Bayesian Regression over Sparse Fatigue Crack Growth Data for Nuclear Piping

Lye, Adolphus, De Angelis, Marco ORCID: 0000-0001-8851-023X and Patelli, Edoardo ORCID: 0000-0002-5007-7247 (2020) Bayesian Regression over Sparse Fatigue Crack Growth Data for Nuclear Piping [Poster]

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Description

This work looks into the use of Bayesian Regression technique to quantify the uncertainty over a set of sparse fatigue crack growth data that is obtained through a 4-point bending test of a carbon-steel nuclear piping. As a form of validation, the Interval Predictor Model is used which also serves as a way to provide a "Reliability Certificate" for the Bayesian Regression results.

Item Type:	Poster
Depositing User:	Symplectic Admin
Date Deposited:	04 Nov 2020 15:27
Last Modified:	08 Feb 2025 02:13
Related Websites:	Author
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3106033
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