Skip to main content
Log in

Efficient non-iterative multi-point method for solving the Riemann problem

  • Original Paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

In computational fluid dynamics (CFD), the Riemann problem is vital for precise fluid flow calculations as it involves the accurate computation of the interactions between different states of fluid flow. Approximate non-iterative Riemann solvers are commonly used for efficiency but introduce errors in complex cases. An exact Riemann solver offers higher accuracy by directly solving the problem without approximations or simplifications. However, it involves nonlinear equations, leading to iterative methods. To promote the use of exact solver, an efficient non-iterative multi-point (NIM) method is proposed to solve the Riemann problem as it has a convergence order of \(\frac{1}{\sqrt 2 }\left[ {(1 + \sqrt 2 )^{n - 1} - (1 - \sqrt 2 )^{n - 1} } \right]\), which exceeds the theoretical limit of \(2^{n - 1}\) and thereby disproving the almost 50-year-old Kung–Traub conjecture. As the conjecture has always served as a basis for designing optimal algorithms to solve nonlinear equations, this finding is crucial as it implies the potential to devise substantially faster algorithms, which could find practical applications in engineering fields such as CFD, as demonstrated in this paper.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. LeVeque, R. J.: Finite volume methods for hyperbolic problems. Cambridge university press, Cambridge, vol. 31 (2002). https://doi.org/10.1017/CBO9780511791253.

  2. Cockburn, B., Karniadakis, G. E., Shu, C.-W.: Discontinuous Galerkin methods: theory, computation and applications. Springer, Berlin, vol. 11 (2012). https://doi.org/10.1007/978-3-642-59721-3.

  3. Hesthaven, J. S., Warburton, T.: Nodal discontinuous Galerkin methods: algorithms, analysis, and applications. Springer, New York (2007). https://doi.org/10.1007/978-0-387-72067-8.

  4. Miller, S., Abedi, R.: Riemann solutions for spacetime discontinuous Galerkin methods. J. Comput. Appl. Math. 270, 510–521 (2014). https://doi.org/10.1016/j.cam.2013.11.027

    Article  MathSciNet  Google Scholar 

  5. Harten, A., Lax, P. D., van Leer, B.: On upstream differencing and Godunov-type schemes for hyperbolic conservation laws. In: Hussaini, M.Y., van Leer, B., Van Rosendale, J. (eds) Upwind and high-resolution schemes. Springer, Heidelberg (1997). https://doi.org/10.1007/978-3-642-60543-7_4

  6. Toro, E.F., Spruce, M., Speares, W.: Restoration of the contact surface in the HLL-Riemann solver. Shock Waves 4(1), 25–34 (1994). https://doi.org/10.1007/BF01414629

    Article  ADS  Google Scholar 

  7. Roe, P.: Approximate Riemann solvers, parameter vectors, and difference schemes. J. Comput. Phys. 43(2), 357–372 (1981). https://doi.org/10.1016/0021-9991(81)90128-5

    Article  ADS  MathSciNet  Google Scholar 

  8. Magiera, J., Ray, D., Hesthaven, J.S., Rohde, C.: Constraint-aware neural networks for Riemann problems. J. Comput. Phys. 409, 109345 (2020). https://doi.org/10.1016/j.jcp.2020.109345

    Article  MathSciNet  Google Scholar 

  9. Wang, J.: Riemann solvers with non-ideal thermodynamics: exact, approximate, and machine learning solutions. Ph.D. dissertation, UWSpace (2022). http://hdl.handle.net/10012/18778. Accessed 5 June 2023.

  10. Ruggeri, M., Roy, I., Mueterthies, M.J., Gruenwald, T., Scalo, C.: Neural-network-based Riemann solver for real fluids and high explosives; application to computational fluid dynamics. Phys. Fluids 34(11), 116121 (2022). https://doi.org/10.1063/5.0123466

    Article  ADS  CAS  Google Scholar 

  11. Wang, J.C.-H., Hickey, J.-P.: Fluxnet: a physics-informed learning-based Riemann solver for transcritical flows with non-ideal thermodynamics. Comput. Methods Appl. Mech. Eng. 411, 116070 (2023). https://doi.org/10.1016/j.cma.2023.116070

    Article  ADS  MathSciNet  Google Scholar 

  12. Colella, P., Glaz, H.M.: Efficient solution algorithms for the Riemann problem for real gases. J. Comput. Phys. 59(2), 264–289 (1985). https://doi.org/10.1016/0021-9991(85)90146-9

    Article  ADS  MathSciNet  Google Scholar 

  13. Hirota equation W.-Q. Peng, Chen, Y.: N-double poles solutions for nonlocal with nonzero boundary conditions using Riemann–Hilbert method and PINN algorithm. Phys. D: Nonlinear Phenomena. 435, 133274 (2022). https://doi.org/10.1016/j.physd.2022.133274.

  14. Peng, W.-Q., Chen, Y.: Double and triple pole solutions for the Gerdjikov-Ivanov type of derivative nonlinear Schr dinger equation with zero/nonzero boundary conditions. J. Math. Phys. 63(3), 033502 (2022). https://doi.org/10.1063/5.0061807

    Article  ADS  Google Scholar 

  15. Zeng, S., Liu, Y.: The Whitham modulation solution of the complex modified KdV equation. Mathematics 11(13), 2810 (2023). https://doi.org/10.3390/math11132810

    Article  Google Scholar 

  16. El, G., Geogjaev, V., Gurevich, A., Krylov, A.: Decay of an initial discontinuity in the defocusing NLS hydrodynamics. Phys. D 87(1), 186–192 (1995). https://doi.org/10.1016/0167-2789(95)00147-V

    Article  MathSciNet  Google Scholar 

  17. Zhu, J.-Y., Chen, Y.: Long-time asymptotic behavior of the coupled dispersive AB system in low regularity spaces. J. Math. Phys. 63(11), 113504 (2022). https://doi.org/10.1063/5.0102264

    Article  ADS  MathSciNet  Google Scholar 

  18. Liu, Y., Wang, D.-S.: Exotic wave patterns in Riemann problem of the high-order Jaulent-Miodek equation: Whitham modulation theory. Stud. Appl. Math. 149(3), 588–630 (2022). https://doi.org/10.1111/sapm.12513

    Article  MathSciNet  Google Scholar 

  19. Kamchatnov, A.M.: Evolution of initial discontinuities in the DNLS equation theory. J. Phys. Commun. 2(2), 025027 (2018). https://doi.org/10.1088/2399-6528/aaae12

    Article  Google Scholar 

  20. Ivanov, S.K.: Riemann problem for the light pulses in optical fibers for the generalized Chen-Lee-Liu equation. Phys. Rev. A 101, 053827 (2020). https://doi.org/10.1103/PhysRevA.101.053827

    Article  ADS  MathSciNet  CAS  Google Scholar 

  21. Zhu, J.-Y., Chen, Y.: A new form of general soliton solutions and multiple zeros solutions for a higher-order Kaup-Newell equation. J. Math. Phys. 62(12), 123501 (2021). https://doi.org/10.1063/5.0064411

    Article  ADS  MathSciNet  Google Scholar 

  22. Chong, C., Herrmann, M., Kevrekidis, P.: Dispersive shock waves in lattices: a dimension reduction approach. Physica D 442, 133533 (2022). https://doi.org/10.1016/j.physd.2022.133533

    Article  MathSciNet  Google Scholar 

  23. Kung, H.T., Traub, J.F.: Optimal order of one-point and multipoint iteration. J. ACM 21(4), 643–651 (1974). https://doi.org/10.1145/321850.321860

    Article  MathSciNet  Google Scholar 

  24. Behl, R., Cordero, A., Motsa, S.S., Torregrosa, J.R.: Multiplicity anomalies of an optimal fourth-order class of iterative methods for solving nonlinear equations. Nonlinear Dyn. 91(1), 81–112 (2018). https://doi.org/10.1007/s11071-017-3858-6

    Article  MathSciNet  Google Scholar 

  25. Behl, R., Alshomrani, A.S., Motsa, S.S.: An optimal scheme for multiple roots of nonlinear equations with eighth-order convergence. J. Math. Chem. 56(7), 2069–2084 (2018). https://doi.org/10.1007/s10910-018-0857-x

    Article  MathSciNet  CAS  Google Scholar 

  26. Zafar, F., Cordero, A., Junjua, M.-U.-D., Torregrosa, J.R.: “Optimal eighth-order iterative methods for approximating multiple zeros of nonlinear functions,” Revista de la Real Academia de Ciencias Exactas. Físicas y Naturales. Serie A. Matemáticas 114(2), 64 (2020). https://doi.org/10.1007/s13398-020-00794-7

    Article  MathSciNet  Google Scholar 

  27. Panday, S., Sharma, A., Thangkhenpau, G.: Optimal fourth and eighth-order iterative methods for non-linear equations. J. Appl. Math. Comput. 69(1), 953–971 (2023). https://doi.org/10.1007/s12190-022-01775-2

    Article  MathSciNet  Google Scholar 

  28. Naber, J.: Building Your Own Shock Tube. ser. Modelling, Analysis and Simulation (MAS). Amsterdam, Netherlands: Stichting Centrum voor Wiskunde en Informatica, 2005, https://ir.cwi.nl/pub/10964. Accessed 5 June 2023.

  29. Chen, X.-D., Shi, J., Ma, W.: A fast and robust method for computing real roots of nonlinear equations. Appl. Math. Lett. 68, 27–32 (2017). https://doi.org/10.1016/j.aml.2016.12.013

    Article  MathSciNet  Google Scholar 

  30. Davis, P.J.: Interpolation and Approximation. Blaisdell Pub. Company, New York (1963)

    Google Scholar 

  31. Habgood, K., Arel, I.: A condensation-based application of Cramers rule for solving large-scale linear systems. J. Discrete Algorithms 10, 98–109 (2012). https://doi.org/10.1016/j.jda.2011.06.007

    Article  MathSciNet  Google Scholar 

  32. Anderson, E., Bai, Z., Bischof, C., Blackford, S., Demmel, J., Dongarra, J., Du Croz, J., Greenbaum, A., Hammarling, S., McKenney, A., Sorensen, D.: LAPACK Users' Guide, 3rd edn. Philadelphia: Society for Industrial and Applied Mathematics, 1999. https://www.netlib.org/lapack/lug/. Accessed 5 June 2023.

  33. Chen, X.-D., Zhang, Y., Shi, J., Wang, Y.: An efficient method based on progressive interpolation for solving non-linear equations. Appl. Math. Lett. 61, 67–72 (2016). https://doi.org/10.1016/j.aml.2016.05.007

    Article  MathSciNet  Google Scholar 

  34. Berthon, C.: Why the MUSCL-Hancock scheme is L1-stable. Numer. Math. 104, 27–46 (2006). https://doi.org/10.1007/s00211-006-0007-4

    Article  MathSciNet  Google Scholar 

  35. Koren, B.: A robust upwind discretization method for advection, diffusion and source terms. In: C. B. Vreugdenhil, B. Koren (Eds.), Numerical Methods for Advection-Diffusion Problems, pp. 117–138. Vieweg (1993)

  36. Sod, G.A.: A survey of several finite difference methods for systems of nonlinear hyperbolic conservation laws. J. Comput. Phys. 27(1), 1–31 (1978). https://doi.org/10.1016/0021-9991(78)90023-2

    Article  ADS  MathSciNet  Google Scholar 

  37. Einfeldt, B., Munz, C., Roe, P., Sjögreen, B.: On Godunov-type methods near low densities. J. Comput. Phys. 92(2), 273–295 (1991). https://doi.org/10.1016/0021-9991(91)90211-3

    Article  ADS  MathSciNet  Google Scholar 

  38. Woodward, P., Colella, P.: The numerical simulation of two-dimensional fluid flow with strong shocks. J. Comput. Phys. 54(1), 115–173 (1984). https://doi.org/10.1016/0021-9991(84)90142-6

    Article  ADS  MathSciNet  Google Scholar 

  39. Toro, E.F.: Riemann solvers and numerical methods for fluid dynamics: a practical introduction. Springer, Berlin (2009). https://doi.org/10.1007/b79761.

Download references

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yi Han Toh.

Ethics declarations

Conflict of interests

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Toh, Y.H. Efficient non-iterative multi-point method for solving the Riemann problem. Nonlinear Dyn 112, 5439–5451 (2024). https://doi.org/10.1007/s11071-023-09229-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-023-09229-5

Keywords

Navigation