In this work, an application of the deterministic sampling (DS) methodology for uncertainty quantification of manufacturing tolerances is assessed. The DS methodology is applied to eight benchmark cases, from two criticality safety benchmark series, extracted from the International Handbook of Evaluated Criticality Safety Benchmark Experiments (i.e., LCT-007 & LCT-039). The DS results are compared to two other sampling techniques: Random Sampling and Latin Hypercube Sampling. Ten input parameters such as isotopic composition of the fuel, geometry properties of the assembly, pitch array, etc. were considered. Only the multiplicative factor (k_eff) was considered as output quantity. Evaluation of the k_eff was obtained using the Monte Carlo code MCNP for the LCT-007 case, and the Serpent code for LCT-039.

Results show very good agreement among all methodologies for the calculated k_eff values and their corresponding uncertainties. The largest uncertainty difference with DS, compared to the reference values, is 46 pcm for LCT-007 and 9 pcm for LCT-039. The use of DS remarkably reduces the number of samples needed to perform an accurate uncertainty quantification (from thousands of samples down to a dozen).

This study provides insights in the application of DS methodology in the neutron physics domain and showcases its benefits and limitations.

在这项工作中，评估了确定性抽样（DS）方法在制造公差不确定性量化中的应用。DS方法论适用于从两个《关键安全指标评估基准手册》（即LCT-007和LCT-039）的“两个关键安全指标”系列中提取的八个基准案例。将DS结果与其他两种采样技术进行比较：随机采样和拉丁超立方体采样。考虑了十个输入参数，例如燃料的同位素组成，组件的几何特性，间距阵列等。仅将乘数（k _eff）视为输出量。k _eff的评估 使用LCT-007盒的蒙特卡罗代码MCNP和LCT-039的蛇形代码获得。

结果表明，所有方法在计算出的k _eff值及其相应不确定性方面都具有很好的一致性。与参考值相比，DS的最大不确定性差异是LCT-007为46 pcm，LCT-039为9 pcm。DS的使用显着减少了执行准确的不确定度定量所需的样本数量（从数千个样本减少到十几个）。

这项研究提供了DS方法在中子物理学领域中的应用的见解，并展示了其好处和局限性。