An Adaptive Mesh Refinement Solver for Regularized Shallow Water Equations
https://doi.org/10.23947/2587-8999-2024-8-2-9-23
Abstract
Introduction. We present a novel adaptive mesh refinement (AMR) solver, SWqgdAMR, based on the open software platform AMReX. The new solver is grounded in regularized shallow water equations. This paper details the equations, their discretization, and implementation features within AMReX. The efficacy of SWqgdAMR is demonstrated through two test cases: a two-dimensional circular dam break (collapse of a liquid column) and the collapse of two liquid columns of different heights.
Materials and Methods. The SWqgdAMR solver is developed to extend the applicability of regularized equations in problems requiring high computational power and adaptive grids. SWqgdAMR is the first solver based on the quasigas dynamic (QGD) algorithm within the AMReX framework. The implementation and validation of SWqgdAMR represent a crucial step towards the further expansion of the QGD software suite.
Results. The AMReX-based shallow water equations solver SWqgdAMR with adaptive mesh refinement is described and tested in detail. Validation of SWqgdAMR involved two-dimensional problems: the breach of a cylindrical dam and the breach of two cylindrical dams of different heights. The presented solver demonstrated high efficiency, with the use of adaptive mesh refinement technology accelerating the computation by 56 times compared to a stationary grid calculation.
Discussion and Conclusions. The algorithm can be expanded to include bathymetry, external forces (wind force, bottom friction, Coriolis forces), and the mobility of the shoreline during wetting and drying phases, as has been done in individual codes for regularized shallow water equations (RSWE). The current implementation of the QGD algorithm did not test the potential for parallel computing on graphical cores.
Keywords
About the Authors
I. I. ButRussian Federation
Ivan I. But, research engineer, Open-source Software Laboratory for Digital Modelling of Technical Systems; Junior Researcher
25, Aleksandr Solzhenitsyn st., Moscow, 109004
4, Miusskaya sq., Moscow, 125047
M. A. Kiryushina
Russian Federation
Maria A. Kiryushina, research associate; phd
25, Aleksandr Solzhenitsyn st., Moscow, 109004
4, Miusskaya sq., Moscow, 125047
S. A. Elistratov
Russian Federation
Stepan A. Elistratov, junior researcher; research intern
36, Nakhimovsky ave., Moscow, 117218
5, Aleksandra Solzhenitsyna st., Moscow, 109004
T. G. Elizarova
Russian Federation
Tatiana G. Elizarova, chief researcher; doctor of physico-mathematical sciences, professor
4, Miusskaya sq., Moscow, 125047
A. D. Tiniakov
Russian Federation
Artem D. T iniakov, 5th year student of the Department of Information Transmission and Data Analysis Problems
9, Institutskiy pereulok, Dolgoprudny, 141701
References
1. TheLinuxFoundation. Linux Foundation Announces Intent to Form the High Performance Software Foundation. URL: https://www.linuxfoundation.org/press/linux-foundation-announces-intent-to-form-high-performance-softwarefoundation-hpsf (accessed: 16.04.2024).
2. Epikhin A., But I. Numerical Simulation of Supersonic Jet Noise Using Open Source Software. International Conference on Computational Science. Springer. 2023. P. 292‒302.
3. Kraposhin M.V. et al. Development of a new OpenFOAM solver using regularized gas dynamic equations. Computers & Fluids. 2018;166:163‒175.
4. Kraposhin M.V., Ryazanov D.A., Elizarova T.G. Numerical algorithm based on regularized equations for incompressible flow modeling and its implementation in OpenFOAM. Computer Physics Communications. 2022;271: 108216.
5. QGDsolver. URL: https://github.com/unicfdlab/QGDsolver (accessed: 16.04.2024).
6. Elizarova T.G. Quasi-gas-dynamic Equations. Springer. 2009.
7. Elizarova T.G. Quasi-gas-dynamic Equations and Methods for Calculating Viscous Flows. Moscow: Nauchnyi Mir; 2007. 350 p. (in Russ.).
8. Chetverushkin B.N. Kinetic Schemes and Quasi-gas-dynamic System of Equations. Moscow: MAKS Press; 2004. 328 p. (in Russ.).
9. Sheretov Yu.V. Regularized Equations of Hydrodynamics. Tver: Tver State University; 2016. 222 p. (in Russ.).
10. Sheretov Yu.V. Dynamics of Continua under Space-Time Averaging. Moscow; Izhevsk: Regular and Chaotic Dynamics; 2009. 400 p. (in Russ.).
11. Bulatov O., Elizarova T.G. Regularized shallow water equations and an efficient method for numerical simulation of shallow water flows. Computational mathematics and mathematical physics. 2011;51:160‒173.
12. Elizarova T.G., Ivanov A.V. Regularized equations for numerical simulation of flows in the two-layer shallow water approximation. Computational Mathematics and Mathematical Physics. 2018;58:714‒734.
13. Saburin D.S., Elizarova T.G. Modelling the Azov Sea circulation and extreme surges in 2013‒2014 using the regularized shallow water equations. Russian Journal of Numerical Analysis and Mathematical Modelling. 2018;33(3):173‒185.
14. Bulatov O.V., Elizarova T.G. Regularized Shallow Water Equations and an Efficient Method for Numerical Simulation of Flows in Shallow Water Bodies. Journal of Computational Mathematics and Mathematical Physics. 2011;51(1):170–184. (in Russ.).
15. Elizarova T.G., Ivanov A.V. Regularized Equations for Numerical Simulation of Flows in the Two-Layer Shallow Water Approximation. Journal of Computational Mathematics and Mathematical Physics. 2018;58(5):741–761. (in Russ.).
16. Ivanov A.V. On the Implementation of the Shallow Water Model Based on the Quasi-gas-dynamic Approach in the OpenFOAM Open Source Software. Preprints of the Institute of Applied Mathematics named after M.V. Keldysh RAS. 2023;28:27. (in Russ.).
17. Delis A., Nikolos I. A novel multidimensional solution reconstruction and edge-based limiting procedure for unstructured cell-centered finite volumes with application to shallow water dynamics. International Journal for Numerical Methods in Fluids. 2013;71(5):584‒633.
18. Delis A.I., Katsaounis T. Numerical solution of the two-dimensional shallow water equations by the application of relaxation methods. Applied Mathematical Modelling. 2005;29(8):754‒783.
19. Ginting B.M., Mundani R.-P. Comparison of shallow water solvers: Applications for dam-break and tsunami cases with reordering strategy for efficient vectorization on modern hardware. Water. 2019;11(4):639.
20. Soares-Fraz ̃ao S., Zech Y. Experimental study of dam-break flow against an isolated obstacle. Journal of Hydraulic Research. 2007;45(1):27‒36.
21. Britov A. et al. Numerical Simulation of Propeller Hydrodynamics Using the Open Source Software. International Conference on Computational Science. Springer. 2023. P. 279‒291.
Review
For citations:
But I.I., Kiryushina M.A., Elistratov S.A., Elizarova T.G., Tiniakov A.D. An Adaptive Mesh Refinement Solver for Regularized Shallow Water Equations. Computational Mathematics and Information Technologies. 2024;8(2):9-23. https://doi.org/10.23947/2587-8999-2024-8-2-9-23