The purpose of this study is to address the complexity involved in computing the fatigue life of casted structure with porosity effects in aero engine applications. The uncertainty of porosity defects is addressed by introducing probabilistic models.
One major issue of casted aluminium alloys in the application of aerospace industries is their internal defects such as porosities, which are directly affecting the fatigue life. Since there is huge cost and time effort involved in understanding the effect of fatigue life in terms of the presence of the internal defects, a probabilistic fatigue model approach is applied in order to define the realistic fatigue limit of the casted structures for the known porosity fractions. This paper describes the probabilistic technique to casted structures with measured porosity fractions and its relation to their fatigue life. The predicted fatigue life for various porosity fractions and dendrite arm spacing values is very well matching with the experimentally predicted fatigue data of the casted AS7G06 aluminium alloys with measured internal defects. The probabilistic analysis approach not only predicts the fatigue life limit of the structure but also provides the limit of fatigue life for the known porosity values of any casted aluminium bearing support structure used in aero engines.
The probabilistic fatigue model for addressing porosity in casting structure is verified with experimental results.
This is grey area in aerospace and automotive industry.
This work is original and not published anywhere else.
The author would like to thank Rolls Royce Deutschland for providing an opportunity to create this work.
Narayanan, G. (2021), "Probabilistic fatigue model for cast alloys of aero engine applications", International Journal of Structural Integrity, Vol. 12 No. 3, pp. 454-469. https://doi.org/10.1108/IJSI-05-2020-0048
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