\`x^2+y_1+z_12^34\`
Advanced Search
Article Contents
Article Contents

A new mixed finite element method for the n-dimensional Boussinesq problem with temperature-dependent viscosity

Funding: This research was partially supported by CONICYT-Chile through the project AFB170001 of the PIA Program: Concurso Apoyo a Centros Científicos y Tecnológicos de Excelencia con Financiamiento Basal, and Fondecyt project 1161325; by Centro de Investigación en Ingeniería Matemática (CI2MA), Universidad de Concepción; and by the Monash Mathematics Research Fund S05802-3951284
Abstract Full Text(HTML) Figure(4) / Table(3) Related Papers Cited by
  • In this paper we propose a new mixed-primal formulation for heat-driven flows with temperature-dependent viscosity modeled by the stationary Boussinesq equations. We analyze the well-posedness of the governing equations in this mathematical structure, for which we employ the Banach fixed-point theorem and the generalized theory of saddle-point problems. The motivation is to overcome a drawback in a recent work by the authors where, in the mixed formulation for the momentum equation, the reciprocal of the viscosity is a pre-factor to a tensor product of velocities; making the analysis quite restrictive, as one needs a given continuous injection that holds only in 2D. We show in this work that by adding both the pseudo-stress and the strain rate tensors as new unknowns in the problem, we get more flexibility in the analysis, covering also the 3D case. The rest of the formulation is based on eliminating the pressure, incorporating augmented Galerkin-type terms in the mixed form of the momentum equation, and defining the normal heat flux as a suitable Lagrange multiplier in a primal formulation for the energy equation. Additionally, the symmetry of the stress is imposed in an ultra-weak sense, and consequently the vorticity tensor is no longer required as part of the unknowns. A finite element method that follows the same setting is then proposed, where we remark that both pressure and vorticity can be recovered from the principal unknowns via postprocessing formulae. The solvability of the discrete problem is analyzed by means of the Brouwer fixed-point theorem, and we derive error estimates in suitable norms. Numerical examples illustrate the performance of the new schem and its use in the simulation of mantle convection, and they also confirm the theoretical rates of convergence.

    Mathematics Subject Classification: 65N30, 65N12, 65N15, 35Q79, 80A20, 76R05.

    Citation:

    \begin{equation} \\ \end{equation}
  • 加载中
  • Figure 5.1.  Numerical results for Example 1. From top-left to right-bottom: XX, XY and YY components of the pseudostress, XX component of the strain rate, velocity components and vector fields, postprocessed pressure, postprocessed vorticity magnitude, and temperature. Snapshots obtained from a simulation with 214,788 DOF and a first order approximation

    Figure 5.2.  Numerical results for Example 2. From top-left to right-bottom: XX, XY and YY components of the pseudostress, XX component of the strain rate, velocity components and vector fields, postprocessed pressure, postprocessed vorticity magnitude, and temperature. Snapshots obtained from a simulation with 724,448 DOF using a second-order approximation

    Figure 5.3.  Example 3. Approximate solutions (from left to right and from up to down): magnitude of strain rate, pseudostress, velocity magnitude and arrows, postprocessed vorticity magnitude, postprocessed pressure, and temperature. Snapshots obtained from a simulation with a lowest-order approximation and 451,690 DOF

    Figure 4.  Example 4. Approximate velocity line integral contours and temperature profiles for the differentially heated cavity at times $ t = 4 $, $ t = 8 $, $ t = 12 $, computed with the lowest-order scheme and a backward Euler time stepping

    Table 1.  Convergence history for Example 1, with a quasi-uniform mesh refinement and approximations of first and second order

    Finite Element: $ \mathbb{P}_0 $ - $ \mathbb{RT}_0 $ - $ {\bf P}_1 $ - $ P_1 $ - $ P_0 $
    DOF $ h $ $ e({\bf t}) $ $ e({{\mathit{\boldsymbol{\sigma}}}}) $ $ e({\bf u}) $ $ e(p) $ $ e({{\mathit{\boldsymbol{\gamma}}}}) $ $ e({\varphi}) $ $ e(\lambda) $
    84 1.4140 5.2972 12.870 9.6113 1.4554 2.8012 0.8379 1.5082
    268 0.7071 2.4345 7.0572 4.6912 1.0387 2.2743 0.8278 0.8069
    948 0.3536 1.2700 3.8456 2.4815 0.5934 1.2154 0.3977 0.4969
    3,556 0.1768 0.6461 1.9470 1.2414 0.3021 0.6162 0.2310 0.2353
    13,764 0.0884 0.3248 0.9766 0.6182 0.1502 0.3084 0.0948 0.0703
    54,148 0.0442 0.1626 0.4887 0.3086 0.0749 0.1542 0.0465 0.0199
    214,788 0.0221 0.0814 0.2444 0.1542 0.0375 0.0771 0.0232 0.0091
    IT $ \widetilde{h} $ $ r({\bf t}) $ $ r({{\mathit{\boldsymbol{\sigma}}}}) $ $ r({\bf u}) $ $ r(p) $ $ r({{\mathit{\boldsymbol{\gamma}}}}) $ $ r({\varphi}) $ $ r(\lambda) $
    11 0.5000
    7 0.2500 1.122 0.8665 1.0352 0.4854 0.3012 0.0176 0.8069
    9 0.1250 0.9385 0.8762 0.9189 0.8072 0.9037 1.0583 1.0917
    8 0.0625 0.9751 0.9814 0.9989 0.9739 0.9798 0.7834 1.1912
    9 0.0312 0.9924 0.9957 1.0061 1.0080 0.9988 1.2842 1.2129
    8 0.0156 0.9978 0.9989 1.0020 1.0031 0.9998 1.0271 1.2816
    8 0.0078 0.9994 0.9997 1.0010 1.0010 1.0000 1.0020 1.1434
    Finite Element: $ \mathbb{P}_1 $ - $ \mathbb{RT}_1 $ - $ {\bf P}_2 $ - $ P_2 $ - $ P_1 $
    DOF $ h $ $ e({\bf t}) $ $ e({{\mathit{\boldsymbol{\sigma}}}}) $ $ e({\bf u}) $ $ e(p) $ $ e({{\mathit{\boldsymbol{\gamma}}}}) $ $ e({\varphi}) $ $ e(\lambda) $
    236 1.4140 1.8442 3.3631 3.4822 0.9773 2.4131 0.7265 2.1308
    820 0.7071 0.4471 1.0930 0.9907 0.2911 0.6832 0.1611 0.3965
    3,044 0.3536 0.1252 0.2853 0.2855 0.0805 0.1857 0.0399 0.0833
    11,716 0.1768 0.0328 0.0732 0.0747 0.0209 0.05792 0.0078 0.0213
    45,956 0.0884 0.0083 0.0185 0.0189 0.0053 0.01905 0.0019 0.0056
    182,020 0.0442 0.0021 0.0046 0.0047 0.0013 0.0054 0.0005 0.0011
    724,448 0.0221 0.0006 0.0012 0.0012 0.0004 0.0013 0.0001 0.0002
    IT $ \widetilde{h} $ $ r({\bf t}) $ $ r({{\mathit{\boldsymbol{\sigma}}}}) $ $ r({\bf u}) $ $ r(p) $ $ r({{\mathit{\boldsymbol{\gamma}}}}) $ $ r({\varphi}) $ $ r(\lambda) $
    6 0.5000
    7 0.2500 2.0445 1.6220 1.8130 1.7471 1.6275 2.1722 2.2383
    8 0.1250 1.8378 1.9377 1.7953 1.8544 1.9316 2.0114 2.2469
    8 0.0625 1.9284 1.9619 1.9332 1.9440 1.9827 2.3410 1.9744
    8 0.0312 1.9771 1.9871 1.9845 1.9821 1.9957 2.0073 2.0656
    8 0.0156 1.9898 1.9955 1.9926 1.9932 1.9989 1.9987 2.1131
    8 0.0078 1.9956 1.9970 1.9931 1.9995 1.9997 2.0031 2.2573
     | Show Table
    DownLoad: CSV

    Table 2.  Convergence history for Example 2, with a quasi-uniform mesh refinement and approximations of first and second order

    Finite Element: $ \mathbb{P}_0 $ - $ \mathbb{RT}_0 $ - $ {\bf P}_1 $ - $ P_1 $ - $ P_0 $
    DOF $ h $ $ e({\bf t}) $ $ e({{\mathit{\boldsymbol{\sigma}}}}) $ $ e({\bf u}) $ $ e(p) $ $ e({{\mathit{\boldsymbol{\gamma}}}}) $ $ e({\varphi}) $ $ e(\lambda) $
    84 0.7071 4.1107 59.150 4.6740 2.1232 3.3978 8.4722 31.684
    268 0.3536 2.9724 48.185 4.8101 1.3070 2.8141 6.1465 17.922
    948 0.1768 1.8371 39.145 4.9700 1.0967 2.8205 17.313 53.771
    3,556 0.0884 1.5104 26.112 2.6239 0.6233 1.6445 2.6532 5.7624
    13,764 0.0442 0.7732 14.525 1.283 0.3384 0.8152 1.2225 2.4021
    54,148 0.0221 0.3889 7.4319 0.6359 0.1707 0.4079 0.5772 1.0130
    214,788 0.0110 0.1948 3.7392 0.3178 0.0848 0.2041 0.2942 0.5675
    IT $ \widetilde{h} $ $ r({\bf t}) $ $ r({{\mathit{\boldsymbol{\sigma}}}}) $ $ r({\bf u}) $ $ r(p) $ $ r({{\mathit{\boldsymbol{\gamma}}}}) $ $ r({\varphi}) $ $ r(\lambda) $
    7 0.5000
    9 0.2500 0.4959 0.5161 0.4126 0.5271 0.2714 0.5463 0.8221
    7 0.1250 0.8588 0.7512 0.7433 0.7982 0.5283 0.7894 0.8585
    7 0.0625 0.9184 0.9209 0.9214 0.8147 0.7781 1.0706 1.0223
    6 0.0312 0.9652 0.9438 1.0327 0.8928 1.0121 1.1193 1.2162
    6 0.0156 0.9912 0.9682 1.0122 0.9854 0.9989 1.0820 1.2245
    6 0.0078 0.9941 0.9778 1.0041 0.9985 0.9991 1.0357 1.1123
    Finite Element: $ \mathbb{P}_1 $ - $ \mathbb{RT}_1 $ - $ {\bf P}_2 $ - $ P_2 $ - $ P_1 $
    DOF $ h $ $ e({\bf t}) $ $ e({{\mathit{\boldsymbol{\sigma}}}}) $ $ e({\bf u}) $ $ e(p) $ $ e({{\mathit{\boldsymbol{\gamma}}}}) $ $ e({\varphi}) $ $ e(\lambda) $
    236 0.7071 3.1423 39.183 4.5951 2.1095 2.8495 7.5735 17.122
    820 0.3536 1.8331 25.442 2.9427 1.5544 1.8810 3.3130 6.5814
    3,044 0.1768 0.6816 10.937 1.3226 0.4762 0.8158 2.4591 3.7876
    11,716 0.0884 0.2082 3.7916 0.3655 0.1364 0.1943 0.3188 0.5948
    45,956 0.0442 0.0531 1.0029 0.0996 0.0322 0.0505 0.0689 0.0355
    182,020 0.0221 0.0136 0.2582 0.0258 0.0082 0.0131 0.0177 0.0052
    724,484 0.0110 0.0034 0.0651 0.0065 0.0021 0.0033 0.0045 0.0011
    IT $ \widetilde{h} $ $ r({\bf t}) $ $ r({{\mathit{\boldsymbol{\sigma}}}}) $ $ r({\bf u}) $ $ r(p) $ $ r({{\mathit{\boldsymbol{\gamma}}}}) $ $ r({\varphi}) $ $ r(\lambda) $
    7 0.5000
    7 0.2500 0.7249 0.4977 0.5891 0.4418 0.5991 1.1924 1.6379
    6 0.1250 1.4279 1.2188 1.1543 1.7063 1.2054 0.4302 1.4443
    6 0.0625 1.7114 1.5283 1.8547 1.8037 2.0781 2.9407 2.1704
    6 0.0312 1.9693 1.9193 1.8755 2.0841 1.9458 2.2135 2.2071
    6 0.0156 1.9614 1.9565 1.9479 1.9752 1.9473 1.9564 2.1078
    6 0.0078 1.9798 1.9884 1.9810 1.9869 1.9776 1.9752 2.1907
     | Show Table
    DownLoad: CSV

    Table 3.  Convergence history for Example 3, with a quasi-uniform mesh refinement and approximations of first and second order

    Finite Element: $ \mathbb{P}_0 $ - $ \mathbb{RT}_0 $ - $ {\bf P}_1 $ - $ P_1 $ - $ P_0 $
    DOF $ h $ $ e({\bf t}) $ $ e({{\mathit{\boldsymbol{\sigma}}}}) $ $ e({\bf u}) $ $ e(p) $ $ e({{\mathit{\boldsymbol{\gamma}}}}) $ $ e({\varphi}) $ $ e(\lambda) $
    900 0.7071 2.1535 6.0574 4.7925 0.6109 1.3478 1.9131 0.0137
    2,848 0.4714 1.1357 4.0980 2.9703 0.3282 1.0283 1.3774 0.0065
    12,564 0.2828 0.7437 2.5440 1.8929 0.2057 0.7164 0.7827 0.0027
    71,068 0.1571 0.3899 1.4422 1.1277 0.1254 0.4506 0.4332 0.0011
    451,690 0.0882 0.1972 0.7612 0.6351 0.0694 0.2348 0.2179 0.0006
    IT $ \tilde{h} $ $ r({\bf t}) $ $ r({{\mathit{\boldsymbol{\sigma}}}}) $ $ r({\bf u}) $ $ r(p) $ $ r({{\mathit{\boldsymbol{\gamma}}}}) $ $ r({\varphi}) $ $ r(\lambda) $
    7 0.7071
    7 0.4714 1.0245 0.9075 0.9573 1.0982 0.8846 0.8338 1.6382
    8 0.2828 0.8937 0.9558 0.9879 0.9818 0.8974 1.1057 1.6072
    8 0.1571 0.9152 0.9831 0.9893 0.9874 0.9509 1.0043 1.6075
    8 0.0882 0.9372 0.9852 1.0505 0.9756 0.9534 0.9891 1.6258
    Finite Element: $ \mathbb{P}_1 $ - $ \mathbb{RT}_1 $ - $ {\bf P}_2 $ - $ P_2 $ - $ P_1 $
    DOF $ h $ $ e({\bf t}) $ $ e({{\mathit{\boldsymbol{\sigma}}}}) $ $ e({\bf u}) $ $ e(p) $ $ e({{\mathit{\boldsymbol{\gamma}}}}) $ $ e({\varphi}) $ $ e(\lambda) $
    3,693 0.7071 0.7084 2.5493 2.8720 0.2803 0.7668 1.0241 0.0092
    11,741 0.4714 0.2268 0.8202 0.9132 0.0846 0.1949 0.3093 0.0023
    51,825 0.2828 0.0603 0.2192 0.2609 0.0217 0.0625 0.0794 0.0005
    286,905 0.1571 0.0169 0.0516 0.0689 0.0575 0.0164 0.0197 0.0001
    1,879,712 0.0882 0.0052 0.0135 0.0186 0.0167 0.0043 0.0051 1.84e-5
    IT $ \tilde{h} $ $ r({\bf t}) $ $ r({{\mathit{\boldsymbol{\sigma}}}}) $ $ r({\bf u}) $ $ r(p) $ $ r({{\mathit{\boldsymbol{\gamma}}}}) $ $ r({\varphi}) $ $ r(\lambda) $
    6 0.7071
    7 0.4714 1.8586 1.8163 1.8545 1.8611 1.7819 1.9314 2.5877
    7 0.2828 1.9004 1.8805 1.8949 1.9072 1.9384 1.8458 2.6167
    8 0.1571 1.9153 1.9572 1.8973 1.9526 1.9742 1.9628 2.5709
    8 0.0882 1.9457 1.9694 1.9407 1.9644 1.9866 1.9764 2.6851
     | Show Table
    DownLoad: CSV
  • [1] R. A. Adams and  J. J. F. FournierSobolev Spaces, Second edition, Pure and Applied Mathematics (Amsterdam), 140. Elsevier/Academic Press, Amsterdam, 2003. 
    [2] R. Aldbaissy, F. Hecht, G. Mansour and T. Sayah, A full discretisation of the time-dependent Boussinesq (buoyancy) model with nonlinear viscosity, Calcolo, 55 (2018), Art. 44, 49 pp. doi: 10.1007/s10092-018-0285-0.
    [3] A. AllendesG. R. Barrenechea and C. Naranjo, A divergence-free low-order stabilized finite element method for a generalized steady state Boussinesq problem, Comput. Methods Appl. Mech. Engrg., 340 (2018), 90-120.  doi: 10.1016/j.cma.2018.05.020.
    [4] J. A. Almonacid and G. N. Gatica, A fully-mixed finite element method for the $n$-dimensional Boussinesq problem with temperature-dependent parameters, Comput. Methods Appl. Math., 20 (2020), 187-213.  doi: 10.1515/cmam-2018-0187.
    [5] J. A. Almonacid, G. N. Gatica and R. Oyarzúa, A mixed-primal finite element method for the Boussinesq problem with temperature-dependent viscosity, Calcolo, 55 (2018), Art. 36, 42 pp. doi: 10.1007/s10092-018-0278-z.
    [6] M. S AlnæsJ. BlechtaJ. HakeA. JohanssonB. KehletA. LoggC. RichardsonJ. RingM. E. Rognes and G. N. Wells, The FEniCS project version 1.5, Arch. Numer. Softw., 3 (2015), 9-23. 
    [7] M. AlvarezG. N. GaticaB. Gómez-Vargas and R. Ruiz-Baier, New mixed finite element methods for natural convection with phase-change in porous media, J. Sci. Comput., 80 (2019), 141-174.  doi: 10.1007/s10915-019-00931-4.
    [8] M. AlvarezG. N. Gatica and R. Ruiz-Baier, An augmented mixed-primal finite element method for a coupled flow-transport problem, ESAIM Math. Model. Numer. Anal., 49 (2015), 1399-1427.  doi: 10.1051/m2an/2015015.
    [9] M. AlvarezG. N. Gatica and R. Ruiz-Baier, A mixed-primal finite element approximation of a sedimentation-consolidation system, Math. Models Methods Appl. Sci., 26 (2016), 867-900.  doi: 10.1142/S0218202516500202.
    [10] P. R. AmestoyI. S. Duff and J.-Y. L'Excellent, Multifrontal parallel distributed symmetric and unsymmetric solvers, Comput. Methods Appl. Mech. Engrg., 184 (2000), 501-520.  doi: 10.1016/S0045-7825(99)00242-X.
    [11] C. BernardiB. Métivet and B. Pernaud-Thomas, Couplage des équations de Navier-Stokes et de la chaleur: Le modèle et son approximation par éléments finis, RAIRO Modél. Math. Anal. Numér., 29 (1995), 871-921.  doi: 10.1051/m2an/1995290708711.
    [12] B. BlankenbachF. BusseU. ChristensenL. CserepesD. GunkelU. HansenH. HarderG. JarvisM. KochG. MarquartD. MooreP. OlsonH. Schmeling and T. Schnaubelt, A benchmark comparison for mantle convection codes, Geophys. J. Int., 98 (1989), 23-38.  doi: 10.1111/j.1365-246X.1989.tb05511.x.
    [13] J. Boland and W. Layton, An analysis of the FEM for natural convection problems, Numer. Methods Partial Differential Equations, 6 (1990), 115-126.  doi: 10.1002/num.1690060202.
    [14] F. Brezzi and M. Fortin, Mixed and Hybrid Finite Element Methods, Springer Series in Computational Mathematics, 15. Springer-Verlag, New York, 1991. doi: 10.1007/978-1-4612-3172-1.
    [15] J. CamañoG. N. GaticaR. Oyarzúa and R. Ruiz-Baier, An augmented stress-based mixed finite element method for the Navier-Stokes equations with nonlinear viscosity, Numer. Methods Partial Differential Equations, 33 (2017), 1692-1725.  doi: 10.1002/num.22166.
    [16] J. CamañoR. OyarzúaR. Ruiz-Baier and G. Tierra, Error analysis of an augmented mixed method for the Navier-Stokes problem with mixed boundary conditions, IMA J. Numer. Anal., 38 (2018), 1452-1484.  doi: 10.1093/imanum/drx039.
    [17] S. ChandrasekharHydrodynamic and Hydromagnetic Stability, The International Series of Monographs on Physics Clarendon Press, Oxford, 1961. 
    [18] Y. Y. ChenB. W. Li and J. K. Zhang, Spectral collocation method for natural convection in a square porous cavity with local thermal equilibrium and non-equilibrium models, Int. J. Heat Mass Transfer, 64 (2013), 35-49.  doi: 10.1016/j.ijheatmasstransfer.2016.01.007.
    [19] A. Çibik and S. Kaya, A projection-based stabilized finite element method for steady-state natural convection problem, J. Math. Anal. Appl., 381 (2011), 469-484.  doi: 10.1016/j.jmaa.2011.02.020.
    [20] E. ColmenaresG. N. Gatica and R. Oyarzúa, Analysis of an augmented mixed-primal formulation for the stationary Boussinesq problem, Numer. Methods Partial Differential Equations, 32 (2016), 445-478.  doi: 10.1002/num.22001.
    [21] E. Colmenares and M. Neilan, Dual-mixed finite element methods for the stationary Boussinesq problem, Comput. Math. Appl., 72 (2016), 1828-1850.  doi: 10.1016/j.camwa.2016.08.011.
    [22] A. Dalal and M. K. Das, Natural convection in a rectangular cavity heated from below and uniformly cooled from the top and both sides, Numer. Heat Tr. A-Appl., 49 (2006), 301-322.  doi: 10.1080/10407780500343749.
    [23] H. Dallmann and D. Arndt, Stabilized finite element methods for the Oberbeck-Boussinesq model, J. Sci. Comput., 69 (2016), 244-273.  doi: 10.1007/s10915-016-0191-z.
    [24] M. FarhoulS. Nicaise and L. Paquet, A mixed formulation of Boussinesq equations: Analysis of nonsingular solutions, Math. Comp., 69 (2000), 965-986.  doi: 10.1090/S0025-5718-00-01186-8.
    [25] M. FarhloulS. Nicaise and L. Paquet, A refined mixed finite element method for the Boussinesq equations in polygonal domains, IMA J. Numer. Anal., 21 (2001), 525-551.  doi: 10.1093/imanum/21.2.525.
    [26] E. Feireisl and J. Málek, On the Navier-Stokes equations with temperature-dependent transport coefficients, Int. J. Diff. Eqns., 2006 (2006), Art. ID 90616, 14 pp. doi: 10.1155/denm/2006/90616.
    [27] G. N. Gatica, An augmented mixed finite element method for linear elasticity with non-homogeneous Dirichlet conditions, Electron. Trans. Numer. Anal., 26 (2007), 421-438.  doi: 10.1080/00207177708922320.
    [28] G. N. Gatica, A Simple Introduction to the Mixed Finite Element Method: Theory and Applications, Springer Briefs in Mathematics, Springer, Cham, 2014. doi: 10.1007/978-3-319-03695-3.
    [29] G. N. GaticaR. Oyarzúa and F.-J. Sayas, Analysis of fully-mixed finite element methods for the Stokes-Darcy coupled problem, Math. Comp., 80 (2011), 1911-1948.  doi: 10.1090/S0025-5718-2011-02466-X.
    [30] P. Z. HuangW. Q. Li and Z. Y. Si, Several iterative schemes for the stationary natural convection equations at different Rayleigh numbers, Numer. Methods Partial Differential Equations, 31 (2015), 761-776.  doi: 10.1002/num.21915.
    [31] K. JulienS. LeggJ. McWilliams and J. Werne, Rapidly rotating turbulent Rayleigh-Bénard convection, J. Fluid Mech., 322 (1996), 243-273.  doi: 10.1017/S0022112096002789.
    [32] M. Kaddiri, M. Naïmi, A. Raji and M. Hasnaoui, Rayleigh-Bénard convection of non-Newtonian power-law fluids with temperature-dependent viscosity, Int. Schol. Res. Netw., (2012), 614712. doi: 10.5402/2012/614712.
    [33] P. Mora and D. A. Yuen, Comparison of convection for Reynolds and Arrhenius temperature dependent viscosities, Fluid Mech. Res. Int., 2 (2018), 99-104.  doi: 10.15406/fmrij.2018.02.00025.
    [34] R. Oyarzúa and P. Zúñiga, Analysis of a conforming finite element method for the Boussinesq problem with temperature-dependent parameters, J. Comput. Appl. Math., 323 (2017), 71-94.  doi: 10.1016/j.cam.2017.04.009.
    [35] C. E. PérezJ.-M. ThomasS. Blancher and R. Creff, The steady Navier-Stokes/energy system with temperature-dependent viscosity. I: Analysis of the continuous problem, Internat. J. Numer. Methods Fluids, 56 (2008), 63-89.  doi: 10.1002/fld.1509.
    [36] C. E. PérezJ.-M. ThomasS. Blancher and R. Creff, The steady Navier-Stokes/energy system with temperature-dependent viscosity. II: The discrete problem and numerical experiments, Internat. J. Numer. Methods Fluids, 56 (2008), 91-114.  doi: 10.1002/fld.1572.
    [37] A. Quarteroni and A. Valli, Numerical Approximation of Partial Differential Equations, Springer Series in Computational Mathematics, 23. Springer-Verlag, Berlin, 1994.
    [38] J. E. Roberts and J. M. Thomas, Mixed and hybrid methods, Handbook of Numerical Analysis, Handb. Numer. Anal., II, North-Holland, Amsterdam, 2 (1991), 523-639. 
    [39] M. Tabata and D. Tagami, Error estimates of finite element methods for nonstationary thermal convection problems with temperature-dependent coefficients, Numer. Math., 100 (2005), 351-372.  doi: 10.1007/s00211-005-0589-2.
    [40] C. WalugaB. Wohlmuth and U. Rüde, Mass-corrections for the conservative coupling of flow and transport on collocated meshes, J. Comput. Phys., 305 (2016), 319-332.  doi: 10.1016/j.jcp.2015.10.044.
    [41] J. WoodfieldM. AlvarezB. Gómez-Vargas and R. Ruiz-Baier, Stability and finite element approximation of phase change models for natural convection in porous media, J. Comput. Appl. Math., 360 (2019), 117-137.  doi: 10.1016/j.cam.2019.04.003.
    [42] T. Zhang and H. X. Liang, Decoupled stabilized finite element methods for the Boussinesq equations with temperature-dependent coefficients, Internat. J. Heat Mass Tr., 110 (2017), 151-165.  doi: 10.1016/j.ijheatmasstransfer.2017.03.002.
    [43] A. G. Zimmerman and J. Kowalski, Simulating convection-coupled phase-change in enthalpy form with mixed finite elements, Preprint, (2019), arXiv: 1907.0441v1.
  • 加载中

Figures(4)

Tables(3)

SHARE

Article Metrics

HTML views(959) PDF downloads(332) Cited by(0)

Access History

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return