Fatigue Reliability Analysis System for Key Components of Aero-Engine
Aero-engine is known as the heart of an aircraft. Fatigue is one of the main causes of aero-engine failure, therefore, it is essential to predict the fatigue life in the aero-engine design process. Due to the uncertainty of influencing factors, it is necessary to further analyze the fatigue reliabil...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/1143901 |
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| author | Huizhi Qi Yaqing Lu Shufang Song Qiannan Xu |
| author_facet | Huizhi Qi Yaqing Lu Shufang Song Qiannan Xu |
| author_sort | Huizhi Qi |
| collection | DOAJ |
| description | Aero-engine is known as the heart of an aircraft. Fatigue is one of the main causes of aero-engine failure, therefore, it is essential to predict the fatigue life in the aero-engine design process. Due to the uncertainty of influencing factors, it is necessary to further analyze the fatigue reliability. First, the fatigue life should be predicted on the basic of finite element analysis. The steps include parametric modeling, stress-strain analysis, load spectrum acquisition, and selection of fatigue life prediction model. Then, the reliability estimation of fatigue life should be employed, including the statistical analysis of influencing factors, reliability analysis method, and reliability estimation of fatigue life. Taking turbine blade and test probe of aero-engine as the research objects, the fatigue reliability analysis system is developed based on the ABAQUS-MATLAB platform. Statistical analysis shows that fatigue life approximately obeys lognormal distribution, and the distribution parameters estimated by MCS and Kriging are coincide, while Kriging only needs dozens of training samples. Under different reliability indexes, the design fatigue life error between Kriging and MCS is less than 1%, which meets the accuracy requirements and can effectively guide the fault detection and maintenance of aero-engine. |
| format | Article |
| id | doaj-art-0ec57b5f3e2c41e8afa512e275baaff7 |
| institution | Kabale University |
| issn | 1687-5974 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-0ec57b5f3e2c41e8afa512e275baaff72025-02-03T06:08:42ZengWileyInternational Journal of Aerospace Engineering1687-59742022-01-01202210.1155/2022/1143901Fatigue Reliability Analysis System for Key Components of Aero-EngineHuizhi Qi0Yaqing Lu1Shufang Song2Qiannan Xu3School of AeronauticsSchool of AeronauticsSchool of AeronauticsAECC Sichuan Gas Turbine EstablishmentAero-engine is known as the heart of an aircraft. Fatigue is one of the main causes of aero-engine failure, therefore, it is essential to predict the fatigue life in the aero-engine design process. Due to the uncertainty of influencing factors, it is necessary to further analyze the fatigue reliability. First, the fatigue life should be predicted on the basic of finite element analysis. The steps include parametric modeling, stress-strain analysis, load spectrum acquisition, and selection of fatigue life prediction model. Then, the reliability estimation of fatigue life should be employed, including the statistical analysis of influencing factors, reliability analysis method, and reliability estimation of fatigue life. Taking turbine blade and test probe of aero-engine as the research objects, the fatigue reliability analysis system is developed based on the ABAQUS-MATLAB platform. Statistical analysis shows that fatigue life approximately obeys lognormal distribution, and the distribution parameters estimated by MCS and Kriging are coincide, while Kriging only needs dozens of training samples. Under different reliability indexes, the design fatigue life error between Kriging and MCS is less than 1%, which meets the accuracy requirements and can effectively guide the fault detection and maintenance of aero-engine.http://dx.doi.org/10.1155/2022/1143901 |
| spellingShingle | Huizhi Qi Yaqing Lu Shufang Song Qiannan Xu Fatigue Reliability Analysis System for Key Components of Aero-Engine International Journal of Aerospace Engineering |
| title | Fatigue Reliability Analysis System for Key Components of Aero-Engine |
| title_full | Fatigue Reliability Analysis System for Key Components of Aero-Engine |
| title_fullStr | Fatigue Reliability Analysis System for Key Components of Aero-Engine |
| title_full_unstemmed | Fatigue Reliability Analysis System for Key Components of Aero-Engine |
| title_short | Fatigue Reliability Analysis System for Key Components of Aero-Engine |
| title_sort | fatigue reliability analysis system for key components of aero engine |
| url | http://dx.doi.org/10.1155/2022/1143901 |
| work_keys_str_mv | AT huizhiqi fatiguereliabilityanalysissystemforkeycomponentsofaeroengine AT yaqinglu fatiguereliabilityanalysissystemforkeycomponentsofaeroengine AT shufangsong fatiguereliabilityanalysissystemforkeycomponentsofaeroengine AT qiannanxu fatiguereliabilityanalysissystemforkeycomponentsofaeroengine |