Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
153 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Step size control for explicit relaxation Runge-Kutta methods preserving invariants (2311.14050v1)

Published 23 Nov 2023 in math.NA and cs.NA

Abstract: Many time-dependent differential equations are equipped with invariants. Preserving such invariants under discretization can be important, e.g., to improve the qualitative and quantitative properties of numerical solutions. Recently, relaxation methods have been proposed as small modifications of standard time integration schemes guaranteeing the correct evolution of functionals of the solution. Here, we investigate how to combine these relaxation techniques with efficient step size control mechanisms based on local error estimates for explicit Runge-Kutta methods. We demonstrate our results in several numerical experiments including ordinary and partial differential equations.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (64)
  1. “Relaxation Deferred Correction Methods and their Applications to Residual Distribution Schemes” In The SMAI Journal of Computational Mathematics 8, 2022, pp. 125–160 DOI: 10.5802/smai-jcm.82
  2. Rasha Al Jahdali, Lisandro Dalcin and Matteo Parsani “On the performance of relaxation and adaptive explicit Runge-Kutta schemes for high-order compressible flow simulations” In Journal of Computational Physics Elsevier, 2022 DOI: 10.1016/j.jcp.2022.111333
  3. GE Alefeld, Florian A Potra and Yixun Shi “Algorithm 748: Enclosing Zeros of Continuous Functions” In ACM Transactions on Mathematical Software (TOMS) 21.3 ACM New York, NY, USA, 1995, pp. 327–344 DOI: 10.1145/210089.210111
  4. Thomas Brooke Benjamin, Jerry Lloyd Bona and John Joseph Mahony “Model equations for long waves in nonlinear dispersive systems” In Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences 272.1220 The Royal Society London, 1972, pp. 47–78 DOI: 10.1098/rsta.1972.0032
  5. “Julia: A Fresh Approach to Numerical Computing” In SIAM Review 59.1 SIAM, 2017, pp. 65–98 DOI: 10.1137/141000671
  6. Abhijit Biswas and David I Ketcheson “Accurate Solution of the Nonlinear Schrödinger Equation via Conservative Multiple-Relaxation ImEx Methods”, 2023 arXiv:2309.02324 [math.NA]
  7. Abhijit Biswas and David I Ketcheson “Multiple relaxation Runge-Kutta methods for conservative dynamical systems”, 2023 arXiv:2302.05235 [math.NA]
  8. “Reproducibility repository for "Step size control for explicit relaxation Runge-Kutta methods preserving invariants"”, https://github.com/ranocha/2023_FSAL_relaxation, 2023 DOI: 10.5281/zenodo.10201246
  9. Przemyslaw Bogacki and Lawrence F Shampine “A 3(2) pair of Runge-Kutta formulas” In Applied Mathematics Letters 2.4 Elsevier, 1989, pp. 321–325 DOI: 10.1016/0893-9659(89)90079-7
  10. John Charles Butcher “Numerical Methods for Ordinary Differential Equations” Chichester: John Wiley & Sons Ltd, 2016 DOI: 10.1002/9781119121534
  11. “On the Preservation of Invariants by Explicit Runge-Kutta Methods” In SIAM Journal on Scientific Computing 28.3 SIAM, 2006, pp. 868–885 DOI: 10.1137/04061979X
  12. Kees Dekker and Jan G Verwer “Stability of Runge-Kutta methods for stiff nonlinear differential equations” 2, CWI Monographs Amsterdam: North-Holland, 1984
  13. John R Dormand and Peter J Prince “A family of embedded Runge-Kutta formulae” In Journal of Computational and Applied Mathematics 6.1 Elsevier, 1980, pp. 19–26 DOI: 10.1016/0771-050X(80)90013-3
  14. Matteo Frigo and Steven G Johnson “The design and implementation of FFTW3” In Proceedings of the IEEE 93.2 IEEE, 2005, pp. 216–231 DOI: 10.1109/JPROC.2004.840301
  15. “High order entropy preserving ADER-DG scheme” In Applied Mathematics and Computation 440.127644 Elsevier, 2023 DOI: 10.1016/j.amc.2022.127644
  16. “Enabling new flexibility in the SUNDIALS suite of nonlinear and differential/algebraic equation solvers” In ACM Transactions on Mathematical Software (TOMS) ACM, 2022 DOI: 10.1145/3539801
  17. Kjell Gustafsson, Michael Lundh and Gustaf Söderlind “A PI stepsize control for the numerical solution of ordinary differential equations” In BIT Numerical Mathematics 28.2 Springer, 1988, pp. 270–287 DOI: 10.1007/BF01934091
  18. Ernst Hairer, Christian Lubich and Gerhard Wanner “Geometric Numerical Integration: Structure-Preserving Algorithms for Ordinary Differential Equations” 31, Springer Series in Computational Mathematics Berlin Heidelberg: Springer-Verlag, 2006 DOI: 10.1007/3-540-30666-8
  19. Ernst Hairer, Syvert Paul Nørsett and Gerhard Wanner “Solving Ordinary Differential Equations I: Nonstiff Problems” 8, Springer Series in Computational Mathematics Berlin Heidelberg: Springer-Verlag, 2008 DOI: 10.1007/978-3-540-78862-1
  20. “Solving Ordinary Differential Equations II: Stiff and Differential-Algebraic Problems” 14, Springer Series in Computational Mathematics Berlin Heidelberg: Springer-Verlag, 2010 DOI: 10.1007/978-3-642-05221-7
  21. George Hall “Equilibrium states of Runge Kutta schemes” In ACM Transactions on Mathematical Software (TOMS) 11.3 ACM, 1985, pp. 289–301 DOI: 10.1145/214408.214424
  22. George Hall “Equilibrium states of Runge-Kutta schemes: part II” In ACM Transactions on Mathematical Software (TOMS) 12.3 ACM, 1986, pp. 183–192 DOI: 10.1145/7921.7922
  23. George Hall and Desmond J Higham “Analysis of stepsize selection schemes for Runge-Kutta codes” In IMA Journal of Numerical Analysis 8.3 Oxford University Press, 1988, pp. 305–310 DOI: 10.1093/imanum/8.3.305
  24. Desmond J Higham and George Hall “Embedded Runge-Kutta formulae with stable equilibrium states” In Journal of Computational and Applied Mathematics 29.1 Elsevier, 1990, pp. 25–33 DOI: 10.1016/0377-0427(90)90192-3
  25. “SUNDIALS: Suite of nonlinear and differential/algebraic equation solvers” In ACM Transactions on Mathematical Software (TOMS) 31.3 ACM, 2005, pp. 363–396 DOI: 10.1145/1089014.1089020
  26. J. D. Hunter “Matplotlib: A 2D graphics environment” In Computing in Science & Engineering 9.3 IEEE Computer Society, 2007, pp. 90–95 DOI: 10.1109/MCSE.2007.55
  27. Shinhoo Kang and Emil M Constantinescu “Entropy-Preserving and Entropy-Stable Relaxation IMEX and Multirate Time-Stepping Methods” In Journal of Scientific Computing 93, 2022, pp. 23 DOI: 10.1007/s10915-022-01982-w
  28. Christopher A Kennedy and Mark H Carpenter “Additive Runge-Kutta schemes for convection–diffusion–reaction equations” In Applied Numerical Mathematics 44.1-2 Elsevier, 2003, pp. 139–181 DOI: 10.1016/S0168-9274(02)00138-1
  29. David I Ketcheson “Relaxation Runge-Kutta Methods: Conservation and Stability for Inner-Product Norms” In SIAM Journal on Numerical Analysis 57.6 Society for IndustrialApplied Mathematics, 2019, pp. 2850–2870 DOI: 10.1137/19M1263662
  30. David I Ketcheson and Hendrik Ranocha “Computing with B-series” In ACM Transactions on Mathematical Software 49.2, 2023 DOI: 10.1145/3573384
  31. David A Kopriva “Implementing Spectral Methods for Partial Differential Equations: Algorithms for Scientists and Engineers” New York: Springer Science & Business Media, 2009 DOI: 10.1007/978-90-481-2261-5
  32. Wilhelm Kutta “Beitrag zur näherungsweisen Integration totaler Differentialgleichungen” In Zeitschrift für Mathematik und Physik 46, 1901, pp. 435–453
  33. “A new entropy-variable-based discretization method for minimum entropy moment approximations of linear kinetic equations” In ESAIM: Mathematical Modelling and Numerical Analysis 55.6 EDP Sciences, 2021, pp. 2567–2608 DOI: 10.1051/m2an/2021065
  34. Dongfang Li, Xiaoxi Li and Zhimin Zhang “Implicit-explicit relaxation Runge-Kutta methods: construction, analysis and applications to PDEs” In Mathematics of Computation American Mathematical Society, 2022 DOI: 10.1090/mcom/3766
  35. Dongfang Li, Xiaoxi Li and Zhimin Zhang “Linearly implicit and high-order energy-preserving relaxation schemes for highly oscillatory Hamiltonian systems” In Journal of Computational Physics Elsevier, 2023, pp. 111925 DOI: 10.1016/j.jcp.2023.111925
  36. Viktor Linders, Hendrik Ranocha and Philipp Birken “Resolving Entropy Growth from Iterative Methods” In BIT Numerical Mathematics, 2023 DOI: 10.1007/s10543-023-00992-w
  37. “A conservative fully-discrete numerical method for the regularized shallow water wave equations” In SIAM Journal on Scientific Computing 42, 2021 DOI: 10.1137/20M1364606
  38. Peter J Olver “Euler operators and conservation laws of the BBM equation” In Mathematical Proceedings of the Cambridge Philosophical Society 85.1, 1979, pp. 143–160 Cambridge University Press DOI: 10.1017/S0305004100055572
  39. “Energy-conserving explicit and implicit time integration methods for the multi-dimensional Hermite-DG discretization of the Vlasov-Maxwell equations”, 2021 arXiv:2110.11511 [math.NA]
  40. “DifferentialEquations.jl – A Performant and Feature-Rich Ecosystem for Solving Differential Equations in Julia” In Journal of Open Research Software 5.1 Ubiquity Press, 2017, pp. 15 DOI: 10.5334/jors.151
  41. Hendrik Ranocha “On Strong Stability of Explicit Runge-Kutta Methods for Nonlinear Semibounded Operators” In IMA Journal of Numerical Analysis 41.1 Oxford University Press, 2021, pp. 654–682 DOI: 10.1093/imanum/drz070
  42. Hendrik Ranocha “SummationByPartsOperators.jl: A Julia library of provably stable semidiscretization techniques with mimetic properties” In Journal of Open Source Software 6.64 The Open Journal, 2021, pp. 3454 DOI: 10.21105/joss.03454
  43. Hendrik Ranocha, Lisandro Dalcin and Matteo Parsani “Fully-Discrete Explicit Locally Entropy-Stable Schemes for the Compressible Euler and Navier-Stokes Equations” In Computers and Mathematics with Applications 80.5 Elsevier, 2020, pp. 1343–1359 DOI: 10.1016/j.camwa.2020.06.016
  44. “Optimized Runge-Kutta Methods with Automatic Step Size Control for Compressible Computational Fluid Dynamics” In Communications on Applied Mathematics and Computation 4, 2021, pp. 1191–1228 DOI: 10.1007/s42967-021-00159-w
  45. “Stability of step size control based on a posteriori error estimates”, 2023 DOI: 10.48550/arXiv.2307.12677
  46. Hendrik Ranocha and David I Ketcheson “Relaxation Runge-Kutta Methods for Hamiltonian Problems” In Journal of Scientific Computing 84.1 Springer Nature, 2020 DOI: 10.1007/s10915-020-01277-y
  47. Hendrik Ranocha, Lajos Lóczi and David I Ketcheson “General Relaxation Methods for Initial-Value Problems with Application to Multistep Schemes” In Numerische Mathematik 146 Springer Nature, 2020, pp. 875–906 DOI: 10.1007/s00211-020-01158-4
  48. Hendrik Ranocha, Manuel Luna and David I Ketcheson “On the Rate of Error Growth in Time for Numerical Solutions of Nonlinear Dispersive Wave Equations” In Partial Differential Equations and Applications 2.6, 2021, pp. 76 DOI: 10.1007/s42985-021-00126-3
  49. Hendrik Ranocha, Dimitrios Mitsotakis and David I Ketcheson “A Broad Class of Conservative Numerical Methods for Dispersive Wave Equations” In Communications in Computational Physics 29.4 Global Science Press, 2021, pp. 979–1029 DOI: 10.4208/cicp.OA-2020-0119
  50. “Relaxation Runge-Kutta Methods: Fully-Discrete Explicit Entropy-Stable Schemes for the Compressible Euler and Navier-Stokes Equations” In SIAM Journal on Scientific Computing 42.2 Society for IndustrialApplied Mathematics, 2020, pp. A612–A638 DOI: 10.1137/19M1263480
  51. “Multiderivative time integration methods preserving nonlinear functionals via relaxation”, 2023 DOI: 10.48550/arXiv.2311.03883
  52. Hendrik Ranocha, Jochen Schütz and Eleni Theodosiou “Functional-preserving predictor-corrector multiderivative schemes” In Proceedings in Applied Mathematics and Mechanics, 2023 DOI: 10.1002/pamm.202300025
  53. “On error-based step size control for discontinuous Galerkin methods for compressible fluid dynamics” In Communications on Applied Mathematics and Computation, 2023 DOI: 10.1007/s42967-023-00264-y
  54. “ARKODE: A flexible IVP solver infrastructure for one-step methods” In ACM Transactions on Mathematical Software 49.2, 2023, pp. 1–26 DOI: 10.1145/3594632
  55. “Performance analysis of relaxation Runge-Kutta methods” In The International Journal of High Performance Computing Applications SAGE, 2022 DOI: 10.1177/10943420221085947
  56. Jesus Maria Sanz-Serna “An explicit finite-difference scheme with exact conservation properties” In Journal of Computational Physics 47.2 Elsevier, 1982, pp. 199–210 DOI: 10.1016/0021-9991(82)90074-2
  57. Jesus Maria Sanz-Serna and Manuel P Calvo “Numerical Hamiltonian Problems” 7, Applied Mathematics and Mathematical Computation London: Chapman & Hall, 1994
  58. Gustaf Söderlind “Time-step selection algorithms: Adaptivity, control, and signal processing” In Applied Numerical Mathematics 56.3-4 Elsevier, 2006, pp. 488–502 DOI: 10.1016/j.apnum.2005.04.026
  59. “Adaptive time-stepping and computational stability” In Journal of Computational and Applied Mathematics 185.2 Elsevier, 2006, pp. 225–243 DOI: 10.1016/j.cam.2005.03.008
  60. James H Verner “Numerically optimal Runge-Kutta pairs with interpolants” In Numerical Algorithms 53.2-3 Springer, 2010, pp. 383–396 DOI: 10.1007/s11075-009-9290-3
  61. John Verzani “Roots.jl: Root finding functions for Julia”, https://github.com/JuliaMath/Roots.jl, 2020
  62. “Entropy stable discontinuous Galerkin methods for balance laws in non-conservative form: Applications to the Euler equations with gravity” In Journal of Computational Physics 468 Elsevier, 2022, pp. 111507 DOI: 10.1016/j.jcp.2022.111507
  63. “Entropy-stable Galerkin difference discretization on unstructured grids” In AIAA AVIATION 2020 FORUM, 2020, pp. 3033 DOI: 10.2514/6.2020-3033
  64. “Highly efficient invariant-conserving explicit Runge-Kutta schemes for nonlinear Hamiltonian differential equations” In Journal of Computational Physics Elsevier, 2020, pp. 109598 DOI: 10.1016/j.jcp.2020.109598
Citations (1)

Summary

We haven't generated a summary for this paper yet.