论文标题
基于亚网格人工粘度建模的缺陷脱授予校正方法
Defect-Deferred Correction Method Based on a Subgrid Artificial Viscosity Modeling
论文作者
论文摘要
提出了基于子网格人工粘度建模（SAV）的替代第一步近似，以用于在高雷诺数下的不可分割的Navier-Stokes方程缺陷式校正方法（DDC）。这种新方法不仅保留了基于常规人工粘度（AV）的所有资格，例如无条件的稳定性，高准确性等等，而且还表明了它优于在预测器步骤中选择AV近似值。本文提出的理论和计算结果都表明，这种替代方法确实提高了DDC方法的效率。
An alternative first step approximation based on subgrid artificial viscosity modeling (SAV) is proposed for defect-deferred correction method (DDC) for incompresible Navier-Stokes equation at high Reynolds number. This new approach not only preserves all qualifications of the conventional artificial viscosity (AV) based DDC, such as unconditional stability, high order of accuracy and so on, it has also shown its superiority over choosing AV approximation in the predictor step. Both theory and computational results presented in this paper illustrate that this alternative approach indeed increases the efficiency of the DDC method.
