描述岩土工程模型不确定性特征的贝叶斯方法

描述岩土工程模型不确定性特征的贝叶斯方法

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作者: 张洁著

出版社: 同济大学出版社

出版时间: 2011-11

版次: 1

ISBN: 9787560846972

定价: 40.00

装帧: 平装

开本: 16开

纸张: 胶版纸

页数: 161页

字数: 268千字

正文语种: 英语

分类: 工程技术

8人买过

Asanymodelisonlyanabstractionoftherealworld，modeluncertaintyalwaysexists.Ingeotechnicalengineering，themodeluncertaintycouldbelarge.Lackofknowledgeaboutmodeluncertaintymayleadtounrealisticpredictions.Whenbackanalysisfromobservedperformances，modeluncertaintyisoftenmixedwithparameteruncertaintyandobservationaluncertainty.Henceitisgenerallydifficulttoisolateandcharacterizemodeluncertainty.Thisbookintroducesthestate-of-the-arttheoriesandmethodologiesforgeotechnicalmodeluncertaintycharacterizationbasedontheBayesiantheory，includingbothrigoroussolutionandapproximatebutpracticalsolutions，wheretheeffectsofparameteruncertaintyandobservationaluncertaintyonmodeluncertaintycharacterizationareappropriatelyaddressed.Thetheoriesandmethodologiesareillustratedindetailwithvariousgeotechnicalproblems.Thebookwillbeofgeneralinteresttoreadersintheprofessionandparticularlyusefulforthosespecializingingeotechnicalinverseanalysisandgeotechnicalreliability. Preface
Chapter1Introduction
1.1Background
1.2ObjectiveandScope
1.3OrganizationoftheBook

Chapter2LiteratureReview
2.1Within-SystemCharacterization
2.1.1LeastSquareMethod
2.1.2MaximumLikelihoodMethod
2.1.3BayesianMethod
2.1.4ExtendedBayesianMethod
2.1.5ModelComparisonandMulti-modelInference
2.2CrossSystemCharacterization
2.3BayesianMethodandComputationalTechniques
2.3.1MaximumPosteriorDensityMethod
2.3.2FirstorderSecondmomentBayesianMethod(FSBM)
2.3.3LaplaceMethod
2.3.4SystemIdentificationMethod
2.3.5SamplingBasedMethods
2.4Summary

Chapter3BayesianFrameworkforCharacterizingModelUncertainty
3.1Parameter,Model,andObservationUncertainties
3.2BayesianEstimationofModelUncertainty
3.2.1ExtensiontoMultiplicativeModelCorrectionFactor
3.2.2ExtensiontoCensoredObservedData
3.2.3ExtensiontoModelCorrectionFunctions
3.3CharacteristicsofCrossSystemModelUncertaintyCharacterization
3.3.1RoleofPriorInformation
3.3.2InterpretationofDeterminedModelUncertainty
3.4AssignmentofPriorUncertainties
3.4.1GeneralGuidelinesforDeterminingf(xi)
3.4.2PriorDistributionforModelUncertaintyParameters
3.5DecisionInvolvedinModelUncertaintyCharacterization
3.5.1SelectionofModelCorrectionFactors
3.5.2UseofModelCorrectionFunction
3.6PredictionofSystemResponses
3.7PossibleSolutionstotheBayesianFramework
3.8Summary

Chapter4SimplifiedBayesianFrameworkforCharacterizingModelUncertainty
4.1Introduction
4.2ApproximateFormulationforCharacterizingModelUncertainty
4.3DiscussionofPriorDistributionsonModelUncertaintyParameters
4.4CharacterizingModelUncertaintybasedontheApproximateFormulation
4.4.1MaximumPosteriorDensityMethod
4.4.2GridCalculationMethod
4.4.3MCMCSimulation
4.5ComparisonofModelUncertaintyFactors
4.5.1SpreadsheetMethod
4.5.2GridCalculationMethod
4.6ApproximatePredictionofSystemResponse
4.7ExtensiontoModelCorrectionFunctions
4.8AnIllustrationExample
4.8.1Background
4.8.2PriorKnowledgeinModelUncertaintyParameters
4.8.3TestUncertainty
4.8.4Calculationof霨(x)and驡(x)
4.8.5SpreadsheetImplementationoftheMaximumPosteriorMethod
4.8.6ComparisonofMethodsforModelUncertaintyCharacterization
4.9Summary

Chapter5EfficientMarkovChainforIdentifyingGeoteehniealModelUncertainty
5.1Introduction
5.2StudyofEfficientMarkovChainforCharacterizingModelUncertainty
5.2.1MarkovChainsunderInvestigation
5.2.2ComparisonofMarkovChains
5.3HybridMarkovChainforModelUncertaintyCharacterizationintheOriginalBayesianFramework
5.3.1StructureoftheHybridMarkovChain
5.3.2DeterminationoftheJumpingFunctions
5.3.3CheckofConvergence
5.4ApplicationtotheSlopeStabilityModelExample
5.4.1PerformanceoftheMarkovChain
5.4.2CheckofConvergence
5.4.3PosteriorDistributions
5.4.4AccuracyofApproximateMethods
5.5ExtensiontoModelCorrectionFunctionCalibration
5.6Summary

Chapter6ProbabilisticBack-AnalysisofSlopeFailure
6.1Introduction
6.2FurtherStudyonModelUncertaintyofLimitEquilibriumMethods
6.2.1EffectofTestUncertainty
6.2.2EffectofQualityofTestData
6.2.3EffectofAmountofTestData
6.3BackAnalysisofSlopeFailurewithUnknownModelUncertainty
6.3.1BayesianFormulation
6.3.2MCMCSimulation
6.3.3ResponseSurfaceApproximation
6.3.4IllustrativeExample
6.4BackAnalysisofSlopeFailurewithKnownModelUncertainty
6.4.1TheoryofBackAnalysiswithKnownModelUncertainty
6.4.2Step-by-stepImplementation
6.4.3ReanalysisofShekKipMeiLandslide
6.5Summary

Chapter7ReliabilityBasedDesignofPileFoundation
7.1Introduction
7.2ProblemDescription
7.3ModelUncertaintyCharacterization
7.3.1ModelUncertaintyCharacterizationUsingApproximateMethods
7.3.2ModelUncertaintyCharacterizationintheOriginalBayesianFramework
7.3.3ComparisonofResults
7.3.4EffectofDataCensoringonModelUncertaintyCharacterization
7.3.5RoleofModelUncertaintyinPileCapacityPrediction
7.4ComparisonofProbabilisticModelsforModelUncertaintyCharacterization
7.4.1UseofAdditiveModelCorrectionFactor
7.4.2UseofModelCorrectionFunctions
7.5ReliabilityBasedDesignofPileFoundations
7.5.1DesignPointMethod
7.5.2ApplicationtoPileCapacityModel
7.5.3AdjustmentinConsiderationofStructuralCodes
7.5.4RegressionAnalysesofPartialFactors
7.6ReliabilityBasedDesignwithEffectiveStressApproach
7.7ComparisonoftheSPTMethodandEffectiveStressMethod
7.8Summary

Chapter8CharacterizingtheModelUncertaintyofaLiquefactionModel
8.1Introduction
8.2ProblemDescription
8.2.1LiquefactionModelunderInvestigation
8.2.2CalibrationDatabase
8.2.3ParameterUncertainty
8.3DeterminationofModelUncertainty
8.3.1BayesianFormulation
8.3.2Choice-basedSamplingBias
8.3.3PriorProbabilisticAnalysisofLiquefactionData
8.3.4CalibrationResults
8.3.5RoleofModelUncertaintyinLiquefactionPotentialEvaluation
8.3.6DeterminationofTargetFactorofSafety
8.4Summary
AppendixA
AppendixB
References
内容简介:
Asanymodelisonlyanabstractionoftherealworld，modeluncertaintyalwaysexists.Ingeotechnicalengineering，themodeluncertaintycouldbelarge.Lackofknowledgeaboutmodeluncertaintymayleadtounrealisticpredictions.Whenbackanalysisfromobservedperformances，modeluncertaintyisoftenmixedwithparameteruncertaintyandobservationaluncertainty.Henceitisgenerallydifficulttoisolateandcharacterizemodeluncertainty.Thisbookintroducesthestate-of-the-arttheoriesandmethodologiesforgeotechnicalmodeluncertaintycharacterizationbasedontheBayesiantheory，includingbothrigoroussolutionandapproximatebutpracticalsolutions，wheretheeffectsofparameteruncertaintyandobservationaluncertaintyonmodeluncertaintycharacterizationareappropriatelyaddressed.Thetheoriesandmethodologiesareillustratedindetailwithvariousgeotechnicalproblems.Thebookwillbeofgeneralinteresttoreadersintheprofessionandparticularlyusefulforthosespecializingingeotechnicalinverseanalysisandgeotechnicalreliability.
目录:
Preface
Chapter1Introduction
1.1Background
1.2ObjectiveandScope
1.3OrganizationoftheBook

Chapter2LiteratureReview
2.1Within-SystemCharacterization
2.1.1LeastSquareMethod
2.1.2MaximumLikelihoodMethod
2.1.3BayesianMethod
2.1.4ExtendedBayesianMethod
2.1.5ModelComparisonandMulti-modelInference
2.2CrossSystemCharacterization
2.3BayesianMethodandComputationalTechniques
2.3.1MaximumPosteriorDensityMethod
2.3.2FirstorderSecondmomentBayesianMethod(FSBM)
2.3.3LaplaceMethod
2.3.4SystemIdentificationMethod
2.3.5SamplingBasedMethods
2.4Summary

Chapter3BayesianFrameworkforCharacterizingModelUncertainty
3.1Parameter,Model,andObservationUncertainties
3.2BayesianEstimationofModelUncertainty
3.2.1ExtensiontoMultiplicativeModelCorrectionFactor
3.2.2ExtensiontoCensoredObservedData
3.2.3ExtensiontoModelCorrectionFunctions
3.3CharacteristicsofCrossSystemModelUncertaintyCharacterization
3.3.1RoleofPriorInformation
3.3.2InterpretationofDeterminedModelUncertainty
3.4AssignmentofPriorUncertainties
3.4.1GeneralGuidelinesforDeterminingf(xi)
3.4.2PriorDistributionforModelUncertaintyParameters
3.5DecisionInvolvedinModelUncertaintyCharacterization
3.5.1SelectionofModelCorrectionFactors
3.5.2UseofModelCorrectionFunction
3.6PredictionofSystemResponses
3.7PossibleSolutionstotheBayesianFramework
3.8Summary

Chapter4SimplifiedBayesianFrameworkforCharacterizingModelUncertainty
4.1Introduction
4.2ApproximateFormulationforCharacterizingModelUncertainty
4.3DiscussionofPriorDistributionsonModelUncertaintyParameters
4.4CharacterizingModelUncertaintybasedontheApproximateFormulation
4.4.1MaximumPosteriorDensityMethod
4.4.2GridCalculationMethod
4.4.3MCMCSimulation
4.5ComparisonofModelUncertaintyFactors
4.5.1SpreadsheetMethod
4.5.2GridCalculationMethod
4.6ApproximatePredictionofSystemResponse
4.7ExtensiontoModelCorrectionFunctions
4.8AnIllustrationExample
4.8.1Background
4.8.2PriorKnowledgeinModelUncertaintyParameters
4.8.3TestUncertainty
4.8.4Calculationof霨(x)and驡(x)
4.8.5SpreadsheetImplementationoftheMaximumPosteriorMethod
4.8.6ComparisonofMethodsforModelUncertaintyCharacterization
4.9Summary

Chapter5EfficientMarkovChainforIdentifyingGeoteehniealModelUncertainty
5.1Introduction
5.2StudyofEfficientMarkovChainforCharacterizingModelUncertainty
5.2.1MarkovChainsunderInvestigation
5.2.2ComparisonofMarkovChains
5.3HybridMarkovChainforModelUncertaintyCharacterizationintheOriginalBayesianFramework
5.3.1StructureoftheHybridMarkovChain
5.3.2DeterminationoftheJumpingFunctions
5.3.3CheckofConvergence
5.4ApplicationtotheSlopeStabilityModelExample
5.4.1PerformanceoftheMarkovChain
5.4.2CheckofConvergence
5.4.3PosteriorDistributions
5.4.4AccuracyofApproximateMethods
5.5ExtensiontoModelCorrectionFunctionCalibration
5.6Summary

Chapter6ProbabilisticBack-AnalysisofSlopeFailure
6.1Introduction
6.2FurtherStudyonModelUncertaintyofLimitEquilibriumMethods
6.2.1EffectofTestUncertainty
6.2.2EffectofQualityofTestData
6.2.3EffectofAmountofTestData
6.3BackAnalysisofSlopeFailurewithUnknownModelUncertainty
6.3.1BayesianFormulation
6.3.2MCMCSimulation
6.3.3ResponseSurfaceApproximation
6.3.4IllustrativeExample
6.4BackAnalysisofSlopeFailurewithKnownModelUncertainty
6.4.1TheoryofBackAnalysiswithKnownModelUncertainty
6.4.2Step-by-stepImplementation
6.4.3ReanalysisofShekKipMeiLandslide
6.5Summary

Chapter7ReliabilityBasedDesignofPileFoundation
7.1Introduction
7.2ProblemDescription
7.3ModelUncertaintyCharacterization
7.3.1ModelUncertaintyCharacterizationUsingApproximateMethods
7.3.2ModelUncertaintyCharacterizationintheOriginalBayesianFramework
7.3.3ComparisonofResults
7.3.4EffectofDataCensoringonModelUncertaintyCharacterization
7.3.5RoleofModelUncertaintyinPileCapacityPrediction
7.4ComparisonofProbabilisticModelsforModelUncertaintyCharacterization
7.4.1UseofAdditiveModelCorrectionFactor
7.4.2UseofModelCorrectionFunctions
7.5ReliabilityBasedDesignofPileFoundations
7.5.1DesignPointMethod
7.5.2ApplicationtoPileCapacityModel
7.5.3AdjustmentinConsiderationofStructuralCodes
7.5.4RegressionAnalysesofPartialFactors
7.6ReliabilityBasedDesignwithEffectiveStressApproach
7.7ComparisonoftheSPTMethodandEffectiveStressMethod
7.8Summary

Chapter8CharacterizingtheModelUncertaintyofaLiquefactionModel
8.1Introduction
8.2ProblemDescription
8.2.1LiquefactionModelunderInvestigation
8.2.2CalibrationDatabase
8.2.3ParameterUncertainty
8.3DeterminationofModelUncertainty
8.3.1BayesianFormulation
8.3.2Choice-basedSamplingBias
8.3.3PriorProbabilisticAnalysisofLiquefactionData
8.3.4CalibrationResults
8.3.5RoleofModelUncertaintyinLiquefactionPotentialEvaluation
8.3.6DeterminationofTargetFactorofSafety
8.4Summary
AppendixA
AppendixB
References

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描述岩土工程模型不确定性特征的贝叶斯方法

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