C
Costas Papadimitriou
Researcher at University of Thessaly
Publications - 249
Citations - 6799
Costas Papadimitriou is an academic researcher from University of Thessaly. The author has contributed to research in topics: Bayesian inference & Uncertainty quantification. The author has an hindex of 37, co-authored 220 publications receiving 5417 citations. Previous affiliations of Costas Papadimitriou include Hong Kong University of Science and Technology & California Institute of Technology.
Papers
More filters
Journal ArticleDOI
Optimal sensor placement methodology for parametric identification of structural systems
TL;DR: The theoretical and computational issues arising in the selection of the optimal sensor configuration for parameter estimation in structural dynamics are addressed and two algorithms are proposed for constructing effective sensor configurations that are superior in terms of computational efficiency and accuracy to the sensor configurations provided by genetic algorithms.
Journal ArticleDOI
A dual Kalman filter approach for state estimation via output-only acceleration measurements
TL;DR: In this article, a dual implementation of the Kalman filter for estimating the unknown input and states of a linear state-space model by using sparse noisy acceleration measurements is proposed, which avoids numerical issues attributed to unobservability and rank deficiency of the augmented formulation of the problem.
Journal ArticleDOI
Entropy-Based Optimal Sensor Location for Structural Model Updating
TL;DR: The proposed entropy-based measure of uncertainty is well-suited for making quantitative evaluations and comparisons of the quality of the parameter estimates that can be achieved using sensor configurations with different numbers of sensors in each configuration.
Journal ArticleDOI
Updating robust reliability using structural test data
TL;DR: In this article, the concept of robust reliability is defined to take into account uncertainties from structural modeling in addition to the uncertain excitement that a structure will experience during its lifetime, and a Bayesian probabilistic methodology for system identification is integrated for updating the assessment of the robust reliability based on dynamic test data.
Journal ArticleDOI
Asymptotic Expansions for Reliability and Moments of Uncertain Systems
TL;DR: In this paper, an asymptotic approximation for evaluating the probability integrals that arise in the determination of the reliability and response moments of uncertain dynamic systems subject to stochastic excitation is developed.