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首页> 外文会议>International meeting on severe accident assessment and management 2012: Lessons learned from fukushima dai-ichi >MAAP PARAMETRIC SENSITIVITY AND UNCERTAINTY ANALYSIS FOR LEVEL 1 LEVEL 2 PROBABILISTIC RISK/SAFETY ASSESSMENT
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MAAP PARAMETRIC SENSITIVITY AND UNCERTAINTY ANALYSIS FOR LEVEL 1 LEVEL 2 PROBABILISTIC RISK/SAFETY ASSESSMENT

机译：1级和2级概率风险/安全性评估的MAAP参数敏感性和不确定性分析

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摘要

The Electric Power Research Institute (EPRI) Modular Accident Analysis Program (MAAP) is an integrated computer code used internationally to assess severe accident analysis progression for a variety of applications. The MAAP code models a significant number of systems and phenomena using a combination of phenomenological and parametric models. It is standard practice in severe accident analysis to define the MAAP parameters using a best estimate approach. It is both good practice and a requirement by some regulators to provide sensitivity/uncertainty analysis of the results. Despite the universal recognition of its importance, there is very little guidance on the practical execution of the sensitivity and uncertainty analysis to be performed, especially as it relates to accident consequence assessment. In this paper an approach to sensitivity and uncertainty analysis is defined. The approach includes a systematic identification of the parameters that should be included in sensitivity analysis. Sensitivity metrics are defined that facilitate interpretation of the sensitivity study results. In the described methodology justified predefined cut-off values of the sensitivity metrics are used to identify the parameters to be included in the uncertainty analysis. Guidance is provided on how uncertainty distributions can be assigned based on sometimes very sparse experimental data. The outputs that are important in interpreting severe accident analysis results in the context of Level 1 and Level 2 Probabilistic Risk/Safety Assessment (PRA/PSA) are identified, and guidance is provided on the statistical interpretation of the uncertainty results. The uncertainty analysis can be used to provide confidence in the robustness of the MAAP results.
机译：电力研究所（EPRI）的模块化事故分析程序（MAAP）是一种集成的计算机代码，在国际上用于评估各种应用程序的严重事故分析进展。 MAAP代码使用现象学模型和参数模型的组合来建模大量系统和现象。在严重事故分析中，标准做法是使用最佳估计方法定义MAAP参数。对结果进行敏感性/不确定性分析既是良好的实践，也是一些监管机构的要求。尽管人们普遍认识到它的重要性，但对于要进行的敏感性和不确定性分析的实际执行，尤其是与事故后果评估有关的指导很少。本文定义了一种敏感性和不确定性分析方法。该方法包括系统地识别应包含在敏感性分析中的参数。定义了敏感度度量标准，以方便对敏感度研究结果的解释。在所描述的方法中，灵敏度度量的合理的预定截止值用于识别不确定性分析中将包括的参数。提供了有关如何基于有时非常稀疏的实验数据分配不确定性分布的指南。确定了在1级和2级概率风险/安全评估（PRA / PSA）的背景下对解释严重事故分析结果至关重要的输出，并提供了不确定性结果的统计解释指南。不确定性分析可用于提供对MAAP结果稳健性的信心。

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