Abstract
Currently, there is not an extensive literature dedicated to the presentation of the diffusive modeling applied to the momentum equation of incompressible and isothermal Newtonian fluid flows solved by the smoothed-particle hydrodynamics (SPH) method. This paper aims to present the most common viscosity modelings and the LES (Large Eddy Simulation) method applied to the solution of the Navier–Stokes (N–S) equations. A comparative study showing different modelings of the diffusive terms has been carried out. Two incompressible free surface flows were simulated: the generation and propagation of waves on a flat beach and the collapse of a water column. In the first case study, the SPH results were compared to the results provided by the Eulerian modeling (Boussinesq-type nonlinear wave equations solved by the finite difference method and validated from laboratory data). It was verified that the laminar shear stress modeling is the most adequate in the wave period and wave amplitude simulated, although great divergences have not been noticed in relation to the other models used. In the collapse of the water column study, the SPH results obtained after implementation of different approaches for the diffusive terms of the N–S equations presented good agreement with experimental or literature data.
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Abbreviations
- \(a\) :
-
Superscript that refers to the fixed particle
- \(b\) :
-
Superscript that refers to the neighbor particle
- \(B\) :
-
Coefficient related to the fluctuations of density
- \(c\) :
-
Sound velocity in the fluid
- \(C_{l}\) :
-
Constant in the sub-grid scale (SGS) shear stress tensor calculus
- \(C_{s}\) :
-
Smagorinsky constant
- \(\frac{{\text{d}}}{{{\text{dt}}}}\) :
-
Material or substantive derivative
- \(\tilde{f}\) :
-
Favre average of the function f
- \({\mathbf{g}}\) :
-
Gravity in vectorial notation
- \(g_{i}\) :
-
Gravity in Einstein notation
- \(h\) :
-
Smoothing length
- \({\text{h}}\) :
-
Mean sea level
- \(H\) :
-
Total depth
- \(i\) :
-
Subscript that refers to the Cartesian directions
- \(j\) :
-
Subscript that refers to the Cartesian directions
- \(k\) :
-
Scale factor that depends on the kernel employed in the interpolations
- \(kh\) :
-
Support radius
- \(m\) :
-
Mass
- \(n\) :
-
Number of neighboring particles
- \(P\) :
-
Pressure
- \(P_{dyn}^\mathbf{{a}}\) :
-
Dynamic pressure acting on the fixed particle
- \(\tilde{S}_{ij}\) :
-
Strain rate tensor
- \({{t}}\) :
-
Time
- \(u_{j}\) :
-
Fluid velocity in Einstein notation
- \({\mathbf{v}}\) :
-
Fluid velocity in vectorial notation
- \({\mathbf{v}}_{\max }\) :
-
Maximum fluid velocity in the simulation
- \({\mathbf{x}}\) :
-
Spatial position in vectorial notation
- \({\mathbf{x}}^{a}\) :
-
Spatial position of the fixed particle
- \({\mathbf{x}}^{b}\) :
-
Spatial position of the neighbor particle
- \(x_{i}\) :
-
Spatial position in Einstein notation
- \(\left| {{\mathbf{x}} - {\mathbf{x^{\prime}}}} \right|\) :
-
Distance between the position of a fixed and a variable point at the domain
- \(W({\mathbf{x}} - {\mathbf{x^{\prime}}},h)\) :
-
Smoothing function (kernel
- \(\alpha_{\pi }\) :
-
Coefficient used in the calculation of the artificial viscosity
- γ:
-
Exponent in the Tait equation
- \(\Delta{x}\) :
-
Initial particle spacing
- \({\delta }_{ij}\) :
-
Kronecker delta function
- \({\upeta }\) :
-
Surface elevation
- \(k\) :
-
Turbulence kinetic energy
- \(\mu\) :
-
Dynamic fluid viscosity
- \(\upsilon\) :
-
Kinematic fluid viscosity
- \(\upsilon^{a}\) :
-
Kinematic viscosity of the fixed particle
- \(\upsilon_{t}\) :
-
Eddy viscosity
- \(\Pi_{{^{ab} }}\) :
-
Artificial viscosity
- \(\rho\) :
-
Fluid density
- \(\overline{\rho }\) :
-
Spatial filtered density
- \(\rho^{0}\) :
-
Density of the fluid in rest
- \({\tau }^{*}\) :
-
Sub-grid scale (SGS) shear stress tensor
- \(\tau_{ij}\) :
-
Elements of the sub-grid scale (SGS) shear stress tensor
- \(\Psi^{a}\) :
-
Diffusive terms of the fixed particle related to the viscosity and turbulence effects
- \(\varphi^{2}\) :
-
Factor that prevents numerical differences when two particles approach one another
- \(\nabla\) :
-
Vector differential mathematical operator
- \(\left( {\upsilon^{a} \nabla^{2} {\mathbf{v}}^{a} } \right)_{{{\text{LAMINAR}}}}\) :
-
Laminar shear stresses of the fixed particle
References
Biscarini C, Di Francesco S, Manciola P (2010) CFD modelling approach for dam break flow studies. Hydrol Earth Syst Sci 14:705–718. https://doi.org/10.5194/hess-14-705-2010
Zheng X, Ma Q, Shao S (2018) Study on SPH Viscosity Term Formulations. Appl Sci 8(2):249. https://doi.org/10.3390/app8020249
Molteni D, Colagrossi A (2009) A simple procedure to improve the pressure evaluation in hydrodynamic context using the SPH. Comput Phys Commun 180(6):861–872. https://doi.org/10.1016/j.cpc.2008.12.004
Antuono M, Colagrossi A, Marrone S (2012) Numerical diffusive terms in weakly-compressible SPH schemes. Comput Phys Commun 183(12):2570–2580. https://doi.org/10.1016/j.cpc.2012.07.006
Green MD, Vacondio R, Peiró J (2019) A smoothed particle hydrodynamics numerical scheme with a consistent diffusion term for the continuity equation. Comput Fluids 179:632–644. https://doi.org/10.1016/j.compfluid.2018.11.020
Gesteira MG, Rogers BD, Dalrymple RA, Crespo AJC, Narayanaswamy M (2010) User Guide for SPHysics Code. University of Manchester, UK. Available at https://wiki.manchester.ac.uk/sphysics/images/SPHysics_v2.2.000_GUIDE.pdf, accessed on 15 July, 2020.
Kirby JT, Lon W, Shi F (2005) FUNWAVE 2.0: Fully Nonlinear Boussinesq Wave Model on Curvilinear Coordinates. Part I. Model Formulations. Delaware, US: University of Delaware, Center for Applied Coastal Research, Dept of Civil & Environmental Engineering.
Kirby JT, Lon W, Shi F (2005) FUNWAVE 2.0: Fully Nonlinear Boussinesq Wave Model on Curvilinear Coordinates. Part II. User’s Manual. Delaware, US: Center for Applied Coastal Research, Department of Civil and Environmental Engineering, 2005.
Fraga Filho CAD (2016) Development of a Computer Code using the Lagrangian Smoothed Particle Hydrodynamics (SPH) Method for Solution of Problems in Fluid Dynamics and Heat Transfer. In: Proceedings of the XXXVII Ibero-Latin American Congress of Computational Method in Engineering–CILAMCE 2016, November 6–9, Brasília, DF, Brazil. Available at http://periodicos.unb.br/index.php/ripe/article/view/14444/12755, accessed on 15 July, 2021.
Fraga CAD (2017) Development of a computational instrument using a lagrangian particle method for physics teaching in the areas of fluid dynamics and transport phenomena. Rev Bras Ensino Fís 39(4):e4401. https://doi.org/10.1590/1806-9126-rbef-2016-0289
Crespo AC, Dominguez JM, Barreiro A, Gómez-Gesteira M, Rogers BD (2006) GPUs, a new tool of acceleration in CFD: efficiency and reliability on Smoothed Particle Hydrodynamics methods. PLoS ONE 6(6):e20685. https://doi.org/10.1371/journal.pone.0020685
Kleefsman KMT, Fekken G, Veldman AEP, Iwanowski B, Buchner B (2005) A Volume-of-Fluid based simulation method for wave impact problems. J Comput Phys 206:363–393. https://doi.org/10.1016/j.jcp.2004.12.007
Gomez-Gesteira M, Rogers BD, Crespo AJC, Dalrymple RA, Narayanaswamy M, Dominguez JM (2012) SPHysics-development of a free surface fluid solver-Part 1: Theory and formulations. Comput Geosci 48:289–299. https://doi.org/10.1016/j.cageo.2012.02.029
Fraga CAD (2019) Smoothed particle hydrodynamics fundamentals and basic applications in continuum mechanics. Springer Nature, Switzerland
Robinson M, Monaghan JJ (2012) Direct numerical simulation of decaying two-dimensional turbulence in a no-slip square box using smoothed particle hydrodynamics. Inte J Numer Methods Fluids 70:37–55. https://doi.org/10.1002/fld.2677
Violeau D, Issa R (2007) Numerical modelling of complex turbulent free-surface flows with the SPH method: an overview. Inte J Numer Methods Fluids 53:277–304. https://doi.org/10.1002/fld.1292
Menzies K (2009) Large eddy simulation applications in gas turbines. Phil Trans R Soc A 367(2827–2838):2009. https://doi.org/10.1098/rsta.2009.0064
Porte-Agel F, Meneveau C, Parlangé MB (2000) A scale-dependent dynamic model for large-eddy simulation: application to a neutral atmospheric boundary layer. J Fluid Mech 415:261–284. https://doi.org/10.1017/S0022112000008776
Bossuyt J, Meneveau C, Meyers J (2018) Large Eddy Simulation of a wind tunnel wind farm experiment with one hundred static turbine models. J Phys: Conf Series 1037(6):062006. https://doi.org/10.1088/1742-6596/1037/6/062006
Piomelli U (1999) Large-eddy simulation: achievements and challenges. Prog Aerosp Sci 35:335–362. https://doi.org/10.1016/S0376-0421(98)00014-1
Zhiyin Y (2015) Large-eddy simulation: Past, present and the future. Chin J Aeronaut 28(1):11–24. https://doi.org/10.1016/j.cja.2014.12.007
Mayrhofer A, Laurence D, Rogers BD, Violeau D (2015) DNS and LES of 3-D wall-bounded turbulence using smoothed particle hydrodynamics. Comput Fluids 115:86–97. https://doi.org/10.1016/j.compfluid.2015.03.029
Lo EYM, Shao S (2002) Simulation of Near-Shore Solitary Wave Mechanics by an Incompressible SPH Method. Appl Ocean Res 24(5):275–286. https://doi.org/10.1016/S0141-1187(03)00002-6
Shao SD, Gotoh H (2004) Simulating coupled motion of progressive wave and floating curtain-wall by SPH-LES model. Coast Eng J 46(2):171–202. https://doi.org/10.1142/S0578563404001026
Shao S, Ji C (2006) SPH computation of plunging waves using a 2-D sub-particle scale (SPS) turbulence model. Int J Numer Methods Fluids 51:913–936. https://doi.org/10.1002/fld.1165
Dalrymple RA, Rogers BD (2006) Numerical modeling of water waves with the SPH method. Coast Eng 53:141–147. https://doi.org/10.1016/j.coastaleng.2005.10.004
Kirkil G, Mirocha J (2012) Implementation and evaluation of dynamic subfilter-scale stress models for Large-Eddy simulation using WRF*. Mon Weather Rev 140:266–284. https://doi.org/10.1175/MWR-D-11-00037.1
Su M, Chen Q, Chiang C-M (2001) Comparison of different subgrid-scale models of large eddy simulation for indoor airflow modelling. J Fluids Eng 123:628–639. https://doi.org/10.1115/1.1378294
Chow FK, Street RL (2009) Evaluation of turbulence closure models for Large-Eddy simulation over complex terrain: flow over Askervein Hill. J Appl Meteorol Climatol 48:1050–1065. https://doi.org/10.1175/2008JAMC1862.1
Smagorinsky J (1963) General circulation experiments with the primitive equations. I. The basic experiment. Mon Wea Rev 91(3):99–164. https://doi.org/10.1175/1520-0493(1963)091%3c0099:GCEWTP%3e2.3.CO;2
Gabreil E, Tait SJ, Shao S, Nichols A (2018) SPHysics simulation of laboratory shallow free surface turbulent flows over a rough bed. J Hydraul Res 56(5):727–747
Monaghan JJ (1992) Smoothed particle hydrodynamics. Annual Rev Astron Appl 30:543–574. https://doi.org/10.1146/annurev.aa.30.090192.002551
De Padova D, Dalrymple R, Mossa M (2014) Analysis of the artificial viscosity in the smoothed particle hydrodynamics modelling of regular waves. J Hydraul Res 52(6):836–848. https://doi.org/10.1080/00221686.2014.932853
Guenter C, Hicks DL, Swegle JW (1994) Conservative Smoothing versus Artificial Viscosity. Sandia Report SAND-94–1853, UC-705 https://doi.org/10.2172/10187573
Hicks DL, Liebrock LM (2004) Conservative smoothing with B-splines stabilizes SPH material dynamics in both tension and compression. Appl Math Comput 150(1):213–234. https://doi.org/10.1016/S0096-3003(03)00222-4
Frontiere N, Raskin CD, Owen JM (2017) CRKSPH–A conservative reproducing kernel smoothed particle hydrodynamics scheme. J Comput Phys 332:160–209. https://doi.org/10.1016/j.jcp.2016.12.004
Fraga Filho CAD, Chacaltana JTA (2016) Boundary Treatment Techniques in Smoothed Particle Hydrodynamics: Implementations in Fluid and Thermal Sciences and Results Analysis, In: Proceedings of the XXXVII Ibero-Latin American Congress of Computational Method in Engineering–CILAMCE 2016, Brasília, DF, Brazil. Revista Interdiscisplinar de Pesquisa em Engenharia, 2(11). Available at https://periodicos.unb.br/index.php/ripe/article/view/21270, accessed on June 25, 2020.
Peregrini DH (1998) Surf zone currents. Theoret Comput Fluid Dynamics 10(1–4):295–309. https://doi.org/10.1007/s001620050065
Kennedy AB, Chen Q, Kirby JT, Dalrymple RA (2000) Boussinesq modeling of wave transformation, breaking, and runup I: 1D. J Waterw, Port, Coastal, Ocean Eng 126(1):39–47. https://doi.org/10.1061/(ASCE)0733-950X(2000)126:1(39)
Bruno D, De Serio F, Mossa M (2009) The FUNWAVE model application and its validation using laboratory data. Coast Eng 56(7):773–787. https://doi.org/10.1016/j.coastaleng.2009.02.001
Fraga Filho CAD, Schuina LL, Porto BS (2020) An investigation into neighbouring search techniques in meshfree particle methods: an evaluation of the neighbour lists and the direct search. Arch Computat Methods Eng 27:1093–1107. https://doi.org/10.1007/s11831-019-09345-9
Chen Q, Kirby JT, Dalrymple RA, Kennedy AB, Chawla A (2000) Boussinesq modeling of wave transformation, breaking, and runup. II: 2D. J Waterw, Port, Coastal, Ocean Eng 126(1):39–47. https://doi.org/10.1061/(ASCE)0733-950X(2000)126:1(48)
Chen Q, Kirby JT, Dalrymple RA, Wei F, Thornton EB (2003) Boussinesq Modeling of Longshore Currents. Journal of Geophysical Research, 108 (C11). https://doi.org/10.1029/2002JC001308
Fraga Filho CAD, Piccoli FP, Barbosa DA, Chacaltana JTA (2015) Numerical Study of the Propagation of Waves on Flat Beaches: An Application in Engineering using SPHysics and FUNWAVE Models. In: Proceedings of the 23rd ABCM International Congress of Mechanical Engineering, December 6–11, Rio de Janeiro, RJ, Brazil. https://doi.org/10.20906/CPS/COB-2015-0561
Monaghan JJ (2000) SPH without tensile instability. J Comput Phys 159(2):290–311. https://doi.org/10.1006/jcph.2000.6439
Fraga Filho CAD, Chacaltana JTA (2015) Study of Fluid Flows using Smoothed Particle Hydrodynamics: the modified Pressure Concept Applied to Quiescent Fluid and Dam Breaking. In: Proceedings of the XXXVI Ibero-Latin American Congress of Computational Method in Engineering–CILAMCE 2015, November 22–25, Rio de Janeiro, Brazil. https://doi.org/10.20906/CPS/CILAMCE2015-0071
Cruchaga MA, Celentano DJ, Tezduyar TE (2007) Collapse of a liquid column: numerical simulation and experimental validation. Comput Mech 39(4):453–476. https://doi.org/10.1007/s00466-006-0043-z
Fraga CAD (2017) An algorithmic implementation of physical reflective boundary conditions in particle methods: Collision detection and response. Phys Fluids 29:113602. https://doi.org/10.1063/1.4997054
Wei G, Kirby JT, Grilli ST, Subramanya R (1995) A fully nonlinear boussinesq model equations for surface waves. Part 1. highly nonlinear, unsteady waves. J Fluid Mech 294:71–92. https://doi.org/10.1017/S0022112095002813
Acknowledgements
The authors would like to thank ESS Engineering Software Steyr GmbH, Austria, for the support provided in carrying out simulations in this work. We would also like to thank SPHERIC—SPH rEsearch and engineeRing International Community and the developers of the SPHysics software for keeping it available for academic use.
A sincere thank you to Ana Carolina Vargas do Vale Amaro for her diligent English proofreading of this paper.
Funding
This work was funded by the Federal Institute of Education, Science and Technology of Espírito Santo, Brazil, during Professor Fraga Filho's post-doctoral internship at ESS Engineering Software Steyr GmbH, Austria.
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Appendices
Appendix
Boussinesq-type nonlinear wave equations
These equations are obtained after integration of mass and momentum conservation equations in the vertical direction [49].
Continuity equation:
where the flux \(M_{i}\) is:
Momentum equation:
where the nonlinear terms \(J_{i}\) and \(K_{i}\) are given as
where the level \(z\) is the reference depth for calculating the velocities, which may be given as
where:
\(\eta\) is the free surface elevation.
\({\text{h}}\) is the total water depth.
\(\text t\) is the time.
\(\delta = {{a_{0} } \mathord{\left/ {\vphantom {{a_{0} } {{\text{h}}_{0} }}} \right. \kern-\nulldelimiterspace} {{\text{h}}_{0} }}\) and \(\chi = k_{0} {\text{h}}_{0}\) are scales of nonlinearity and dispersion, respectively.
\(a_{0} ,{\text{h}}_{0} ,k_{0}\) are, in sequence, the typical wave amplitude, the depth of water at rest and the number of waves.
\(u_{i} = (u,v)\) is the velocity at depth in the coordinated \(z:u_{i} = \left( {\frac{\partial \phi }{{\partial x_{i} }}} \right)\), \(\phi\) being the velocity potential.
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Filho, C.A.D.F., Piccoli, F.P. Diffusive terms applied in smoothed particle hydrodynamics simulations of incompressible and isothermal Newtonian fluid flows. J Braz. Soc. Mech. Sci. Eng. 43, 479 (2021). https://doi.org/10.1007/s40430-021-03158-3
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DOI: https://doi.org/10.1007/s40430-021-03158-3