Next:
List of Figures
Up:
Bayesian Modelling of Short
Previous:
Acknowledgements
Contents
List of Figures
List of Tables
Introduction
Review of Current Models
Statistical Methodology
Growth Model
Coalescence
Joint Model
Overall Framework and Major Contributions
Modelling Fatigue and Crack Propagation
Factors Important to Modelling Fatigue
Specimen Geometry
Material Properties
Nature of Loading
Statistics of Interest
Manufacturing Issues
Deterministic Models for Crack Growth
Wöhler or S-N Curve
Empirical Models
Paris-Erdogan Equation
Forman Equation
Theoretical Models
Cumulative Damage Theories
Elastic Fatigue Fracture
J Integral Methods
Empirical Stochastic Parameterisation
Stochastic Models
Fatigue Crack Growth Process
Current Research Questions
Growth Aspect
Coalescence Aspect
Other Considerations
Statistical Methodology
Statistics
Bayesian Approach
Formal Bayesian Methodology
Prior Knowledge
Model or Likelihood
An Example
Posterior Distribution
Predictive Distribution
Kernel Density Estimation
A Simple Example -
Prior Elicitation and Non-informative Priors
Sampling from the Posterior Distribution
Stratified Sampling
Importance Sampling
Monte Carlo Method
Markov Chains
Markov Chain Monte Carlo
Metropolis Hastings
Gibbs Sampling
Issues of Convergence
Nature of Multidimensional Posterior
Graphical Representation of a Model
Growth Model
Stages of Crack Growth
Characteristics of Microcracks
Experimental Details
Data
Treatment of Raw Data - Coalescence
Model
Hierarchical Population Model
Directed Graph
Analysis
Likelihood
Priors for the Parameters
Priors on
,
M
and
d
.
Evaluation of the Posterior distribution
Evaluation of Other Quantities
Practicalities
Evaluation of
Sampling from Posterior
Algorithm
Preliminaries
Algorithm
Assessing Convergence
Transforming the Variables
Programming
Results
Conclusions
Coalescence
Motivation
Fatigue in PMMA
Data
Preliminary Analysis
Model
Analysis
Likelihood
Priors
Evaluation of Posterior
Results
Conclusions
Combining Coalescence and Growth
Background
Data
Model
Analysis
Likelihood
Priors
Evaluation of Posterior
Results
Conclusions
Summary & Conclusions
Summary of Growth Model
Summary of Coalescence Model
Summary of Joint Model
Conclusions
Further Work
Spatial Aspect
Methodological Issues
Factors Influencing Coalescence
General Process of Failure
Alternative Growth Models
Closing Remarks
Calculations
Bayes Theorem
Inverse Gamma
Constant Variance Growth Model
Multiplicative Variance Growth Model
Acceptance Probabilities
Growth Model for
with Multiplicative Variance
Growth Model for
Constant Variance
References
About this document ...
Cathal Walsh
Sat Jan 22 17:09:53 GMT 2000