Particle-based adaptive coupling of 3D and 2D fluid flow models

SUCHDE, Pratik

doi:10.1016/j.cma.2024.117199

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Particle-based adaptive coupling of 3D and 2D fluid flow models

SUCHDE, Pratik

2024 • In Computer Methods in Applied Mechanics and Engineering, 429, p. 117199

Peer Reviewed verified by ORBi

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https://hdl.handle.net/10993/61556

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10.1016/j.cma.2024.117199

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Keywords :

meshfree; cfd; free surface flow; shallow water; model adaptivity; discretization adaptivity

Abstract :

[en] This paper proposes the notion of model adaptivity for fluid flow modelling, where the under- lying model (the governing equations) is adaptively changed in space and time. Specifically, this work introduces a hybrid and adaptive coupling of a 3D bulk fluid flow model with a 2D thin film flow model. As a result, this work extends the applicability of existing thin film flow models to complex scenarios where, for example, bulk flow develops into thin films after striking a surface. At each location in space and time, the proposed framework automatically decides whether a 3D model or a 2D model must be applied. Using a meshless approach for both 3D and 2D models, at each particle, the decision to apply a 2D or 3D model is based on the user-prescribed resolution and a local principal component analysis. When a particle needs to be changed from a 3D model to 2D, or vice versa, the discretization is changed, and all relevant data mapping is done on-the-fly. Appropriate two-way coupling conditions and mass conservation considerations between the 3D and 2D models are also developed. Numerical results show that this model adaptive framework shows higher flexibility and compares well against finely resolved 3D simulations. In an actual application scenario, a 3 factor speed up is obtained, while maintaining the accuracy of the solution.

Disciplines :

Mechanical engineering
Engineering, computing & technology: Multidisciplinary, general & others
Aerospace & aeronautics engineering
Mathematics

Author, co-author :

SUCHDE, Pratik ; University of Luxembourg

External co-authors :

Language :

English

Title :

Particle-based adaptive coupling of 3D and 2D fluid flow models

Publication date :

September 2024

Journal title :

Computer Methods in Applied Mechanics and Engineering

ISSN :

0045-7825

eISSN :

1879-2138

Publisher :

Elsevier BV

Volume :

429

Pages :

117199

Peer reviewed :

Peer Reviewed verified by ORBi

Focus Area :

Computational Sciences

Additional URL :

https://api.elsevier.com/content/article/PII:S0045782524004559?httpAccept=text/xml

European Projects :

H2020 - 892761 - SURFING - Flow on thin fluid sheets

Name of the research project :

U-AGR-6054 - IAS-AUDACITY ADONIS - BORDAS Stéphane

Funders :

Marie Skłodowska-Curie Actions
Union Européenne

Funding text :

Pratik Suchde would like to acknowledge partial support from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Actions grant agreement No. 892761 ‘‘SURFING’’. Pratik Suchde would also like to acknowledge funding from the Institute of Advanced Studies, University of Luxembourg, under the AUDACITY programme grant ‘‘ADONIS’’.

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Bibliography

Vreugdenhil, C.B., Numerical Methods for Shallow-Water Flow, 2013, Springer Science & Business Media.
Bertozzi, A.L., Pugh, M., The lubrication approximation for thin viscous films: Regularity and long-time behavior of weak solutions. Commun. Pure Appl. Math. 49:2 (1996), 85–123.
Chakraborty, S., Nguyen, P.-K., Ruyer-Quil, C., Bontozoglou, V., Extreme solitary waves on falling liquid films. J. Fluid Mech. 745 (2014), 564–591.
Fries, T.-P., Higher-order surface FEM for incompressible Navier-Stokes flows on manifolds. Int. J. Numer. Methods Fluids 88:2 (2018), 55–78.
Martin-Linares, C.P., Psarellis, Y.M., Karapetsas, G., Koronaki, E.D., Kevrekidis, I.G., Physics-agnostic and physics-infused machine learning for thin films flows: modelling, and predictions from small data. J. Fluid Mech., 975, 2023, A41.
Rohlfs, W., Rietz, M., Scheid, B., WaveMaker: The three-dimensional wave simulation tool for falling liquid films. SoftwareX 7 (2018), 211–216.
Ling, G., Matsumoto, J., Kashiyama, K., A two-way coupling 2D-3D hybrid finite element numerical model using overlapping method for tsunami simulation. Internat. J. Numer. Methods Fluids 95:11 (2023), 1732–1755.
Mintgen, F., Manhart, M., A bi-directional coupling of 2D shallow water and 3D Reynolds-averaged Navier–Stokes models. J. Hydraul. Res. 56:6 (2018), 771–785.
Pan, S., Nomura, R., Ling, G., Takase, S., Moriguchi, S., Terada, K., Variable passing method for combining 3D MPM–FEM hybrid and 2D shallow water simulations of landslide-induced tsunamis. Internat. J. Numer. Methods Fluids 96:1 (2024), 17–43.
Pan, S., Yamaguchi, Y., Suppasri, A., Moriguchi, S., Terada, K., MPM–FEM hybrid method for granular mass–water interaction problems. Comput. Mech. 68:1 (2021), 155–173.
Suchde, P., Kuhnert, J., Tiwari, S., On meshfree GFDM solvers for the incompressible Navier–Stokes equations. Comput. & Fluids 165 (2018), 1–12.
Bharadwaj, A.S., Kuhnert, J., Bordas, S.P., Suchde, P., A discrete droplet method for modelling thin film flows. Appl. Math. Model. 112 (2022), 486–504.
Behrens, J., Towards model-adaptivity: Localized non-hydrostatic wave modeling. Geophysical Research Abstracts, Vol. 21, 2019.
Braack, M., Ern, A., A posteriori control of modeling errors and discretization errors. Multiscale Model. Simul. 1:2 (2003), 221–238.
Suchde, P., Kuhnert, J., Schröder, S., Klar, A., A flux conserving meshfree method for conservation laws. Internat. J. Numer. Methods Engrg. 112:3 (2017), 238–256.
Suchde, P., Kuhnert, J., A fully Lagrangian meshfree framework for PDEs on evolving surfaces. J. Comput. Phys. 395 (2019), 38–59.
Löhner, R., Onate, E., An advancing front point generation technique. Commun. Numer. Methods Eng. 14:12 (1998), 1097–1108.
Slak, J., Kosec, G., On generation of node distributions for meshless PDE discretizations. SIAM J. Sci. Comput. 41:5 (2019), A3202–A3229.
Suchde, P., Leithäuser, C., Kuhnert, J., Bordas, S., Volume and mass conservation in Lagrangian meshfree methods. 2023 arXiv preprint arXiv:2303.13410.
Chorin, A.J., Numerical solution of the Navier-Stokes equations. Math. Comput. 22:104 (1968), 745–762.
Suchde, P., Kuhnert, J., Point cloud movement for fully Lagrangian meshfree methods. J. Comput. Appl. Math. 340 (2018), 89–100.
Suchde, P., Jacquemin, T., Davydov, O., Point cloud generation for meshfree methods: An overview. Arch. Comput. Methods Eng. 30:2 (2023), 889–915.
Michel, I., Seifarth, T., Kuhnert, J., Suchde, P., A meshfree generalized finite difference method for solution mining processes. Comput. Part. Mech. 8:3 (2021), 561–574.
Drumm, C., Tiwari, S., Kuhnert, J., Bart, H.-J., Finite pointset method for simulation of the liquid - liquid flow field in an extractor. Comput. Chem. Eng. 32:12 (2008), 2946–2957.
Seibold, B., M-Matrices in Meshless Finite Difference Methods. (Ph.D. thesis), 2006, University of Kaiserslautern, Germany.
Benito, J., Urena, F., Gavete, L., Influence of several factors in the generalized finite difference method. Appl. Math. Model. 25:12 (2001), 1039–1053.
Rao, X., An upwind generalized finite difference method (GFDM) for meshless analysis of heat and mass transfer in porous media. Comput. Part. Mech. 10:3 (2023), 533–554.
Zheng, Z., Li, X., Theoretical analysis of the generalized finite difference method. Comput. Math. Appl. 120 (2022), 1–14.
Jacquemin, T., Tomar, S., Agathos, K., Mohseni-Mofidi, S., Bordas, S.P., Taylor-series expansion based numerical methods: a primer, performance benchmarking and new approaches for problems with non-smooth solutions. Arch. Comput. Methods Eng. 27 (2020), 1465–1513.
Suchde, P., Kuhnert, J., A meshfree generalized finite difference method for surface PDEs. Comput. Math. Appl. 78:8 (2019), 2789–2805.
Bharadwaj, A.S., Thiel, E., Suchde, P., A Lagrangian meshfree model for solidification of liquid thin-films. Comput. & Fluids, 2024, 106267.
Marras, S., Mandli, K.T., Modeling and simulation of tsunami impact: a short review of recent advances and future challenges. Geosciences, 11(1), 2020, 5.
Masó, M., Franci, A., De-Pouplana, I., Cornejo, A., Oñate, E., A Lagrangian–Eulerian procedure for the coupled solution of the Navier–Stokes and shallow water equations for landslide-generated waves. Adv. Model. Simul. Eng. Sci., 9(1), 2022, 15.
Shlens, J., A tutorial on principal component analysis. 2014 arXiv preprint arXiv:1404.1100.
Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., Stuetzle, W., Surface reconstruction from unorganized points. SIGGRAPH Comput. Graph. 26:2 (1992), 71–78.
Liang, J., Zhao, H., Solving partial differential equations on point clouds. SIAM J. Sci. Comput. 35:3 (2013), A1461–A1486.
Awile, O., Büyükkeçeci, F., Reboux, S., Sbalzarini, I.F., Fast neighbor lists for adaptive-resolution particle simulations. Comput. Phys. Comm. 183:5 (2012), 1073–1081.
Lu, P., Guo, S., Shu, Y., Liu, B., Li, P., Cao, W., Jiang, K., A local search scheme in the natural element method for the analysis of elastic-plastic problems. Adv. Eng. Softw., 176, 2023, 103403.
Onderik, J., Durikovic, R., Efficient neighbor search for particle-based fluids. J. Appl. Math. Stat. Inform. 4:1 (2008), 29–43.
Mehl, M., Uekermann, B., Bijl, H., Blom, D., Gatzhammer, B., Van Zuijlen, A., Parallel coupling numerics for partitioned fluid–structure interaction simulations. Comput. Math. Appl. 71:4 (2016), 869–891.
Liu, W.-B., Ma, D.-J., Qian, J.-Z., Zhang, M.-Y., He, A.-M., Liu, N.-S., Wang, P., High-accuracy three-dimensional surface detection in smoothed particle hydrodynamics for free-surface flows. Comput. Phys. Comm., 290, 2023, 108789.
Lu, Y., Hu, A.-k., Liu, Y.-c., A finite pointset method for the numerical simulation of free surface flow around a ship. J. Mar. Sci. Technol. 21 (2016), 190–202.
Saucedo-Zendejo, F.R., Reséndiz-Flores, E.O., Kuhnert, J., Three-dimensional flow prediction in mould filling processes using a GFDM. Comput. Part. Mech. 6:3 (2019), 411–425.
Tiwari, S., Kuhnert, J., Particle method for simulation of free surface flows. Hyperbolic Problems: Theory, Numerics, Applications: Proceedings of the Ninth International Conference on Hyperbolic Problems Held in CalTech, Pasadena, March 25–29, 2002, 2003, Springer, 889–898.
Budarapu, P.R., Zhuang, X., Rabczuk, T., Bordas, S.P., Multiscale modeling of material failure: Theory and computational methods. Adv. Appl. Mech. 52 (2019), 1–103.
Talebi, H., Silani, M., Bordas, S.P., Kerfriden, P., Rabczuk, T., Molecular dynamics/XFEM coupling by a three-dimensional extended bridging domain with applications to dynamic brittle fracture. Int. J. Multiscale Comput. Eng., 11(6), 2013.
Veltmaat, L., Mehrens, F., Endres, H.-J., Kuhnert, J., Suchde, P., Mesh-free simulations of injection molding processes. Phys. Fluids, 34(3), 2022.
Zhang, H., Li, X., Feng, K., Liu, M., 3D large-scale SPH modeling of vehicle wading with GPU acceleration. Sci. China Phys. Mech. Astron., 66(10), 2023, 104711.
Castillo, E., Liang, J., Zhao, H., Point cloud segmentation and denoising via constrained nonlinear least squares normal estimates. Breuß, M., Bruckstein, A., Maragos, P., (eds.) Innovations for Shape Analysis: Models and Algorithms, 2013, Springer Berlin Heidelberg, Berlin, Heidelberg, 283–299.
Chirco, L., Maarek, J., Popinet, S., Zaleski, S., Manifold death: a volume of fluid implementation of controlled topological changes in thin sheets by the signature method. J. Comput. Phys., 467, 2022, 111468.
Jacquemin, T., Suchde, P., Bordas, S.P., Smart cloud collocation: geometry-aware adaptivity directly from CAD. Comput. Aided Des., 154, 2023, 103409.
Zienkiewicz, O.C., The background of error estimation and adaptivity in finite element computations. Comput. Methods Appl. Mech. Engrg. 195:4–6 (2006), 207–213.