煤層底板巖體參數(shù)隨機場建模及采動穩(wěn)定可靠度研究

煤層底板巖體參數(shù)隨機場建模及采動穩(wěn)定可靠度研究摘要

本文針對煤層底板巖體參數(shù)不確定性引起的采動災害問題，基于隨機場理論，建立了煤層底板巖體參數(shù)隨機場模型，采用最小二乘法擬合半方差函數(shù)，根據(jù)巖體特性和采動工況，擬合得出了煤層底板巖體的空間相關性函數(shù)。運用該隨機場模型，以某煤礦為例，對其煤層底板進行了參數(shù)隨機場生成與采動數(shù)值模擬分析，得到了煤層底板位移、應力等采動影響因素的隨機分布和變化規(guī)律，為采力建設提供了科學的決策依據(jù)。同時，利用可靠度理論，對煤層采動過程的穩(wěn)定性進行了分析，通過MonteCarlo模擬方法，得到了不同設計參數(shù)下采動穩(wěn)定性的可靠度，并修正了采動設計參數(shù)。研究結果表明，在多重不確定因素影響下，利用隨機場模型和可靠度理論相結合，可以評估煤層底板巖體的采動穩(wěn)定可靠度，提高了工程實踐的可操作性和可靠性。

關鍵詞：煤層底板；巖體參數(shù)；隨機場模型；采動穩(wěn)定可靠度；MonteCarlo模擬

Abstract

Inresponsetotheproblemofminingdisasterscausedbytheuncertaintyofcoalfloorparameters,arandomfieldmodelofcoalfloorrockmassparameterswasestablishedbasedonthetheoryofrandomfields.Thesemi-variancefunctionwasfittedusingtheleastsquaresmethod,andthespatialcorrelationfunctionofthecoalfloorrockmasswasobtainedbasedonthecharacteristicsoftherockmassandminingconditions.Usingtherandomfieldmodel,thecoalfloorofacertaincoalminewassubjectedtoparameterrandomfieldgenerationandminingnumericalsimulationanalysis,andtherandomdistributionandvariationlawofmininginfluencingfactorssuchascoalfloordisplacementandstresswereobtained,providingascientificdecision-makingbasisforminingconstruction.Atthesametime,usingthetheoryofreliability,thestabilityofthecoalminingprocesswasanalyzed,andthereliabilityofminingstabilityunderdifferentdesignparameterswasobtainedthroughMonteCarlosimulationmethod.Theminingdesignparameterswerecorrected.Theresearchresultsshowthatundertheinfluenceofmultipleuncertainfactors,thecombinationofrandomfieldmodelandreliabilitytheorycanevaluatetheminingstabilityandreliabilityofcoalfloorrockmass,whichimprovestheoperabilityandreliabilityofengineeringpractice.

Keywords:coalfloor;rockmassparameters;randomfieldmodel;miningstabilityandreliability;MonteCarlosimulatioMiningoperationsinthecoalindustryinvolvesignificantrisksanduncertaintiesduetothecomplexgeologicalandminingconditions.Inordertoimprovethesafetyandefficiencyoftheminingprocess,itisnecessarytoevaluatethestabilityandreliabilityofthecoalfloorrockmass.However,duetotheuncertaintiesassociatedwiththerockmassparametersandminingdesign,traditionalanalyticalmethodsoftenfailtoprovideaccurateandreliableresults.

Inrecentyears,therandomfieldmodelandMonteCarlosimulationmethodhavebeenwidelyusedintheanalysisofgeotechnicalproblems.Therandomfieldmodelcaneffectivelycapturethespatialvariabilityofrockmassparametersandprovideamorerealisticrepresentationofthegeologicalconditions.MonteCarlosimulation,ontheotherhand,cangeneratelargenumbersofrandomsamplesandevaluatethestatisticaldistributionoftheoutputvariables,whichimprovestheaccuracyandreliabilityoftheanalysis.

Inthisstudy,therandomfieldmodelandMonteCarlosimulationmethodwereappliedtoevaluatetheminingstabilityandreliabilityofacoalfloorrockmassinChina.Therockmassparameterswerecharacterizedbyarandomfieldmodel,andtheminingdesignparameterswerecorrectedbasedonthesimulationresults.Thestabilityandreliabilityanalysiswasperformedusingthelimitequilibriummethodandreliabilitytheory.

Theresearchresultsshowedthatthecombinationofrandomfieldmodelandreliabilitytheorycaneffectivelyevaluatetheminingstabilityandreliabilityofcoalfloorrockmassundertheinfluenceofmultipleuncertainfactors.TheMonteCarlosimulationmethodcangeneratealargenumberofrandomsamplesandprovideamoreaccuraterepresentationofthestatisticaldistributionoftheoutputvariables.Thisapproachimprovestheoperabilityandreliabilityofengineeringpracticeandhelpstoreducetherisksassociatedwithminingoperationsinthecoalindustry.

Inconclusion,therandomfieldmodelandMonteCarlosimulationmethodprovideapowerfultoolfortheanalysisofgeotechnicalproblemsinthecoalindustry.ThecombinationofthesemethodscaneffectivelyevaluatethestabilityandreliabilityofcoalfloorrockmassandimprovethesafetyandefficiencyofminingoperationsMiningcoalfromtheearthisanessentialtasktomeettheenergydemandsofthemodernworld.Coalminingoperationscanalsoposesignificantrisksandhazardstoworkersandsurroundingcommunities.Therefore,itisessentialtoensurethestabilityandreliabilityofcoalfloorrockmassduringminingoperationstominimizetherisksandimprovetheefficiencyandproductivityofminingoperations.Inthisessay,wehavediscussedtherandomfieldmodelandMonteCarlosimulationmethodasaneffectivetoolforanalyzinggeotechnicalproblemsinthecoalminingindustry.

Therandomfieldmodelisastatisticalapproachthatconsiderstheuncertaintiesandvariationsingeotechnicalparameterssuchasrockstrength,porosity,andpermeability.Themodelcharacterizesthespatialvariabilityoftheseparametersusingthemean,variance,andcorrelationfunctions.TheMonteCarlosimulationmethodisusedtoperformrandomsamplingoftheparametersusingtherandomfieldmodel.Thesimulationgeneratesalargenumberofscenarioswithdifferentparametercombinations,andeachscenarioisanalyzedtodeterminetheprobabilityoffailureandstabilityofthecoalfloorrockmass.

TheapplicationoftherandomfieldmodelandMonteCarlosimulationmethodhasseveraladvantagesinthecoalminingindustry.First,itprovidesacomprehensiveanalysisofthegeotechnicalconditionsandtheirvariability,consideringtheuncertaintiesthatexistintherockmass.Second,itcanidentifypotentialfailuremodesandpredicttheprobabilityoffailure,providingaproactiveapproachtominingoperations.Third,itallowsfortheoptimizationofmininglayoutsandsupportstructuresbasedontheanalysisresults,leadingtobetteruseofresources.

TheapplicationoftherandomfieldmodelandMonteCarlosimulationmethodhasbeensuccessfullydemonstratedinseveralstudiesinthecoalminingindustry.Forexample,astudybyLiuandZhang(2015)analyzedthestabilityofcoalfloorrockmassinamineinChinausingarandomfieldmodelandMonteCarlosimulationmethod.Thestudyidentifiedpotentialfailuremodesandprovidedrecommendationsforimprovingthestabilityandsafetyofminingoperations.Similarly,astudybyWangetal.(2016)analyzedthestabilityofcoalfloorrockmassinamineinAustraliausingasimilarapproach,andtheresultswereusedtooptimizethesupportstructuresandmininglayout.

Inconclusion,therandomfieldmodelandMonteCarlosimulationmethodprovideapowerfultoolforanalyzinggeotechnicalproblemsinthecoalminingindustry.Thecombinationofthesemethodscaneffectivelyevaluatethestabilityandreliabilityofcoalfloorrockmassandimprovethesafetyandefficiencyofminingoperations.Theapplicationofthesemethodshasseveraladvantages,includingproactiveriskmanagement,resourceoptimization,andcomprehensiveanalysisofgeotechnicalconditions.Therefore,itisrecommendedthatthesemethodsbeusedinfuturegeotechnicalinvestigationsandminingoperationsinthecoalminingindustryMoreover,remotesensingtechnologiescanalsoplayanimportantroleincoalmininggeotechnicalinvestigations.Forexample,remotesensingdatasuchassatelliteimagesandLiDAR(LightDetectionandRanging)datacanbeusedtoobtaintopographicinformationandtoidentifygeologicalfeaturessuchasfaultsandfractures.Thiscanbeparticularlyusefulinregionswhereground-basedinvestigationsaredifficultorimpossible.

Inaddition,theuseofmachinelearningalgorithmsandartificialintelligencecanalsocontributetotheimprovementofgeotechnicalinvestigationsincoalmining.Thesetechnologiescanbeusedtoprocessandanalyzelargeamountsofdataobtainedfromvarioussourcessuchasdrillinglogs,geophysicalsurveys,andmonitoringsensors.Thiscanhelpinidentifyingpotentialhazardsandpredictingthebehaviorofrockmassesunderdifferentminingconditions.

Furthermore,thedevelopmentofnewsensingtechnologiessuchasfiberopticsensorsandacousticemissionsensorscanalsoimprovethemonitoringandmanagementofcoalfloorrockmassstability.Thesesensorscanprovidereal-timedataonchangesinstressanddeformationofrockmasses,allowingearlydetectionofpotentialhazardsandproactiveriskmanagement.

Inconclusion,geotechnicalinvestigationsplayacriticalroleinensuringthestabilityandreliabilityofcoalfloorrockmassinminingoperations.Theuseofvariousmethodssuchasgeophysicalsurveys,numericalmodeling,andmonitoringsensorscanprovideacomprehensiveanalysisofgeotechnicalconditionsandhelpinidentifyingpotentialhazards.Furthermore,theadoptionofnewtechnologiessuchasremotesensing,machi