A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Model Identification and Calibration
This chapter provides additional information about the “identification of conversion model” step and the “strength estimation” step as defined in the flowchart summarizing the RILEM recommendation. The advantages and limits of the various options are illustrated by analyzing the results of synthetic simulations. Based on the developed synthetic database, a comparison of the performance of different possible univariate conversion models identified and bi-objective method using linear regression is presented and discussed. It is shown here that the issue of the “best conversion model” is secondary, and that the choice of the conversion model has only negligible effects on the final uncertainty of the final strength. In fact, prediction error is the only way to address correctly. It is also shown why the bi-objective approach must be privileged as it provides, without any additional cost, a better estimation of concrete variability, without reducing the performance regarding the assessment of mean strength and local strength.
Model Identification and Calibration
This chapter provides additional information about the “identification of conversion model” step and the “strength estimation” step as defined in the flowchart summarizing the RILEM recommendation. The advantages and limits of the various options are illustrated by analyzing the results of synthetic simulations. Based on the developed synthetic database, a comparison of the performance of different possible univariate conversion models identified and bi-objective method using linear regression is presented and discussed. It is shown here that the issue of the “best conversion model” is secondary, and that the choice of the conversion model has only negligible effects on the final uncertainty of the final strength. In fact, prediction error is the only way to address correctly. It is also shown why the bi-objective approach must be privileged as it provides, without any additional cost, a better estimation of concrete variability, without reducing the performance regarding the assessment of mean strength and local strength.
Model Identification and Calibration
RILEM State Art Reports
Breysse, Denys (editor) / Balayssac, Jean-Paul (editor) / Sbartaï, Zoubir Mehdi (author) / Alwash, Maitham (author) / Breysse, Denys (author) / Gonçalves, Arlindo (author) / Grantham, Michael (author) / Romão, Xavier (author) / Balayssac, Jean-Paul (author)
2021-04-28
17 pages
Article/Chapter (Book)
Electronic Resource
English
Model Bias Identification for Bayesian Calibration of Stochastic Digital Twins of Bridges
| BASE | 2024
| British Library Online Contents | 2016
| British Library Online Contents | 2016
| British Library Online Contents | 2016