不确定性分析是衡量计算流体力学（computational fluid dynamics, CFD）计算精确度的重要手段，利用CFD开展了圆管临界热流密度（critical heat flux, CHF）模拟计算，并构建二阶混沌多项式（polynomial chaos expansions, PCE）替代模型开展入口温度、质量流率、壁面热流密度对近壁面最大传热系数和壁面最大温度输入参数的不确定性分析。分析结果表明：基于计算流体力学程序计算临界热流密度（CFD-CHF）构建的PCE替代模型具有较高的计算精度，壁面热流密度对CHF模型中近壁面最大传热系数和壁面最大温度计算结果影响最大，通过构建适用于特殊场景的PCE替代模型能有效降低CFD不确定性分析的计算时间。

Uncertainty analysis is an essential approach to evaluate the accuracy of CFD (computational fluid dynamics) calculation. CFD was used to simulate CHF (critical heat flux) in a circular tube, and a second-order PCE (polynomial chaos expansions) surrogate model was developed. This model was used to analyze the uncertainty of input parameters (such as inlet temperature, mass flow rate, and wall heat flux) on the maximum wall adjacent heat transfer coefficient and the maximum wall temperature. The results show that the PCE surrogate model developed based on using CFD-CHF (computational fluid dynamics to calculate critical heat flux) has high computational accuracy, and the wall heat flux has the greatest impact on the wall adjacent heat transfer coefficient and the maximum wall temperature, and the application of PCE surrogate model suitable for to specific scenarios effectively reduced the computational time for CFD uncertainty analysis.