Development of Neural Network for Analysis of Local Power Distributions in BWR Fuel Bundles.

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概要

• 論文の詳細を見る

• A neural network model has been developed to learn the local power distributions in a BWR fuel bundle. A two layers neural network with total 128 elements is used for this model. The neural network learns 33 cases of local power peaking factors of fuel rods with given enrichment distribution as the teacher signals, which were calculated by a fuel bundle nuclear analysis code based on precise physical models. This neural network model studied well the teacher signals within 1% error. It is also able to calculate the local power distributions within several % error for the different enrichment distributions from the teacher signals when the average enrichment is close to 2%. This neural network is simple and the computing speed of this model is 300 times faster than that of the precise nuclear analysis code. This model was applied to survey the enrichment distribution to meet a target local power distribution in a fuel bundle, and the enrichment distribution with flat power shape are obtained within short computing time.

著者

• SHINFUKU Kimihiro

  Toshiba Information Systems Corp.

関連論文

• Development of Neural Network for Predicting Local Power Distributions in BWR Fuel Bundles Considering Burnable Neutron Absorber
• Simplification of Neural Network Model for Predicting Local Power Distributions of BWR Fuel Bundle Using Learning Algorithm with Forgetting
• Development of Neural Network for Analysis of Local Power Distributions in BWR Fuel Bundles.

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