Neutron transport solving method for reactor with uniformly distributed materials

Abstract

The invention discloses a neutron transport solving method for a reactor with uniformly distributed materials. According to the method, machine learning and a Monte Carlo method are combined. Firstly, a series of reactors with uniformly distributed materials need to be constructed, and each reactor contains different material components or densities. Solving the reactors by applying a Monte Carlo method, and counting the scattering and fission probabilities of neutrons and the characteristic distribution of the neutrons after simulation is finished; and training to obtain a full-connection neural network model which takes neutron energy and material composition as input and takes characteristic distribution of scattering and fission neutrons as output by utilizing the probabilities and characteristic distribution data. And finally, by using the obtained full-connection neural network model, taking neutrons and materials generated by fission as input to obtain fission neutrons of the next generation, and carrying out iterative calculation until convergence. Compared with an existing Monte Carlo method, the method has the advantages that a large number of sampling processes are not needed any more, the calculation speed is higher, and neutron transport calculation can be rapidly completed for a reactor with materials evenly distributed.

Description

technical field [0001] The invention relates to the field of nuclear reactor core design and safety, in particular to a neutron transport solution method for a reactor with uniform distribution of materials. The main idea of ​​the method is to combine Monte Carlo method and machine learning for transportation solution. Background technique [0002] The numerical simulation of the reactor is closely related to the design, operation and safety of the reactor. The continuous development of the nuclear industry has put forward higher requirements for the accuracy and efficiency of the numerical simulation of the core. The solution of the neutron transport equation is the core of the numerical simulation of the reactor. The current main solution methods are divided into determinism and Monte Carlo method (Mont Carlo method for short). [0003] The deterministic method solves the simplified neutron transport equation after discretizing energy, space and angle. This method is rela...

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Problems solved by technology

Compared with the deterministic method, the advantages of the Monte Carlo method are: the geometric versatility is strong, and various complex geometric structures can be described; the point section of continuous energy can be used to process various complex energy spectra, avoiding tedious combination and resonance Processing process; as long as enough particles and simulation times are guaranteed, good calculation accuracy can be obtained; although the Monte Carlo method has many advantages, the simulation process requires repeated sampling of a large number of particles, which is still quite time-consuming even if parallel computing is used. The sampling process will also generate a large amount of particle data, which occupies a large amount of memory and has a low utilization rate, which also affects the improvement of computing efficiency.

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