Probabilistic finite element model updating using Bayesian statistics: applications to aeronautical and mechanical engineering
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Chichester, UK
John Wiley & Sons
2016
|
| Schlagworte: | |
| Online-Zugang: | FRO01 UBG01 Volltext |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | 1 online resource |
| ISBN: | 111915300X 1119153018 1119153026 9781119153009 9781119153016 9781119153023 |
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| 245 | 1 | 0 | |a Probabilistic finite element model updating using Bayesian statistics |b applications to aeronautical and mechanical engineering |c Tshilidzi Marwala, Ilyes Boulkaibet, and Sondipon Adhikari |
| 264 | 1 | |a Chichester, UK |b John Wiley & Sons |c 2016 | |
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| 505 | 8 | |a Title Page ; Copyright; Contents; Acknowledgements; Nomenclature ; Chapter 1 Introduction to Finite Element Model Updating ; 1.1 Introduction; 1.2 Finite Element Modelling; 1.3 Vibration Analysis; 1.3.1 Modal Domain Data; 1.3.2 Frequency Domain Data; 1.4 Finite Element Model Updating; 1.5 Finite Element Model Updating and Bounded Rationality; 1.6 Finite Element Model Updating Methods; 1.6.1 Direct Methods; 1.6.2 Iterative Methods; 1.6.3 Artificial Intelligence Methods; 1.6.4 Uncertainty Quantification Methods; 1.7 Bayesian Approach versus Maximum Likelihood Method; 1.8 Outline of the Book | |
| 505 | 8 | |a Chapter 3 Bayesian Statistics in Structural Dynamics 3.1 Introduction; 3.2 Bayes ́Rule; 3.3 Maximum Likelihood Method; 3.4 Maximum a Posteriori Parameter Estimates; 3.5 Laplaceś Method; 3.6 Prior, Likelihood and Posterior Function of a Simple Dynamic Example; 3.6.1 Likelihood Function; 3.6.2 Prior Function; 3.6.3 Posterior Function; 3.6.4 Gaussian Approximation; 3.7 The Posterior Approximation; 3.7.1 Objective Function; 3.7.2 Optimisation Approach; 3.7.3 Case Example; 3.8 Sampling Approaches for Estimating Posterior Distribution; 3.8.1 Monte Carlo Method | |
| 505 | 8 | |a 3.8.2 Markov Chain Monte Carlo Method3.8.3 Simulated Annealing; 3.8.4 Gibbs Sampling; 3.9 Comparison between Approaches; 3.9.1 Numerical Example; 3.10 Conclusions; References; Chapter 4 Metropolis-Hastings and Slice Sampling for Finite Element Updating ; 4.1 Introduction; 4.2 Likelihood, Prior and the Posterior Functions; 4.3 The Metropolis-Hastings Algorithm; 4.4 The Slice Sampling Algorithm; 4.5 Statistical Measures; 4.6 Application 1: Cantilevered Beam; 4.7 Application 2: Asymmetrical H-Shaped Structure; 4.8 Conclusions; References | |
| 505 | 8 | |a Chapter 5 Dynamically Weighted Importance Sampling for Finite Element Updating 5.1 Introduction; 5.2 Bayesian Modelling Approach; 5.3 Metropolis-Hastings (M-H) Algorithm; 5.4 Importance Sampling; 5.5 Dynamically Weighted Importance Sampling; 5.5.1 Markov Chain; 5.5.2 Adaptive Pruned-Enriched Population Control Scheme; 5.5.3 Monte Carlo Dynamically Weighted Importance Sampling; 5.6 Application 1: Cantilevered Beam; 5.7 Application 2: H-Shaped Structure; 5.8 Conclusions; References; Chapter 6 Adaptive Metropolis-Hastings for Finite Element Updating ; 6.1 Introduction | |
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| 650 | 4 | |a Finite element method | |
| 650 | 4 | |a Bayesian statistical decision theory | |
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Datensatz im Suchindex
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| author | Marwala, Tshilidzi Boulkaibet, Ilyes Adhikari, Sondipon |
| author_facet | Marwala, Tshilidzi Boulkaibet, Ilyes Adhikari, Sondipon |
| author_role | aut aut aut |
| author_sort | Marwala, Tshilidzi |
| author_variant | t m tm i b ib s a sa |
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| bvnumber | BV043897353 |
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| contents | Title Page ; Copyright; Contents; Acknowledgements; Nomenclature ; Chapter 1 Introduction to Finite Element Model Updating ; 1.1 Introduction; 1.2 Finite Element Modelling; 1.3 Vibration Analysis; 1.3.1 Modal Domain Data; 1.3.2 Frequency Domain Data; 1.4 Finite Element Model Updating; 1.5 Finite Element Model Updating and Bounded Rationality; 1.6 Finite Element Model Updating Methods; 1.6.1 Direct Methods; 1.6.2 Iterative Methods; 1.6.3 Artificial Intelligence Methods; 1.6.4 Uncertainty Quantification Methods; 1.7 Bayesian Approach versus Maximum Likelihood Method; 1.8 Outline of the Book Chapter 3 Bayesian Statistics in Structural Dynamics 3.1 Introduction; 3.2 Bayes ́Rule; 3.3 Maximum Likelihood Method; 3.4 Maximum a Posteriori Parameter Estimates; 3.5 Laplaceś Method; 3.6 Prior, Likelihood and Posterior Function of a Simple Dynamic Example; 3.6.1 Likelihood Function; 3.6.2 Prior Function; 3.6.3 Posterior Function; 3.6.4 Gaussian Approximation; 3.7 The Posterior Approximation; 3.7.1 Objective Function; 3.7.2 Optimisation Approach; 3.7.3 Case Example; 3.8 Sampling Approaches for Estimating Posterior Distribution; 3.8.1 Monte Carlo Method 3.8.2 Markov Chain Monte Carlo Method3.8.3 Simulated Annealing; 3.8.4 Gibbs Sampling; 3.9 Comparison between Approaches; 3.9.1 Numerical Example; 3.10 Conclusions; References; Chapter 4 Metropolis-Hastings and Slice Sampling for Finite Element Updating ; 4.1 Introduction; 4.2 Likelihood, Prior and the Posterior Functions; 4.3 The Metropolis-Hastings Algorithm; 4.4 The Slice Sampling Algorithm; 4.5 Statistical Measures; 4.6 Application 1: Cantilevered Beam; 4.7 Application 2: Asymmetrical H-Shaped Structure; 4.8 Conclusions; References Chapter 5 Dynamically Weighted Importance Sampling for Finite Element Updating 5.1 Introduction; 5.2 Bayesian Modelling Approach; 5.3 Metropolis-Hastings (M-H) Algorithm; 5.4 Importance Sampling; 5.5 Dynamically Weighted Importance Sampling; 5.5.1 Markov Chain; 5.5.2 Adaptive Pruned-Enriched Population Control Scheme; 5.5.3 Monte Carlo Dynamically Weighted Importance Sampling; 5.6 Application 1: Cantilevered Beam; 5.7 Application 2: H-Shaped Structure; 5.8 Conclusions; References; Chapter 6 Adaptive Metropolis-Hastings for Finite Element Updating ; 6.1 Introduction |
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| dewey-full | 620.001/51825 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 620 - Engineering and allied operations |
| dewey-raw | 620.001/51825 |
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| spelling | Marwala, Tshilidzi aut Probabilistic finite element model updating using Bayesian statistics applications to aeronautical and mechanical engineering Tshilidzi Marwala, Ilyes Boulkaibet, and Sondipon Adhikari Chichester, UK John Wiley & Sons 2016 1 online resource txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references and index Title Page ; Copyright; Contents; Acknowledgements; Nomenclature ; Chapter 1 Introduction to Finite Element Model Updating ; 1.1 Introduction; 1.2 Finite Element Modelling; 1.3 Vibration Analysis; 1.3.1 Modal Domain Data; 1.3.2 Frequency Domain Data; 1.4 Finite Element Model Updating; 1.5 Finite Element Model Updating and Bounded Rationality; 1.6 Finite Element Model Updating Methods; 1.6.1 Direct Methods; 1.6.2 Iterative Methods; 1.6.3 Artificial Intelligence Methods; 1.6.4 Uncertainty Quantification Methods; 1.7 Bayesian Approach versus Maximum Likelihood Method; 1.8 Outline of the Book Chapter 3 Bayesian Statistics in Structural Dynamics 3.1 Introduction; 3.2 Bayes ́Rule; 3.3 Maximum Likelihood Method; 3.4 Maximum a Posteriori Parameter Estimates; 3.5 Laplaceś Method; 3.6 Prior, Likelihood and Posterior Function of a Simple Dynamic Example; 3.6.1 Likelihood Function; 3.6.2 Prior Function; 3.6.3 Posterior Function; 3.6.4 Gaussian Approximation; 3.7 The Posterior Approximation; 3.7.1 Objective Function; 3.7.2 Optimisation Approach; 3.7.3 Case Example; 3.8 Sampling Approaches for Estimating Posterior Distribution; 3.8.1 Monte Carlo Method 3.8.2 Markov Chain Monte Carlo Method3.8.3 Simulated Annealing; 3.8.4 Gibbs Sampling; 3.9 Comparison between Approaches; 3.9.1 Numerical Example; 3.10 Conclusions; References; Chapter 4 Metropolis-Hastings and Slice Sampling for Finite Element Updating ; 4.1 Introduction; 4.2 Likelihood, Prior and the Posterior Functions; 4.3 The Metropolis-Hastings Algorithm; 4.4 The Slice Sampling Algorithm; 4.5 Statistical Measures; 4.6 Application 1: Cantilevered Beam; 4.7 Application 2: Asymmetrical H-Shaped Structure; 4.8 Conclusions; References Chapter 5 Dynamically Weighted Importance Sampling for Finite Element Updating 5.1 Introduction; 5.2 Bayesian Modelling Approach; 5.3 Metropolis-Hastings (M-H) Algorithm; 5.4 Importance Sampling; 5.5 Dynamically Weighted Importance Sampling; 5.5.1 Markov Chain; 5.5.2 Adaptive Pruned-Enriched Population Control Scheme; 5.5.3 Monte Carlo Dynamically Weighted Importance Sampling; 5.6 Application 1: Cantilevered Beam; 5.7 Application 2: H-Shaped Structure; 5.8 Conclusions; References; Chapter 6 Adaptive Metropolis-Hastings for Finite Element Updating ; 6.1 Introduction TECHNOLOGY & ENGINEERING / Engineering (General) bisacsh TECHNOLOGY & ENGINEERING / Reference bisacsh Bayesian statistical decision theory fast Engineering / Mathematical models fast Finite element method fast Ingenieurwissenschaften Mathematisches Modell Finite element method Bayesian statistical decision theory Engineering / Mathematical models Boulkaibet, Ilyes aut Adhikari, Sondipon aut Erscheint auch als Druckausgabe 978-1-119-15303-0 https://onlinelibrary.wiley.com/doi/book/10.1002/9781119153023 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Marwala, Tshilidzi Boulkaibet, Ilyes Adhikari, Sondipon Probabilistic finite element model updating using Bayesian statistics applications to aeronautical and mechanical engineering Title Page ; Copyright; Contents; Acknowledgements; Nomenclature ; Chapter 1 Introduction to Finite Element Model Updating ; 1.1 Introduction; 1.2 Finite Element Modelling; 1.3 Vibration Analysis; 1.3.1 Modal Domain Data; 1.3.2 Frequency Domain Data; 1.4 Finite Element Model Updating; 1.5 Finite Element Model Updating and Bounded Rationality; 1.6 Finite Element Model Updating Methods; 1.6.1 Direct Methods; 1.6.2 Iterative Methods; 1.6.3 Artificial Intelligence Methods; 1.6.4 Uncertainty Quantification Methods; 1.7 Bayesian Approach versus Maximum Likelihood Method; 1.8 Outline of the Book Chapter 3 Bayesian Statistics in Structural Dynamics 3.1 Introduction; 3.2 Bayes ́Rule; 3.3 Maximum Likelihood Method; 3.4 Maximum a Posteriori Parameter Estimates; 3.5 Laplaceś Method; 3.6 Prior, Likelihood and Posterior Function of a Simple Dynamic Example; 3.6.1 Likelihood Function; 3.6.2 Prior Function; 3.6.3 Posterior Function; 3.6.4 Gaussian Approximation; 3.7 The Posterior Approximation; 3.7.1 Objective Function; 3.7.2 Optimisation Approach; 3.7.3 Case Example; 3.8 Sampling Approaches for Estimating Posterior Distribution; 3.8.1 Monte Carlo Method 3.8.2 Markov Chain Monte Carlo Method3.8.3 Simulated Annealing; 3.8.4 Gibbs Sampling; 3.9 Comparison between Approaches; 3.9.1 Numerical Example; 3.10 Conclusions; References; Chapter 4 Metropolis-Hastings and Slice Sampling for Finite Element Updating ; 4.1 Introduction; 4.2 Likelihood, Prior and the Posterior Functions; 4.3 The Metropolis-Hastings Algorithm; 4.4 The Slice Sampling Algorithm; 4.5 Statistical Measures; 4.6 Application 1: Cantilevered Beam; 4.7 Application 2: Asymmetrical H-Shaped Structure; 4.8 Conclusions; References Chapter 5 Dynamically Weighted Importance Sampling for Finite Element Updating 5.1 Introduction; 5.2 Bayesian Modelling Approach; 5.3 Metropolis-Hastings (M-H) Algorithm; 5.4 Importance Sampling; 5.5 Dynamically Weighted Importance Sampling; 5.5.1 Markov Chain; 5.5.2 Adaptive Pruned-Enriched Population Control Scheme; 5.5.3 Monte Carlo Dynamically Weighted Importance Sampling; 5.6 Application 1: Cantilevered Beam; 5.7 Application 2: H-Shaped Structure; 5.8 Conclusions; References; Chapter 6 Adaptive Metropolis-Hastings for Finite Element Updating ; 6.1 Introduction TECHNOLOGY & ENGINEERING / Engineering (General) bisacsh TECHNOLOGY & ENGINEERING / Reference bisacsh Bayesian statistical decision theory fast Engineering / Mathematical models fast Finite element method fast Ingenieurwissenschaften Mathematisches Modell Finite element method Bayesian statistical decision theory Engineering / Mathematical models |
| title | Probabilistic finite element model updating using Bayesian statistics applications to aeronautical and mechanical engineering |
| title_auth | Probabilistic finite element model updating using Bayesian statistics applications to aeronautical and mechanical engineering |
| title_exact_search | Probabilistic finite element model updating using Bayesian statistics applications to aeronautical and mechanical engineering |
| title_full | Probabilistic finite element model updating using Bayesian statistics applications to aeronautical and mechanical engineering Tshilidzi Marwala, Ilyes Boulkaibet, and Sondipon Adhikari |
| title_fullStr | Probabilistic finite element model updating using Bayesian statistics applications to aeronautical and mechanical engineering Tshilidzi Marwala, Ilyes Boulkaibet, and Sondipon Adhikari |
| title_full_unstemmed | Probabilistic finite element model updating using Bayesian statistics applications to aeronautical and mechanical engineering Tshilidzi Marwala, Ilyes Boulkaibet, and Sondipon Adhikari |
| title_short | Probabilistic finite element model updating using Bayesian statistics |
| title_sort | probabilistic finite element model updating using bayesian statistics applications to aeronautical and mechanical engineering |
| title_sub | applications to aeronautical and mechanical engineering |
| topic | TECHNOLOGY & ENGINEERING / Engineering (General) bisacsh TECHNOLOGY & ENGINEERING / Reference bisacsh Bayesian statistical decision theory fast Engineering / Mathematical models fast Finite element method fast Ingenieurwissenschaften Mathematisches Modell Finite element method Bayesian statistical decision theory Engineering / Mathematical models |
| topic_facet | TECHNOLOGY & ENGINEERING / Engineering (General) TECHNOLOGY & ENGINEERING / Reference Bayesian statistical decision theory Engineering / Mathematical models Finite element method Ingenieurwissenschaften Mathematisches Modell |
| url | https://onlinelibrary.wiley.com/doi/book/10.1002/9781119153023 |
| work_keys_str_mv | AT marwalatshilidzi probabilisticfiniteelementmodelupdatingusingbayesianstatisticsapplicationstoaeronauticalandmechanicalengineering AT boulkaibetilyes probabilisticfiniteelementmodelupdatingusingbayesianstatisticsapplicationstoaeronauticalandmechanicalengineering AT adhikarisondipon probabilisticfiniteelementmodelupdatingusingbayesianstatisticsapplicationstoaeronauticalandmechanicalengineering |