An Optimally Accurate Discrete Regularization for Second Order Timestepping Methods for Navier-Stokes Equations
Abstract
We propose a new, optimally accurate numerical regularization/stabilization for (a family of) second order timestepping methods for the Navier-Stokes equations (NSE). The method combines a linear treatment of the advection term, together with stabilization terms that are proportional to discrete curvature of the solutions in both velocity and pressure. We rigorously prove that the entire new family of methods are unconditionally stable and O(Δt2) accurate. The idea of 'curvature stabilization' is new to CFD and is intended as an improvement over the commonly used 'speed stabilization', which is only first order accurate in time and can have an adverse effect on important flow quantities such as drag coefficients. Numerical examples verify the predicted convergence rate and show the stabilization term clearly improves the stability and accuracy of the tested flows.
Recommended Citation
N. Jiang et al., "An Optimally Accurate Discrete Regularization for Second Order Timestepping Methods for Navier-Stokes Equations," Computer Methods in Applied Mechanics and Engineering, vol. 310, pp. 388 - 405, Elsevier, Oct 2016.
The definitive version is available at https://doi.org/10.1016/j.cma.2016.07.017
Department(s)
Mathematics and Statistics
Keywords and Phrases
Computational fluid dynamics; Drag; Finite difference method; Numerical methods; Stabilization; BDF2; Discrete regularization; IMEX methods; Second order convergence; Speed stabilization; Time stepping method; Unconditional stability; Unconditionally stable; Navier Stokes equations; Crank–Nicolson; Navier–Stokes
International Standard Serial Number (ISSN)
0045-7825
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2016 Elsevier, All rights reserved.
Publication Date
01 Oct 2016
Comments
The first author is partially supported by Air Force grant FA 9550-12-1-0191 . The second author is partially supported by NSF Grant DMS15222191 . The third author is partially supported by NSF Grant DMS1522191 and US Army Grant 65294-MA . The fourth author is partially supported by Air Force grant FA 9550-12-1-0191 and NSF grant DMS-1522574 .