57 citations · 127 across the 6 of their papers we have counts for
6 papers
On the Integration of Physics-Based Machine Learning with Hierarchical Bayesian Modeling Techniques
Omid Sedehi, Antonina M. Kosikova, Costas Papadimitriou +1
Machine Learning (ML) has widely been used for modeling and predicting physical systems. These techniques offer high expressive power and good generalizability for interpolation wi…
Bayesian Structural Identification using Gaussian Process Discrepancy Models
Antonina M. Kosikova, Omid Sedehi, Costas Papadimitriou +1
Bayesian model updating based on Gaussian Process (GP) models has received attention in recent years, which incorporates kernel-based GPs to provide enhanced fidelity response pred…
Input-State-Parameter-Noise Identification and Virtual Sensing in Dynamical Systems: A Bayesian Expectation-Maximization (BEM) Perspective
Daniz Teymouri, Omid Sedehi, Lambros S. Katafygiotis +1
Structural identification and damage detection can be generalized as the simultaneous estimation of input forces, physical parameters, and dynamical states. Although Kalman-type fi…
Hierarchical Bayesian Uncertainty Quantification of Finite Element Models using Modal Statistical Information
Omid Sedehi, Costas Papadimitriou, Lambros S. Katafygiotis
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…
Data-Driven Uncertainty Quantification and Propagation in Structural Dynamics through a Hierarchical Bayesian Framework
Omid Sedehi, Costas Papadimitriou, Lambros S. Katafygiotis
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 para…
Hierarchical Bayesian Operational Modal Analysis: Theory and Computations
Omid Sedehi, Lambros S. Katafygiotis, Costas Papadimitriou
This paper presents a hierarchical Bayesian modeling framework for the uncertainty quantification in modal identification of linear dynamical systems using multiple vibration data…