Research on the Solution and Acceleration Algorithm of Source Iteration Method Based on PINN

Jiang Yong; An Ping; Liu Dong; Yu Yang

doi:10.13832/j.jnpe.2024.090040

Volume 46 Issue 2

Apr. 2025

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Jiang Yong, An Ping, Liu Dong, Yu Yang. Research on the Solution and Acceleration Algorithm of Source Iteration Method Based on PINN[J]. Nuclear Power Engineering, 2025, 46(2): 148-155. doi: 10.13832/j.jnpe.2024.090040

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Jiang Yong, An Ping, Liu Dong, Yu Yang. Research on the Solution and Acceleration Algorithm of Source Iteration Method Based on PINN[J]. Nuclear Power Engineering, 2025, 46(2): 148-155. doi: 10.13832/j.jnpe.2024.090040

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Research on the Solution and Acceleration Algorithm of Source Iteration Method Based on PINN

doi: 10.13832/j.jnpe.2024.090040

National Key Laboratory of Nuclear Reactor Technology, Nuclear Power Institute of China, Chengdu, 610213, China

Received Date: 2024-09-16
Rev Recd Date: 2024-12-22

Available Online: 2025-01-15

Publish Date: 2025-04-02

Abstract

Abstract

This paper integrates physics-driven artificial intelligence methods with the traditional source iteration method to establish a novel approach for solving the few-group diffusion equations, and employs the Anderson acceleration method to accelerate the iterative source term. The results of numerical examples such as two-dimensional multi material and three-dimensional single material show that the combination of physics-driven Physics-Informed Neural Networks (PINN) and traditional source iteration method can calculate the continuous neutron flux density distribution while ensuring calculation accuracy. The use of Anderson acceleration method can reduce the number of iteration, ssuccessfully achieving the forward solution of the few-group neutron diffusion equations. This advancement promotes the application of artificial intelligence algorithms in the nuclear field.
- PINN,
- Anderson acceleration,
- Source iteration,
- Neutron diffusion equation

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References(14)

References

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