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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| Format: | Article |
| Language: | zho |
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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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| _version_ | 1841535698597838848 |
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| author | LI Chong LV JingWei GUO RuiChen LU Tan |
| author_facet | LI Chong LV JingWei GUO RuiChen LU Tan |
| author_sort | LI Chong |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-69cc0560ec38472ab05260b2339ae280 |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2020-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-69cc0560ec38472ab05260b2339ae2802025-01-15T02:28:43ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692020-01-014222823330607160COLLABORATIVE ANALYSIS OF AIR-COOLED TURBINE BLADE LOW-CYCLE FATIGUE RELIABILITYLI ChongLV JingWeiGUO RuiChenLU TanConsidering 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.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2020.01.035Air-cooled turbine bladeLow-cycle fatigue lifeReliabilityDistributed collaborative response surface methodArtificial neural network |
| spellingShingle | LI Chong LV JingWei GUO RuiChen LU Tan COLLABORATIVE ANALYSIS OF AIR-COOLED TURBINE BLADE LOW-CYCLE FATIGUE RELIABILITY Jixie qiangdu Air-cooled turbine blade Low-cycle fatigue life Reliability Distributed collaborative response surface method Artificial neural network |
| title | COLLABORATIVE ANALYSIS OF AIR-COOLED TURBINE BLADE LOW-CYCLE FATIGUE RELIABILITY |
| title_full | COLLABORATIVE ANALYSIS OF AIR-COOLED TURBINE BLADE LOW-CYCLE FATIGUE RELIABILITY |
| title_fullStr | COLLABORATIVE ANALYSIS OF AIR-COOLED TURBINE BLADE LOW-CYCLE FATIGUE RELIABILITY |
| title_full_unstemmed | COLLABORATIVE ANALYSIS OF AIR-COOLED TURBINE BLADE LOW-CYCLE FATIGUE RELIABILITY |
| title_short | COLLABORATIVE ANALYSIS OF AIR-COOLED TURBINE BLADE LOW-CYCLE FATIGUE RELIABILITY |
| title_sort | collaborative analysis of air cooled turbine blade low cycle fatigue reliability |
| topic | Air-cooled turbine blade Low-cycle fatigue life Reliability Distributed collaborative response surface method Artificial neural network |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2020.01.035 |
| work_keys_str_mv | AT lichong collaborativeanalysisofaircooledturbinebladelowcyclefatiguereliability AT lvjingwei collaborativeanalysisofaircooledturbinebladelowcyclefatiguereliability AT guoruichen collaborativeanalysisofaircooledturbinebladelowcyclefatiguereliability AT lutan collaborativeanalysisofaircooledturbinebladelowcyclefatiguereliability |