Skip to content
DraconiticResearch
Search Sources API
190,335 studies31 sourcesUpdated 15 min ago
Peer-reviewedCC BY 4.0Mathematics

An Efficient Error-Controlled POD Reduced-Order Collocation Spectral Method for Unsteady Incompressible Navier–Stokes Equations

  1. 1College of Sciences, China Jiliang University, Hangzhou 310018, China
  2. 2School of Nuclear Science and Engineering, North China Electric Power University, Beijing 102206, China

Abstract

The efficient numerical solution of the unsteady incompressible Navier–Stokes equations requires a balance between computational accuracy and efficiency. Although spectral methods provide high-order spatial approximation, the dense algebraic systems generated by their global discretization lead to relatively high computational costs. To address this issue, a POD-based reduced-order collocation spectral method is developed in this paper. First, a nonlinear collocation spectral method (NCSM) is constructed using the projection method and Chebyshev collocation discretization. An SVD-based linearization is then introduced to obtain a linearized collocation spectral method (LCSM) compatible with POD reduction. Based on snapshots generated by the LCSM, a reduced-order collocation spectral method (ROCSM) is further established. Error estimates are derived for the full-order discretization, linearization, and POD reduction, and a residual-based criterion is introduced to guide the selection and updating of the POD basis. Numerical experiments on a body-force-driven multimode vortex flow and an unsteady lid-driven cavity flow verify the theoretical error estimates and demonstrate the effectiveness of the proposed method. The ROCSM accurately reproduces the principal flow structures while substantially reducing the computational cost. Moreover, the results show that the POD-basis updating strategy guided by the POD reduction error effectively prevents error accumulation in long-time simulations. These results confirm that the proposed method provides an accurate and efficient approach for unsteady incompressible Navier–Stokes flows.

Related

  1. An Efficient Quantum Spectral-Galerkin Method for Linear Elliptic Equations
    Dongjie Wang, Sheng Chen
    arXivPreprintarXiv licenceFull textComputational physicsarXiv
  2. Homothetic Self-Similar Solutions to the Incompressible Navier-Stokes Equations
    Tim Binz, Matei P. Coiculescu
    arXivPreprintarXiv licenceFull textAnalysis & PDEsFluid dynamicsarXiv
  3. Solving the Incompressible Navier-Stokes Equations on Oriented Curved Surfaces Discretized by Point Clouds
    Alejandra Foggia, Ivo F. Sbalzarini
    arXivPreprintCC BY 4.0Full textNumerical analysis & scientific computingComputational physicsarXiv
  4. Projection-based segregated, iterative, and multi-stage physics-informed neural network for incompressible Navier-stokes equations
    Zhenyu Zhang, Zhixiang Ling, Yinghao Huo +2
    arXivPreprintarXiv licenceFull textComputational physicsFluid dynamicsarXiv
  5. Exact Periodic Solutions of the Forced Incompressible Navier-Stokes Equations in Arbitrary Dimensions
    R. K. Michael Thambynayagam
    arXivPreprintarXiv licenceFull textFluid dynamicsarXiv
BibTeX
@article{xu2026efficient,
  title = {{An Efficient Error-Controlled POD Reduced-Order Collocation Spectral Method for Unsteady Incompressible Navier–Stokes Equations}},
  author = {Yige Xu and Shiju Jin and Mingzhou Yu and Mei Huang},
  journal = {Mathematics},
  year = {2026},
  month = oct,
  doi = {10.3390/math14203663},
  url = {https://www.mdpi.com/2227-7390/14/20/3663},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - An Efficient Error-Controlled POD Reduced-Order Collocation Spectral Method for Unsteady Incompressible Navier–Stokes Equations
AU  - Yige Xu
AU  - Shiju Jin
AU  - Mingzhou Yu
AU  - Mei Huang
PY  - 2026
DA  - 2026/10/10
JO  - Mathematics
DO  - 10.3390/math14203663
UR  - https://www.mdpi.com/2227-7390/14/20/3663
AB  - The efficient numerical solution of the unsteady incompressible Navier–Stokes equations requires a balance between computational accuracy and efficiency. Although spectral methods provide high-order spatial approximation, the dense algebraic systems generated by their global discretization lead to relatively high computational costs. To address this issue, a POD-based reduced-order collocation spectral method is developed in this paper. First, a nonlinear collocation spectral method (NCSM) is constructed using the projection method and Chebyshev collocation discretization. An SVD-based linearization is then introduced to obtain a linearized collocation spectral method (LCSM) compatible with POD reduction. Based on snapshots generated by the LCSM, a reduced-order collocation spectral method (ROCSM) is further established. Error estimates are derived for the full-order discretization, linearization, and POD reduction, and a residual-based criterion is introduced to guide the selection and updating of the POD basis. Numerical experiments on a body-force-driven multimode vortex flow and an unsteady lid-driven cavity flow verify the theoretical error estimates and demonstrate the effectiveness of the proposed method. The ROCSM accurately reproduces the principal flow structures while substantially reducing the computational cost. Moreover, the results show that the POD-basis updating strategy guided by the POD reduction error effectively prevents error accumulation in long-time simulations. These results confirm that the proposed method provides an accurate and efficient approach for unsteady incompressible Navier–Stokes flows.
SN  - 2227-7390
ER  -