Gamma spectrometry is a passive nondestructive assay method used to quantify radionuclides present in nuclear objects. Basic methods using empirical calibration with a standard to quantify the activity of nuclear materials by determining the calibration coefficient are ineffective on nonreproducible nuclear objects such as waste packages. Package specifications such as composition or geometry change from one package to another and exhibit large variability of objects. The current standard quantification process uses numerical modeling of the measured scene with few available data such as geometry or composition, in particular density, material, screen, geometric shape, matrix composition, matrix, and source distribution. Some of them are strongly dependent on package data knowledge and operator backgrounds. The French Atomic Energy Commission (CEA) is developing a methodology to quantify nuclear materials in waste packages and waste drums without operator adjustment and internal package configuration knowledge. This method suggests combining a stochastic approach which uses, among others, surrogate models available to simulate the gamma attenuation behavior, a Bayesian approach considering conditional probability densities and prior information of problem inputs, and Markov Chain Monte Carlo (MCMC) algorithms which solve inverse problems, with gamma ray emission radionuclide spectra, and the outside dimensions of the objects of interest. The methodology has been tested to quantify actinide activity with a low bulk density matrix, weakly attenuating compositions, without information on the distribution of the source in terms of actinide masses and materials composing the drums. Activity uncertainties are taken into account.

中文翻译：

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应用于弱衰减核废料桶的多伽马放射性核素定量贝叶斯方法

伽马光谱法是一种被动无损检测方法，用于量化核物体中存在的放射性核素。使用标准经验校准通过确定校准系数来量化核材料活性的基本方法对不可再生的核物体（如废物包）无效。包装规格（例如成分或几何形状）从一个包装更改为另一个包装，并且表现出很大的对象可变性。当前的标准量化过程使用测量场景的数值建模，几乎没有可用的数据，例如几何或组成，特别是密度、材料、屏幕、几何形状、矩阵组成、矩阵和源分布。其中一些严重依赖于包装数据知识和操作员背景。法国原子能委员会 (CEA) 正在开发一种方法来量化废物包和废物桶中的核材料，而无需操作员调整和内部包配置知识。该方法建议结合使用可用于模拟伽马衰减行为的替代模型的随机方法、考虑条件概率密度和问题输入的先验信息的贝叶斯方法以及解决逆问题的马尔可夫链蒙特卡罗 (MCMC) 算法，具有伽马射线发射放射性核素谱，以及感兴趣物体的外部尺寸。该方法已经过测试以量化具有低堆积密度基质、弱衰减组合物的锕系元素活性，没有关于来源在锕系元素质量和构成鼓的材料方面的分布的信息。活动的不确定性被考虑在内。