Details
| Original language | English |
|---|---|
| Article number | 111262 |
| Number of pages | 17 |
| Journal | Reliability Engineering and System Safety |
| Volume | 263 |
| Early online date | 23 May 2025 |
| Publication status | E-pub ahead of print - 23 May 2025 |
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.
Keywords
- Aeroengine, Surrogate model, System reliability, Time-variant reliability, Turbine blisk
ASJC Scopus subject areas
- Engineering(all)
- Safety, Risk, Reliability and Quality
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Reliability Engineering and System Safety, Vol. 263, 111262, 11.2025.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Physics-embedding multi-response regressor for time-variant system reliability assessment
AU - Song, Lu Kai
AU - Tao, Fei
AU - Li, Xue Qin
AU - Yang, Le Chang
AU - Wei, Yu Peng
AU - Beer, Michael
N1 - Publisher Copyright: © 2025 Elsevier Ltd
PY - 2025/5/23
Y1 - 2025/5/23
N2 - 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.
AB - 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.
KW - Aeroengine
KW - Surrogate model
KW - System reliability
KW - Time-variant reliability
KW - Turbine blisk
UR - http://www.scopus.com/inward/record.url?scp=105006713963&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2025.111262
DO - 10.1016/j.ress.2025.111262
M3 - Article
AN - SCOPUS:105006713963
VL - 263
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
SN - 0951-8320
M1 - 111262
ER -