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AXSP程序中不可分辨能区共振自屏截面计算模块开发和验证

Development and Validation of Resonance Self-shielding Cross Section Calculation Module of the Unresolved Energy Region in AXSP Program

  • 摘要: 在不可分辨能区,由于共振峰非常密集,受核测量仪器分辨率的限制,不能测得对应能量点下精确的共振参数数据。对该能区,评价核数据库只给出共振参数的平均值和分布函数。为了考虑不可分辨共振能区的共振自屏效应,需要根据这些具有概率分布性质的参数计算有效自屏截面。针对不可分辨共振能区的共振自屏效应的处理,采用“Ladder Sampling”和积分统计原理方法,在先进核截面处理程序AXSP中开发了概率表模块PUnresXS和有效自屏截面计算模块UnresXS,并对概率表计算模块中的算法进行了改进。以NJOY2016的计算结果作为参考解,分别对PUnresXS和UnresXS模块进行了验证,结果表明:概率表模块计算效率提高了60%以上,基准题keff与中子能谱结果与参考解符合良好,开发的共振自屏截面计算模块计算精度与NJOY2016相当,表明了这两个模块在AXSP程序中开发的正确性。

     

    Abstract: In the unresolved energy region, due to the dense distribution of resonance peaks, the precise resonance parameter data cannot be obtained due to the resolution limitation of the nuclear measuring instrument. For this energy region, the Evaluation Nuclear Data Files only provides the average values and distribution functions of the resonance parameters. In order to consider the resonance self-shielding effect in the unresolved resonance energy region, it is necessary to calculate the effective self-shielding cross-section based on these parameters with probability distribution properties. For the treatment of resonance self-shielding effect in the unresolved resonance energy region, a probability table module PUnresXS and an effective self-shielding cross-section calculation module UnresXS were developed in the advanced nuclear cross-section processing program AXSP based on the "Ladder Sampling" and integral statistics principle method. The algorithms in the probability table calculation module were also improved. By comparing with the reference solution obtained from NJOY2016 calculations, the PUnresXS and UnresXS modules were independently validated. The results showed that the efficiency of the probability table module was improved by more than 60%, the keff and neutron spectrum were in good agreement with the reference solution. The developed resonance self-shielding cross-section calculation module exhibited similar accuracy to NJOY2016, demonstrating the correctness of these two modules developed in the AXSP program.

     

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