×

A spatially adaptive high-order meshless method for fluid-structure interactions. (English) Zbl 1441.76061

Summary: We present a scheme implementing an a posteriori refinement strategy in the context of a high-order meshless method for problems involving point singularities and fluid-solid interfaces. The generalized moving least squares (GMLS) discretization used in this work has been previously demonstrated to provide high-order compatible discretization of the Stokes and Darcy problems, offering a high-fidelity simulation tool for problems with moving boundaries. The meshless nature of the discretization is particularly attractive for adaptive \(h\)-refinement, especially when resolving the near-field aspects of variables and point singularities governing lubrication effects in fluid-structure interactions. We demonstrate that the resulting spatially adaptive GMLS method is able to achieve optimal convergence in the presence of singularities for both the div-grad and Stokes problems. Further, we present a series of simulations for flows of colloid suspensions, in which the refinement strategy efficiently achieved highly accurate solutions, particularly for colloids with complex geometries.

MSC:

76M10 Finite element methods applied to problems in fluid mechanics
65N30 Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs
74F10 Fluid-solid interactions (including aero- and hydro-elasticity, porosity, etc.)
76D07 Stokes and related (Oseen, etc.) flows

References:

[1] Nikolov, S. V.; Shum, H.; Balazs, A. C.; Alexeev, A., Computational design of microscopic swimmers and capsules: From directed motion to collective behavior, Curr. Opin. Colloid Interface Sci., 21, 44-56 (2016)
[2] Patteson, A. E.; Gopinath, A.; Arratia, P. E., Active colloids in complex fluids, Curr. Opin. Colloid Interface Sci., 21, 86-96 (2016)
[3] Ma, F.; Wang, S.; Wu, D. T.; Wu, N., Electric-field – induced assembly and propulsion of chiral colloidal clusters, Proc. Natl. Acad. Sci., 201502141 (2015)
[4] Bueno, J.; Bona-Casas, C.; Bazilevs, Y.; Gomez, H., Interaction of complex fluids and solids: theory, algorithms and application to phase-change-driven implosion, Comput. Mech., 55, 6, 1105-1118 (2015) · Zbl 1325.76114
[5] Ten Hagen, B.; Kümmel, F.; Wittkowski, R.; Takagi, D.; Löwen, H.; Bechinger, C., Gravitaxis of asymmetric self-propelled colloidal particles, Nature Commun., 5, 4829 (2014)
[6] Goto, Y.; Tanaka, H., Purely hydrodynamic ordering of rotating disks at a finite reynolds number, Nature Commun., 6, 5994 (2015)
[7] Randles, A.; Frakes, D. H.; Leopold, J. A., Computational fluid dynamics and additive manufacturing to diagnose and treat Cardiovascular disease, Trends Biotechnol., 35, 11, 1049-1061 (2017)
[8] Kamps, T.; Biedermann, M.; Seidel, C.; Reinhart, G., Design approach for additive manufacturing employing constructal theory for point-to-circle flows, Additive Manuf., 20, 111-118 (2018)
[9] Sochol, R.; Sweet, E.; Glick, C.; Venkatesh, S.; Avetisyan, A.; Ekman, K.; Raulinaitis, A.; Tsai, A.; Wienkers, A.; Korner, K., 3D printed microfluidic circuitry via multijet-based additive manufacturing, Lab Chip, 16, 4, 668-678 (2016)
[10] Bazilevs, Y.; Hsu, M.-C.; Scott, M., Isogeometric fluid – structure interaction analysis with emphasis on non-matching discretizations, and with application to wind turbines, Comput. Methods Appl. Mech. Engrg., 249-252, 28-41 (2012) · Zbl 1348.74094
[11] Agamloh, E. B.; Wallace, A. K.; von Jouanne, A., Application of fluid – structure interaction simulation of an ocean wave energy extraction device, Renew. Energy, 33, 4, 748-757 (2008)
[12] Yan, J.; Korobenko, A.; Deng, X.; Bazilevs, Y., Computational free-surface fluid – structure interaction with application to floating offshore wind turbines, Comput. & Fluids, 141, 155-174 (2016) · Zbl 1390.76376
[13] Calderer, A.; Guo, X.; Shen, L.; Sotiropoulos, F., Fluid – structure interaction simulation of floating structures interacting with complex, large-scale ocean waves and atmospheric turbulence with application to floating offshore wind turbines, J. Comput. Phys., 355, 144-175 (2018) · Zbl 1380.76147
[14] Trask, N.; Perego, M.; Bochev, P., A high-order staggered meshless method for elliptic problems, SIAM J. Sci. Comput., 39, 2, A479-A502 (2017) · Zbl 1365.65264
[15] Trask, N.; Maxey, M.; Hu, X., A compatible high-order meshless method for the Stokes equations with applications to suspension flows, J. Comput. Phys., 355, 310-326 (2018) · Zbl 1380.76109
[16] Wendland, H., Scattered Data Approximation, Vol. 17 (2004), Cambridge University Press
[17] Mirzaei, D.; Schaback, R.; Dehghan, M., On generalized moving least squares and diffuse derivatives, IMA J. Numer. Anal., 32, 3, 983-1000 (2012) · Zbl 1252.65037
[18] Kordilla, J.; Pan, W.; Tartakovsky, A., Smoothed particle hydrodynamics model for Landau-Lifshitz-Navier-Stokes and advection-diffusion equations, J. Chem. Phys., 141, 22, 224112 (2014)
[19] Pan, W.; Bao, J.; Tartakovsky, A. M., Smoothed particle hydrodynamics continuous boundary force method for navier-Stokes equations subject to a Robin boundary condition, J. Comput. Phys., 259, 242-259 (2014) · Zbl 1349.76724
[20] Pan, W.; Kim, K.; Perego, M.; Tartakovsky, A. M.; Parks, M. L., Modeling electrokinetic flows by consistent implicit incompressible smoothed particle hydrodynamics, J. Comput. Phys., 334, 125-144 (2017) · Zbl 1375.76149
[21] Trask, N.; Maxey, M.; Kimb, K.; Perego, M.; Parks, M. L.; Yang, K.; Xu, J., A scalable consistent second-order SPH solver for unsteady low reynolds number flows, Comput. Methods Appl. Mech. Engrg., 289, 155-178 (2015) · Zbl 1423.76372
[22] Hu, W.; Pan, W.; Rakhsha, M.; Tian, Q.; Hu, H.; Negrut, D., A consistent multi-resolution smoothed particle hydrodynamics method, Comput. Methods Appl. Mech. Engrg., 324, 278-299 (2017) · Zbl 1439.76128
[23] Hu, W.; Guo, G.; Hu, X.; Negrut, D.; Xu, Z.; Pan, W., A consistent spatially adaptive smoothed particle hydrodynamics method for fluid-structure interactions, Comput. Methods Appl. Mech. Engrg., 347, 402-424 (2019) · Zbl 1440.76111
[24] Verfürth, R., A review of a posteriori error estimation and adaptive mesh-refinement techniques (1996), John Wiley & Sons · Zbl 0853.65108
[25] Nochetto, R. H.; Siebert, K. G.; Veeser, A., Theory of adaptive finite element methods: an introduction, (Multiscale, Nonlinear and Adaptive Approximation (2009), Springer), 409-542 · Zbl 1190.65176
[26] Zienkiewicz, O.; Zhu, J., The superconvergent patch recovery SPR and adaptive finite element refinement, Comput. Methods Appl. Mech. Engrg., 101, 1-3, 207-224 (1992) · Zbl 0779.73078
[27] Ainsworth, M.; Oden, J. T., (A Posteriori Error Estimation in Finite Element Analysis (2000), John Wiley & Sons), 65-84, Ch. Recovery-Based Error Estimators · Zbl 1008.65076
[28] Xu, J.; Zhang, Z., Analysis of recovery type a posteriori error estimators for mildly structured grids, Math. Comp., 73, 247, 1139-1152 (2004) · Zbl 1050.65103
[29] Zhang, Z.; Naga, A., A new finite element gradient recovery method: Superconvergence property, SIAM J. Sci. Comput., 26, 4, 1192-1213 (2005) · Zbl 1078.65110
[30] Naga, A.; Zhang, Z., A posteriori error estimates based on the polynomial preserving recovery, SIAM J. Numer. Anal., 42, 4, 1780-1800 (2004) · Zbl 1078.65098
[31] Dörfler, W., A convergent adaptive algorithm for Poisson’s equation, SIAM J. Numer. Anal., 33, 3, 1106-1124 (1996) · Zbl 0854.65090
[32] Stevenson, R., Optimality of a standard adaptive finite element method, Found. Comput. Math., 7, 2, 245-269 (2007) · Zbl 1136.65109
[33] Butcher, J. C., Numerical Methods for Ordinary Differential Equations (2016), John Wiley & Sons · Zbl 1354.65004
[34] Bochev, P. B.; Hyman, J. M., Principles of mimetic discretizations of differential operators, (Compatible Spatial Discretizations (2006), Springer), 89-119 · Zbl 1110.65103
[35] Lipnikov, K.; Manzini, G.; Shashkov, M., Mimetic finite difference method, J. Comput. Phys., 257, 1163-1227 (2014) · Zbl 1352.65420
[36] Ainsworth, M.; Oden, J. T., A Posteriori Error Estimation in Finite Element Analysis (2000), John Wiley & Sons · Zbl 1008.65076
[37] Saad, Y., Iterative Methods for Sparse Linear Systems (2003), Society for Industrial and Applied Mathematics: Society for Industrial and Applied Mathematics Philadelphia, PA · Zbl 1002.65042
[38] Schiff, B., Finite element eigenvalues for the Laplacian over an L-shaped domain, J. Comput. Phys., 76, 2, 233-242 (1988) · Zbl 0644.65079
[39] Johannessen, K. A.; Kvamsdal, T.; Dokken, T., Isogeometric analysis using LR B-splines, Comput. Methods Appl. Mech. Engrg., 269, 471-514 (2014) · Zbl 1296.65021
[40] Ern, A.; Mozolevski, I.; Schuh, L., Discontinuous Galerkin approximation of two-phase flows in heterogeneous porous media with discontinuous capillary pressures, Comput. Methods Appl. Mech. Engrg., 199, 23, 1491-1501 (2010) · Zbl 1231.76143
[41] Hou, T. Y.; Wu, X.-H., A multiscale finite element method for elliptic problems in composite materials and porous media, J. Comput. Phys., 134, 1, 169-189 (1997) · Zbl 0880.73065
[42] Helmig, R.; Huber, R., Comparison of Galerkin-type discretization techniques for two-phase flow in heterogeneous porous media, Adv. Water Resour., 21, 8, 697-711 (1998)
[43] Durlofsky, L. J., Numerical calculation of equivalent grid block permeability tensors for heterogeneous porous media, Water Resour. Res., 27, 5, 699-708 (1991)
[44] Jadhao, V.; Solis, F. J.; Olvera de la Cruz, M., A variational formulation of electrostatics in a medium with spatially varying dielectric permittivity, J. Chem. Phys., 138, 5, 054119 (2013)
[45] Luo, X.; Beskok, A.; Karniadakis, G. E., Modeling electrokinetic flows by the smoothed profile method, J. Comput. Phys., 229, 10, 3828-3847 (2010) · Zbl 1423.76345
[46] Davis, M. E.; McCammon, J. A., Dielectric boundary smoothing in finite difference solutions of the poisson equation: An approach to improve accuracy and convergence, J. Comput. Chem., 12, 7, 909-912 (1991)
[47] Epperson, J. F., On the runge example, Amer. Math. Monthly, 94, 4, 329-341 (1987) · Zbl 0636.41004
[48] T.H. Michael, Scientific computing: an introductory survey, The McGraw-540 Hill Companies Inc.: New York, NY, USA.; T.H. Michael, Scientific computing: an introductory survey, The McGraw-540 Hill Companies Inc.: New York, NY, USA. · Zbl 0903.68072
[49] Wannier, G. H., A contribution to the hydrodynamics of lubrication, Quart. Appl. Math., 8, 1, 1-32 (1950) · Zbl 0036.25804
[50] Yuan, X.; Ball, R., Rheology of hydrodynamically interacting concentrated hard disks, J. Chem. Phys., 101, 10, 9016-9021 (1994)
[51] Kromkamp, J.; van den Ende, D.; Kandhai, D.; van der Sman, R.; Boom, R., Lattice Boltzmann simulation of 2D and 3D non-brownian suspensions in couette flow, Chem. Eng. Sci., 61, 2, 858-873 (2006)
[52] Yeo, K.; Maxey, M. R., Simulation of concentrated suspensions using the force-coupling method, J. Comput. Phys., 229, 6, 2401-2421 (2010) · Zbl 1303.76012
[53] Darabaner, C.; Raasch, J.; Mason, S., Particle motions in sheared suspensions XX: Circular cylinders, Can. J. Chem. Eng., 45, 1, 3-12 (1967)
[54] Bian, X.; Ellero, M., A splitting integration scheme for the SPH simulation of concentrated particle suspensions, Comput. Phys. Comm., 185, 1, 53-62 (2014) · Zbl 1344.65033
[55] P. Kuberry, P. Bosler, N. Trask, Compadre Toolkit Version 1.0.1, https://doi.org/10.5281/zenodo.2560287; P. Kuberry, P. Bosler, N. Trask, Compadre Toolkit Version 1.0.1, https://doi.org/10.5281/zenodo.2560287
[56] Maxey, M., Simulation methods for particulate flows and concentrated suspensions, Annu. Rev. Fluid Mech., 49, 171-193 (2017) · Zbl 1359.76232
[57] Shankar, V.; Fogelson, A. L., Hyperviscosity-based stabilization for radial basis function-finite difference (RBF-FD) discretizations of advection – diffusion equations, J. Comput. Phys., 372, 616-639 (2018) · Zbl 1415.65199
[58] Flyer, N.; Lehto, E.; Blaise, S.; Wright, G. B.; St-Cyr, A., A guide to RBF-generated finite differences for nonlinear transport: shallow water simulations on a sphere, J. Comput. Phys., 231, 11, 4078-4095 (2012) · Zbl 1394.76078
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.