Abstract Unsteady Reynolds-Average Navier-Stocks (URANS) simulation was conducted, in which the mixing of two immiscible fluids with different densities were measured using the multi-component material model for the OECD-TAMU cold-leg mixing benchmark. The turbulence models (i.e. realizable κ-e, standard κ-ω and κ-ω SST) were validated against the particle image velocimetry (PIV) data and sensitivity analysis of uncertain input parameters were carried out. Turbulence models for the prediction of mean velocity components and root mean square velocity components, the mixing phenomena in the cold-leg were found in good agreement with the PIV data. However, the turbulence models unable to predict the close agreement with PIV data in the downcomer. Numerical uncertainty of two meshes was conducted for cold-leg and downcomer. It is observed that the numerical uncertainty band is within the range of experimental measurement data. Furthermore, The sensitivity of five uncertain input parameters (i.e. Schmidt number, density difference, heavy fluid viscosity, light fluid viscosity) was analyzed and their influence on the output parameters was noticed. Therefore, the turbulent Schmidt number and density difference, revealing significant effect on the out parameters. As a consequence, the major contribution of turbulent Schmidt number and density difference will be observed in the propagation of input uncertainty.

中文翻译：

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OECD-TAMU 冷腿混合基准的非稳态 RANS 模拟

摘要 进行了非稳态雷诺-平均纳维-斯托克 (URANS) 模拟，其中使用 OECD-TAMU 冷腿混合基准的多组分材料模型测量具有不同密度的两种不混溶流体的混合。湍流模型（即可实现的κ-e、标准κ-ω 和κ-ω SST）针对粒子图像测速（PIV）数据进行了验证，并对不确定的输入参数进行了敏感性分析。用于预测平均速度分量和均方根速度分量的湍流模型、冷段中的混合现象与 PIV 数据非常吻合。然而，湍流模型无法预测与下降管中的 PIV 数据的密切一致性。对冷段和降液管进行了两个网格的数值不确定性。观察到数值不确定带在实验测量数据的范围内。此外，分析了五个不确定输入参数（即施密特数、密度差、重流体粘度、轻流体粘度）的敏感性，并注意到它们对输出参数的影响。因此，湍流施密特数和密度差，揭示出对输出参数的显着影响。因此，将在输入不确定性的传播中观察到湍流施密特数和密度差异的主要贡献。轻流体粘度）进行了分析，并注意到它们对输出参数的影响。因此，湍流施密特数和密度差，揭示出对输出参数的显着影响。因此，将在输入不确定性的传播中观察到湍流施密特数和密度差异的主要贡献。轻流体粘度）进行了分析，并注意到它们对输出参数的影响。因此，湍流施密特数和密度差，揭示出对输出参数的显着影响。因此，将在输入不确定性的传播中观察到湍流施密特数和密度差异的主要贡献。