Journal
INTERNATIONAL JOURNAL OF FATIGUE
Volume 152, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ijfatigue.2021.106422
Keywords
Reliability-based design optimization; Low cycle fatigue; Surrogate model; Artificial neural network
Funding
- National Natural Science Foundation of China [51975028]
- China Postdoctoral Science Foundation [2021M690290]
- National Science and Technology Major Project [J2019IV00160084]
Ask authors/readers for more resources
The study introduces a unified framework integrating hierarchical fuzzy-neuro surrogate method and multi-level collaboration optimization model for fatigue reliability-based design optimization (FRBDO) of aircraft turbine disk. By applying the framework to a high-pressure turbine disk, it was found that the optimization results demonstrate high computational efficiency and accuracy in FRBDO of turbine disk.
To improve the modeling efficiency and optimization accuracy for fatigue reliability-based design optimization (FRBDO) of aircraft turbine disk, a unified framework integrating by hierarchical fuzzy-neuro (HFN) surrogate method and multi-level collaboration (MLC) optimization model are presented. The HFN method is developed with absorbing fuzzy-neuro surrogate into hierarchical modeling strategy. The MLC model is proposed by considering influencing factors and constraint conditions in multiple layers and multiple cycles. The presented framework was applied to the FRBDO of a high-pressure turbine disk. The optimization results show that the presented framework holds high computational efficiency and accuracy in FRBDO of turbine disk.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available