Probabilistic finite element model updating using Bayesian statistics :
General Material Designation
[Book]
Other Title Information
applications to aeronautical and mechanical engineering /
First Statement of Responsibility
Tshilidzi Marwala, Ilyes Boulkaibet, and Sondipon Adhikari.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index
CONTENTS NOTE
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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
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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
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Chapter 3 Bayesian Statistics in Structural Dynamics 3.1 Introduction; 3.2 Bayeś 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
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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