Journal of Hydraulics

Journal of Hydraulics

Numerical Simulation of Water Flow Passing over the Steps using the Weakly Compressible Smoothed Particle Hydrodynamics Method with the Cubic Spline Kernel

Document Type : Research Article

Authors
1 department of civil eng. university of birjand
2 Department of civil engineering, Faculty of Engineering, University of Birjand
3 Department of Civil Eng, University of Sistan and Baluchestan, Zahedan, Iran
4 department of civil engineering. birjand university. birjand. iran
Abstract
Extended Abstract
Introduction
The Eulerian framework is the most widely used method for modelling physical problems. This type of modelling requires the use of mesh-dependent numerical methods to solve differential equations. In addition to the problems of stability and expensive processing, these types of methods encounter serious problems in complex geometries and moving boundaries. On the other hand, the basic assumption of Lagrangian modelling is to divide the domain into particles. The smoothed particle hydrodynamics method is a common meshless method that has received considerable attention. This method replaces a fluid with a set of particles to achieve an approximate numerical solution. of fluid dynamics equations. Because of the capability of this method to simulate flow on a large and complex scale, in this study, the flood phenomenon was simulated on a smaller scale. Therefore, flood flow with less water volume and obstacles in the flood path is considered as a positive and negative step. According to the authors' information, such an application of the smoothed particle hydrodynamic method has not yet been simulated.
Methodology
To simulate the water flow over the steps using the Weakly Compressible Smoothed Particle Hydrodynamics method, a two-dimensional model of the steps and water should be created first. Then, the governing equations of the fluid flow should be discretised, and the characteristics of the flow and modelling algorithm should be determined. In the next step, SPHYSICS code is used to define the boundaries. In this process, small particles are considered mass representatives of the water flow and walls. In this research, a comparison between the experimental results of a laboratory model of a dam-break flow and the numerical results was performed for verification. Considering that the particle distance and kernel type are very important in the Weakly Compressible Smoothed Particle Hydrodynamics method, the effects of these parameters on the results of the mentioned method are analysed and investigated. Subsequently, the modelling of water passing over the steps is performed and analysed in two scenarios: (I) dam break and water flow falling from two consecutive steps downwards, and (II) collision and passage of water flow over two fixed obstacles. The simulation results from both scenarios were compared with the results of the STAR-CD software, which is a mesh-based commercial software solving the Navier-Stokes equations based on the finite volume method.
Results and Discussion
The available experimental data of a dam-break problem were adopted to determine the validity of the Weakly Compressible Smoothed Particle hydrodynamics method. In addition, two kernel functions, the cubic spline and quintic spline, were considered to investigate their performance during this test. A comparison of the numerical model results with experimental data showed that the Weakly Compressible Smoothed Particle Hydrodynamics method produces acceptable outputs. Moreover, the cubic spline performed better than the other kernel functions for the dam-break problem. Then, the effect of the particle distance on the numerical results has been investigated and concluded that the use of the particle size of 0.01m compared to 0.0009m increases the error criteria. This analysis can be generalised to other particle distances. By examining the results of changing the particle distance, it is possible to understand the superiority of selecting smaller particle distances. However, it is worth noting that selecting smaller intervals increases the cost and computational time. The dam-break flow over two consecutive negative steps is simulated in the next step. The results were also compared with the STAR-CD software. In the second scenario, two obstacles in the form of steps were located, and a dam-break flow collided with these obstacles. Despite the complexity of the simulation process for these cases and the turbulent nature of the collision, the results obtained using the Weakly Compressible Smoothed Particle Hydrodynamics with cubic spline kernel function were in good agreement with the STAR-CD results. This proves the applicability of the numerical method.
Conclusion
This research showed that reducing the distance between particles causes more convergence of the results, although it increases the calculation time. In addition, the cubic spline kernel generates better results than the quintic spline kernel. A comparison was made between the results of the Weakly Compressible Smoothed Particle Hydrodynamics method and the outputs of STAR-CD. Moreover, the RMSE and Euclidean Error Norm criteria were calculated. Despite the differences between the methods, good agreement between the results was observed, which shows that the Smoothed Particle Hydrodynamics method can be used as a suitable method to simulate the flow over the steps.
Keywords:
Weakly Compressible Smoothed Particle Hydrodynamics, Numerical Simulation, Dam-break, STAR-CD Software.
Keywords

Subjects


Adami, S., Hu, X.Y. & Adams, N.A. (2012). A generalized wall boundary condition for smoothed particle hydrodynamics. Journal of computational physics, 231(21), 7057- 7075.
Balakin, B.V., Hoffmann, A.C. & Kosinski, P. (2014). Coupling STAR-CD with a population-balance technique based on the classes method. Powder Technology, 257, 47-54.
Bishop, C.M. & Nasrabadi, N.M. (2006). Pattern recognition and machine learning, Vol. 4, Springer.
Colombo, M., Thakrar, R., Fairweather, M. & Walker, S.P. (2019). Assessment of semi-mechanistic bubble departure diameter modelling for the CFD simulation of boiling flows. Nuclear Engineering and Design, 344, 15-27.
Cruchaga, M.A., Celentano, D.J. & Tezduyar, T.E. (2007). Collapse of a liquid column: numerical simulation and experimental validation. Computational Mechanics, 39, 453- 476.
Dernowsek, J., Rezende, R., Passamai, V., Noritomi, P., Kemmoku, D., Nogueira, J., Lara, V., Vilalba, F., Mironov, V. & da Silva, J. (2016). Modeling and simulation of diffusion process in tissue spheroids encaged into microscaffolds (lockyballs). In: Computer Aided Chemical Engineering, Vol. 38, pp. 1737-1742, Elsevier. Doi: 10.1016/B978-0-444-63428-3.50294-0
Fourtakas, G., Vacondio, R. & Rogers, B.D. (2015). On the approximate zeroth and first‐order consistency in the presence of 2‐D irregular boundaries in SPH obtained by the virtual boundary particle methods. International journal for numerical methods in fluids, 78(8),475-501.
Fraga Filho, C.A.D., Fraga Filho, C.A.D. & Castro. (2019). Smoothed Particle Hydrodynamics. Springer. Doi: 10.1007/978-3-030-00773-7
Gingold, R. & Monaghan, J. (1982). Kernel estimates as a basis for general particle methods in hydrodynamics. Journal of Computational Physics, 46(3), 429- 453.
Gingold, R.A. & Monaghan, J.J. (1977). Smoothed particle hydrodynamics: theory and application to non-spherical stars. Monthly notices of the royal astronomical society, 181(3), 375-389.
Harten, A. (1997). High resolution schemes for hyperbolic conservation laws. Journal of computational physics, 135(2), 260-278.
Lee, B.-H., Park, J.-C., Kim, M.-H. & Hwang, S.-C. (2011). Step-by-step improvement of MPS method in simulating violent free-surface motions and impact-loads. Computer methods in applied mechanics and engineering, 200(9-12), 1113- 1125.
Lee, E.-S., Moulinec, C., Xu, R., Violeau, D., Laurence, D. & Stansby, P. (2008). Comparisons of weakly compressible and truly incompressible algorithms for the SPH mesh free particle method. Journal of Computational Physics, 227(18), 8417- 8436.
LeVeque, R.J. (1998). Balancing source terms and flux gradients in high-resolution Godunov methods: the quasi-steady wave-propagation algorithm. Journal of computational physics, 146(1), 346-365.
Liu, G.-R. & Liu, M. B. (2003). Smoothed particle hydrodynamics: a meshfree particle method. World scientific, 472p. https://doi.org/10.1142/5340
Liu, M., Liu, G., Lam, K. & Zong, Z. (2003). Smoothed particle hydrodynamics for numerical simulation of underwater explosion. Computational Mechanics, 30(2), 106-118.
Lobovský, L. & Groenenboom, P.H. (2009). Smoothed particle hydrodynamics modelling in continuum mechanics: fluid-structure interaction, Applied and Computational Mechanics, 3, 101–110.
Lucy, L.B. (1977). A numerical approach to the testing of the fission hypothesis. The astronomical journal, 82, 1013-1024.
Mahdizadeh, H., Stansby, P.K. & Rogers, B.D. (2011). On the approximation of local efflux/influx bed discharge in the shallow water equations based on a wave propagation algorithm. International Journal for Numerical Methods in Fluids, 66(10), 1295-1314.
Mahdizadeh, H., Stansby, P.K. & Rogers, B.D. (2012). Flood wave modeling based on a two-dimensional modified wave propagation algorithm coupled to a full-pipe network solver. Journal of Hydraulic Engineering, 138(3), 247-259.
Monaghan, J.J. (1994). Simulating free surface flows with SPH. Journal of computational physics, 110(2), 399- 406.
Monaghan, J.J. (2012). Smoothed particle hydrodynamics and its diverse applications. Annual Review of Fluid Mechanics, 44, 323-346.
Monaghan, J.J. & Kos, A. (1999). Solitary waves on a Cretan beach. Journal of waterway, port, coastal, and ocean engineering, 125(3), 145- 155.
Monaghan, J.J. & Rafiee, A. (2013). A simple SPH algorithm for multi‐fluid flow with high density ratios. International journal for numerical methods in fluids, 71(5), 537- 561.
Moodi, S., Azhdary Moghaddam, M. & Mahdizadeh, H. (2023). Numerical Simulation of Water Flow over a Stair Through Improved Weakly Compressible Moving Particle Semi-implicit Method. International Journal of Civil Engineering, 1-12. Doi: 10.1007/s40999-023-00884-8.
Omidvar, P., Stansby, P.K. & Rogers, B.D. (2012). Wave body interaction in 2D using smoothed particle hydrodynamics (SPH) with variable particle mass. International journal for numerical methods in fluids, 68(6), 686-705.
Omidvar, P., Stansby, P.K. & Rogers, B.D. (2013). SPH for 3D floating bodies using variable mass particle distribution. International journal for numerical methods in fluids, 72(4), 427-452.
Ozmen-Cagatay, H. & Kocaman, S. (2010). Dam-break flows during initial stage using SWE and RANS approaches. Journal of Hydraulic Research, 48(5), 603-611.
Purkayastha, S. & Afzal, M.S. (2022). Review of Smooth Particle Hydrodynamics and its Applications for Environmental Flows. Journal of The Institution of Engineers (India): Series A, 103(3), 921-941.
Ramli, M., Temarel, P. & Tan, M. (2015). Smoothed Particle Hydrodynamics (SPH) method for modelling 2-dimensional free surface hydrodynamics. In: Analysis and Design of Marine Structures, C., Guedes Soares, R.A., Shenoi, eds., CRC Press, 45-52.
Valizadeh, A., Shafieefar, M., Monaghan, J. & Neyshabouri, A. (2008). Modeling two-phase flows using SPH method. Journal of Applied Sciences, 8(21), 3817-3826.
Vermeire, B.C., Witherden, F.D. & Vincent, P.E. (2017). On the utility of GPU accelerated high-order methods for unsteady flow simulations: A comparison with industry-standard tools. Journal of computational physics, 334, 497-521.
Yildiz, M., Rook, R. & Suleman, A. (2009). SPH with the multiple boundary tangent method. International Journal for Numerical Methods in Engineering, 77(10), 1416- 1438.

  • Receive Date 25 February 2024
  • Revise Date 28 July 2024
  • Accept Date 12 August 2024