Statistical Methodology for a Quantified Validation of Sodium Fast Reactor Simulation Tools

IF 0.5 Q4 ENGINEERING, MECHANICAL
N. Marie, A. Marrel, K. Herbreteau
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引用次数: 5

Abstract

This paper presents a statistical methodology for a quantified validation of the OCARINa simulation tool, which models the unprotected transient overpower (UTOP) accidents. This validation on CABRI experiments is based on a best-estimate plus uncertainties (BEPU) approach. To achieve this, a general methodology based on recent statistical techniques is developed. In particular, a method for the quantification of multivariate data is applied for the visualization of simulator outputs and their comparison with experiments. Still for validation purposes, a probabilistic indicator is proposed to quantify the degree of agreement between the simulator OCARINa and the experiments, taking into account both experimental uncertainties and those on OCARINa inputs. Going beyond a qualitative validation, this work is of great interest for the verification, validation and uncertainty quantification or evaluation model development and assessment process approaches, which leads to the qualification of scientific calculation tools. Finally, for an in-depth analysis of the influence of uncertain parameters, a sensitivity analysis based on recent dependence measures is also performed. The usefulness of the statistical methodology is demonstrated on CABRI-E7 and CABRI-E12 tests. For each case, the BEPU propagation study is carried out performing 1000 Monte Carlo simulations with the OCARINa tool, with nine uncertain input parameters. The validation indicators provide a quantitative conclusion on the validation of the OCARINa tool on both transients and highlight future efforts to strengthen the demonstration of validation of safety tools. The sensitivity analysis improves the understanding of the OCARINa tool and the underlying UTOP scenario.
钠快堆模拟工具量化验证的统计方法
本文提出了一种统计方法,用于对OCARINa模拟工具进行量化验证,该工具对无保护瞬态超功率(UTOP)事故进行建模。CABRI实验的验证基于最佳估计加不确定性(BEPU)方法。为了实现这一点,开发了一种基于最新统计技术的通用方法。特别是,一种用于量化多变量数据的方法被应用于模拟器输出的可视化及其与实验的比较。仍然出于验证目的,提出了一个概率指标来量化模拟器OCARINa和实验之间的一致性程度,同时考虑了实验的不确定性和OCARINa输入的不确定性。除了定性验证之外,这项工作对验证、验证和不确定性量化或评估模型开发和评估过程方法非常感兴趣,从而使科学计算工具获得资格。最后,为了深入分析不确定参数的影响,还基于最近的相关性测度进行了敏感性分析。CABRI-E7和CABRI-E12测试证明了统计方法的有用性。对于每种情况,BEPU传播研究都是使用OCARINa工具进行1000次蒙特卡罗模拟,其中有9个不确定的输入参数。验证指标提供了OCARINa工具在两种瞬态情况下验证的定量结论,并强调了未来加强安全工具验证的努力。敏感性分析提高了对OCARINa工具和底层UTOP场景的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.60
自引率
16.70%
发文量
12
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