Finite Element Based Vibration Fatigue Analysis Of A New Two-Stroke Linear Generator Engine Component
This paper presents the finite element analysis technique topredict the fatigue life using the narrow band frequencyresponse approach. Such life prediction results are useful forimproving the component design at the very early stage. Thispaper describes how this technique can be implemented in thef...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Malaya
2007
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/8459/ http://umpir.ump.edu.my/id/eprint/8459/ http://umpir.ump.edu.my/id/eprint/8459/1/fkm-2007-mmrahman-finite_element_based.pdf |
| Summary: | This paper presents the finite element analysis technique topredict the fatigue life using the narrow band frequencyresponse approach. Such life prediction results are useful forimproving the component design at the very early stage. Thispaper describes how this technique can be implemented in thefinite element environment to rapidly identify critical areas inthe structure. Fatigue damage is traditionally determined fromthe time signals of the loading, usually in the form of stress andstrain. However, there are scenarios when a spectral form of loading is more appropriate. In this case the loading is definedin terms of its magnitude at different frequencies in the form of a power spectral density (PSD) plot. A frequency domainfatigue calculation can be utilized where the random loadingand response are categorized using power spectral densityfunctions and the dynamic structure is modeled as a lineartransfer function. This paper investigates the effect of meanstress on the fatigue life prediction by using a random varyingload. The obtained results indicate that the Goodman meanstress correction method gives the most conservative resultscompared with Gerber, and no mean stress correction method.The proposed analysis technique is capable of determiningpremature products failure phenomena. Therefore, it can reducecost, time to market, improve product reliability and customerconfidence. |
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