EFAST analysis applied to a PA model for a generic HLW repository in clay

Spiessl, Sabine M.; Becker, Dirk-A.; Rubel, Alexander

doi:10.1016/j.ress.2012.04.012

Cited by 7 publications

(1 citation statement)

References 9 publications

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“…As indicated in [15], CSV plots provide a considerably higher amount of information than provided by sensitivity indices obtained using global sensitivity methods. Recent applications of CSM and CSV for importance ranking were reported in the studies dealing with a water hammer model [15] and a performance assessment model for a generic high-level waste repository in clay [16]. The CSM method capabilities were tested for a radioactive high-level waste repository in [14].…”

Section: Introductionmentioning

confidence: 99%

Uncertainty and Sensitivity Analysis at Low Value of Determination Coefficient of Regression Analysis: Case of I-129 Release from RBMK-1500 SNF under Disposal Conditions

2019

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As in other nuclear countries, the operation of the Ignalina nuclear power plant in Lithuania has led to the accumulation of around 22 thousand assemblies of spent nuclear fuel (SNF). The development of geological disposal program involves an iterative assessment of the system safety supported by scientific research on radionuclides migration and related processes. This study focused on the application of Contribution to the Sample Mean (CSM) and Contribution to Sample Variance (CSV) methods to complement the uncertainty and sensitivity analyses of the time-dependent flux of I-129 from the engineered barriers of a conceptual disposal facility for RBMK-1500 SNF (RBMK is abbreviation of "High Power Channel-type Reactor" (in Russian)). The analysis was performed using a MATLAB platform (8.0.0.783 (R2012b), MathWorks, MA, USA). The mean and variance ratios derived from CSM and CSV plots were applied to estimate the effect of reduced uncertainty range on mean flux and its variance, and the uncertainty analysis was also complimented. Increasing the lower bounding value of defect size enlargement time range to 4.6 × 10 4 years would lead to a lower mean flux until 5 × 10 4 years after repository closure. Later on (up to 1 million years after repository closure), the only reduction of the upper bounding value of the SNF dissolution rate range would affect a decreased mean flux.Keywords: RBMK-1500 spent nuclear fuel; deep geological repository; uncertainty and sensitivity; CSM; CSV; radionuclide migration 3 × 10 −12 (p = 0.15) 1 × 10 −11 (p = 0.7) 3 × 10 −11 (p = 0.15) Discrete 1 Probability density function. SNF: spent nuclear fuel.Minerals 2019, 9, 521 5 of 26 Characterization of Model BehaviorThe model realized using the computer code AMBER [34] assessed time-dependent radionuclide release from the SNF matrix, dissolution, radioactive decay, and contaminant transport by diffusion through engineered barriers. The uncertainty of the main transport-related parameters, including defect size enlargement time, was characterized by probability density function for each parameter. The model output was a large number of the time-dependent flux values over an extended period (10 3 -10 6 years after repository closure), which allowed for the evaluation of the mean flux, the quantiles, and the distribution of the peak flux, as illustrated in Figure 2.

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Section: Introductionmentioning

confidence: 99%

Uncertainty and Sensitivity Analysis at Low Value of Determination Coefficient of Regression Analysis: Case of I-129 Release from RBMK-1500 SNF under Disposal Conditions

2019

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Channel Stability Analysis by One-Way Fluid Structure Interaction: A Case Study in China

Zhu

Wang

Liu

et al. 2017

Trans. Tianjin Univ.

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The wide adoption of Large language models (LLMs) makes their dependability a pressing concern. Detection of errors is the first step to mitigating their impact on a system and thus, efficient error detection for LLMs is an important issue. In many settings, the LLM is considered as a black box with no access to the internal nodes; this prevents the use of many error detection schemes that need access to the model's internal nodes. An interesting observation is that the output of LLMs in error-free operation should be valid and normal text. Therefore, when the text is not valid or differs significantly from normal text, it is likely that there is an error. Based on this observation we propose to perform Concurrent Linguistic Error Detection (CLED); this scheme extracts some linguistic features of the text generated by the LLM and feeds them to a concurrent classifier that detects errors. Since the proposed error detection mechanism only relies on the outputs of the model, then it can be used on LLMs in which there is no access to the internal nodes. The proposed CLED scheme has been evaluated on the T5 model when used for news summarization and on the OPUS-MT model when used for translation. In both cases, the same set of linguistic features has been used for error detection to illustrate the applicability of the proposed scheme beyond a specific case. The results show that CLED can detect most of the errors at a low overhead penalty. The use of the concurrent classifier also enables a trade-off between error detection effectiveness and its associated overhead, so providing flexibility to a designer.

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On the inclusion of forest exposure pathways into a stylized lake-farm scenario in a geological repository safety analysis

Pohjola

Turunen

Lipping

et al. 2022

Journal of Environmental Radioactivity

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EFAST analysis applied to a PA model for a generic HLW repository in clay

Cited by 7 publications

References 9 publications

Uncertainty and Sensitivity Analysis at Low Value of Determination Coefficient of Regression Analysis: Case of I-129 Release from RBMK-1500 SNF under Disposal Conditions

Uncertainty and Sensitivity Analysis at Low Value of Determination Coefficient of Regression Analysis: Case of I-129 Release from RBMK-1500 SNF under Disposal Conditions

Channel Stability Analysis by One-Way Fluid Structure Interaction: A Case Study in China

On the inclusion of forest exposure pathways into a stylized lake-farm scenario in a geological repository safety analysis

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