论文标题
使用稀疏多项式插值进行模型降低，用于不可压缩的Navier-Stokes方程
Model Reduction Using Sparse Polynomial Interpolation for the Incompressible Navier-Stokes Equations
论文作者
论文摘要
这项工作调查了稀疏多项式插值作为不可压缩的Navier-Stokes方程的模型订购方法。给出了数值结果，强调了稀疏多项式近似的有效性，并与已建立的还原技术进行了比较。两个数值模型可访问降低订单模型（ROM）的准确性，特别是详细研究了由弯曲几何形状引起的参数非线性。除了ROM的准确性外，该方法的其他重要特征还涵盖了诸如离线划分，运行时间和易于实现的功能。这些发现将稀疏的多项式插值作为破坏维度诅咒的工具箱中的另一种仪器。
This work investigates the use of sparse polynomial interpolation as a model order reduction method for the incompressible Navier-Stokes equations. Numerical results are presented underscoring the validity of sparse polynomial approximations and comparing with established reduced basis techniques. Two numerical models serve to access the accuracy of the reduced order models (ROMs), in particular parametric nonlinearities arising from curved geometries are investigated in detail. Besides the accuracy of the ROMs, other important features of the method are covered, such as offline-online splitting, run time and ease of implementation. The findings establish sparse polynomial interpolation as another instrument in the toolbox of methods for breaking the curse of dimensionality.
