Dealing with uncertainty in model updating for damage assessment: A review
In structural engineering, model updating is often used for non-destructive damage
assessment: by calibrating stiffness parameters of finite element models based on …
assessment: by calibrating stiffness parameters of finite element models based on …
Review of statistical model calibration and validation—from the perspective of uncertainty structures
Computer-aided engineering (CAE) is now an essential instrument that aids in engineering
decision-making. Statistical model calibration and validation has recently drawn great …
decision-making. Statistical model calibration and validation has recently drawn great …
Hierarchical Bayesian model updating for structural identification
A new probabilistic finite element (FE) model updating technique based on Hierarchical
Bayesian modeling is proposed for identification of civil structural systems under changing …
Bayesian modeling is proposed for identification of civil structural systems under changing …
Interval model updating with irreducible uncertainty using the Kriging predictor
Interval model updating in the presence of irreducible uncertain measured data is defined
and solutions are made available for two cases. In the first case, the parameter vertex …
and solutions are made available for two cases. In the first case, the parameter vertex …
Forward and inverse structural uncertainty propagations under stochastic variables with arbitrary probability distributions
In this study, a general frame of the forward and inverse structural uncertainty propagations
(UPs) based on the dimension reduction (DR) method and the derivative lambda probability …
(UPs) based on the dimension reduction (DR) method and the derivative lambda probability …
Stochastic model updating: part 1—theory and simulated example
The usual model updating method may be considered to be deterministic since it uses
measurements from a single test system to correct a nominal finite element model. There …
measurements from a single test system to correct a nominal finite element model. There …
Perturbation methods for the estimation of parameter variability in stochastic model updating
The problem of model updating in the presence of test-structure variability is addressed.
Model updating equations are developed using the sensitivity method and presented in a …
Model updating equations are developed using the sensitivity method and presented in a …
Well logging prediction and uncertainty analysis based on recurrent neural network with attention mechanism and Bayesian theory
L Zeng, W Ren, L Shan, F Huo - Journal of Petroleum Science and …, 2022 - Elsevier
Deep learning technology can fit the nonlinear relations between different logging
sequences. It solves the prediction problems that cannot be effectively disposed by …
sequences. It solves the prediction problems that cannot be effectively disposed by …
[HTML][HTML] Quantify and account for field reference errors in forest remote sensing studies
Field inventoried data are often used as references (ground truth) in forest remote sensing
studies. However, the reference values are affected by various kinds of errors, which tend to …
studies. However, the reference values are affected by various kinds of errors, which tend to …
Hierarchical Bayesian operational modal analysis: Theory and computations
This paper presents a hierarchical Bayesian modeling framework for the uncertainty
quantification in modal identification of linear dynamical systems using multiple vibration …
quantification in modal identification of linear dynamical systems using multiple vibration …