Browsing by Author "Sedehi O., Papadimitriou C., Katafygiotis L.S."
Now showing items 1-4 of 4
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Data-driven uncertainty quantification and propagation in structural dynamics through a hierarchical Bayesian framework
Sedehi O., Papadimitriou C., Katafygiotis L.S. (2020)In the presence of modeling errors, the mainstream Bayesian methods seldom give a realistic account of uncertainties as they commonly underestimate the inherent variability of parameters. This problem is not due to any ... -
Hierarchical Bayesian uncertainty quantification of dynamical models utilizing modal statistical information
Sedehi O., Papadimitriou C., Katafygiotis L.S. (2020)Updating dynamical models based on experimental modal information has become an important topic in structural health monitoring. This paper revisits this significant problem and develops a new two-stage hierarchical Bayesian ... -
Hierarchical Bayesian uncertainty quantification of Finite Element models using modal statistical information
Sedehi O., Papadimitriou C., Katafygiotis L.S. (2022)This paper develops a Hierarchical Bayesian Modeling (HBM) framework for uncertainty quantification of Finite Element (FE) models based on modal information. This framework uses an existing Fast Fourier Transform (FFT) ... -
Probabilistic hierarchical Bayesian framework for time-domain model updating and robust predictions
Sedehi O., Papadimitriou C., Katafygiotis L.S. (2019)A new time-domain hierarchical Bayesian framework is proposed to improve the performance of Bayesian methods in terms of reliability and robustness of estimates particularly for uncertainty quantification and propagation ...