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Uncertainty Quantification and Sensitivity Analysis of SA Turbulence Model Coefficients in Two and Three Dimensions

机译:SA湍流模型系数的不确定度量和敏感性分析两三维度

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The goal of this work is to quantify the uncertainty and sensitivity of the Spalart-Allmaras turbulence model in Reynolds-Averaged Navier-Stokes codes due to uncertainty in the values of model coefficients for three wall-bounded flows, and to rank the contribution of each coefficient to uncertainty in various output flow quantities of interest. Specifically, uncertainty quantification of turbulence model coefficients is performed for a subsonic flat plate, the RAE 2822 transonic airfoil, and transonic flow over the NASA Common Research Model. The Boeing-developed BCFD code is used as the flow solver. The uncertainty quantification analysis employs stochastic expansions based on non-intrusive polynomial chaos for efficient uncertainty propagation. Integrated force coefficients, loads reports, pressure coefficient distributions, and skin friction coefficient distributions are considered as uncertain output quantities of interest. Turbulence model coefficients are treated as epistemic uncertain variables represented with intervals. Sobol indices are used to rank the relative contributions of each coefficient to the total uncertainty in the output quantities of interest. A new method of characterizing the Spalart-Allmaras coefficient uncertainties is discussed and comparisons are made with the old method. The new method employs relations between coefficients which were fundamental to the original development of the model, and in particular allows only a much narrower range for the variations of the logarithmic law.
机译:这项工作的目标是量化Spalart-Allmaras湍流模型在雷诺平均的Navier-Stokes代码中的不确定度和敏感性,由于三个壁限流的模型系数的值,并对每个的贡献进行排名各种输出流量的不确定性系数。具体地,对亚态平板,RAE 2822跨音翼型和NASA常见研究模型上的跨音速流动进行湍流模型系数的不确定度量。波音开发的BCFD代码用作流动求解器。不确定性量化分析采用基于非侵入式多项式混沌的随机扩展,以有效的不确定性繁殖。综合力系数,负载报告,压力系数分布和皮肤摩擦系数分布被认为是不确定的兴趣输出量。湍流模型系数被视为以间隔表示的认识不确定变量。 SOBOL指数用于将每个系数的相对贡献与感兴趣的输出量中的总不确定性进行排名。讨论了表征Spalart-Allmaras系数不确定性的新方法,并用旧方法进行比较。新方法采用与模型原始开发的基础之间的系数之间的关系,特别是对于对数法的变化仅允许更窄的范围。

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