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Numerical simulation on staggered grids of three-dimensional brinkman-forchheimer flow and heat transfer in porous media

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Abstract

In this paper, three-dimensional numerical algorithm is constructed to simulate the behavior of the Brinkman-Forchheimer flow and thermal fields. Numerical results of velocity, pressure and temperature are obtained by applying the efficient modified two-grid marker and cell (MAC) algorithm on staggered grids with the second-order backward difference formula (BDF2) time approximation. The modified-upwind idea is introduced to convective heat transfer equations for improving accuracy without any numerical oscillation. The second-order convergence rate can be achieved for pressure, velocity and temperature of considered three-dimensional model. Some numerical experiments are presented to illustrate the efficiency of algorithm. The numerical example with analytical solution is used to validate the effectiveness and accuracy of the algorithm by comparing with the results of traditional MAC algorithm. A time-dependent test is proposed to show a detailed sensitivity analysis to indicate the influence of parameters including the \(\varepsilon \), Forchheimer number, Brinkman number and thermal diffusivity on the physical properties of Brinkman-Forchheimer flow and heat transfer in porous media.

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References

  1. Straughan, B.: Stability and wave motion in porous media. in: Appl. Math. Sci. 91(2004), Springer

  2. Zhou, Z., Liang, D.: The mass-preserving and modified-upwind splitting DDM scheme for time-dependent convection-diffusion equations. J. Comput. Appl. Math. 317, 247–273 (2017)

    Article  Google Scholar 

  3. Fan, G., Liu, W., Song, Y.: A modified-upwind with block-centred finite difference scheme based on the two-grid algorithm for convection-diffusion-reaction equations. Int. J. Comput. Math. 100(5), 1009–1030 (2023)

    Article  Google Scholar 

  4. Yang, K., Li, X., Liu, K., Wang, J.: Coupling effect of heat transfer in plate heat exchanger filled with porous media. Int. J. Heat Mass. Tran. 182(2022). https://doi.org/10.1016/j.ijheatmasstransfer.2021.121966

  5. Leroy, V., Goyeau, B., Taline, J.: Coupled upscaling approaches for conduction, convection, and radiation in porous media: theoretical developments. Transp. Porous Media. 98(2), 323–347 (2013)

    Article  Google Scholar 

  6. Alzahrani, A.K.: Importance of Darcy-Forchheimer porous medium in 3D convection flow of carbon nanotubes. Phys. Lett. A. 382(40), 2983–2943 (2018)

    Article  Google Scholar 

  7. Ambartsumyan, I., Khattatov, E., Nguyen, T., Yotov, I.: Flow and transport in fractured poroelastic media. GEM Int. J. Geomath. 10(1), 34 (2019)

    Google Scholar 

  8. Lam, PAK., Prakash, KA.: A numerical study on natural convection and entropy generation in a porous enclosure with heat sources. Int. J. Heat Mass Transf. 69, 390-407 (2014)

  9. Rashidi, S., Dehghan, M., Ellahi, R., Riaz, M., Jamal-Abad, M.T.: Study of stream wise transverse magnetic fluid flow with heat transfer around an obstacle embedded in a porous medium. J. Magn. Magn. Mater. 378, 128–137 (2015)

    Article  Google Scholar 

  10. Garcia-Chan, N., Licea-Salazar, J.A., Gutierrez-lbarra, L.G.: Urban heat island dynamics in an Urban-Rural domain with variable porosity: numerical methodology and simulation. Mathematics. 11(5) (2021)

  11. Lebedev, V.L.: Difference analogues of orthogonal decompositions, fundamental differential operators and certainboundary-value problems of mathematical physics. Z. Vycisl. Mat. i Mat. Fiz. 4, 449–465 (1964)

    Google Scholar 

  12. Daly, B.J., Harlow, F.H., Shannon, J.P., Welch, J.E.: The MAC method. Tech. Rep. No. LA-3425, Los AlamosScientific Laboratory, (1965)

  13. Nicolaides, R.A.: Analysis and convergence of the MAC scheme I The linear problem. SIAM J. Numer. Anal. 29, 1579–1591 (1992)

    Article  Google Scholar 

  14. Han, H., Wu, X.: A new mixed finite element formulation and the MAC method for the Stokes equations. SIAM J. Numer. Anal. 35, 650–571 (1998)

    Article  Google Scholar 

  15. Girault, V., Lopez, H.: Finite-element error estimates for the MAC scheme. IMA J. Numer. Anal. 16, 347–379 (1996)

    Article  Google Scholar 

  16. Li, J., Sun, S.: The superconvergence phenomenon and proof of the MAC scheme for the stokes equations on non-uniform rectangular meshes. J. Sci. Comput. 65(1), 341–362 (2015)

    Article  Google Scholar 

  17. Rui, H., Li, X.: Stability and superconvergence of MAC scheme for stokes equations on nonuniform grids. SIAM J. Numer. Anal. 55(3), 1135–1158 (2017)

    Article  Google Scholar 

  18. Li, X., Rui, H.: Superconvergence of MAC scheme for a coupled free flow-porous media system with heat transport on non-uniform grids. J. Sci. Comput. 90(3) (2022)

  19. Bijl, H., Carpenter, M.H., Vatsa, V.N., Kennedy, C.A.: Implicit time integration schemes for the unsteady compressible Navier-CStokes equations: laminar flow. J. Comput. Phys. 179(1), 313–329 (2002)

  20. Carpenter, M.H., Viken, S.A., Nielsen, E.J.: The efficiency of high order temporal schemes, In: AIAA Paper. 86, (2003)

  21. Wang, L., Mavriplis, D.J.: Implicit solution of the unsteady euler equations for high-order accurate discontinuous Galerkin discretizations. J. Comput. Phys. 225(2), 1994–2015 (2007)

    Article  Google Scholar 

  22. Hairer, E., Wanner, G.: Solving differential equations II: stiff and differential-algebraic problems, in: Spring Series in Computational Mathematics. 14, second ed., Springer, Berlin, (1996)

  23. Chen, H., Xu, D., Cao, J., Zhou, J.: A formally second order BDF ADI difference scheme for the three-dimensional time-fractional heat equation. Int. J. Comput. Math. 97(5), 1100–1117 (2020)

    Article  Google Scholar 

  24. Chen, W., Wang, X., Yang, Y., Zhang, Z.: A second order BDF numerical scheme with variable steps for the Cahn-Hilliard equation. SIAM J. Numer. Anal. 57(1), 495–525 (2019)

    Article  Google Scholar 

  25. Ikoen, S., Toivanen, J.: Operator splitting methods for pricing american options under stochastic volatility. Numer. Math. 113, 299–324 (2009)

    Article  Google Scholar 

  26. Xu, J.: A novel two-grid method for semilinear elliptic equations. SIAM J. Sci. Comput. 15(1), 231–237 (1994)

    Article  Google Scholar 

  27. Xu, J.: Two-grid discretization techniques for linear and nonlinear PDEs. SIAM J. Numer. Anal. 33(5), 1759–1777 (1996)

    Article  Google Scholar 

  28. Rui, H., Liu, W.: A two-grid block-centered finite difference method for Darcy-Forchheimer flow in porous media. SIAM J. Numer. Anal. 53(4), 1941–1962 (2015)

    Article  Google Scholar 

  29. Chen, C., Liu, W.: Two-grid volume element methods for semilinear parabolic problems. Appl. Numer. Math. 60(1–2), 10–18 (2010)

    Article  Google Scholar 

  30. Chen, C., Li, K., Chen, Y., Huang, Y.: Two-grid finite element methods combined with Crank-Nicolson scheme for nonlinear Sobolev equations. Adv. Comput. Math. 45(2), 611–630 (2019)

    Article  Google Scholar 

  31. Chen, L., Zheng, B., Lin, G., Voulgarakis, N.: A two-level stochastic collacation method for semilinear elliptic equations with random coefficients. J. Comput. Appl. Math. 315, 195–207 (2017)

    Article  Google Scholar 

  32. Chen, L., Chen, Y.: A novel discretization method for Semilinear Reaction-Diffusion Equation. Adv. Appl. Math. Mech. 10(2), 409–423 (2018)

    Article  Google Scholar 

  33. Raghavan, A., Wei, H., Palmer, T., Debroy, T.: Heat transfer and fluid flow in additive manufacturing. J. Laser Appl. 25, 052006 (2013)

    Article  Google Scholar 

  34. Mahdi, J.M., Lohrasbi, S., Nsofor, E.C.: Hybrid heat transfer enhancement for latent-heat thermal energy storge systems: a review. Int. J. Heat Mass Transf. 137, 630–649 (2019)

    Article  Google Scholar 

  35. Weiser, A., Wheeler, M.F.: On convergence of block-centered finite differences for elliptic problems. SIAM J. Numer. Anal. 25, 351–375 (1988)

    Article  Google Scholar 

  36. Rui, H., Zhao, D., Pan, H.: A block-centered finite difference method for Darcy-Forchheimer model with variable Forchheimer number. Numer. Meth. Part. Diff. Equ. 31, 1603–1622 (2015)

    Article  Google Scholar 

  37. Rui, H., Pan, H.: A block-centered finite difference method for Darcy-Forchheimer model. SIAM J. Numer. Anal. 50, 2612–2631 (2012)

    Article  Google Scholar 

  38. Cen, D., Wang, Z.: Time two-grid technique combined with temporal second order difference method for two-dimensional semilinear fractional sub-diffusion equations. Appl. Math. Lett. 129 (2022), https://doi.org/10.1016/j.aml.2022.107919

  39. Darcy, H.P.: Les Fontaines publiques de la ville de Dijon. Exposition et application des principes á suivre et des formules á employer dans les questions de distribution deau, etc. V. Dalamont. (1856)

  40. Ebrahimnia-Bajestan, E., Moghadam, M.C., Niazmand, H., Daungthongsuk, W., Wongwises, S.: Experimental and numerical investigation of nanofluids heat transfer characteristics for application in solar heat exchangers. Int. J. Heat Mass Transf. 92, 1041–1052 (2015)

    Article  Google Scholar 

  41. Nissen, A., Keilegavlen, E., Sandve, T.H., Berre, I., Nordbotten, J.M.: Heterogeneity preserving upscaling for heat transport in fractured geothermal reservoirs. Comput. Geosci. 22(2), 451–467 (2018)

    Article  Google Scholar 

  42. Sanchez, M.T., Perez, M.A., Garcia-Aznar, J.M.: The role of fluid flow on bone mechanobiology: mathematical modeling and simulation. Comput. Geosci. 25(2), 823–830 (2020)

    Article  Google Scholar 

  43. Bao, K., Lavrov, A., Nilsen, H.M.: Numerical modeling of non-Newtonian fluid flow in fractures and porous media. Comput. Geosci. 21(5–6), 1313–1324 (2017)

    Article  Google Scholar 

  44. Tasnim, S.H., Mahmud, S., Fraser, R.A., Pop, I.: Brinkman-Forchheimer modeling for porous media thermoacoustic system. Int. J. Heat Mass Transf. 54(17–18), 3811–3821 (2011)

    Article  Google Scholar 

  45. Sun, S., Firoozababi, A., Kou, J.S.: Numerical modeling of two-phase binary fluid mixing using mixed finite elements. Comput. Geosci. 16(4), 1101–1124 (2012)

    Article  Google Scholar 

  46. Lee, S., Wheeler, M.F., Wick, T.: Pressure and fluid-driven fracture propagation in porous media using an adaptive finite element phase field model. Comput. Meth. Appl. Mech. Eng. 305, 111–132 (2016)

    Article  Google Scholar 

  47. Boon, W.M., Nordbotten, J.M., Yotov, I.: Roubust discretization of flow in fractured porous media. SIAM J. Numer. Anal. 56(4), 2203–2233 (2018)

    Article  Google Scholar 

  48. Wang, Y., Sun, S., Yu, B.: Acceleration of gas flow simulations in Dual-Continuum porous media based on the Mass-Conservation POD method. Energies. 10(9) (2017)

  49. Liu, C., Frank, F., Thiele, C., Alpak, F.O., Berg, S., Chapman, W., Riviere, B.: An efficient numerical algorithm for solving viscosity contrast Cahn-Hilliard-Navier-Stokes system in porous media. J. Comput. Phys. 400,(2019)

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Acknowledgements

This work is supported by China Postdoctoral Science Foundation No. 2021T140576 and No. 2020M672505, Shandong Provincial Natural Science Foundation No. ZR2023MA052.

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Appendix: error proof

Appendix: error proof

1.1 Error proof for the Lemma 11

Here we show the error proof for the Lemma 11.

Proof

Set

$$\begin{aligned}&E_{p}=P_{H}-p,\quad E_{\tilde{\textbf{u}}}=(E_{\tilde{\textbf{u}}}^{x},E_{\tilde{\textbf{u}}}^{y},E_{\tilde{\textbf{u}}}^{z})=\textbf{U}_{H}-{\tilde{\textbf{u}}},\\&E_{T}=Z_{H}-T,\quad E_{\textbf{w}}=(E_{\textbf{w}}^{x},E_{\textbf{w}}^{y},E_{\textbf{w}}^{z})=\textbf{W}_{H}-\textbf{w},\\&H=\text {max}_{i,j,l}\{H_{i}^{x},H_{i+1/2}^{x},H_{j}^{y},H_{j+1/2}^{y},H_{l}^{z},H_{l+1/2}^{z}\}. \end{aligned}$$

We define

$$\begin{aligned}&\delta _{p,i+1/2,j+1/2,l+1/2}^{\tilde{\textbf{u}}}\\&=\frac{(h_{i+1/2}^{x})^2}{8}\frac{\partial ^{2}p_{i+1/2,j+1/2,l+1/2}^{K+1}}{\partial x^2}\nonumber \\&\quad +\frac{(h_{j+1/2}^{y})^2}{8}\frac{\partial ^{2}p_{i+1/2,j+1/2,l+1/2}^{K+1}}{\partial y^2}\nonumber \\&\quad +\frac{(h_{l+1/2}^{z})^2}{8}\frac{\partial ^{2}p_{i+1/2,j+1/2,l+1/2}^{K+1}}{\partial z^2}\\&\quad +\frac{F}{8}\frac{[\tilde{u}^{x}\tilde{u}^{y}\tilde{u}^{z}]}{|{\tilde{\textbf{u}}}_{i+1/2,j+1/2,l+1/2}|}\big (\frac{\partial \tilde{u}_{i+1/2,j+1/2,l+1/2}^y}{\partial x}(h_{i+1/2}^x)^{2}\nonumber \\&\quad +\frac{\partial \tilde{u}_{i+1/2,j+1/2,l+1/2}^z}{\partial x}(h_{i+1/2}^x)^{2}\\&+\frac{\partial \tilde{u}_{i+1/2,j+1/2,l+1/2}^x}{\partial y}(h_{j+1/2}^y)^{2}\nonumber \\&\quad +\frac{\partial \tilde{u}_{i+1/2,j+1/2,l+1/2}^z}{\partial y}(h_{j+1/2}^y)^{2}\\&+\frac{\partial \tilde{u}_{i+1/2,j+1/2,l+1/2}^x}{\partial z}(h_{l+1/2}^z)^{2}\nonumber \\&\quad +\frac{\partial \tilde{u}_{i+1/2,j+1/2,l+1/2}^y}{\partial z}(h_{l+1/2}^z)^{2}\big ). \end{aligned}$$

From Lemma 4 and 5 and Eq. 2.26, we obtain that for \(i=1,...,N_{x}-1\), \(j=0,...,N_{y}-1\), \(l=0,...,N_{z}-1\),

$$\begin{aligned}&[D_{t}E_{\tilde{\textbf{u}}}^{x}]_{i,j+1/2,l+1/2}^{K+1} -vD_{x}[d_{x}E_{\tilde{\textbf{u}}}^{x}]_{i,j+1/2,l+1/2}^{K+1}\nonumber \\&\quad -vd_{y}[D_{y}E_{\tilde{\textbf{u}}}^{x}]_{i,j+1/2,l+1/2}^{K+1}-vd_{z}[D_{z}E_{\tilde{\textbf{u}}}^{x}]_{i,j+1/2,l+1/2}^{K+1}\nonumber \\&\quad +F([S_{x}\textbf{U}_{H}]_{i,j+1/2,l+1/2}^{K+1}U_{H,i,j+1/2,l+1/2}^{x,K+1}\nonumber \\&\quad -[S_{x}{\tilde{\textbf{u}}}]_{i,j+1/2,l+1/2}^{K+1}\tilde{u}_{i,j+1/2,l+1/2}^{x,K+1})\nonumber \\&\quad +[D_{x}(E_{p}+\delta _{p}^{\tilde{\textbf{u}}})]_{i,j+1/2,l+1/2}^{K+1}\nonumber \\&=vD_{x}\epsilon _{i,j+1/2,l+1/2}^{x,x,K+1}+vd_{y}\epsilon _{i,j+1/2,l+1/2}^{x,y,K+1}\nonumber \\&\quad +vd_{z}\epsilon _{i,j+1/2,l+1/2}^{x,z,K+1}+g^{x}\Pi _{h}(E_{T}+\delta _{T})_{i,j+1/2,l+1/2}^{K+1}\nonumber \\&\quad +R_{i,j+1/2,l+1/2}^{x,K+1}. \end{aligned}$$
(1.1)

where,

$$\begin{aligned}&\Vert \textbf{R}^{1}\Vert = O(\Delta T+(H^{x})^{2}+(H^{y})^{2}+(H^{z})^{2}),\end{aligned}$$
(1.2)
$$\begin{aligned}&\Vert \textbf{R}^{K+1}\Vert = O((\Delta T)^{2}+(H^{x})^{2}+(H^{y})^{2}+(H^{z})^{2}). \end{aligned}$$
(1.3)

Noting Lemma 2 and multiplying Eq. 6.1 by \(v_{i.j+1/2,l+1/2}^{x}H_{i}^{x}H_{j+1/2}^{y}H_{l+1/2}^{z}\) with discrete function \(\textbf{v}=(v^{x},v^{y},v^{z})\in \textbf{V}_{H}\) making summation on \(i=1,\cdots ,N_{x}-1\), \(j=0,...,N_{y}-1\), \(l=0,...,N_{z}-1\), and similarly in y and z direction, we have

$$\begin{aligned}&(D_{t}E_{\tilde{\textbf{u}}}^{K+1},\textbf{v})+v(\textbf{D}E_{\tilde{\textbf{u}}}^{K+1},\textbf{Dv})\nonumber \\&\quad +(F[\textbf{SU}^{K+1}]\textbf{U}^{K+1}-F[\textbf{S}\tilde{\textbf{u}}^{K+1}]{\tilde{\textbf{u}}}^{K+1},\textbf{v})\nonumber \\&\quad -((E_{p}+\delta _{p}^{\tilde{\textbf{u}}})^{K+1},d_{x}v^{x}+d_{y}v^{y}+d_{z}v^{z})_{M}\nonumber \\&=-v(\epsilon ^{x,x,K+1},d_{x}v^{x})_{M}-v(\epsilon ^{x,y,K+1},D_{y}v^{x})_{T_{y}}\nonumber \\&\quad -v(\epsilon ^{x,z,K+1},D_{z}v^{x})_{T_{z}}\nonumber \\&\quad -v(\epsilon ^{y,x,K+1},D_{x}v^{y})_{T_{x}}-v(\epsilon ^{y,y,K+1},d_{y}v^{y})_{M}\nonumber \\&\quad -v(\epsilon ^{y,z,K+1},D_{z}v^{y})_{T_{z}}\nonumber \\&\quad -v(\epsilon ^{z,x,K+1},D_{x}v^{z})_{T_{x}}-v(\epsilon ^{z,y,K+1},D_{y}v^{z})_{T_{y}}\nonumber \\&\quad -v(\epsilon ^{z,z,K+1},d_{z}v^{z})_{M}\nonumber \\&\quad +(\textbf{R}^{K+1},\textbf{v})_{M}+(g\Pi _{h}(E_{T}+\delta _{T})^{K+1},\textbf{v})_{M}. \end{aligned}$$
(1.4)

Choosing \(\textbf{v}=E_{\tilde{\textbf{u}}}^{K+1}\) in Eq. 6.4, and then since \(F([\textbf{SU}^{K+1}]\textbf{U}^{K+1}-[\textbf{S}\tilde{\textbf{u}}^{K+1}]\tilde{\textbf{u}}^{K+1},E_{\tilde{\textbf{u}}}^{K+1})\ge 0\) and noting Lemma 10, we have

$$\begin{aligned}&\beta \Vert (E_{p}+\delta _{p}^{\tilde{{\textbf {u}}}})^{K+1}\Vert _{M}\nonumber \\&\quad \le \sup \dfrac{\!-((E_{p}\!+\!\delta _{p}^{\tilde{{\textbf {u}}}})^{K\!+\!1}\!,d_{x}E_{\tilde{{\textbf {u}}}}^{x,K\!+\!1}\!+\!d_{y}E_{\tilde{{\textbf {u}}}}^{y,K\!+\!1}\!+\!d_{z}E_{\tilde{{\textbf {u}}}}^{z,K\!+\!1})}{\Vert {{\textbf {D}}}E_{\tilde{{\textbf {u}}}}^{K+1}\Vert }\nonumber \\&\quad \le C(\Vert D_{t}E_{\tilde{{\textbf {u}}}}^{K+1}\Vert _{M}+\Vert {{\textbf {D}}}E_{\tilde{{\textbf {u}}}}^{K+1}\Vert _{M}+\Vert E_{\tilde{{\textbf {u}}}}^{K+1}\Vert _{M})\nonumber \\&\qquad +C\Vert (E_{T}+\delta _{T})^{K+1}\Vert _{M}+C((\Delta T)^{2}+H^{2}), \quad K\ge 1, \end{aligned}$$
(1.5)

and

$$\begin{aligned}&\beta \Vert (E_{p}+{\delta _{p}^{\tilde{{\textbf {u}}}}})^{1}\Vert _{M}\nonumber \\&\quad \le \sup \dfrac{-((E_{p}+{\delta _{p}^{\tilde{{\textbf {u}}}}})^{1},d_{x}E_{\tilde{{\textbf {u}}}}^{x,1}+d_{y}E_{\tilde{{\textbf {u}}}}^{y,1}+d_{z}E_{\tilde{{\textbf {u}}}}^{z,1})}{\Vert {{\textbf {D}}}E_{\tilde{{\textbf {u}}}}^{1}\Vert }\nonumber \\&\quad \le C(\Vert d_{t}E_{\tilde{{\textbf {u}}}}^{1}\Vert _{M}+\Vert {{\textbf {D}}}E_{\tilde{{\textbf {u}}}}^{1}\Vert _{M}+\Vert E_{\tilde{{\textbf {u}}}}^{1}\Vert _{M})\nonumber \\&\qquad +C\Vert (E_{T}+\delta _{T})^{1}\Vert _{M}+C(\Delta T+H^{2}). \end{aligned}$$
(1.6)

Therefore, we have

$$\begin{aligned}&\Vert E_{\tilde{{\textbf {u}}}}^{q+1}\Vert ^{2}+\sum _{K=0}^{q}\Delta T\Vert {{\textbf {D}}}E_{\tilde{{\textbf {u}}}}^{K+1}\Vert ^{2}\nonumber \\&\quad \le C\sum _{K=0}^{q}\Delta T\Vert (E_{T}+\delta _{T})^{K+1}\Vert _{M}^{2}+O((\Delta T)^{4}+H^{4}). \end{aligned}$$
(2.1)

Choosing \({\textbf {v}}= D_{t}{E_{\tilde{{\textbf {u}}}}^{K+1}}\) in Eq. 6.4, and deducing in a similar way then we can get

$$\begin{aligned}&\Vert {{\textbf {D}}}E_{\tilde{{\textbf {u}}}}^{q+1}\Vert ^{2}+\sum _{K=1}^{q}\Delta T\Vert {D_{t}}E_{\tilde{{\textbf {u}}}}^{K+1}\Vert ^{2}+\Delta T\Vert { d_{t}}E_{\tilde{{\textbf {u}}}}^{1}\Vert ^{2}\nonumber \\&\le C\sum _{K=0}^{q}\Delta T\Vert (E_{T}+\delta _{T})^{K+1}\Vert _{M}^{2}+O((\Delta T)^{4}+H^{4}). \end{aligned}$$
(2.2)

and

$$\begin{aligned}&\sum _{K=0}^{q}\Delta T\Vert (E_{p}+\delta _{p}^{\tilde{{\textbf {u}}}})^{K+1}\Vert _{M}^{2}\nonumber \\&\quad \le C\sum _{K=0}^{q}\Delta T\Vert (E_{T}+\delta _{T})^{K+1}\Vert _{M}^{2}+O((\Delta T)^{4}+H^{4}). \end{aligned}$$
(2.3)

In what follows, we establish the error analysis for the temperature. Recalling Eq. 2.29, we have for \(i=0,...,N_{x}-1\), \(j=0,...,N_{y}-1\) and \(l=0,...,N_{z}-1\),

$$\begin{aligned}&[D_{t}(E_{T}+\delta _{T})]_{i+1/2,j+1/2,l+1/2}^{K+1}+[d_{x}E_{w}^{x}]_{i+1/2,j+1/2,l+1/2}^{K+1}\nonumber \\&\quad +[d_{y}E_{w}^{y}]_{i+1/2,j+1/2,l+1/2}^{K+1}\nonumber \\&+[d_{z}E_{w}^{z}]_{i+1/2,j+1/2,l+1/2}^{K+1}=R_{T,i+1/2,j+1/2,l+1/2}^{K+1}, \end{aligned}$$
(2.4)

where

$$\begin{aligned} R_{T,i+1/2,j+1/2,l+1/2}^{1}=&d_{t}\delta _{T,i+1/2,j+1/2,l+1/2}^{1}\nonumber \\&+O(\Delta T+H^2),\end{aligned}$$
(2.5)
$$\begin{aligned} R_{T,i+1/2,j+1/2,l+1/2}^{K+1}=&d_{t}\delta _{T,i+1/2,j+1/2,l+1/2}^{K+1}\nonumber \\&+O((\Delta T)^{2}+H^2). \end{aligned}$$
(2.6)

Recalling Eq. 2.28 we can get

$$\begin{aligned} E_{{\textbf {w}}}^{K+1}=&{{\textbf {U}}}^{K+1}(E_{T}+\delta _{T})^{k+1}+E_{\tilde{{\textbf {u}}}}^{K+1}(T-\delta _{T})^{K+1}\nonumber \\&-\lambda [\nabla _{h}(E_{T}+\delta _{T})]^{K+1}+R_{w}^{K+1}, \end{aligned}$$
(2.7)

where \(\nabla _{h}=(D_{x},D_{y},D_{z})\), and

$$\begin{aligned} R_{w}^{K+1}=&(\tilde{{\textbf {u}}}^{K+1}-{{\textbf {u}}}^{K+1})(T^{K+1}-\delta _{T}^{K+1})-{{\textbf {u}}}^{K+1}\delta _{T}^{K+1}\nonumber \\&+\lambda \epsilon ^{K+1}(T)+O(H^2). \end{aligned}$$
(2.8)

Combining Lemma 2, Eqs. 6.10 and 6.13, we get

$$\begin{aligned}&\Vert (E_{T}+\delta _{T})^{q+1}\Vert _{M}^{2}+\sum _{K=0}^{q}\Delta T\Vert \nabla _{h}(E_{T}+\delta _{T})^{K+1}\Vert _{M}^{2}\nonumber \\&\le C\sum _{K=0}^{q}\Delta T\Vert E_{\tilde{{\textbf {u}}}}^{K+1}\Vert ^{2}+O((\Delta T)^{4}+H^{4}). \end{aligned}$$
(2.9)

We are now in position to prove our main results. Combining Eqs. 6.7, 6.9 and 6.15 we obtain

$$\begin{aligned} \Vert E_{\tilde{{\textbf {u}}}}^{q+1}\Vert ^{2}+&\sum _{K=0}^{q}\Delta T\Vert {{\textbf {D}}}E_{\tilde{{\textbf {u}}}}^{K+1}\Vert ^{2}\nonumber \\&+\sum _{K=0}^{q}\Delta T\Vert (E_{p}+\delta _{p}^{\tilde{{\textbf {u}}}})^{K+1}\Vert _{M}^{2}\nonumber \\&+\Vert (E_{T}+\delta _{T})^{q+1}\Vert _{M}^{2}\le O((\Delta T)^{4}+H^{4}). \end{aligned}$$
(2.10)

According to the definition of \({\delta _{p}^{\tilde{{\textbf {u}}}},{K+1}}\) and \(\delta _{T}^{K+1}\), we can complete the proof.

1.2 Error proof for the Lemma 16

Here we show the error proof for the lemma 16.

Proof

Set

$$\begin{aligned}&e_{p}=P_{h}-p,\quad e_{\tilde{\textbf{u}}}=(e_{\tilde{\textbf{u}}}^{x},e_{\tilde{\textbf{u}}}^{y},e_{\tilde{\textbf{u}}}^{z})={{\textbf {U}}}_{h}-{\tilde{\textbf{u}}},\\&e_{T}=Z_{h}-T,\quad e_{\textbf{w}}=(e_{\textbf{w}}^{x},e_{\textbf{w}}^{y},e_\textbf{w}^{z})=\textbf{W}_{h}-\textbf{w},\\&h=\text {max}_{m,n,b}\{h_{m}^{x},h_{m+1/2}^{x},h_{n}^{y},h_{n+1/2}^{y},h_{b}^{z},h_{b+1/2}^{z}\}. \end{aligned}$$

Similar to the proof of Lemma 11, the definition of \(\delta _{p}^{\tilde{\textbf{u}}}\), Lemmas 4, 5 and Eq. 2.30, we can get that for \(m=1,\cdots ,n_{x}-1\), \(n=0,\cdots ,n_{y}-1\), \(b=0,\cdots ,n_{z}-1\),

$$\begin{aligned}&[D_{t}e_{\tilde{{\textbf {u}}}}^{x}]_{m,n+1/2,b+1/2}^{k+1} -vD_{x}[d_{x}e_{\tilde{\textbf{u}}}^{x}]_{m,n+1/2,b+1/2}^{k+1}\nonumber \\&\quad -vd_{y}[D_{y}E_{\tilde{{\textbf {u}}}}^{x}]_{m,n+1/2,b+1/2}^{k+1}\nonumber \\&\quad -vd_{z}[D_{z}e_{\tilde{{\textbf {u}}}}^{x}]_{m,n+1/2,b+1/2}^{k+1}+Q_{\varepsilon }^{x}(\textbf{U}_{h})_{m,n+1/2,b+1/2}^{k+1}\nonumber \\&\quad -q^{x}({\tilde{\textbf{u}}})_{m,n+1/2,b+1/2}^{k+1}\nonumber \\&\quad +[D_{x}(e_{p}+\delta _{p}^{\tilde{\textbf{u}}})]_{m,n+1/2,b+1/2}^{k+1}\nonumber \\&=vD_{x}\epsilon _{m,n+1/2,b+1/2}^{x,x,k+1}+vd_{y}\epsilon _{m,n+1/2,b+1/2}^{x,y,k+1}\nonumber \\&\quad +vd_{z}\epsilon _{m,n+1/2,b+1/2}^{x,z,k+1}\nonumber \\&\quad +g^{x}\Pi _{h}(E_{T}+\delta _{T})_{m,n+1/2,b+1/2}^{k+1}+R_{m,n+1/2,b+1/2}^{x,k+1}. \end{aligned}$$
(2.11)

Combining the Taylor expansion, the definition of \(Q_{\varepsilon }^{x}({{\textbf {U}}}_{h})_{m,n+1/2,b+1/2}^{k+1}\) and Eq. 6.17, we can obtain

$$\begin{aligned}{} & {} (D_{t}e_{\tilde{{\textbf {u}}}}^{x,k+1},{\textbf {v}})_{m} +v({{\textbf {D}}}e_{\tilde{{\textbf {u}}}}^{k+1},{\textbf {Dv}})_{m}\nonumber \\{} & {} +(q_{\varepsilon }^{x}({\tilde{{\textbf {u}}}})^{k+1}-q^{x}({\tilde{{\textbf {u}}}})^{k+1},v^{x})_{Tmm}\nonumber \\{} & {} +(q^{x}(\hat{{\textbf {U}}}_{H})^{k+1}-q_{\varepsilon }^{x}(\hat{{\textbf {U}}}_{H})^{k+1},v^{x})_{Tmm}\nonumber \\{} & {} +(q_{\varepsilon }^{y}({\tilde{{\textbf {u}}}})^{k+1}-q^{y}({\tilde{{\textbf {u}}}})^{k+1},v^{y})_{Tmm}\nonumber \\{} & {} +(q^{y}(\hat{{\textbf {U}}}_{H})^{k+1}-q_{\varepsilon }^{y}(\hat{{\textbf {U}}}_{H})^{k+1},v^{y})_{Tmm}\nonumber \\{} & {} +(q_{\varepsilon }^{z}({\tilde{{\textbf {u}}}})^{k+1}-q^{z}({\tilde{{\textbf {u}}}})^{k+1},v^{z})_{Tmm}\nonumber \\{} & {} +(q^{z}(\hat{{\textbf {U}}}_{H})^{k+1}-q_{\varepsilon }^{z}(\hat{{\textbf {U}}}_{H})^{k+1},v^{z})_{Tmm}\nonumber \\{} & {} +(\dfrac{\partial q_{\varepsilon }^{x}}{\partial u^{x}}(\hat{{\textbf {U}}}_{H})^{k+1}e_{\tilde{{\textbf {u}}}}^{x,k+1},v^{x})_{Tmm}\nonumber \\{} & {} +(\dfrac{\partial q_{\varepsilon }^{y}}{\partial u^{y}}(\hat{{\textbf {U}}}_{H})^{k+1}e_{\tilde{{\textbf {u}}}}^{y,k+1},v^{y})_{mTm}\nonumber \\{} & {} +(\dfrac{\partial q_{\varepsilon }^{z}}{\partial u^{z}}(\hat{{\textbf {U}}}_{H})^{k+1}e_{\tilde{{\textbf {u}}}}^{z,k+1},v^{z})_{mmT}\nonumber \\{} & {} -((e_{p}+\delta _{p}^{\tilde{{\textbf {u}}}})^{k+1},d_{x}v_{x}+d_{y}v_{y}+d_{z}v_{z})_{m}\nonumber \\{} & {} +((\dfrac{\partial q_{\varepsilon }^{x}}{\partial u_{1}^{y}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{x}}{\partial u_{2}^{y}}(\hat{{\textbf {U}}}_{H})^{k+1}\nonumber \\{} & {} +\dfrac{\partial q_{\varepsilon }^{x}}{\partial u_{3}^{y}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{x}}{\partial u_{4}^{y}}(\hat{{\textbf {U}}}_{H})^{k+1})e_{\tilde{{\textbf {u}}}}^{y,k+1},v^{x})_{T,m,m}\nonumber \\{} & {} +((\dfrac{\partial q_{\varepsilon }^{x}}{\partial u_{1}^{z}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{x}}{\partial u_{2}^{z}}(\hat{{\textbf {U}}}_{H})^{k+1}\nonumber \\{} & {} +\dfrac{\partial q_{\varepsilon }^{x}}{\partial u_{3}^{z}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{x}}{\partial u_{4}^{z}}(\hat{{\textbf {U}}}_{H})^{k+1})e_{\tilde{{\textbf {u}}}}^{z,k+1},v^{x})_{Tmm}\nonumber \\{} & {} +((\dfrac{\partial q_{\varepsilon }^{y}}{\partial u_{1}^{x}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{y}}{\partial u_{2}^{x}}(\hat{{\textbf {U}}}_{H})^{k+1}\nonumber \\{} & {} +\dfrac{\partial q_{\varepsilon }^{y}}{\partial u_{3}^{x}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{y}}{\partial u_{4}^{x}}(\hat{{\textbf {U}}}_{H})^{k+1})e_{\tilde{{\textbf {u}}}}^{x,k+1},v^{y})_{mTm}\nonumber \\{} & {} +((\dfrac{\partial q_{\varepsilon }^{y}}{\partial u_{1}^{z}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{y}}{\partial u_{2}^{z}}(\hat{{\textbf {U}}}_{H})^{k+1}\nonumber \\{} & {} +\dfrac{\partial q_{\varepsilon }^{y}}{\partial u_{3}^{z}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{y}}{\partial u_{4}^{z}}(\hat{{\textbf {U}}}_{H})^{k+1})e_{\tilde{{\textbf {u}}}}^{z,k+1},v^{y})_{mTm}\nonumber \\{} & {} +((\dfrac{\partial q_{\varepsilon }^{z}}{\partial u_{1}^{x}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{z}}{\partial u_{2}^{x}}(\hat{{\textbf {U}}}_{H})^{k+1}\nonumber \\{} & {} +\dfrac{\partial q_{\varepsilon }^{z}}{\partial u_{3}^{x}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{z}}{\partial u_{4}^{x}}(\hat{{\textbf {U}}}_{H})^{k+1})e_{\tilde{{\textbf {u}}}}^{x,k+1},v^{z})_{mmT}\nonumber \\{} & {} +((\dfrac{\partial q_{\varepsilon }^{z}}{\partial u_{1}^{y}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{z}}{\partial u_{2}^{y}}(\hat{{\textbf {U}}}_{H})^{k+1}\nonumber \\{} & {} +\dfrac{\partial q_{\varepsilon }^{z}}{\partial u_{3}^{y}}(\hat{{\textbf {U}}}_{H})^{k+1}+\dfrac{\partial q_{\varepsilon }^{z}}{\partial u_{4}^{y}}(\hat{{\textbf {U}}}_{H})^{k+1})e_{\tilde{{\textbf {u}}}}^{y,k+1},v^{z})_{mmT}\nonumber \\{} & {} =({{\textbf {g}}}\Pi _{h}(E_{T}+\delta _{T})^{k+1},v_{x}+v_{y}+v_{z})_{m}\nonumber \\{} & {} -(v\epsilon ^{x,x,k+1},d_{x}v_{x})_{m}-(v\epsilon ^{x,y,k+1},D_{y}v_{x})_{m}\nonumber \\{} & {} -(v\epsilon ^{x,z,k+1},D_{z}v_{x})_{m}\nonumber \\{} & {} -(v\epsilon ^{y,x,k+1},D_{x}v_{x})_{m}-(v\epsilon ^{y,y,k+1},d_{y}v_{x})_{m}\nonumber \\{} & {} -(v\epsilon ^{y,z,k+1},D_{z}v_{x})_{m}\nonumber \\{} & {} -(v\epsilon ^{z,x,k+1},D_{x}v_{x})_{m}-(v\epsilon ^{z,y,k+1},D_{y}v_{x})_{m}\nonumber \\{} & {} -(v\epsilon ^{z,z,k+1},d_{z}v_{x})_{m}\nonumber \\{} & {} +(R^{x,k+1},v_{x})_{Tmm}+(R^{y,k+1},v_{y})_{mTm}\nonumber \\{} & {} +(R^{z,k+1},v_{z})_{mmT}+(O((\Delta T)^{4}+H^{4}),{{\textbf {v}}}). \end{aligned}$$
(2.12)

By Eq. 6.18, Lemmas 10, 14 and Cauchy-Schwartz inequality, we obtain

$$\begin{aligned}&\beta \Vert (e_{p}+\delta _{p}^{\tilde{\textbf{u}}})^{k+1}\Vert _{m}\nonumber \\&\quad \le \sup \dfrac{-((e_{p}+\delta _{p}^{\tilde{\textbf{u}}})^{k+1},d_{x}v_{x}+d_{y}v_{y}+d_{z}v_{z})}{\Vert {{\textbf {Dv}}}\Vert }\nonumber \\&\quad \le C(\Vert D_{t}e_{\tilde{\textbf{u}}}^{k+1}\Vert +\Vert {{\textbf {D}}}e_{\tilde{\textbf{u}}}^{k+1}\Vert +\Vert e_{\tilde{\textbf{u}}}^{k+1}\Vert )\nonumber \\&\qquad +C\Vert (e_{T}+\delta _{T})^{k+1}\Vert _{m}\nonumber \\&\qquad +C(\varepsilon +(\Delta t)^{2}+(\Delta T)^{4}+h^{2}+H^{4}), \quad K\ge 1. \end{aligned}$$
(2.13)

Similarly we can get

$$\begin{aligned} \beta \Vert (e_{p}+\delta _{p}^{\tilde{\textbf{u}}})^{1}\Vert _{m}&\le \sup \dfrac{-((e_{p}\!+\!\delta _{p}^{\tilde{\textbf{u}}})^{1},d_{x}v_{x}+d_{y}v_{y}+d_{z}v_{z})}{\Vert {{\textbf {Dv}}}\Vert }\nonumber \\&\le C(\Vert d_{t}e_{\tilde{\textbf{u}}}^{1}\Vert +\Vert {{\textbf {D}}}e_{\tilde{\textbf{u}}}^{1}\Vert +\Vert e_{\tilde{\textbf{u}}}^{1}\Vert )\nonumber \\&\quad +C\Vert (e_{T}+\delta _{T})^{1}\Vert _{m}\nonumber \\&\quad +C(\varepsilon +\Delta t+(\Delta T)^{4}+h^{2}+H^{4}). \end{aligned}$$
(2.14)

And the rest proof process is similar to the Lemma 11, we shall omit it for simplicity. Finally, we can get,

$$\begin{aligned}&\Vert e_{\tilde{\textbf{u}}}^{q+1}\Vert ^{2}+\sum _{k=0}^{q}\Delta t\Vert {{\textbf {D}}}e_{\tilde{\textbf{u}}}^{k+1}\Vert ^{2}+\sum _{k=0}^{q}\Delta t\Vert (e_{p}+\delta _{p}^{\tilde{\textbf{u}}})^{k+1}\Vert _{m}^{2}\nonumber \\&+\Vert (e_{T}+\delta _{T})^{q+1}\Vert _{m}^{2}\nonumber \\&\le O(\varepsilon ^{2}+(\Delta t)^{4}+(\Delta T)^{8}+h^{4}+H^{8}). \end{aligned}$$
(2.15)

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Liu, W., Song, Y., Chen, Y. et al. Numerical simulation on staggered grids of three-dimensional brinkman-forchheimer flow and heat transfer in porous media. Comput Geosci (2024). https://doi.org/10.1007/s10596-023-10266-7

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