基于优化算法的中子自屏蔽修正方法研究

A Method for Correcting the Neutron Self-Shielding Based on Optimization Algorithms

  • 摘要: 瞬发伽马中子活化分析(PGNAA)技术可以对大体积样品进行元素无损检测,然而测量过程中的中子自屏蔽效应会导致实验测量值与实际值偏差较大,本研究提出一种基于优化算法的修正方法,实现对PGNAA技术测量过程中的中子自屏蔽修正。采用AmBe中子源与高纯锗探测器组成的PGNAA装置对水溶液中的硼元素进行分析,对标准样品进行测量并结合MCNP模拟计算中子自屏蔽修正因子,建立硼元素浓度与特征伽马射线计数的校准曲线。之后利用MCNP模拟计算硼溶液的中子自屏蔽修正曲线,并与差分进化算法结合建立的校准曲线对未知样品的浓度进行分析。留一法验证结果显示,平均误差仅为1.5%,验证了该方法对未知浓度含硼水溶液测量的可行性。

     

    Abstract: Prompt Gamma Neutron Activation Analysis (PGNAA) is a nondestructive technique for elemental analysis of large-volume samples. However, the presence of neutron self-shielding effects during measurements can cause significant discrepancies between measured and true values. To address this issue, this study proposes a correction method based on an optimization algorithm to compensate for neutron self-shielding in PGNAA measurements. An experimental setup consisting of an AmBe neutron source and a high-purity germanium detector was employed to analyze boron in aqueous solutions. Standard samples were measured, and neutron self-shielding correction factors derived from MCNP simulations were used to establish a calibration curve relating boron concentration to characteristic gamma-ray counts. A neutron self-shielding correction curve for boron solutions was then computed via MCNP simulations and incorporated into a calibration model developed using the differential evolution algorithm to estimate the concentrations of unknown samples. Validation using leave-one-out cross-validation demonstrated an average relative error of 1.5%, confirming the feasibility of the proposed method for accurately determining boron concentrations in aqueous solutions of unknown composition.

     

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