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基于蒙特卡罗方法的中子-光子耦合多群截面库制作

Fabrication of Neutron-photon Coupling Multi-group Cross-section Library Based on Monte Carlo Method

  • 摘要: 确定论计算程序具有计算效率高的优点,适用于核反应堆辐射屏蔽计算,但其精度主要取决于多群截面库的准确性。由于不同类型的反应堆具有不同的能谱,目前通用的多群截面库无法保证不同类型反应堆的计算精度。基于蒙特卡罗程序OpenMC,改进了制作中子-光子耦合多群截面库的方法;增加了统计光子产生截面的新功能,用于统计由中子反应引起的光子产生截面;考虑了原子弛豫、韧致辐射和正负电子湮灭产生的光子源,并对其进行散射化处理。为了验证本方法的适用性,采用了OECD/NEA快堆基准题、“萨凡纳”热堆基准题和HBR-2屏蔽基准题进行中子-光子耦合多群截面的制作,并将制作的多群截面库提供给确定论程序DORT进行计算。计算结果与OpenMC结果进行了对比:对于快堆模型和热堆模型,使用本方法制作的多群截面库计算结果与OpenMC的计算结果符合较好,且优于使用Bugle96库的计算结果;对于屏蔽问题,使用本方法制作的多群截面库计算结果与OpenMC结果的误差符合工程要求,且优于使用Bugle96库的计算结果。

     

    Abstract: Deterministic calculation codes have the advantage of high calculation efficiency and are suitable for radiation shielding calculation of nuclear reactors, but its accuracy mainly depends on the precision of multi-group cross-section library. Different types of reactors have varying energy spectra, and the currently available general multi-group cross-section libraries cannot ensure calculation accuracy across different reactor types. This study improves the method for generating neutron-photon coupled multi-group cross-section libraries based on the Monte Carlo code OpenMC. A new feature for counting photon production cross-sections resulting from neutron reactions has been added. The photon sources produced by atomic relaxation, bremsstrahlung and positron and electron annihilation are considered and treated by scattering. To validate the applicability of this method, the OECD/NEA fast reactor benchmark, the Savannah thermal reactor benchmark, and the HBR-2 shielding benchmark are utilized for generating the neutron-photon coupled multi-group cross-sections. The produced multi-group cross-section libraries are provided to the deterministic code DORT for calculations. The results are compared with those from OpenMC. For both fast and thermal reactor models, the results using the newly developed multi-group cross-section libraries show good agreement with OpenMC results and outperformed those obtained using the Bugle96 library.

     

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