Reactivity identification during physics start-up of a reactor based on neural network

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Reactivity identification during physics start-up of a reactor based on neural network

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- Reactivity identification during physics start-up of a reactor based on neural network
- NUCLEAR TECHNIQUES Issue 1, (2007)
- 作者机构：
  
  海军工程大学
- 作者简介：
- 基金信息：
- DOI：
  CLC： TL32
- Published：01 January 2007
- 稿件说明：
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[1]李凤宇,张大发,陆古兵,杨仕本.基于神经网络的反应堆物理启动中的反应性辨识[J].核技术,2007(01):78-80.

Reactivity identification during physics start-up of a reactor based on neural network[J]. Nuclear techniques, 2007, (1): 78-80.
[1]李凤宇,张大发,陆古兵,杨仕本.基于神经网络的反应堆物理启动中的反应性辨识[J].核技术,2007(01):78-80. DOI：

Reactivity identification during physics start-up of a reactor based on neural network[J]. Nuclear techniques, 2007, (1): 78-80. DOI：

摘要

采用神经网络来对反应性进行辨识

辨识的结果可与其他反应性测量方法结果相互比较以降低物理启动的风险。神经网络的训练采用一阶梯度优化算法

利用点堆中子动力学模型产生训练样本。分析了正常物理启动时中子的倍增特性。仿真结果表明

该网络具有推广能力

能有效辨识反应性。

Abstract

In this paper the neural network is used to identify reactivity.The identification result can be compared with those using other methods to reduce the start-up risk.The first order gradient optimization algorithm is employed to train the network．The training samples stem from the neutron kinetics of the point-reactor.The character of neutron multiplication is analyzed.Simulation results indicate that being capable of effectively identifying reactivity

the neural network method is worth spreading.

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Related Institution

Shanghai Institute of Applied Physics, Chinese Academy of Sciences

University of Chinese Academy of Sciences

College of Energy, Xiamen University

Key Laboratory of Radiation Physics and Technology of the Ministry of Education, Institute of Nuclear Science and Technology, Sichuan University

Nuclear Power Institute of China

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