高等巖石力學(xué)課程報(bào)告英文讀書(shū)報(bào)告

高等巖石力學(xué)英文讀書(shū)報(bào)告1530767葉宇航ReadingreportPapertitle:AnewhardrockTBMperformancepredictionmodelforprojectplanningMajor:隧道與地下工程N(yùn)ame:葉宇航Number:1530767SeveralmodelshavebeenintroducedovertheyearsforpredictionofhardrockTBMperformance.TheTBMperformancepredictionmodelsaremostlybasedonanempiricalorasemi-theoreticalapproach.Althoughtheyhaveadvantagesandareaofapplications,theyalsohavedisadvantages,suchasCSMmodeldon’tconsiderthemaininfluencingparameter,NTNUmodelrequirespecialexperimentsoriginatedfromthedrilling,QTBMaretoocomplicated.Theauthorshopetobetterunderstandmachine-rockinteractionandtodevelopamoreaccuratemodelforperformanceestimateofhardrockTBMs.Inordertoachieveit,theauthorsinvestigatethefielddataofthreemaintunnelingprojectsinIranandManapouritunnelprojectinNewZealand.Thedataobtainedfromtheprojectsasbeforementionincludinggeologicalandperformanceparameters,havewiderangesofvariations.ButthesewiderangesofgeologicalandperformanceparametershelpedindevelopingamorecomprehensiveTBMperformancepredictionmodelwhichhascovereddifferentgeologicalconditions.Ingeneral,tojustifytheuseofTBMinanyprojectandforplanningpurposes,areasonablyaccurateestimationofrateofpenetration(ROP),dailyrateofadvance(AR),andcuttercost/lifeestimateisnecessary.ButtheauthorschosenFieldPenetrationIndex(FPI)whichisacompositeparameterasthemachineparameter.Inthetext,bothsingleandmulti-variableregressionanalyzeswereusedtoinvestigaterelationshipbetweenengineeringrockpropertiesandTBMperformanceparametersandfinallytodevelopempiricalequation.TheanalysisofthedataobtainedfromtheprojectsprovedthatFPIisasuitablemachineperformanceparameterfordevelopingempiricalrelationshipswithgeologicalparameters.Andmulti-variableregressionanalysisshowgoodcorrelationbetweenln(FPI)asresponseparameterandUCSandRQDaspredictors.InconclusionFPIisagoodparameterfortheevaluationofhardrockTBMperformance.Therefore,theauthorsdevelopedachartofFPIprediction.ThischartcanbeusedforquickestimationofrangeofvaluesforFPIingroundswithdifferentrockstrengthandrockquality.ExceptstheFPI,theauthorsalsoconcernedtheboreability.Boreabilityisthetermcommonlyusedtoexpresstheeaseordifficultyofrockmassexcavationbyatunnelboringmachine.Rockmassboreabilitydependsonanumberofinfluencingparametersincludingintactrock/rockmassproperties,machinespecificationsandoperationalparameters.Intunnelingprojects,groundcharacteristicsorboreabilityoftherockmassisanimportantparameterforselectingmachinetypeandspecifications.Itisclearthatproperevaluationofrockmassboreabilitycanalsoplayamajorroleinmachineoperationtoachievethebestperformance.FPIcanbeselectedasanindexforcategorizingrockmassboreability.Basedontheanalysisofgiveprojects,theauthorsdefinedsixrockmassboreabilityclasses,frommostdifficultforboringorB-0class(Tough)toeasiestforboringorB-Vclass(Excellent).ConsideredtherelationshipbetweenFPIandboreability,theauthorsgiveatableofTBMperformanceestimationinrockmasseswithdifferentboreabilityclasses.Allinall,thepaperproposedasimplemodeltoevaluaterockmassboreabilityandTBMperformancerange.Thismodeldemonstratesthatmachineperformancehasbeenrelatedtotwomainrockproperties(UCSandRQD)andtwooperationalparameters(averagecutterheadthrustandRPM).TheseInputparametersofthemodelareavailableinthepreliminarystagesofthetunneldesignandplanning.Fromthispaper,IhaveamuchbetterunderstandingoftheestimationofTBMperformanceandtheimpactfactorsofFPIandboreability.AndIthinkthemodelproposedinthispapercanbeappliedasausefultoolforquickestimationofTBMperformanceinprojectswithdifferentgeologicalconditionsandmachinediameters.Andthismodelisworthusingwidely.ThenewboreabilityclassificationwhichbasedonrockmassescharacteristicstoallowforpredictionofFPIvaluesalsoworthlearning.Theauthorsadoptbothsingleandmulti-variableregressiontoanalyzetherelationshipbetweenengineeringrockpropertiesandTBMperformanceparameters.Asaresult,itobtainsagoodresult.So,Ithinkwhenweinvestigateaproblemwhichinfluencedbyvariousparameters,wecanconsidernotjustsingleparameterbutmulti-variableregression.Intheprocessofdevelopedmodel,varietiesofchartswhichdemonstratetherelationshipbetweendifferentparameterplayanimportantrole.Thus,chartisan