Parametric vector flows for registration fields in bounded domains with applications to nonlinear interpolation of shock-dominated flows
Jon Labatut, Jean-Baptiste Chapelier, Angelo Iollo, Tommaso Taddei

TL;DR
This paper introduces a registration method using parametric vector flows to improve model order reduction and nonlinear interpolation of shock-dominated fluid flows in bounded domains.
Contribution
It develops a novel registration approach based on diffeomorphisms generated by velocity fields, combined with an EM algorithm for point cloud matching, enhancing fluid flow interpolation accuracy.
Findings
Effective registration of shock structures in fluid flows
Improved nonlinear interpolation accuracy for transonic flows
Demonstrated success on 2D and 3D flow examples
Abstract
We present a registration procedure for parametric model order reduction (MOR) in two- and three-dimensional bounded domains. In the MOR framework, registration methods exploit solution snapshots to identify a parametric coordinate transformation that improves the approximation of the solution set through linear subspaces. For each training parameter, optimization-based (or variational) registration methods minimize a target function that measures the alignment of the coherent structures of interest (e.g., shocks, shear layers, cracks) for different parameter values, over a family of bijections of the computational domain . We consider diffeomorphisms that are vector flows of given velocity fields with vanishing normal component on ; we rely on a sensor to extract appropriate point clouds from the solution snapshots and we develop an…
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Taxonomy
TopicsModel Reduction and Neural Networks · Advanced Numerical Methods in Computational Mathematics · Fluid Dynamics and Turbulent Flows
