Bayesian updating of mechanical models-Application in fracture mechanics

@inproceedings{Perrin2007BayesianUO,
  title={Bayesian updating of mechanical models-Application in fracture mechanics},
  author={Fr{\'e}d{\'e}ric Perrin and B. Sudret and Maurice Pendola},
  year={2007}
}
The objective of this paper is to develop a general framework for updating the predictions of models of structures using observations gathered from the monitoring of these structures. A general Bayesian updating scheme is developed, combining prior information on model parameters and monitoring data (including measurement uncertainties). A Markov chain Monte-Carlo (MCMC) sampling method is used for computing the posterior probability density functions (PDF) of input random variables. Then the… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.

References

Publications referenced by this paper.
Showing 1-10 of 10 references

Bayesian prediction of elastic modulus of concrete

P. Geyskens, A. Der Kiureghian, P. Monteiro
J. Struct. Eng • 1993
View 4 Excerpts
Highly Influenced

The statistical nature of fatigue crack propagation

D. A. Virkler, B. M. Hillberry, P. K. Goel
Trans. ASME, J. Eng. Mat. Tech • 1979
View 3 Excerpts
Highly Influenced

Comparison of Markov chain Monte-Carlo simulation and a FORM-based approach for Bayesian updating of mechanical models

F. Perrin, B. Sudret, M. Pendola, E. de Rocquigny
In 10 Int. Conf on Applications of Stat. and Prob. in Civil Engineering, • 2007
View 1 Excerpt

A probabilistic approach to structural model updating

L. S. Katafygiotis, C. Papadimitriou, H. F. Lam
Soil Dyn. Earth. Eng • 1998
View 1 Excerpt

A critical analysis of crack propagation laws

P. Paris, F. Erdogan
Trans. the ASME, J. Basic Eng • 1963