Abstract
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.
| Original language | English |
|---|---|
| Article number | 106422 |
| Journal | International Journal of Fatigue |
| Volume | 152 |
| DOIs | |
| State | Published - Nov 2021 |
Keywords
- Artificial neural network
- Low cycle fatigue
- Reliability-based design optimization
- Surrogate model
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