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Axisymmetric thermal flows in cylindrical systems are widely encountered in engineering practices. Typically, axisymmetric thermal flows belong in three-dimensional (3D) problems. However, taking advantage of the axisymmetric condition, the 3D axisymmetric flows can be reduced to quasi two-dimensional (2D) problems in the meridian plane, which significantly reduces the computational requirements and avoids treating the curved boundary. In recent years, various 2D lattice Boltzmann (LB) models, including single relaxation time LB (SRT-LB, or LBGK) and multiple relaxation time LB (MRT-LB) models, for axisymmetric thermal flows have been proposed. In the LB community, it is well accepted that the MRT-LB is superior to the LBGK in terms of numerical stability. The existing MRT-LB model for axisymmetric thermal flows are developed based on orthogonal basis vectors obtained from the combination of the lattice velocity components, i.e., the transform matrix in the existing MRT-LB is an orthogonal one. Unlike the existing MRT-LB model, in this paper, a non-orthogonal multiple-relaxation-time lattice Boltzmann (MRT-LB) method of simulating axisymmetric thermal flows is proposed. In the proposed MRT-LB method, the velocity field is solved by a D2Q9 discrete velocity set while the temperature by a D2Q5 discrete velocity set. The main advantage of the present MRT-LB model is that the transform matrix of the model is a non-orthogonal one, which is comprised of some proper non-orthogonal basis vectors obtained from the combination of the lattice velocity components. The non-orthogonal transform matrix of the present MRT-LB model contains more zero elements than the classical orthogonal transform matrix, and thus the present MRT-LB model is expected to be more efficient than the existing orthogonal-based MRT-LB model. The equilibrium velocity and temperature moments of the present MRT-LB model are expressed by mapping the equilibrium distribution functions onto their moment spaces through using the non-orthogonal transformation matrix. Also the vectors in the forcing term are modified according to the matrix mapping. Through the Chapman-Enskog analysis, it is demonstrated that the macroscopic governing equations in the cylindrical coordinate can be recovered from the present MRT-LB model. Then several numerical tests, including thermal Womersley flow, Rayleigh-Bnard convection in a vertical cylinder and natural convection in a vertical annulus, are conducted to validate the present model. It is found that the present numerical results are in good agreement with the analytical solutions and/or other numerical results reported in the literature. Numerical stability is also tested, and the results suggest that the present MRT model shows better numerical stability than its LBGK counterpart. Moreover, the numerical results also indicate that the present MRT-LB model is more computationally efficient than the existing MRT-LB model for axisymmetric thermal flow. These findings indicate that the present MRT-LB model can serve as a powerful method of computing the axisymmetric thermal flows.
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Keywords:
- axisymmetric thermal flow /
- lattice Boltzmann method
[1] Vynnycky M, Maeno N 2012 Int. J. Heat Mass Transfer 55 7297
[2] Grosan T, Pop I 2011 Int. J. Heat Mass Transfer 54 3139
[3] Huang H, Hong N, Liang H, Shi B C, Chai Z H 2016 Acta Phys. Sin. 65 084702 (in Chinese)[黄虎, 洪宁, 梁宏, 施保昌, 柴振华 2016 65 084702]
[4] Aidun C K, Clausen J R 2009 Annu. Rev. Fluid Mech. 42 439
[5] Li Q, Luo K H, Kang Q J, He Y L, Chen Q, Liu Q 2015 Prog. Energy Combust. Sci. 52 62
[6] Lallemand P, Luo L S 2000 Phys. Rev. E 61 6546
[7] d'Humières D, Ginzburg I, Krafczyk M, Lallemand P, Luo L S 2002 Philos. Trans. R. Soc. London A 360 437
[8] Halliady I, Hammond L A, Care C M, Good K, Stevens A 2001 Phys. Rev. E 64 011208
[9] Lee T S, Huang H, Shu C 2006 Int. J. Mod. Phys. C 17 645
[10] Reis T, Phillips T N 2007 Phys. Rev. E 75 056703
[11] Reis T, Phillips T N 2008 Phys. Rev. E 2008 77 026703
[12] Guo Z L, Han H F, Shi B C, Zheng C G 2009 Phys. Rev. E 79 046708
[13] Li Q, He Y L, Tang G H, Tao W Q 2010 Phys. Rev. E 81 056707
[14] Zhou J G 2011 Phys. Rev. E 84 036704
[15] Peng Y, Shu C, Chew Y T, Qiu J 2003 J. Comput. Phys. 186 295
[16] Huang H, Lee T S, Shu C 2007 Int. J. Numer. Methods Fluids 53 1707
[17] Li Q, He Y L, Tang G H, Tao W Q 2009 Phys. Rev. E 80 037702
[18] Zheng L, Shi B C, Guo Z L, Zheng C G 2010 Comput. Fluids 39 945
[19] Meng X, Guo Z L 2015 Phys. Rev. E 92 043305
[20] Liu Q, He Y L 2015 Physica A 429 215
[21] Li Q, He Y L, Tang G H, Tao W Q 2011 Microfluid. Nanofluid. 10 607
[22] Wang L, Guo Z L, Zheng C G 2010 Comput. Fluids 39 1542
[23] Premnath K N, Banerjee S 2009 Phys. Rev. E 80 036702
[24] Geier M, Schönherr M, Pasquali A, Krafczyk M 2015 Comput. Math. Appl. 70 507
[25] Liu Q, He Y L, Li D, Li Q 2016 Int. J. Heat Mass Transfer 102 1334
[26] Guo Z L, Shi B C, Zheng C G 2002 Chin. Phys. B 11 366
[27] Lemembre A, Petit J P 1998 Int. J. Heat Mass Transfer 41 2437
[28] Li L K, Mei R W, Klausner J F 2013 Int. J. Heat Mass Transfer 67 338
[29] Kumar R, Kalam M A 1991 Int. J. Heat Mass Transfer 34 513
[30] Venkatachalappa M, Sankar M, Natarajan A A 2001 Acta Mech. 147 173
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[1] Vynnycky M, Maeno N 2012 Int. J. Heat Mass Transfer 55 7297
[2] Grosan T, Pop I 2011 Int. J. Heat Mass Transfer 54 3139
[3] Huang H, Hong N, Liang H, Shi B C, Chai Z H 2016 Acta Phys. Sin. 65 084702 (in Chinese)[黄虎, 洪宁, 梁宏, 施保昌, 柴振华 2016 65 084702]
[4] Aidun C K, Clausen J R 2009 Annu. Rev. Fluid Mech. 42 439
[5] Li Q, Luo K H, Kang Q J, He Y L, Chen Q, Liu Q 2015 Prog. Energy Combust. Sci. 52 62
[6] Lallemand P, Luo L S 2000 Phys. Rev. E 61 6546
[7] d'Humières D, Ginzburg I, Krafczyk M, Lallemand P, Luo L S 2002 Philos. Trans. R. Soc. London A 360 437
[8] Halliady I, Hammond L A, Care C M, Good K, Stevens A 2001 Phys. Rev. E 64 011208
[9] Lee T S, Huang H, Shu C 2006 Int. J. Mod. Phys. C 17 645
[10] Reis T, Phillips T N 2007 Phys. Rev. E 75 056703
[11] Reis T, Phillips T N 2008 Phys. Rev. E 2008 77 026703
[12] Guo Z L, Han H F, Shi B C, Zheng C G 2009 Phys. Rev. E 79 046708
[13] Li Q, He Y L, Tang G H, Tao W Q 2010 Phys. Rev. E 81 056707
[14] Zhou J G 2011 Phys. Rev. E 84 036704
[15] Peng Y, Shu C, Chew Y T, Qiu J 2003 J. Comput. Phys. 186 295
[16] Huang H, Lee T S, Shu C 2007 Int. J. Numer. Methods Fluids 53 1707
[17] Li Q, He Y L, Tang G H, Tao W Q 2009 Phys. Rev. E 80 037702
[18] Zheng L, Shi B C, Guo Z L, Zheng C G 2010 Comput. Fluids 39 945
[19] Meng X, Guo Z L 2015 Phys. Rev. E 92 043305
[20] Liu Q, He Y L 2015 Physica A 429 215
[21] Li Q, He Y L, Tang G H, Tao W Q 2011 Microfluid. Nanofluid. 10 607
[22] Wang L, Guo Z L, Zheng C G 2010 Comput. Fluids 39 1542
[23] Premnath K N, Banerjee S 2009 Phys. Rev. E 80 036702
[24] Geier M, Schönherr M, Pasquali A, Krafczyk M 2015 Comput. Math. Appl. 70 507
[25] Liu Q, He Y L, Li D, Li Q 2016 Int. J. Heat Mass Transfer 102 1334
[26] Guo Z L, Shi B C, Zheng C G 2002 Chin. Phys. B 11 366
[27] Lemembre A, Petit J P 1998 Int. J. Heat Mass Transfer 41 2437
[28] Li L K, Mei R W, Klausner J F 2013 Int. J. Heat Mass Transfer 67 338
[29] Kumar R, Kalam M A 1991 Int. J. Heat Mass Transfer 34 513
[30] Venkatachalappa M, Sankar M, Natarajan A A 2001 Acta Mech. 147 173
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