Structural failure at low temperatures and stability diagnostics
| Autor: | M. S. Anosova, I. L. Laptev, D. A. Shatagina, Yu. G. Kabaldin, V. O. Zotova |
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| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Materials science Quantitative Biology::Neurons and Cognition Artificial neural network business.industry Mechanical Engineering Structural failure 02 engineering and technology Structural engineering Stability (probability) Fractal analysis Industrial and Manufacturing Engineering 020303 mechanical engineering & transports 020901 industrial engineering & automation Wavelet Fractal Brittleness 0203 mechanical engineering Acoustic emission business |
| Zdroj: | Russian Engineering Research. 36:289-293 |
| ISSN: | 1934-8088 1068-798X |
| DOI: | 10.3103/s1068798x16040079 |
| Popis: | The influence of impurities on the cold brittleness of materials is studied. A neural network is trained to model fatigue and brittle failure of samples. The neural network generates numerical sequences that evolve analogously to the fractal characteristics of acoustic emission studied in fatigue tests with various loads. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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