| Recent advances in reliability analysis of aeroengine rotor system: a review XQ Li, LK Song, GC Bai International Journal of Structural Integrity 13 (1), 1-29, 2022 | 121 | 2022 |
| Probabilistic LCF life assessment for turbine discs with DC strategy-based wavelet neural network regression LK Song, GC Bai, CW Fei International Journal of Fatigue 119, 204-219, 2019 | 85 | 2019 |
| Multi-objective reliability-based design optimization approach of complex structure with multi-failure modes LK Song, CW Fei, J Wen, GC Bai Aerospace Science and Technology 64, 52-62, 2017 | 81 | 2017 |
| Dynamic surrogate modeling approach for probabilistic creep-fatigue life evaluation of turbine disks LK Song, GC Bai, CW Fei Aerospace Science and Technology 95, 105439, 2019 | 73 | 2019 |
| 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 159, 106812, 2022 | 64 | 2022 |
| Multivariate ensembles-based hierarchical linkage strategy for system reliability evaluation of aeroengine cooling blades XQ Li, LK Song, YS Choy, GC Bai Aerospace Science and Technology 138, 108325, 2023 | 59 | 2023 |
| Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression LK Song, J Wen, CW Fei, GC Bai Mechanical Systems and Signal Processing 104, 72-86, 2018 | 54 | 2018 |
| Dynamic neural network method-based improved PSO and BR algorithms for transient probabilistic analysis of flexible mechanism LK Song, CW Fei, GC Bai, LC Yu Advanced Engineering Informatics 33, 144-153, 2017 | 53 | 2017 |
| Multi-failure probabilistic design for turbine bladed disks using neural network regression with distributed collaborative strategy LK Song, GC Bai, CW Fei Aerospace Science and Technology 92, 464-477, 2019 | 52 | 2019 |
| Physics-informed distributed modeling for CCF reliability evaluation of aeroengine rotor systems XQ Li, LK Song, GC Bai, DG Li International Journal of Fatigue 167, 107342, 2023 | 49 | 2023 |
| A unified fatigue reliability-based design optimization framework for aircraft turbine disk LK Song, GC Bai, XQ Li, J Wen International Journal of Fatigue 152, 106422, 2021 | 46 | 2021 |
| Advanced multiple response surface method of sensitivity analysis for turbine blisk reliability with multi-physics coupling C Zhang, L Song, C Fei, C Lu, Y Xie Chinese Journal of Aeronautics 29 (4), 962-971, 2016 | 43 | 2016 |
| Vectorial surrogate modeling approach for multi-failure correlated probabilistic evaluation of turbine rotor XQ Li, LK Song, GC Bai Engineering with Computers 39 (3), 1885-1904, 2023 | 39 | 2023 |
| PSO-LSSVR: A surrogate modeling approach for probabilistic flutter evaluation of compressor blade BW Wang, WZ Tang, LK Song, GC Bai Structures 28, 1634-1645, 2020 | 38 | 2020 |
| Fatigue reliability estimation framework for turbine rotor using multi-agent collaborative modeling XQ Li, GC Bai, LK Song, J Wen Structures 29, 1967-1978, 2021 | 37 | 2021 |
| A novel metamodeling approach for probabilistic LCF estimation of turbine disk LK Song, GC Bai, XQ Li Engineering Failure Analysis 120, 105074, 2021 | 33 | 2021 |
| Active extremum Kriging-based multi-level linkage reliability analysis and its application in aeroengine mechanism systems H Zhang, LK Song, GC Bai, XQ Li Aerospace Science and Technology 131, 107968, 2022 | 30 | 2022 |
| Improved Kriging-based hierarchical collaborative approach for multi-failure dependent reliability assessment K Deng, LK Song, GC Bai, XQ Li International Journal of Fatigue 160, 106842, 2022 | 30 | 2022 |
| Multi-surrogate collaboration approach for creep-fatigue reliability assessment of turbine rotor LK Song, GC Bai IEEE Access 8, 39861-39874, 2020 | 26 | 2020 |
| Cascade ensemble learning for multi-level reliability evaluation LK Song, XQ Li, SP Zhu, YS Choy Aerospace Science and Technology 148, 109101, 2024 | 25 | 2024 |
Choy Yat SzeAssociate Professor, The Hong Kong Polytechnic UniversityVahvistettu sähköpostiosoite verkkotunnuksessa polyu.edu.hk