Compound uncertainty quantification and aggregation (CUQA) for reliability assessment in industrial maintenance

Loading...
Thumbnail Image

Date published

Free to read from

Authors

Grenyer, Alex
Erkoyuncu, John Ahmet
Addepalli, Sri
Zhao, Yifan

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Department

Course name

ISSN

2075-1702

Format

Citation

Grenyer A, Erkoyuncu JA, Addepalli S, Zhao Y. (2023) Compound uncertainty quantification and aggregation (CUQA) for reliability assessment in industrial maintenance. Machines, Volume 11, Issue 5, May 2023, Article number 560

Abstract

The mounting increase in the technological complexity of modern engineering systems requires compound uncertainty quantification, from a quantitative and qualitative perspective. This paper presents a Compound Uncertainty Quantification and Aggregation (CUQA) framework to determine compound outputs along with a determination of the greatest uncertainty contribution via global sensitivity analysis. This was validated in two case studies: a bespoke heat exchanger test rig and a simulated turbofan engine. The results demonstrated the effective measurement of compound uncertainty and the individual impact on system reliability. Further work will derive methods to predict uncertainty in-service and the incorporation of the framework with more complex case studies.

Description

Software Description

Software Language

Github

Keywords

coefficient of variation, global sensitivity analysis, measurement, pedigree, reliability, uncertainty quantification

DOI

Rights

Attribution 4.0 International

Funder/s

Relationships

Relationships

Resources