2009
DOI: 10.1080/10426910802609144
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Elongation of Irradiated Steels

Abstract: A neural network was designed to model the elongation of neutron-irradiated steels. Predictions were compared to experimental values and were in agreement. The model was extrapolated to predict the elongation at high irradiation doses (200 dpa) and high temperatures (750• C). Because of the lack of experimental values at such doses and temperatures, predictions were accompanied with very large modelling uncertainties.

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Cited by 3 publications
(1 citation statement)
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“…Such complex processes were successfully handled through ANN by adequate metallurgical analyses of the predicted results. 239,240 In an attempt to predict the Charpy transition temperature of irradiated martensitic steel a sparsely populated dataset was used to assess the relative significance of the material and irradiation parameters, as well as the modelling uncertainty. 239 The model predicted that elongation in such steels is controlled by features like microstructure, plasticity (i.e.…”
Section: Composition Process Property Correlationmentioning
confidence: 99%
“…Such complex processes were successfully handled through ANN by adequate metallurgical analyses of the predicted results. 239,240 In an attempt to predict the Charpy transition temperature of irradiated martensitic steel a sparsely populated dataset was used to assess the relative significance of the material and irradiation parameters, as well as the modelling uncertainty. 239 The model predicted that elongation in such steels is controlled by features like microstructure, plasticity (i.e.…”
Section: Composition Process Property Correlationmentioning
confidence: 99%