Study on application of artificial neural network to debris bed coolability calculations for sodium-cooled fast reactors

Study on application of artificial neural network to debris bed coolability calculations for sodium-cooled fast reactors

Understanding the effect of uncertainties of Core Disruptive Accident (CDA) scenarios on debris bed coolability on a core catcher is required for decision making on design options to mitigate a CDA consequence. For the understanding, a huge number of calculations are required but are extremely diffi...

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Autores principales: Eiji MATSUO, Kyohei SASA, Hiroyuki SAITO, Yutaka ABE
Formato: article
Lenguaje:EN
Publicado: The Japan Society of Mechanical Engineers 2020
Materias:
sodium-cooled fast reactor
debris bed coolability
speed-up calculations
artificial neural network
machine learning
application
latin hypercube sampling
Mechanical engineering and machinery
TJ1-1570
Acceso en línea:https://doaj.org/article/a47719620ca94f79ab0356c26014b793
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https://doaj.org/article/a47719620ca94f79ab0356c26014b793

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