Listar por tema "Model updating"
Mostrando ítems 1-20 de 20
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Adaptive Bayesian Inference Framework for Joint Model and Noise Identification
(2022)Model updating, the process of inferring a model from data, is prone to the adverse effects of modeling error, which is caused by simplification and idealization assumptions in the mathematical models. In this study, an ... -
Bridge health monitoring system based on vibration measurements
(2009)A bridge health monitoring system is presented based on vibration measurements collected from a network of acceleration sensors. Sophisticated structural identification methods, combining information from the sensor network ... -
Component mode synthesis techniques for finite element model updating
(2013)Deterministic and Bayesian finite element (FE) model updating techniques are computationally very demanding operations due to the large number of FE model re-analyses required. Component mode synthesis techniques are ... -
Data features-based likelihood-informed Bayesian finite element model updating
(2019)A new formulation for likelihood-informed Bayesian inference is proposed in this work based on probability models introduced for the features between the measurements and model predictions. The formulation applies to both ... -
Data-driven uncertainty quantification and propagation in structural dynamics through a hierarchical Bayesian framework
(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 ... -
The effect of prediction error correlation on optimal sensor placement in structural dynamics
(2012)The problem of estimating the optimal sensor locations for parameter estimation in structural dynamics is re-visited. The effect of spatially correlated prediction errors on the optimal sensor placement is investigated. ... -
Finite element model validation and predictions using dynamic reduction techniques
(2011)Finite element (FE) model updating and validation techniques are formulated as single and multi-objective optimization problems. A multi-objective optimization framework results in multiple Pareto optimal models that are ... -
Hierarchical bayesian model updating for probabilistic damage identification
(2015)This paper presents the newly developed Hierarchical Bayesian model updating method for identification of civil structures. The proposed updating method is suitable for uncertainty quantification of model updating parameters, ... -
Hierarchical Bayesian modeling framework for model updating and robust predictions in structural dynamics using modal features
(2022)The hierarchical Bayesian modeling (HBM) framework has recently been developed to tackle the uncertainty quantification and propagation in structural dynamics inverse problems. This new framework characterizes the ensemble ... -
Hierarchical Bayesian uncertainty quantification of Finite Element models using modal statistical information
(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) ... -
Model calibration of metsovo bridge using ambient vibration measurements from various construction phases
(2015)Available methods for structural model updating are employed to develop high fidelity models of the soil-foundation-structure of Metsovo bridge using ambient vibration measurements. The Metsovo bridge, the highest bridge ... -
A Nonlinear Model Inversion Method for Joint System Parameter, Noise, and Input Identification of Civil Structures
(2017)This paper presents a framework for nonlinear system identification of civil structures using sparsely measured dynamic output response of the structure. Using a sequential maximum likelihood estimation (MLE) approach, the ... -
Online damage detection via a synergy of proper orthogonal decomposition and recursive Bayesian filters
(2017)In this paper, an approach based on the synergistic use of proper orthogonal decomposition and Kalman filtering is proposed for the online health monitoring of damaged structures. The reduced-order model of a structure is ... -
Pareto optimal structural models and predictions consistent with data and modal residuals
(2008)A multi-objective identification method for model updating based on modal residuals is proposed. The method results in multiple Pareto optimal structural models that are consistent with the measured modal data, the class ... -
Probabilistic hierarchical Bayesian framework for time-domain model updating and robust predictions
(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 ... -
Structural identification of Egnatia Odos bridges based on ambient and earthquake induced vibrations
(2009)The dynamic characteristics of two representative R/C bridges on Egnatia Odos motorway in Greece are estimated based on low amplitude ambient and earthquake-induced vibrations. The present work outlines the instrumentation ... -
Structural model updating and prediction variability using Pareto optimal models
(2008)A multi-objective identification method for structural model updating based on modal residuals is presented. The method results in multiple Pareto optimal structural models that are consistent with the experimentally ... -
System identification of a R/C bridge based on ambient vibrations and 3D numerical simulations of the entire soil-structure system
(2011)The scope of this paper is to identify the parameters affecting the dynamic response of an existing R/C bridge, based on low ambient amplitude vibration measurements and numerical predictions using complex finite element ... -
Two-Stage Hierarchical Bayesian Framework for Finite Element Model Updating
(2020)A hierarchical Bayesian modeling (HBM) framework is presented for updating finite element (FE) models. A two stage approach is proposed for which in the first stage the modal data properties (modal frequencies, damping ... -
Uncertainty calibration of large-order models of bridges using ambient vibration measurements
(2014)A computational efficient Bayesian inference framework based on stochastic simulation algorithms is presented for calibrating the parameters of large-order linear finite element (FE) models of bridges. The effectiveness ...