COLLABORATIVE ANALYSIS OF AIR-COOLED TURBINE BLADE LOW-CYCLE FATIGUE RELIABILITY
Considering the dispersion of the material properties and load,the collaborative analysis of the air-cooled turbine blade low-cycle fatigue reliability was done using the distributed collaborative response surface method. The deterministic analysis of the turbine blade was completed by the finite el...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Strength
2020-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2020.01.035 |
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| Summary: | Considering the dispersion of the material properties and load,the collaborative analysis of the air-cooled turbine blade low-cycle fatigue reliability was done using the distributed collaborative response surface method. The deterministic analysis of the turbine blade was completed by the finite elements software. The total strain amplitude and mean stress response surface was established using the artificial neural network and the material life response surface using the linear hetero-variance regression method. The blade life response surface was established by collaborating with the two response surfaces. The low-cycle fatigue reliability analysis of the blade was completed using the Monte-Carlo method. Comparing with the traditional response surface method,the distributed collaborative response surface method is more accurate. |
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| ISSN: | 1001-9669 |