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细胞神经网络求解点堆的动力学方程

Solution of point reactor neutron kinetic equations using cellular neural network
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摘要 为有效克服点堆中子动力学方程的刚性,准确、快速、稳定地求解方程,同时考虑到缓发中子对堆内中子的影响,采用Simulink建立了三层12×12的细胞神经网络模型,模拟实现1/4均匀裸堆在稳态和插入控制棒两种情况下的中子通量分布,利用二分法求解堆内的有效增殖系数。结果表明,细胞神经网络计算结果正确,能比较准确地预测反应堆中子通量密度。细胞神经网络可用于模拟反应堆堆内中子的动态变化。 This paper is an attempt to effectively overcome the stiffness inherent in the point reactor neutron kinetic equations and come up with a more accurate,quick and steady solution of the equation,with a simultaneous consideration of the effect of delayed neutrons on neutrons in the reactor.The targeted study involves establishing a cellular neural network model with the three layers of 12×12 using Simulink;thereby simulating the neutron flux distribution of 1/4 bare homogeneous reactor in the two cases:steady state and insertion of control rods;and obtaining the solution to the effective proliferation coefficient in reactor using dichotomy.The results demonstrate that the cellular neural network could enable a correct calculation and a more accurate prediction of the reactor neutron flux density.The cellular neural network could work better for the simulation of the dynamic changes of neutrons in a reactor.
作者 李忠勤 Li Zhongqin(School of Electrical&Control Engineering,Heilongjiang University of Science&Technology,Harbin 150022,China)
出处 《黑龙江科技大学学报》 CAS 2018年第6期712-717,共6页 Journal of Heilongjiang University of Science And Technology
基金 国家自然科学基金项目(51674109) 哈尔滨市科技创新人才研究专项资金项目(2017RAQXJ114)
关键词 细胞神经网络 点堆动力学方程 SIMULINK cellular neural network point reactor neutron kinetic equations Simulink
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