Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges

Y Xu, S Kohtz, J Boakye, P Gardoni, P Wang - Reliability Engineering & …, 2023 - Elsevier
The computerized simulations of physical and socio-economic systems have proliferated in
the past decade, at the same time, the capability to develop high-fidelity system predictive …

Recent advances in reliability analysis of aeroengine rotor system: a review

XQ Li, LK Song, GC Bai - International Journal of Structural Integrity, 2022 - emerald.com
Purpose To provide valuable information for scholars to grasp the current situations,
hotspots and future development trends of reliability analysis area. Design/methodology …

Probabilistic framework for fatigue life assessment of notched components under size effects

D Liao, SP Zhu, B Keshtegar, G Qian… - International Journal of …, 2020 - Elsevier
Structural integrity assessments with discontinuities are critical for ensuring operational life
and reliability of engineering components. In this work, through combining with the …

A novel fault diagnosis method based on CNN and LSTM and its application in fault diagnosis for complex systems

T Huang, Q Zhang, X Tang, S Zhao, X Lu - Artificial Intelligence Review, 2022 - Springer
Fault diagnosis plays an important role in actual production activities. As large amounts of
data can be collected efficiently and economically, data-driven methods based on deep …

Transfer learning using deep representation regularization in remaining useful life prediction across operating conditions

W Zhang, X Li, H Ma, Z Luo, X Li - Reliability Engineering & System Safety, 2021 - Elsevier
Intelligent data-driven system prognostic methods have been popularly developed in the
recent years. Despite the promising results, most approaches assume the training and …

Probabilistic fatigue modelling of metallic materials under notch and size effect using the weakest link theory

XK Li, SP Zhu, D Liao, JAFO Correia, F Berto… - International Journal of …, 2022 - Elsevier
Notch fatigue analysis is vital for structural integrity design, while efficient fatigue models
coupling notch and size effect are still lacking, which are highly desired for fatigue design of …

Computational-experimental approaches for fatigue reliability assessment of turbine bladed disks

SP Zhu, Q Liu, W Peng, XC Zhang - International Journal of Mechanical …, 2018 - Elsevier
In the present study, a computational-experimental framework is developed for fatigue
reliability assessment of turbine bladed disks. Within the framework, the overspeed testing is …

Deep learning regression-based stratified probabilistic combined cycle fatigue damage evaluation for turbine bladed disks

XQ Li, LK Song, GC Bai - International Journal of Fatigue, 2022 - Elsevier
Probabilistic combined cycle fatigue (CCF) damage evaluation involves complex large-scale
simulations of low cycle fatigue (LCF) damage, high cycle fatigue (HCF) damage and …

Transfer learning with deep recurrent neural networks for remaining useful life estimation

A Zhang, H Wang, S Li, Y Cui, Z Liu, G Yang, J Hu - Applied Sciences, 2018 - mdpi.com
Prognostics, such as remaining useful life (RUL) prediction, is a crucial task in condition-
based maintenance. A major challenge in data-driven prognostics is the difficulty of …

[HTML][HTML] A data-driven roadmap for creep-fatigue reliability assessment and its implementation in low-pressure turbine disk at elevated temperatures

RZ Wang, HH Gu, SP Zhu, KS Li, J Wang… - Reliability Engineering & …, 2022 - Elsevier
High-reliability life design process not only can ensure system safety in service, but also can
provide scientific life management during the maintenance period. The objective of the …