Neural network model of creep strength of austenitic stainless steels
The creep rupture life and rupture strength of austenitic stainless steels have been expressed as functions of chemical composition, test conditions, stabilisation ratio, and solution treatment temperature. The method involved a neural network analysis of a vast and general database assembled from p...
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| Veröffentlicht in: | Materials science and technology 2002-06, Vol.18 (6), p.655-663 |
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| container_title | Materials science and technology |
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| creator | Sourmail, T. Bhadeshia, H. K. D. H. MacKay, D. J. C. |
| description | The creep rupture life and rupture strength of austenitic stainless steels have been expressed as functions of chemical composition, test conditions, stabilisation ratio, and solution treatment temperature. The method involved a neural network analysis of a vast and general database assembled from published data. The outputs of the model have been assessed against known metallurgical trends and other empirical modelling approaches. The models created are shown to capture important trends and to extrapolate better than conventional techniques. |
| doi_str_mv | 10.1179/026708302225002065 |
| format | Article |
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| ispartof | Materials science and technology, 2002-06, Vol.18 (6), p.655-663 |
| issn | 0267-0836 1743-2847 |
| language | eng |
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| source | SAGE Complete A-Z List |
| subjects | Applied sciences Creep Exact sciences and technology Mechanical properties and methods of testing. Rheology. Fracture mechanics. Tribology Metals. Metallurgy |
| title | Neural network model of creep strength of austenitic stainless steels |
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