Fuzzy inference system using genetic algorithm and pattern search for predicting roof fall rate in underground coal mines

One of the most dangerous safety hazard in underground coal mines is roof falls during retreat mining.Roof falls may cause life-threatening and non-fatal injuries to miners and impede mining and transportation operations.As a result,a reliable roof fall prediction model is essential to tackle such challenges.Different parameters that substantially impact roof falls are ill-defined and intangible,making this an uncertain and challenging research issue.The National Institute for Occupational Safety and Health assembled a national database of roof performance from 37 coal mines to explore the factors contributing to roof falls.Data acquired for 37 mines is limited due to several restrictions,which increased the likelihood of incompleteness.Fuzzy logic is a technique for coping with ambiguity,incompleteness,and uncertainty.Therefore,In this paper,the fuzzy inference method is presented,which employs a genetic algorithm to create fuzzy rules based on 109 records of roof fall data and pattern search to refine the membership functions of parameters.The performance of the deployed model is evaluated using statistical measures such as the Root-Mean-Square Error,Mean-Absolute-Error,and coefficient of determination(R_(2)).Based on these criteria,the suggested model outperforms the existing models to precisely predict roof fall rates using fewer fuzzy rules.

SDH-FCOS:An Efficient Neural Network for Defect Detection in Urban Underground Pipelines

Urban underground pipelines are an important infrastructure in cities,and timely investigation of problems in underground pipelines can help ensure the normal operation of cities.Owing to the growing demand for defect detection in urban underground pipelines,this study developed an improved defect detection method for urban underground pipelines based on fully convolutional one-stage object detector(FCOS),called spatial pyramid pooling-fast(SPPF)feature fusion and dual detection heads based on FCOS(SDH-FCOS)model.This study improved the feature fusion component of the model network based on FCOS,introduced an SPPF network structure behind the last output feature layer of the backbone network,fused the local and global features,added a top-down path to accelerate the circulation of shallowinformation,and enriched the semantic information acquired by shallow features.The ability of the model to detect objects with multiple morphologies was strengthened by introducing dual detection heads.The experimental results using an open dataset of underground pipes show that the proposed SDH-FCOS model can recognize underground pipe defects more accurately;the average accuracy was improved by 2.7% compared with the original FCOS model,reducing the leakage rate to a large extent and achieving real-time detection.Also,our model achieved a good trade-off between accuracy and speed compared with other mainstream methods.This proved the effectiveness of the proposed model.

Deep Learning Based Underground Sewer Defect Classification Using a Modified RegNet

The sewer system plays an important role in protecting rainfall and treating urban wastewater.Due to the harsh internal environment and complex structure of the sewer,it is difficult to monitor the sewer system.Researchers are developing different methods,such as the Internet of Things and Artificial Intelligence,to monitor and detect the faults in the sewer system.Deep learning is a promising artificial intelligence technology that can effectively identify and classify different sewer system defects.However,the existing deep learning based solution does not provide high accuracy prediction and the defect class considered for classification is very small,which can affect the robustness of the model in the constraint environment.As a result,this paper proposes a sewer condition monitoring framework based on deep learning,which can effectively detect and evaluate defects in sewer pipelines with high accuracy.We also introduce a large dataset of sewer defects with 20 different defect classes found in the sewer pipeline.This study modified the original RegNet model by modifying the squeeze excitation(SE)block and adding the dropout layer and Leaky Rectified Linear Units(LeakyReLU)activation function in the Block structure of RegNet model.This study explored different deep learning methods such as RegNet,ResNet50,very deep convolutional networks(VGG),and GoogleNet to train on the sewer defect dataset.The experimental results indicate that the proposed system framework based on the modified-RegNet(RegNet+)model achieves the highest accuracy of 99.5 compared with the commonly used deep learning models.The proposed model provides a robust deep learning model that can effectively classify 20 different sewer defects and be utilized in real-world sewer condition monitoring applications.

A methodology for damage evaluation of underground tunnels subjected to static loading using numerical modeling

We have proposed a methodology to assess the robustness of underground tunnels against potential failure.This involves developing vulnerability functions for various qualities of rock mass and static loading intensities.To account for these variations,we utilized a Monte Carlo Simulation(MCS)technique coupled with the finite difference code FLAC^(3D),to conduct two thousand seven hundred numerical simulations of a horseshoe tunnel located within a rock mass with different geological strength index system(GSIs)and subjected to different states of static loading.To quantify the severity of damage within the rock mass,we selected one stress-based(brittle shear ratio(BSR))and one strain-based failure criterion(plastic damage index(PDI)).Based on these criteria,we then developed fragility curves.Additionally,we used mathematical approximation techniques to produce vulnerability functions that relate the probabilities of various damage states to loading intensities for different quality classes of blocky rock mass.The results indicated that the fragility curves we obtained could accurately depict the evolution of the inner and outer shell damage around the tunnel.Therefore,we have provided engineers with a tool that can predict levels of damages associated with different failure mechanisms based on variations in rock mass quality and in situ stress state.Our method is a numerically developed,multi-variate approach that can aid engineers in making informed decisions about the robustness of underground tunnels.

Hydromechanical characterization of gas transport amidst uncertainty for underground nuclear explosion detection

Given the challenge of definitively discriminating between chemical and nuclear explosions using seismic methods alone,surface detection of signature noble gas radioisotopes is considered a positive identification of underground nuclear explosions(UNEs).However,the migration of signature radionuclide gases between the nuclear cavity and surface is not well understood because complex processes are involved,including the generation of complex fracture networks,reactivation of natural fractures and faults,and thermo-hydro-mechanical-chemical(THMC)coupling of radionuclide gas transport in the subsurface.In this study,we provide an experimental investigation of hydro-mechanical(HM)coupling among gas flow,stress states,rock deformation,and rock damage using a unique multi-physics triaxial direct shear rock testing system.The testing system also features redundant gas pressure and flow rate measurements,well suited for parameter uncertainty quantification.Using porous tuff and tight granite samples that are relevant to historic UNE tests,we measured the Biot effective stress coefficient,rock matrix gas permeability,and fracture gas permeability at a range of pore pressure and stress conditions.The Biot effective stress coefficient varies from 0.69 to 1 for the tuff,whose porosity averages 35.3%±0.7%,while this coefficient varies from 0.51 to 0.78 for the tight granite(porosity<1%,perhaps an underestimate).Matrix gas permeability is strongly correlated to effective stress for the granite,but not for the porous tuff.Our experiments reveal the following key engineering implications on transport of radionuclide gases post a UNE event:(1)The porous tuff shows apparent fracture dilation or compression upon stress changes,which does not necessarily change the gas permeability;(2)The granite fracture permeability shows strong stress sensitivity and is positively related to shear displacement;and(3)Hydromechanical coupling among stress states,rock damage,and gas flow appears to be stronger in tight granite than in porous tuff.

Sealing capacity evaluation of underground gas storage under intricate geological conditions

Evaluating underground gas storage(UGS)sealing capacity is essential for its safe construction and operational efficiency.This involves evaluating both the static sealing capacity of traps during hydrocarbon accumulation and the dynamic sealing capacity of UGS under intensive gas injection and withdrawal,and alternating loads.This study detailed the methodology developed by Sinopec.The approach merges disciplines like geology,geomechanics,and hydrodynamics,employing both dynamic-static and qualitative-quantitative analyses.Sinopec's evaluation methods,grounded in the in situ stress analysis,include mechanistic studies,laboratory tests,geological surveys,stress analysis,and fluid-solid interactions.Through tests on the static and dynamic sealing capacity of UGS,alongside investigations into sealing mechanisms and the geological and geomechanical properties of cap rocks and faults,A geomechanics-rock damage-seepage mechanics dynamic coupling analysis method has been developed to predict in situ stress variations relative to pore pressure changes during UGS operations and evaluate fault sealing capacity and cap rock integrity,thereby setting the maximum operational pressures.Utilizing this evaluation technique,Sinopec has defined performance metrics and criteria for evaluating the sealing capacity of depleted gas reservoirs,enabling preliminary sealing capacity evaluations at UGS sites.These evaluations have significantly informed the design of UGS construction schemes and the evaluation of fault sealing capacity and cap rock integrity during UGS operations.

A routing and positioning algorithm based on a K-barrier for use in an underground wireless sensor network

Deployment of nodes based on K-barrier coverage in an underground wireless sensor network is described. The network has automatic routing recovery by using a basic information table (BIT) for each node. An RSSI positioning algorithm based on a path loss model in the coal mine is used to calculate the path loss in real time within the actual lane way environment. Simulation results show that the packet loss can be controlled to less than 15% by the routing recovery algorithm under special recovery circum- stances. The location precision is within 5 m, which greatly enhances performance compared to tradi- tional frequency location systems. This approach can meet the needs for accurate location underground.

Preliminary research and scheme design of deep underground in situ geo-information detection experiment for Geology in Time

The deep earth,deep sea,and deep space are the main parts of the national“three deep”strategy,which is in the forefront of the strategic deployment clearly defined in China’s 14th Five-Year Plan(2021-2025)and the Long-Range Objectives Through the Year 2035.It is important to reveal the evolutionary process and mechanism of deep tectonics to understand the earth’s past,present and future.The academic con-notation of Geology in Time has been given for the first time,which refers to the multi-field evolution response process of geological bodies at different time and spatial scales caused by geological processes inside and outside the Earth.Based on the deep in situ detection space and the unique geological envi-ronment of China Jinping Underground Laboratory,the scientific issue of the correlation mechanism and law between deep internal time-varying and shallow geological response is given attention.Innovative research and frontier exploration on deep underground in situ geo-information detection experiments for Geology in Time are designed to be carried out,which will have the potential to explore the driving force of Geology in Time,reveal essential laws of deep earth science,and explore innovative technologies in deep underground engineering.

Artificial ground freezing of underground mines in cold regions using thermosyphons with air insulation

Current practice of underground artificial ground freezing(AGF)typically involves huge refrigeration systems of large economic and environmental costs.In this study,a novel AGF technique is proposed deploying available cold wind in cold regions.This is achieved by a static heat transfer device called thermosyphon equipped with an air insulation layer.A refrigeration unit can be optionally integrated to meet additional cooling requirements.The introduction of air insulation isolates the thermosyphon from ground zones where freezing is not needed,resulting in:(1)steering the cooling resources(cold wind or refrigeration)towards zones of interest;and(2)minimizing refrigeration load.This design is demonstrated using well-validated mathematical models from our previous work based on two-phase enthalpy method of the ground coupled with a thermal resistance network for the thermosyphon.Two Canadian mines are considered:the Cigar Lake Mine and the Giant Mine.The results show that our proposed design can speed the freezing time by 30%at the Giant Mine and by two months at the Cigar Lake Mine.Further,a cooling load of 2.4 GWh can be saved at the Cigar Lake Mine.Overall,this study provides mining practitioners with sustainable solutions of underground AGF.

Global stability coefficient of large underground caverns under static loading and earthquake wave condition

Underground energy and resource development,deep underground energy storage and other projects involve the global stability of multiple interconnected cavern groups under internal and external dynamic disturbances.An evaluation method of the global stability coefficient of underground caverns based on static overload and dynamic overload was proposed.Firstly,the global failure criterion for caverns was defined based on its band connection of plastic-strain between multi-caverns.Then,overloading calculation of the boundary geostress and seismic intensity on the caverns model was carried out,and the critical unstable state of multi-caverns can be identified,if the plastic-strain band appeared between caverns during these overloading processes.Thus,the global stability coefficient for the multi-caverns under static loading and earthquake was obtained based on the corresponding overloading coefficient.Practical analysis for the Yingliangbao(YLB)hydraulic caverns indicated that this method can not only effectively obtain the global stability coefficient of caverns under static and dynamic earthquake conditions,but also identify the caverns’high-risk zone of local instability through localized plastic strain of surrounding rock.This study can provide some reference for the layout design and seismic optimization of underground cavern group.

Mechanism,prevention,and control of mining-induced dynamic disasters in underground metal mines in China:Challenges and solutions

Metal mineral resources play an indispensable role in the development of the national economy.Dynamic disasters in underground metal mines seriously threaten mining safety,which are major scientific and technological problems to be solved urgently.In this article,the occurrence status and grand challenges of some typical dynamic disasters involving roof falling,spalling,collapse,large deformation,rockburst,surface subsidence,and water inrush in metal mines in China are systematically presented,the characteristics of mining-induced dynamic disasters are analyzed,the examples of dynamic disasters occurring in some metal mines in China are summarized,the occurrence mechanism,monitoring and early warning methods,and prevention and control techniques of these disasters are highlighted,and some new opinions,suggestions,and solutions are proposed simultaneously.Moreover,some shortcomings in current disaster research are pointed out,and the direction of efforts to improve the prevention and control level of dynamic disasters in China’s metal mines in the future is prospected.The integration of forward-looking key innovative theories and technologies in the abovementioned aspects will greatly enhance the cognitive level of disaster prevention and mitigation in China’s metal mining industry and achieve a significant shift from passive disaster relief to active disaster prevention.

Comparative analysis of thermodynamic and mechanical responses between underground hydrogen storage and compressed air energy storage in lined rock caverns

Underground hydrogen storage(UHS)and compressed air energy storage(CAES)are two viable largescale energy storage technologies for mitigating the intermittency of wind and solar power.Therefore,it is meaningful to compare the properties of hydrogen and air with typical thermodynamic storage processes.This study employs a multi-physical coupling model to compare the operations of CAES and UHS,integrating gas thermodynamics within caverns,thermal conduction,and mechanical deformation around rock caverns.Gas thermodynamic responses are validated using additional simulations and the field test data.Temperature and pressure variations of air and hydrogen within rock caverns exhibit similarities under both adiabatic and diabatic simulation modes.Hydrogen reaches higher temperature and pressure following gas charging stage compared to air,and the ideal gas assumption may lead to overestimation of gas temperature and pressure.Unlike steel lining of CAES,the sealing layer(fibre-reinforced plastic FRP)in UHS is prone to deformation but can effectively mitigates stress in the sealing layer.In CAES,the first principal stress on the surface of the sealing layer and concrete lining is tensile stress,whereas UHS exhibits compressive stress in the same areas.Our present research can provide references for the selection of energy storage methods.

Residual subsidence time series model in mountain area caused by underground mining based on GNSS online monitoring

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.

Simulation of Underground Reservoir Stability of Pumped Storage Power Station Based on Fluid-Structure Coupling

Based on global initiatives such as the clean energy transition and the development of renewable energy,the pumped storage power station has become a new and significant way of energy storage and regulation,and its construction environment is more complex than that of a traditional reservoir.In particular,the stability of the rock strata in the underground reservoirs is affected by the seepage pressure and rock stress,which presents some challenges in achieving engineering safety and stability.Using the advantages of the numerical simulation method in dealing deal with nonlinear problems in engineering stability,in this study,the stability of the underground reservoir of the Shidangshan(SDS)pumped storage power station was numerically calculated and quantitatively analyzed based on fluid-structure coupling theory,providing an important reference for the safe operation and management of the underground reservoir.First,using the COMSOL software,a suitablemechanicalmodel was created in accordance with the geological structure and project characteristics of the underground reservoir.Next,the characteristics of the stress field,displacement field,and seepage field after excavation of the underground reservoir were simulated in light of the seepage effect of groundwater on the nearby rock of the underground reservoir.Finally,based on the construction specifications and Molar-Coulomb criterion,a thorough evaluation of the stability of the underground reservoir was performed through simulation of the filling and discharge conditions and anti-seepage strengthening measures.The findings demonstrate that the numerical simulation results have a certain level of reliability and are in accordance with the stress measured in the project area.The underground reservoir excavation resulted in a maximum displacement value of the rock mass around the caverns of 3.56 mm in a typical section,and the safety coefficient of the parts,as determined using the Molar-Coulomb criterion,was higher than 1,indicating that the project as a whole is in a stable state.

Direct measurement of the break-out ^(19)F(p,γ)^(20)Ne reaction in the China Jinping underground laboratory(CJPL)

Calcium production and the stellar evolution of first-generation stars remain fascinating mysteries in astrophysics.As one possible nucleosynthesis scenario,break-out from the hot carbon–nitrogen–oxygen(HCNO)cycle was thought to be the source of the calcium observed in these oldest stars.However,according to the stellar modeling,a nearly tenfold increase in the thermonuclear rate ratio of the break-out ^(19)F(p,γ)^(20) Ne reaction with respect to the competing ^(19)F(p,α)^(16) O back-processing reaction is required to reproduce the observed calcium abundance.We performed a direct measurement of this break-out reaction at the China Jinping underground laboratory.The measurement was performed down to the low-energy limit of E_(c.m.)=186 keV in the center-of-mass frame.The key resonance was observed at 225.2 keV for the first time.At a temperature of approximately 0.1 GK,this new resonance enhanced the thermonuclear ^(19)F(p,γ)^(20) Ne rate by up to a factor of≈7.4,compared with the previously recommended NACRE rate.This is of particular interest to the study of the evolution of the first stars and implies a stronger breakdown in their“warm”CNO cycle through the ^(19)F(p,γ)^(20) Ne reaction than previously envisioned.This break-out resulted in the production of the calcium observed in the oldest stars,enhancing our understanding of the evolution of the first stars.

Modularized and Parametric Modeling Technology for Finite Element Simulations of Underground Engineering under Complicated Geological Conditions

The surrounding geological conditions and supporting structures of underground engineering are often updated during construction,and these updates require repeated numerical modeling.To improve the numerical modeling efficiency of underground engineering,a modularized and parametric modeling cloud server is developed by using Python codes.The basic framework of the cloud server is as follows:input the modeling parameters into the web platform,implement Rhino software and FLAC3D software to model and run simulations in the cloud server,and return the simulation results to the web platform.The modeling program can automatically generate instructions that can run the modeling process in Rhino based on the input modeling parameters.The main modules of the modeling program include modeling the 3D geological structures,the underground engineering structures,and the supporting structures as well as meshing the geometric models.In particular,various cross-sections of underground caverns are crafted as parametricmodules in themodeling program.Themodularized and parametric modeling program is used for a finite element simulation of the underground powerhouse of the Shuangjiangkou Hydropower Station.This complicatedmodel is rapidly generated for the simulation,and the simulation results are reasonable.Thus,this modularized and parametric modeling program is applicable for three-dimensional finite element simulations and analyses.

Numerical analysis on seismic performance of underground structures in liquefiable interlayer sites from centrifuge shaking table test

When an underground structure passes through a liquefiable soil layer,the soil liquefaction may pose a significant threat to the structure.A centrifuge shaking table test was performed to research the seismic response of underground structures in liquefiable interlayer sites,and a valid numerical model was obtained through simulation model test.Finally,the calibrated numerical model was used to perform further research on the influence of various distribution characteristics of liquefiable interlayers on the seismic reaction of underground structures.The key findings are as follows.The structure faces the most unfavorable condition once a liquefiable layer is located in the middle of the underground structure.When a liquefiable layer exists in the middle of the structure,the seismic reactions of both the underground structure and model site will increase with the rise of the thickness of the liquefiable interlayer.The inter-story drift of the structure in the non-liquefiable site is much smaller than that in the liquefiable interlayer site.The inter-story drift of the structure is not only associated with the site displacement and the soil-structure stiffness ratio but also closely associated with the slippage of the soil-structure contact interface under the condition of large deformation of the site.

Microscopic experiment on efficient construction of underground gas storages converted from water-invaded gas reservoirs

Based on the microfluidic technology,a microscopic visualization model was used to simulate the gas injection process in the initial construction stage and the bottom water invasion/gas injection process in the cyclical injection-production stage of the underground gas storage(UGS)rebuilt from water-invaded gas reservoirs.Through analysis of the gas-liquid contact stabilization mechanism,flow and occurrence,the optimal control method for lifecycle efficient operation of UGS was explored.The results show that in the initial construction stage of UGS,the action of gravity should be fully utilized by regulating the gas injection rate,so as to ensure the macroscopically stable migration of the gas-liquid contact,and greatly improve the gas sweeping capacity,providing a large pore space for gas storage in the subsequent cyclical injection-production stage.In the cyclical injection-production stage of UGS,a constant gas storage and production rate leads to a low pore space utilization.Gradually increasing the gas storage and production rate,that is,transitioning from small volume to large volume,can continuously break the hydraulic equilibrium of the remaining fluid in the porous media,which then expands the pore space and flow channels.This is conducive to the expansion of UGS capacity and efficiency for purpose of peak shaving and supply guarantee.

A 2D stability analysis of the rock surrounding underground liquified natural gas storage cavern based on COMSOL Multiphysics

Underground liquified natural gas(LNG)storage is essential in guaranteeing national energy strategic reserves,and its construction is being accelerated.The stability of surrounding rock of underground LNG storage caverns under stress-low temperature coupling effect is the key factor determining the feasibility of LNG storage.First,a mathematical model used for controlling the stress-low temperature coupling and the processes of rock damage evolution is given,followed by a 2-D numerical execution process of the mathematical model mentioned above described based on Comsol Multiphysics and Matlab code.Finally,a series of 2-D simulations are performed to study the influence of LNG storage cavern layout,burial depth,temperature and internal pressure on the stability of surrounding rocks of these underground storage caverns.The results indicate that all the factors mentioned above affect the evolution of deformation and plastic zone of surrounding rocks.The research results contribute to the engineering design of underground LNG storage caverns.

Deep sea mineral resources and underground space as well as infrastructure for sustainable and liveable cities

This issue covers the papers on two special themes:(1)Mineral resources from deep sea—Science and Engineering and(2)Planning and development of underground space and infrastructure for sustainable and liveable cities.