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|a 9783030836405
|q (electronic bk.)
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|z 9783030836399
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|a (MiAaPQ)EBC6824949
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|a (Au-PeEL)EBL6824949
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|a (OCoLC)1290485018
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|a MiAaPQ
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|c MiAaPQ
|d MiAaPQ
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|a QA276-280
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|a Aslett, Louis J. M.
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|a Uncertainty in Engineering :
|b Introduction to Methods and Applications.
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| 250 |
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|a 1st ed.
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| 264 |
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1 |
|a Cham :
|b Springer International Publishing AG,
|c 2021.
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| 264 |
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4 |
|c Ã2022.
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| 300 |
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|a 1 online resource (148 pages)
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
1 |
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|a SpringerBriefs in Statistics Series
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| 505 |
0 |
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|a 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.
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| 505 |
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|a 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.
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|a 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.
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| 588 |
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|a Description based on publisher supplied metadata and other sources.
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| 590 |
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|a Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2023. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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| 655 |
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4 |
|a Electronic books.
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| 700 |
1 |
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|a Coolen, Frank P. A.
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| 700 |
1 |
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|a De Bock, Jasper.
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| 776 |
0 |
8 |
|i Print version:
|a Aslett, Louis J. M.
|t Uncertainty in Engineering
|d Cham : Springer International Publishing AG,c2021
|z 9783030836399
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| 797 |
2 |
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|a ProQuest (Firm)
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| 830 |
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0 |
|a SpringerBriefs in Statistics Series
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| 856 |
4 |
0 |
|u https://ebookcentral.proquest.com/lib/matrademy/detail.action?docID=6824949
|z Click to View
|
