the fracture propagation characteristics and failure mechanism of anti-dip rock slope induced by underground mining,the Jiguanling landslide in Wulong,Chongqing,China is taken as the prototype,and physical model test is utilized to study the fracture evolution process,deformation characteristics and failure mechanism of anti-dip rock slope.In this study,the digital image correlation(DIC)technique and pressure acquisition system are combined to analyze the displacement and stress field of rock slope during underground mining stages.The results show that the anti-dip rock slope experiences four stages during underground coal mining:tensile fracture propagation in upper toppling zone,shallow damage in the lower shear zone,coal seam roof caving,failure of the whole slope.There is a phenomenon of local tensile and compressive stress conversion in upper toppling zone after roof caving.The appearance of coal seam roof caving increases the compressive area and pressure of the shear zone,leading to the failure of the shear blocks at the front edge,and ultimately causing failure of the whole slope.Mining with retained coal pillar before shallow failure in the shear zone can effectively block the impact of lower mining on the upper toppling zone,achieve a 16%contraction in toppling zone,and improve the stability of the slope.The failure mode of slope can be summarized as shear–slip–toppling collapse failure.This paper improves the understanding on the failure mechanism of anti-dip rock slope caused by underground mining.
基金Project(52374153)supported by the National Natural Science Foundation of ChinaProject(kq2502150)supported by the Natural Science Foundation of Changsha,China。
文摘Cemented tailings backfill(CTB)is a crucial support material for ensuring the long-term stability of underground goafs.A comprehensive understanding of its compressive mechanical behavior is essential for improving engineering safety.Although extensive studies have been conducted on the uniaxial compressive properties of CTB,damage constitutive models that effectively capture its damage evolution process remain underdeveloped,and its failure mechanisms are not yet fully clarified.To address these gaps,this study conducted systematic uniaxial compression tests on CTB specimens prepared with varying cement-tailings ratios.The results revealed distinct compaction and softening phases in the stress−strain curves.A lower cement-tailings ratio significantly reduced the strength and deformation resistance of CTB,along with a decrease in elastic energy accumulation at peak stress and dissipation energy in the post peak stage.Based on these findings,a modified damage constitutive model was developed by introducing a correction factor,enabling accurate simulation of the entire uniaxial compression process of CTB with different cement-tailings ratios.Comparative analysis with classical constitutive models validated the proposed model’s accuracy and applicability in describing the compressive behavior of CTB.Furthermore,particle size distribution and acoustic emission tests were employed to investigate the influence of cement-tailings ratio on failure mechanisms.The results indicated that a lower cement-tailings ratio leads to coarser particle sizes,which intensify shear-related acoustic emission signals and ultimately result in more pronounced macroscopic shear failure.This study provides theoretical support and practical guidance for the optimal design of CTB mix ratios.
基金supported by the National Natural Science Foundation of China(Nos.12172248,12302022,12021002,and 12132010)the Tianjin Research Program of Application Foundation and Advanced Technology of China(No.23JCZDJC00950)。
文摘Belt conveyors are extensively utilized in mining and power industries.In a typical coal mine conveyor system,coal is transported over distances exceeding 2 km,involving more than 20000 idlers,which far exceeds a reasonable manual inspection capacity.Given that idlers typically have a lifespan of 1-2 years,there is an urgent need for a rapid,cost-effective,and intelligent safety monitoring system.However,current embedded systems face prohibitive replacement costs,while conventional monitoring technologies suffer from inefficiency at low rotational speeds and lack systematic structural optimization frameworks for diverse idler types and parameters.To address these challenges,this paper introduces an integrated,on-site detachable self-powered idler condition monitoring system(ICMS).This system combines energy harvesting based on the magnetic modulation technology with wireless condition monitoring capabilities.Specifically,it develops a data-driven model integrating convolutional neural networks(CNNs) with genetic algorithms(GAs).The conventional testing results show that the data-driven model not only significantly accelerates the parameter response time,but also achieves a prediction accuracy of 92.95%.The in-situ experiments conducted in coal mines demonstrate the system's reliability and monitoring functionality under both no-load and fullload conditions.This research provides an innovative self-powered condition monitoring solution and develops an efficient data-driven model,offering feasible online monitoring approaches for smart mine construction.
基金financial support from the Young Scientist Project of the National Key Research and Development Program of China(Grant No.2021YFC2900600)the Beijing Nova Program(Grant No.20220484057)+1 种基金The authors acknowledge the financial support from the Natural Sciences and Engineering Research Council of Canada(Grant No.RGPIN-2018-06902)industrial partners of the Research Institute on Mines and the Environment(RIME UQAT-Polytechnique:https://irme.ca/en/).
文摘In the underhand cut-and-fill mining method,a sill mat(i.e.an artificial horizontal pillar)constructed by cemented backfill is essential to prevent mine workers from being directly exposed under problematic rock roofs.A critical issue is to determine the minimum required strength of the sill mat to ensure a safe and cost-effective design.Until now,Mitchell’s analytical solution is the only available option,considering two stiff and immobile rock walls.Unavoidable rock wall closure associated with stope excavation below the sill mat was neglected.This,along with other undefined parameters,explains why Mitchell’s solution is rarely used in sill mat design.A new analytical solution for determining the minimum required strength of the sill mat accounting for wall closure is necessary.In this study,a closed-form analytical solution for estimating rock wall closure generated by stope excavation below a sill mat is developed by using Salamon’s and Flamant’s models.The proposed analytical solution does not contain any coefficients of correction or calibration.Despite several assumptions(or somewhat of oversimplifications)necessary to render a simple analytical solution possible,good agreements are obtained between the rock wall closures predicted by applying the proposed analytical solution and those obtained numerically with FLAC3D for many cases with arbitrarily chosen geometrical and material parameters.The proposed analytical solution is therefore validated and can be used to evaluate the rock wall closure generated by stope excavation below a sill mat.
基金National Natural Science Foundation of China,Grant/Award Numbers:U22A20598,52104107National Key Research and Development Program of China,Grant/Award Numbers:2023YFC2907300,2019YFE0118500,2019YFC1904304Natural Science Foundation of Jiangsu Province,Grant/Award Number:BK20200634。
文摘Gas storage in abandoned mines is one way to reuse waste space resources.The surrounding rock of gas storage reservoirs in underground roadways undergoes damage and deformation under the cyclic loading of gas charging and discharging,which can pose a risk to the safety of the reservoirs.This study establishes a true triaxial numerical model of rock mass with the discrete element method(DEM)and explores the crack evolution of surrounding rock of underground gas storage during cyclic loading and unloading.Also,a damage evolution model in numerical analysis considering residual deformation is developed to explain the experimental results.As was revealed,cyclic loading and unloading resulted in fatigue damage in the specimen and caused strength deterioration of the specimen.During the loading process,the uniformly distributed force chains of the rock mass redistributed,evolving gradually to mostly transverse force chains.This contributed to the appearance of blank areas in the force chains when through cracks appear.The ratio of tensile cracks to shear cracks gradually decreases and finally stabilizes at 7:1.The damage evolution model considering residual strain can be mutually verified with the numerical simulation results.Based on the DEM model,it was found that there was a certain threshold of confining pressure.When the confining pressure exceeded 30 MPa,the deformation to ductility of sandstone samples began to accelerate,with a greater residual strength.This study provides a theoretical basis for analyzing the long-term mechanical behavior of surrounding rock of gas storage in abandoned mines.
文摘This paper dwells on regression models of cash-cost and country-benefit developed to enable accounting for the cumulative impact of the determinant parameters in the prediction of cash-costs and country-benefits of gold mining opportunities in the justification of taxation regimes and selection of investment targets worldwide. The data used in the generation of regression models include the total cash-cost and country-benefit per ounce vs the parameters of rock-mass (type of ore body, its dip angle, strike length and thickness), mine-design (rate of gold production, type of mine, depth of mine, gold price and age of mine) and country parameters (the Fraser Institute parameters: taxation regime, infrastructure, environmental regime, political stability, labor regulations and security) were generated from 160 gold mines in the top 20 gold rich countries for a period of 7 years from 2002 to 2008. The regression models show that the determinants account for 71% and 55% of the determinants of cash-cost and country-benefit respectively. Depending on the availability of data, the regression models generated in this study could be enhanced by adding into the parameters used in the regression analysis, the unaccounted for mine and country parameters. Also, Depending on the availability of data, the Regression models generated in this study could be enhanced further by replacing the parameters of Fraser Institute ranking used in the regression analysis with the actual parameters of country effect on cash-cost and country-benefit of the gold produced. Nevertheless, the regression models generated in this study could be used to predict the cash-costs and country-benefits of gold mining opportunities in the justification of taxation regimes and selection of investment targets worldwide.
