Physics-embedding multi-response regressor for time-variant system reliability assessment
Abstract
Efficient time-variant reliability assessment for complex systems is of great interest but challenging as the highly complex multiple output responses under time-variant uncertainties are hard to quantify. The task becomes even more challenging if the interconnected dependencies between multiple failure modes are involved. In this study, an eXtreme physics-embedding multi-response regressor (X-PMR) is presented for time-variant system reliability assessment. Firstly, by transforming time-variant multiple responses to time-invariant extreme values, an eXtreme multi-domain transformation concept is presented, to establish the time-invariant multi-input multi-output (TiMIMO) dataset; moreover, by embedding physics/mathematics knowledge into multi-objective ensemble modeling, a physics-embedding multi-response regressor is proposed, to synchronously construct the surrogate model for highly complex multiple output responses. The validation effectiveness and benefit illustration of the X-PMR method are revealed by introducing three numerical systems (i.e., series system, parallel system and series/parallel hybrid system) and a real application system (i.e., dynamic aeroengine turbine blisk), in comparison with a number of state-of-the-art methods investigated in the literature. The current efforts can provide a novel sight to address the time-variant system reliability assessment problems.
Details
- Organisation(s)
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Institute for Risk and Reliability
- External Organisation(s)
-
Beihang University
City University of Hong Kong
University of Science and Technology Beijing
University of Liverpool
Tongji University
- Type
- Article
- Journal
- Reliability Engineering and System Safety
- Volume
- 263
- No. of pages
- 17
- ISSN
- 0951-8320
- Publication date
- 11.2025
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality, Industrial and Manufacturing Engineering
- Electronic version(s)
-
https://doi.org/10.1016/j.ress.2025.111262 (Access:
Closed
)
