In this paper, a non-probabilistic method based on fuzzy logic is used to update finite element models (FEMs). Model updating techniques use the measured data to improve the accuracy of numerical models of structures. However, the measured data are contaminated with experimental noise and the models are inaccurate due to randomness in the parameters. This kind of aleatory uncertainty is irreduc...

In this paper, Bayesian finite element (FE) model updating is applied for uncertainty quantification in the multi-stage damage assessment of a seven-story reinforced building slice. The results of the Bayesian updating scheme are analyzed using a detailed uncertainty and resolution analysis which involves computing the posterior statistics and solving an eigenvalue problem. It is shown that the...

In order to identify more accurate finite element (FE) model parameters for an as-built structure, experimental data collected from the actual structure can be used to update the parameter values. In practice, experimental data is inevitably contaminated with measurement noise, which may lead to inaccurate FE model updating. This research compares the performance of two model updating approache...

Model updating concerns the modification of an existing but inaccurate model with measured data. For models characterized by quadratic pencils, the measured data usually involve incomplete knowledge of natural frequencies, mode shapes, or other spectral information. In conducting the updating, it is often desirable to match only the part of observed data without tampering with the other part of...

Structural joints provide connection between structural element (beam, plate etc.) in order to construct a whole assembled structure. There are many types of structural joints such as bolted joint, riveted joints and welded joints. The joints structures significantly contribute to structural stiffness and dynamic behaviour of structures hence the main objectives of this paper are to review on m...

In this paper we aim to estimate the differential student knowledge model in a probabilistic domain within an intelligent tutoring system. The student answers to questions requiring diagnosing skills are used to estimate the actual student model. Updating and verification of the model are conducted based on the matching between the student's and model answers. Two different approaches to updati...

This paper describes a study of the effects of discretisation on model updating analysis. Minimising the discrepancy between FE model predictions and experimental modal test data is the primary objective of model updating. Numerical case studies presented in this paper show the influence on the final values of the updating parameters for an initial FE model with and without discretisation error...