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Sensitivity analysis of a final repository model with quasi-discrete behaviour using quasi-random sampling and a metamodel approach in comparison to other variance-based techniques

机译:与其他基于方差的技术相比,使用准随机抽样和元模型方法对具有准离散行为的最终存储库模型进行敏感性分析

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摘要

This paper contributes to the investigation of recent computationally efficient variance-based methods for sensitivity analysis and sampling schemes on the basis of a Performance Assessment (PA) model for a repository for Low- and Intermediate-Level Radioactive Waste (LILW) in an abandonned salt mine. The PA model takes account of typical characteristics of repository systems including a quasi-discrete nature. The results indicate best convergence of the State-Dependent-Parameter (SDP) metamodel method and the simple first-order sensitivity indices (SI1) calculation scheme (EASI) if combined with the LpTau low discrepancy sampling method. The SI1 indices obtained from the SDP and EASI methods are very similar. The Fourier Amplitude Sensitivity Test (EFAST) seems to have some convergence problems, likely due to the quasi-discrete behaviour of the PA model. Due to parameter interactions, none of the investigated methods, however, could directly determine all significant parameters. This is illustrated by means of a simplified way of factor fixing.
机译:本文基于对废弃盐中低级和中级放射性废物(LILW)储存库的性能评估(PA)模型,对基于计算效率的基于方差的敏感性分析和采样方案的最新方法的研究做出了贡献矿。 PA模型考虑了存储系统的典型特征,包括准离散性质。结果表明,如果与LpTau低差异采样方法结合使用,则状态依赖参数(SDP)元模型方法和简单的一阶灵敏度指标(SI1)计算方案(EASI)的最佳收敛性。从SDP和EASI方法获得的SI1指数非常相似。傅里叶振幅灵敏度测试(EFAST)似乎有一些收敛性问题,可能是由于PA模型的准离散行为所致。由于参数之间的相互作用,但是,研究的方法都无法直接确定所有重要参数。这是通过简化的因子确定方法来说明的。

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