Self Powered neutron detector based reactor flux estimation using multisensor particle filter

P. Tamboli, S. Duttagupta, K. Roy
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引用次数: 1

Abstract

In this paper, we propose an improved method of In-core neutron flux estimation using Inconel Self Powered Neutron Detectors (SPNDs). The method proposed here is based upon multi-sensor based particle filter utilizing a number of uniformly distributed SPNDs along with the out-core ionization chambers which measure the overall flux. The proposed method estimates the neutron flux of large non-linear core volume involving stiff non-linearities with non-Gaussian uncertainties both in the process and sensor model. We propose an improved particle filtering based data fusion algorithm on multi-sensor network for flux estimation under nonlinear non-Gaussian environment. The nonlinear system in our study is a large core nuclear reactor measured through in-core Self Powered Neutron Detectors. Many critical applications such as reactor protection and control rely upon the neutron flux information and thus make the reliability of data an utmost important. The point kinetic model based on neutron transport theory conveniently explains the dynamics of nuclear reactor. The state equation in point kinetic model is stiff nonlinear set of equations. The neutron flux in the large core, loosely coupled reactor are sensed by multiple sensors measuring point fluxes located at various locations inside the reactor core. The flux values are coupled to each other through diffusion equation. The coupling facilitates redundancy in the information. The multiple independent information about the localized flux peaking can be fused together to enhance the estimation accuracy to a great extent. In our work, we establish, observation model for the neutron flux sensor used for large core flux measurement i.e. Self Powered Neutron Detectoric document.
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基于自供电中子探测器的多传感器粒子滤波反应堆通量估计
本文提出了一种利用铬镍铁合金自供电中子探测器(spnd)估算堆芯内中子通量的改进方法。本文提出的方法是基于基于多传感器的粒子滤波,利用许多均匀分布的spnd以及测量总通量的核外电离室。该方法对过程和传感器模型中具有非高斯不确定性的刚性非线性大体积非线性堆芯的中子通量进行估计。提出了一种改进的基于粒子滤波的多传感器网络数据融合算法,用于非线性非高斯环境下的通量估计。本文研究的非线性系统是一个大型堆芯核反应堆,通过堆芯内自供电中子探测器进行测量。许多关键应用,如反应堆保护和控制,依赖于中子通量信息,因此使数据的可靠性至关重要。基于中子输运理论的点动力学模型方便地解释了核反应堆的动力学。点动力学模型中的状态方程是刚性非线性方程组。大堆芯松耦合堆的中子通量由多个传感器测量堆芯内不同位置的中子通量。通量值通过扩散方程相互耦合。这种耦合促进了信息的冗余。将局部磁通峰值的多个独立信息融合在一起,可以极大地提高估计精度。本文建立了用于大磁芯通量测量的中子通量传感器——自供电中子探测器的观测模型。
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