کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
780624 1463747 2016 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fatigue life estimation of aero engine mount structure using Monte Carlo simulation
ترجمه فارسی عنوان
برآورد عمر خستگی از ساختار نصب موتور هواپیما با استفاده از شبیه سازی مونت کارلو
کلمات کلیدی
خستگی؛ ساختار کوه؛ مونت کارلو؛ شبیه سازی؛ احتمالاتی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی مکانیک
چکیده انگلیسی


• The fatigue life of front mount structure of an aero engine is dealt with Fan blade off scenario.
• Stochastic model approach is implemented and compared with experiments.
• Monte Carlo simulation with more number of random samples provides better results.
• Stochastic model will be improved further with more degree of parameters.

The estimation of fatigue life of mount structures in aero engine has become crucial for safe fly-home period in the event of a fan blade off situation since it has many random factors which will be influencing the durability of these structures either direct or indirect way. The imbalanced rotation during windmilling post fan blade off (FBO) creates vibratory loads of such low frequency but in high amplitude that leads to have the shorter fatigue life of these mount structures. Regression analysis during the evaluation of fatigue life under this circumstance provides the frequency of the front rotor shaft as most influencing parameter affecting the durability of the mount structures even though there are many other factors like, tribological conditions, material properties, impact fraction, environmental and thermal effects. Since it has low probability of occurrences but with high impact, the degree of conservatism in the estimated life is still hidden. Monte Carlo simulation of randomly selected lives from a predicted distribution of all dependent factors brings the variations in fatigue life of the mount structure. This can be estimated as a function of populated size. The mean and standard deviation of the simulated fatigue life converges with more number of randomly varied samples.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Fatigue - Volume 83, Part 1, February 2016, Pages 53–58
نویسندگان
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