Uncertainty in Engineering : : Introduction to Methods and Applications.
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Superior document: | SpringerBriefs in Statistics Series |
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TeilnehmendeR: | |
Place / Publishing House: | Cham : : Springer International Publishing AG,, 2021. Ã2022. |
Year of Publication: | 2021 |
Edition: | 1st ed. |
Language: | English |
Series: | SpringerBriefs in Statistics Series
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Online Access: | |
Physical Description: | 1 online resource (148 pages) |
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Table of Contents:
- Intro
- Preface
- Contents
- 1 Introduction to Bayesian Statistical Inference
- 1.1 Introduction
- 1.2 Specification of the Prior
- 1.2.1 Conjugate Priors
- 1.3 Point Estimation
- 1.4 Credible Sets
- 1.5 Hypothesis Test
- 1.5.1 Model Selection
- References
- 2 Sampling from Complex Probability Distributions: A Monte Carlo Primer for Engineers
- 2.1 Motivation
- 2.1.1 Generality of Expectations
- 2.1.2 Why Consider Monte Carlo?
- 2.2 Monte Carlo Estimators
- 2.3 Simple Monte Carlo Sampling Methods
- 2.3.1 Inverse Sampling
- 2.3.2 Rejection Sampling
- 2.3.3 Importance Sampling
- 2.4 Further Reading
- References
- 3 Introduction to the Theory of Imprecise Probability
- 3.1 Introduction
- 3.2 Fundamental Concepts
- 3.2.1 Basic Concepts
- 3.2.2 Coherence
- 3.3 Previsions and Probabilities
- 3.3.1 Previsions as Prices for Gambles
- 3.3.2 Probabilities as Previsions of Indicator Gambles
- 3.3.3 Assessments of Lower Previsions
- 3.3.4 Working on Linear Spaces of Gambles
- 3.4 Sets of Probabilities
- 3.4.1 From Lower Previsions to Credal Sets
- 3.4.2 From Credal Sets to Lower Previsions
- 3.5 Basics of Conditioning
- 3.6 Remarks About Infinite Possibility Spaces
- 3.7 Conclusion
- References
- 4 Imprecise Discrete-Time Markov Chains
- 4.1 Introduction
- 4.2 Precise Probability Models
- 4.3 Imprecise Probability Models
- 4.4 Discrete-Time Uncertain Processes
- 4.5 Imprecise Probability Trees
- 4.6 Imprecise Markov Chains
- 4.7 Examples
- 4.8 A Non-linear Perron-Frobenius Theorem, and Ergodicity
- 4.9 Conclusion
- References
- 5 Statistics with Imprecise Probabilities-A Short Survey
- 5.1 Introduction
- 5.2 Some Elementary Background on Imprecise Probabilities
- 5.3 Types of Imprecision in Statistical Modelling
- 5.4 Statistical Modelling Under Model Imprecision.
- 5.4.1 Probabilistic Assumptions on the Sampling Model Matter: Frequentist Statistics and Imprecise Probabilities
- 5.4.2 Model Imprecision and Generalized Bayesian Inference
- 5.4.3 Some Other Approaches
- 5.5 Statistical Modelling Under Data Imprecision
- 5.6 Concluding Remarks
- References
- 6 Reliability
- 6.1 Introduction
- 6.2 System Reliability Methods
- 6.2.1 Fault Tree Analysis
- 6.2.2 Fault Tree Extensions: Common Cause Failures
- 6.2.3 Phased Mission Analysis
- 6.3 Basic Statistical Concepts and Methods for Reliability Data
- 6.4 Statistical Models for Reliability Data
- 6.5 Stochastic Processes in Reliability-Models and Inference
- 7 Simulation Methods for the Analysis of Complex Systems
- 7.1 Introduction
- 7.2 Reliability Modelling of Systems and Networks
- 7.2.1 Traditional Approaches
- 7.2.2 Interdependencies in Complex Systems
- 7.3 Load Flow Simulation
- 7.3.1 Simulation of Interdependent and Reconfigurable Systems
- 7.3.2 Maintenance Strategy Optimization
- 7.3.3 Case Study: Station Blackout Risk Assessment
- 7.4 Survival Signature Simulation
- 7.4.1 Systems with Imprecision
- 7.4.2 Case Study: Industrial Water Supply System
- 7.5 Final Remarks
- References
- 8 Overview of Stochastic Model Updating in Aerospace Application Under Uncertainty Treatment
- 8.1 Introduction
- 8.2 Overview of the State of the Art: Deterministic or Stochastic?
- 8.3 Overall Technique Route of Stochastic Model Updating
- 8.3.1 Feature Extraction
- 8.3.2 Parameter Selection
- 8.3.3 Surrogate Modelling
- 8.3.4 Test Analysis Correlation: Uncertainty Quantification Metrics
- 8.3.5 Model Adjustment and Validation
- 8.4 Uncertainty Treatment in Parameter Calibration
- 8.4.1 The Bayesian Updating Framework
- 8.4.2 A Novel Uncertainty Quantification Metric
- 8.5 Example: The NASA UQ Challenge.
- 8.6 Conclusions and Prospects
- References
- 9 Aerospace Flight Modeling and Experimental Testing
- 9.1 Introduction
- 9.2 Aerospace Flights and Planetary Re-entry
- 9.3 Similitude Approach for Hypersonic Flows
- 9.3.1 Inviscid Hypersonics
- 9.3.2 Viscous Hypersonics
- 9.3.3 High-Temperature Hypersonics
- 9.4 Duplication of Dissociated Boundary Layer with Surface Reaction
- 9.5 Considering Flow Radiation
- 9.6 Ground Testing Strategy for High-Speed Re-entry
- 9.7 Conclusion
- References.