Numerically Modelling 2D Swash Zone Flows SMAC VS VOF
Keywords:
Computational Fluid Dynamics (CFD); MATALAB; Numerical Model; Simplified Marker and Cell (SMAC); Swash Zone; Volume of Fluid (VOF).Abstract
In recent years, numerically modelling the swash-zone has proven a feasible approach in unraveling the zone’s intricacies. Whilst many researchers have used and examined many swash-zone numerical models, no specific research has examined the comparative performance of the Simplified Marker and Cell (SMAC) method relative to the status quo; the Volume of Fluid (VOF) method, in 2D applications of the zone. This study investigates the performance of these numerical methods via comparative simulations of 2D dam-break swash like flows across both models. The results show that an adapted Finite Difference (FD)- Finite Volume (FV) discretization of the SMAC method with reductions in marker particles yields smooth interfacial predictions and clear convergence with mesh refinement, while being less computationally demanding than the VOF method for the test scenario. The study demonstrates the suitability of the SMAC method for simulating swash zone flows and highlights its potential for efficient and accurate 2D simulations.
References
1. Ali, A., and D. Villarroel-Lamb. 2020a. “A Swash-Zone Seaward Boundary Condition for Impermeable Beaches.” In Sustainable Built Environment – Proceedings of the International Conference on Emerging Trends in Engineering & Technology (IConETech-2020), 1- 5 June, 2020, edited by Boppana V. Chowdary, 134- 143. St. Augustine: Faculty of Engineering, The University of the West Indies. https://doi.org/10.47412/oedt3765.
2. Amsden, A. Anthony, and Francis H. Harlow. 1970. “The SMAC Method: A Numerical Technique for Calculating Incompressible Fluid Flows.” Technical Report No. LA-4370, New Mexico. Los Alamos: Los Alamos National Laboratory.
3. Garapati, R. S. (2022). Web-Centric Cloud Framework for Real-Time Monitoring and Risk Prediction in Clinical Trials Using Machine Learning. Current Research in Public Health, 2, 1346.
4. Briganti, Riccardo, Alec Torres-Freyermuth, Tom E. Baldock, Maurizio Brocchini, Nicholas Dodd, Tian-Jian Hsu, Zhonglian Jiang, Yeulwoo Kim, Jose Carlos Pintado-Patiño, and Matteo Postacchini. 2016. “Advances in Numerical Modelling of Swash Zone Dynamics.” Coastal Engineering 115: 26–41. https://doi.org/10.1016/j.coastaleng.2016.05.001.
5. Gao, Donghong, N. B. Morley, and V. Dhir. 2003. “Numerical Simulation of Wavy Falling Film Flow Using VOF Method.” Journal of Computational Physics 192 (2): 624– 642. https://doi.org/10.1016/j.jcp.2003.07.013.
6. Gao, Donghong, and Jin Sun. 2011. “Using DEM in Particulate Flow Simulations.” In Hydrodynamics - Optimizing Methods and Tools, edited by Harry Schulz, André Simões and Raquel Lobosco, 29- 50. London: IntechOpen. https://doi.org/10.5772/26681.
7. Harlow, Francis H., and J. Eddie Welch. 1965. “Numerical Calculation of Time-Dependent Viscous Incompressible Flow of Fluid with Free Surface.” The Physics of Fluids 8 (12): 2182-2189. https://doi.org/10.1063/1.1761178.
8. Kolla, S. K., & Mangalampalli, B. M. (2024). Edge-Based Deep Learning Systems for Point-of-Care Diagnostic Intelligence. Journal of Neonatal Surgery, 13(1), 2387-2399.
9. Hirt, Cyril W., and B. D. Nichols. 1981. “Volume of Fluid (VOF) Method for the Dynamics of Free Boundaries.” Journal of Computational Physics 39(1): 201-225. https://doi.org/10.1016/00219991(81)90145-5.
10. Johnson, N. Lloyd. 1996. “The Legacy and Future of CFD at Los Alamos.” In Proceedings of the 1996 Canadian CFD Conference, 3- 4 June 1996, Ottawa, Canada.
11. Kothe, Douglas Brian, Raymond C. Mjolsness, and Martin D. Torrey. 1991. “RIPPLE: A Computer Program for Incompressible Flows with Free Surfaces.” Technical Report No. LA-12007-MS. New Mexico. Los Alamos: Los Alamos National Laboratory. https://doi.org/10.13140/RG.2.1.1397.5200.
12. Kranenborg, J., G. Campmans, J. V. D. Werf, A. Reniers, and S. Hulscher. 2019. “Depth-Resolving vs Depth-Averaged Modelling of Swash Zone Hydrodynamics.” In Coastal Structures 2019 Conference, 30 September – 2 October, 2019, edited by Nils Goseberg and Torsten Schlurmann, Hannover, Germany: Bundesanstalt für Wasserbau. https://doi.org/10.18451/978-3-939230-64-9_083.
13. Pamisetty, V., & Amistapuram, K. Smart Decision Support Systems For Dynamic Tax Policy Optimization Using Reinforcement Learning.
14. Krüger, Timm, Halim Kusumaatmaja, Alexandr Kuzmin, Orest Shardt, Goncalo Silva, and Erlend Magnus Viggen. 2017. The Lattice Boltzmann Method Principles and Practice. Switzerland: Springer Cham. https://doi.org/10.1007/978-3-319-44649-3.
15. May, Sandra, Andrew Nonaka, Ann Almgren, and John Bell. 2011. “An Unsplit, Higher-Order Godunov Method Using Quadratic Reconstruction for Advection in Two Dimensions.” Communications in Applied Mathematics and Computational Science 6 (1): 27–61. https://doi.org/10.2140/camcos.2011.6.27.
16. Mory, M., S. Abadie, S. Mauriet, and P. Lubin. 2011. “Run-up Flow of a Collapsing Bore over a Beach.” European Journal of Mechanics - B/Fluids 30 (6): 565–576. https://doi.org/10.1016/j.euromechflu.2010.11.005.
17. Mangala, N. (2024). Leveraging Microsoft Fabric lakehouse as an AI-ready data platform for enterprise analytics. Journal of Information Systems Engineering and Management.
18. Peregrine, D. H., and S. M. Williams. 2001. “Swash Overtopping a Truncated Plane Beach.” Journal of Fluid Mechanics 440: 391–399. https://doi.org/10.1017/s002211200100492x.
19. Pillord, James Edward, and Elbridge Gerry Puckett. 2004. “Second-order accurate volume-of-fluid algorithms for tracking material interfaces.” Journal of Computational Physics 199(2): 465-502. https://doi.org/10.1016/j.jcp.2003.12.023.
20. Prosperetti, Andrea, and Tryggvason Grétar. 2007. Computational Methods for Multiphase Flow. Cambridge: Cambridge University Press.
21. Puckett, E. Gerry, A. S. Almgren, J. B. Bell, D. L. Marcus, and W. J. Rider. 1997. “A High-Order Projection Method for Tracking Fluid Interfaces in Variable Density Incompressible Flows.” Journal of Computational Physics 130 (2): 269– 282. https://doi.org/10.1006/jcph.1996.5590.
22. Rudman, Murray. 1997. “Volume-Tracking Methods for Interfacial Flow Calculations.” International Journal for Numerical Methods in Fluids 24 (7): 671–691. https://doi.org/10.1002/(sici)1097-0363(19970415)24:7<671::aid-fld508>3.0.co;2-9.
23. Svendsen, I. A., and P. A. Madsen. 1984. “A Turbulent Bore on a Beach.” Journal of Fluid Mechanics 148: 73–96. https://doi.org/10.1017/s0022112084002251.
24. Tomé, Murilo F., A. Castelo, J. Murakami, J. A. Cuminato, R. Minghim, M. C. F. Oliveira, N. Mangiavacchi and S. McKee. 2000. “Numerical Simulation of Axisymmetric Free Surface Flows.” Journal of Computational Physics 157(2): 441- 472. https://doi.org/10.1006/jcph.1999.6348.
25. Gottimukkala, V. R. R. (2021). Digital Signal Processing Challenges in Financial Messaging Systems: Case Studies in High-Volume SWIFT Flows.
26. Tomé, Murilo F, Brian Duffy, and Sean McKee. 1996. “A numerical technique for solving unsteady non-Newtonian free surface flows.” Journal of Non-Newtonian Fluid Mechanics 62(1): 9- 34. https://doi.org/10.1016/0377-0257(95)01391-1.
27. Tomé, Murilo F., and Sean McKee. 1994. “GENSMAC: A Computational Marker and Cell Method for Free Surface Flows in General Domains.” Journal of Computational Physics 110 (1): 171- 186. https://doi.org/10.1006/jcph.1994.1013.
28. Tu, Jiyuan, Kiao Inthavong, and Goodarz Ahmadi. 2013. Computational Fluid and Particle Dynamics in the Human Respiratory System. Dordrecht, Netherlands: Springer.
29. Yeoh, Guan Heng, and Jiyuan Tu. 2010. Computational Techniques for Multiphase Flows: Basics and Applications. Amsterdam, Netherlands: Elsevier.
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