Core Concepts
This research paper proposes novel data augmentation techniques for reduced-order modeling of laminar incompressible flows, enhancing the accuracy and efficiency of simulations by generating physically-consistent artificial snapshots.
Stats
The study uses a P2/P1 finite element discretization for the full-order solver.
The 2D examples use a mesh with 10,962 triangular elements, resulting in 44,400 degrees of freedom for velocity and 5,610 for pressure.
The truncation tolerance for the velocity training set (εu) is set to 10^-3.
The truncation tolerance for the pressure training set (εp) is set to 0.25.
Data augmentation is performed using weighting coefficients (α) ranging from 0.1 to 0.9.