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Main Authors: Azaïez, Mejdi, Guo, Yayu, Fernández, Carlos Núñez, Rubino, Samuele, Xu, Chuanju
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2512.10473
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author Azaïez, Mejdi
Guo, Yayu
Fernández, Carlos Núñez
Rubino, Samuele
Xu, Chuanju
author_facet Azaïez, Mejdi
Guo, Yayu
Fernández, Carlos Núñez
Rubino, Samuele
Xu, Chuanju
contents The numerical simulation of incompressible flows is challenging due to the tight coupling of velocity and pressure. Projection methods offer an effective solution by decoupling these variables, making them suitable for large-scale computations. This work focuses on reduced-order modeling using incremental projection schemes for the Stokes equations. We present both semi-discrete and fully discrete formulations, employing BDF2 in time and finite elements in space. A proper orthogonal decomposition (POD) approach is adopted to construct a reduced-order model for the Stokes problem. The method enables explicit computation of reduced velocity and pressure while preserving accuracy. We provide a detailed stability analysis and derive error estimates, showing second-order convergence in time. Numerical experiments are conducted to validate the theoretical results and demonstrate computational efficiency.
format Preprint
id arxiv_https___arxiv_org_abs_2512_10473
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Second order reduced model via incremental projection for Navier Stokes
Azaïez, Mejdi
Guo, Yayu
Fernández, Carlos Núñez
Rubino, Samuele
Xu, Chuanju
Numerical Analysis
The numerical simulation of incompressible flows is challenging due to the tight coupling of velocity and pressure. Projection methods offer an effective solution by decoupling these variables, making them suitable for large-scale computations. This work focuses on reduced-order modeling using incremental projection schemes for the Stokes equations. We present both semi-discrete and fully discrete formulations, employing BDF2 in time and finite elements in space. A proper orthogonal decomposition (POD) approach is adopted to construct a reduced-order model for the Stokes problem. The method enables explicit computation of reduced velocity and pressure while preserving accuracy. We provide a detailed stability analysis and derive error estimates, showing second-order convergence in time. Numerical experiments are conducted to validate the theoretical results and demonstrate computational efficiency.
title Second order reduced model via incremental projection for Navier Stokes
topic Numerical Analysis
url https://arxiv.org/abs/2512.10473