Uncertainties of numerical predictions play important role in assessment of safety margins in nuclear reactors. Critical Flow models are used in the different types of Nuclear Safety Analysis but these are especially important in Loss of Coolant Accidents (LOCA) analyses.

In this paper validation of the input decks is performed of all of the Marviken critical flow tests. Next uncertainties of the prediction of these models implemented into TRACE and MELCOR computer codes are analysed and discussed. Results of the global uncertainty analysis are shown in terms of trends of uncertainty values with respect to the pressure, nozzle length, water level, discharge coefficient and hydraulic diameter.

Application of the global sensitivity analysis methods allowed ranking of the sources of uncertainties over large spectrum of experimental conditions. This was achieved thanks to usage of Bayesian Integrated Uncertainty and Sensitivity Analysis (BIGUSA) methodology. The analysis revealed that the uncertainties of critical mass flow predictions are predominantly resulting from uncertainties of the hydraulic diameter in both codes. In the TRACE code the hydraulic diameter, nozzle length and discharge coefficient were dominating factors. For MELCOR dominating factors were hydraulic diameter, discharge coefficient and pressure.

数值预测的不确定性在核反应堆安全裕度评估中起着重要作用。临界流模型用于不同类型的核安全分析中，但在冷却剂事故损失（LOCA）分析中尤其重要。

在本文中，对所有Marviken关键流量测试的输入平台进行了验证。分析和讨论了在TRACE和MELCOR计算机代码中实现的这些模型的预测的下一步不确定性。全局不确定性分析的结果以不确定性值相对于压力，喷嘴长度，水位，排放系数和水力直径的趋势显示。

全局敏感性分析方法的应用允许在大范围的实验条件下对不确定性来源进行排序。这要归功于贝叶斯综合不确定度和灵敏度分析（BIGUSA）方法的使用。分析表明，临界质量流量预测的不确定性主要是由两个规范中液压直径的不确定性引起的。在TRACE代码中，水力直径，喷嘴长度和排放系数是主要因素。对于MELCOR，主要因素是水力直径，排放系数和压力。