Model Reduction Using Sparse Polynomial Interpolation for the Incompressible Navier-Stokes Equations

This work investigates the use of sparse polynomial interpolation as a model order reduction method for the parametrized 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 assess 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 provide a clear indication that sparse polynomial interpolation is a valid instrument in the toolbox of ROM methods.

Automated summary

This work investigates the use of sparse polynomial interpolation as a model order reduction method for the parametrized incompressible Navier-Stokes equations and compares it with established reduced basis techniques. The findings suggest that sparse polynomial interpolation is a valid instrument in the toolbox of ROM methods.