Neutron Transport Theory and Simulation

Wu, Yican

doi:10.1007/978-981-10-5469-3_2

Fusion Neutronics 2017

DOI: 10.1007/978-981-10-5469-3_2

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Neutron Transport Theory and Simulation

Yican Wu

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2024

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An efficient calculation method for particle transport problems based on neural network

Ma,

Wang,

et al. 2024

Acta Phys. Sin.

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The Monte Carlo (MC) method is a powerful tool for solving particle transport problems. However, it is extremely time-consuming to obtain results that meet the specified statistical error requirements, especially for large-scale refined models. This paper focuses on improving the computational efficiency of neutron transport simulations. Accordingly, this study presents a novel method for executing fast calculation of neutron fixed source problems, which have broad applications. This type of particle transport problem aims at obtaining a fixed target tally corresponding to different source distributions for fixed geometry and material. First, a fast simulation is achieved by treating the source distribution as the input to a neural network, with the estimated target tally as the output. This neural network is trained with data from MC simulations of diverse source distributions, ensuring its reusability. Second, since the data acquisition is time consuming, the importance principle of MC method is utilized to efficiently generate training data. This method has been tested on several benchmark models. The relative errors of results from neural networks are less than 5% and the time required to obtain these results is negligible compared to that of original Monte Carlo simulations. In conclusion, this paper has proposed a method that trains neural networks with MC simulation results containing importance data and uses this network to accelerate the computation of neutron fixed source problems.

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An efficient calculation method for particle transport problems based on neural network

Ma,

Wang,

et al. 2024

Acta Phys. Sin.

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Neutron Transport Theory and Simulation

Cited by 1 publication

References 14 publications

An efficient calculation method for particle transport problems based on neural network

An efficient calculation method for particle transport problems based on neural network

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