Sfoglia per Soggetto "Model errors"
Items 1-7 di 7
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Accounting for amplitude of excitation in model updating through a hierarchical Bayesian approach: Application to a two-story reinforced concrete building
(2019)Calibrated linear equivalent models of civil structures are often used for response prediction and performance assessment. However, these models are only valid for a narrow range of excitation level for which these models ... -
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 ... -
Adaptive Kalman filters for nonlinear finite element model updating
(2020)This paper presents two adaptive Kalman filters (KFs) for nonlinear model updating where, in addition to nonlinear model parameters, the covariance matrix of measurement noise is estimated recursively in a near online ... -
Hierarchical Bayesian calibration and response prediction of a 10-story building model
(2019)This paper presents Hierarchical Bayesian model updating of a 10-story building model based on the identified modal parameters. The identified modal parameters are numerically simulated using a frame model (exact model) ... -
Nonlinear Model Updating Using Recursive and Batch Bayesian Methods
(2020)This paper studies the performance of recursive and batch Bayesian methods for nonlinear model updating. Unscented Kalman filter (UKF) is selected to represent the recursive Bayesian method, and two UKF approaches are ... -
Probabilistic damage identification of a designed 9-story building using modal data in the presence of modeling errors
(2017)Validity and accuracy of model based identification techniques such as linear finite element (FE) model updating are sensitive to modeling errors. Models used for the design and performance assessment of civil structures ... -
Robust optimal sensor configuration using the value of information
(2022)Sensing is the cornerstone of any functional structural health monitoring technology, with sensor number and placement being a key aspect for reliable monitoring. We introduce for the first time a robust methodology for ...