Prediction of the fatigue strength of metals at low temperatures based on artificial intelligence
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An intelligent system for predicting the fatigue strength of metals in a wide temperature range is developed using a specially trained neural network. The system makes it possible to predict the number of load cycles of a part to failure, as well as the start of formation and growth rate of fatigue cracks for different test conditions, including at low temperatures. Keywords: neural network, prediction of loading cycles, low temperatures, fatigue strength. [email protected]
2021 ◽
2020 ◽
Vol E103.A
(12)
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pp. 1367-1380
2011 ◽
Vol 6
(4)
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pp. 13-26
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2006 ◽
Vol 15
(3-4)
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pp. 373-382
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