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Statistical prior modeling with radius-uniform distribution for a correlation hyperparameter in bayesian calibration

Published Online: 2023-03-16

Published Print: 2023-04

Authors

Jeong, Sehui

Choi, Hyunhee

Youn, Byeng D. https://orcid.org/0000-0003-0135-3660
Son, Hyejeong
Funding

Funding for this research was provided by:

Ministry of Science and ICT, Republic of Korea (2020R1A2C3003644)
License Information

Text and Data Mining valid from 2023-03-16

Version of Record valid from 2023-03-16
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Article History

Received: 2 May 2022

Revised: 22 December 2022

Accepted: 2 February 2023

First Online: 16 March 2023

Declarations

:

: The author(s) declared that there are no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

: To facilitate the replication of results, the paper provides all model formulations and input parameters for each of the case studies. All computations in this work rely on MATLAB; calculation for Bayesian calibration requires the Statistics and Machine Learning Toolbox; the observation from the engineering case study was conducted using the Partial Differential Equation Toolbox. For the second engineering case study, the observation data were generated using the COMSOL and LiveLink™ for MATLAB, and the kriging model was generated by the DACE Toolbox. Important details required to calculate the bounds of the radius-uniform distribution (file name: psi_bound.m) and the probability density function (file name: radius_uniform_pdf.m) are provided as supplementary materials.

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