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Unfitted Finite Element Methods for Axisymmetric Two-Phase Flow

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Abstract

We propose and analyze unfitted finite element approximations for the two-phase incompressible Navier–Stokes flow in an axisymmetric setting. The discretized schemes are based on an Eulerian weak formulation for the Navier–Stokes equation in the 2d-meridian halfplane, together with a parametric formulation for the generating curve of the evolving interface. We use lowest order Taylor–Hood and piecewise linear elements for discretizing the Navier–Stokes formulation in the bulk and the moving interface, respectively. We discuss a variety of schemes, amongst which is a linear scheme that enjoys an equidistribution property on the discrete interface and good volume conservation. An alternative scheme can be shown to be unconditionally stable and to conserve the volume of the two phases exactly. Numerical results are presented to show the robustness and accuracy of the introduced methods for simulating both rising bubble and oscillating droplet experiments.

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Data Availability

The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Aalilija, A., Gandin, C.A., Hachem, E.: On the analytical and numerical simulation of an oscillating drop in zero-gravity. Comput. Fluids 197, 104362 (2020)

    MathSciNet  MATH  Google Scholar 

  2. Agnese, M., Nürnberg, R.: Fitted front tracking methods for two-phase incompressible Navier–Stokes flow: Eulerian and ALE finite element discretizations. Int. J. Numer. Anal. Mod. 17, 613–642 (2020)

    MathSciNet  MATH  Google Scholar 

  3. Anderson, D.M., McFadden, G.B., Wheeler, A.A.: Diffuse-interface methods in fluid mechanics. Annu. Rev. Fluid Mech. 30, 139–165 (1998)

    MathSciNet  MATH  Google Scholar 

  4. Anjos, G., Mangiavacchi, N., Borhani, N., Thome, J.R.: 3D ALE finite-element method for two-phase flows with phase change. Heat Transf. Engrg. 35, 537–547 (2014)

    MATH  Google Scholar 

  5. Bänsch, E.: Finite element discretization of the Navier–Stokes equations with a free capillary surface. Numer. Math. 88, 203–235 (2001)

    MathSciNet  MATH  Google Scholar 

  6. Bao, W., Zhao, Q.: A structure-preserving parametric finite element method for surface diffusion. SIAM J. Numer. Anal. 59, 2775–2799 (2021)

    MathSciNet  MATH  Google Scholar 

  7. Bao, W., Garcke, H., Nürnberg, R., Zhao, Q.: Volume-preserving parametric finite element methods for axisymmetric geometric evolution equations. J. Comput. Phys. 460, 111180 (2022)

    MathSciNet  MATH  Google Scholar 

  8. Barrett, J.W., Garcke, H., Nürnberg, R.: A parametric finite element method for fourth order geometric evolution equations. J. Comput. Phys. 222, 441–467 (2007)

    MathSciNet  MATH  Google Scholar 

  9. Barrett, J.W., Garcke, H., Nürnberg, R.: On stable parametric finite element methods for the Stefan problem and the Mullins–Sekerka problem with applications to dendritic growth. J. Comput. Phys. 229, 6270–6299 (2010)

    MathSciNet  MATH  Google Scholar 

  10. Barrett, J.W., Garcke, H., Nürnberg, R.: Eliminating spurious velocities with a stable approximation of viscous incompressible two-phase Stokes flow. Comput. Methods Appl. Mech. Eng. 267, 511–530 (2013)

    MathSciNet  MATH  Google Scholar 

  11. Barrett, J.W., Garcke, H., Nürnberg, R.: A stable parametric finite element discretization of two-phase Navier–Stokes flow. J. Sci. Comput. 63, 78–117 (2015)

    MathSciNet  MATH  Google Scholar 

  12. Barrett, J.W., Garcke, H., Nürnberg, R.: Finite element methods for fourth order axisymmetric geometric evolution equations. J. Comput. Phys. 376, 733–766 (2019)

    MathSciNet  MATH  Google Scholar 

  13. Barrett, J.W., Garcke, H., Nürnberg, R.: Variational discretization of axisymmetric curvature flows. Numer. Math. 141, 791–837 (2019)

    MathSciNet  MATH  Google Scholar 

  14. Barrett, J.W., Garcke, H., Nürnberg, R.: Parametric finite element approximations of curvature driven interface evolutions. Handb. Numer. Anal. 21, 275–423 (2020)

    MathSciNet  MATH  Google Scholar 

  15. Belhachmi, Z., Bernardi, C., Deparis, S.: Weighted Clément operator and application to the finite element discretization of the axisymmetric stokes problem. Numer. Math. 105, 217–247 (2006)

    MathSciNet  MATH  Google Scholar 

  16. Bernardi, C., Dauge, M., Maday, Y.: Spectral Methods for Axisymmetric Domains, vol. 3. Gauthier-Villars, Éditions Scientifiques et Médicales. Elsevier, Paris (1999)

  17. Chessa, J., Belytschko, T.: An enriched finite element method and level sets for axisymmetric two-phase flow with surface tension. Int. J. Numer. Methods Eng. 58, 2041–2064 (2003)

    MathSciNet  MATH  Google Scholar 

  18. Cheung, S.W., Chung, E., Kim, H.H.: A mass conservative scheme for fluid-structure interaction problems by the staggered discontinuous Galerkin method. J. Sci. Comput. 74, 1423–1456 (2018)

    MathSciNet  MATH  Google Scholar 

  19. Duan, B., Li, B., Yang, Z.: An energy diminishing arbitrary Lagrangian–Eulerian finite element method for two-phase Navier–Stokes flow. J. Comput. Phys. 461, 111215 (2022)

    MathSciNet  MATH  Google Scholar 

  20. Dziuk, G.: An algorithm for evolutionary surfaces. Numer. Math. 58, 603–611 (1990)

    MathSciNet  MATH  Google Scholar 

  21. Elliott, C.M., Fritz, H.: On approximations of the curve shortening flow and of the mean curvature flow based on the DeTurck trick. IMA J. Numer. Anal. 37, 543–603 (2017)

    MathSciNet  MATH  Google Scholar 

  22. Feng, X.: Fully discrete finite element approximations of the Navier–Stokes–Cahn–Hilliard diffuse interface model for two-phase fluid flows. SIAM J. Numer. Anal. 44, 1049–1072 (2006)

    MathSciNet  MATH  Google Scholar 

  23. Frachon, T., Zahedi, S.: A cut finite element method for incompressible two-phase Navier–Stokes flows. J. Comput. Phys. 384, 77–98 (2019)

    MathSciNet  MATH  Google Scholar 

  24. Ganesan, S.: Finite element methods on moving meshes for free surface and interface flows, Ph.D. thesis. University Magdeburg, Magdeburg, Germany (2006)

  25. Ganesan, S., Tobiska, L.: An accurate finite element scheme with moving meshes for computing 3D-axisymmetric interface flows. Int. J. Numer. Methods Fluids 57, 119–138 (2008)

    MathSciNet  MATH  Google Scholar 

  26. Garcke, H., Hinze, M., Kahle, C.: A stable and linear time discretization for a thermodynamically consistent model for two-phase incompressible flow. Appl. Numer. Math. 99, 151–171 (2016)

    MathSciNet  MATH  Google Scholar 

  27. Garcke, H., Nürnberg, R., Zhao, Q.: Structure-preserving discretizations of two-phase Navier–Stokes flow using fitted and unfitted approaches. J. Comput. Phys. 489, 112276 (2023)

    MathSciNet  MATH  Google Scholar 

  28. Gibou, F., Fedkiw, R., Osher, S.: A review of level-set methods and some recent applications. J. Comput. Phys. 353, 82–109 (2018)

    MathSciNet  MATH  Google Scholar 

  29. Gros, E., Anjos, G.R., Thome, J.R.: Interface-fitted moving mesh method for axisymmetric two-phase flow in microchannels. Int. J. Numer. Methods Fluids 86, 201–217 (2018)

    MathSciNet  Google Scholar 

  30. Groß, S., Reusken, A.: An extended pressure finite element space for two-phase incompressible flows with surface tension. J. Comput. Phys. 224, 40–58 (2007)

    MathSciNet  MATH  Google Scholar 

  31. Groß, S., Reusken, A.: Numerical Methods for Two-Phase Incompressible Flows. Springer Series in Computational Mathematics, vol. 40. Springer, Berlin (2011)

    MATH  Google Scholar 

  32. Grün, G., Klingbeil, F.: Two-phase flow with mass density contrast: stable schemes for a thermodynamic consistent and frame-indifferent diffuse-interface model. J. Comput. Phys. 257, 708–725 (2014)

    MathSciNet  MATH  Google Scholar 

  33. Hirt, C.W., Nichols, B.D.: Volume of fluid (VOF) method for the dynamics of free boundaries. J. Comput. Phys. 39, 201–225 (1981)

    MATH  Google Scholar 

  34. Hu, J., Li, B.: Evolving finite element methods with an artificial tangential velocity for mean curvature flow and Willmore flow. Numer. Math. 152, 127–181 (2022)

    MathSciNet  MATH  Google Scholar 

  35. Huang, F., Bao, W., Qian, T.: Diffuse-interface approach to competition between viscous flow and diffusion in pinch-off dynamics. Phys. Rev. Fluids 7, 094004 (2022)

    Google Scholar 

  36. Hughes, T.J., Liu, W.K., Zimmermann, T.K.: Lagrangian–Eulerian finite element formulation for incompressible viscous flows. Comput. Methods Appl. Mech. Engrg. 29, 329–349 (1981)

    MathSciNet  MATH  Google Scholar 

  37. Hysing, S.R., Turek, S., Kuzmin, D., Parolini, N., Burman, E., Ganesan, S., Tobiska, L.: Quantitative benchmark computations of two-dimensional bubble dynamics. Int. J. Numer. Methods Fluids 60, 1259–1288 (2009)

    MathSciNet  MATH  Google Scholar 

  38. Jiang, W., Li, B.: A perimeter-decreasing and area-conserving algorithm for surface diffusion flow of curves. J. Comput. Phys. 443, 110531 (2021)

    MathSciNet  MATH  Google Scholar 

  39. Kim, J.: A diffuse-interface model for axisymmetric immiscible two-phase flow. Appl. Math. Comput. 160, 589–606 (2005)

    MathSciNet  MATH  Google Scholar 

  40. Lamb, H.: On the oscillations of a viscous spheroid. Proc. Lond. Math. Soc. 1, 51–70 (1881)

    MathSciNet  MATH  Google Scholar 

  41. Mirjalili, S., Jain, S.S., Dodd, M.: Interface-capturing methods for two-phase flows: an overview and recent developments. CTR Ann. Res. Briefs 2017, 13 (2017)

    Google Scholar 

  42. Olsson, E., Kreiss, G., Zahedi, S.: A conservative level set method for two phase flow II. J. Comput. Phys. 225, 785–807 (2007)

    MathSciNet  MATH  Google Scholar 

  43. Osher, S., Fedkiw, R.: Level Set Methods and Dynamic Implicit Surfaces, vol. 153. Springe, Berlin (2002)

    MATH  Google Scholar 

  44. Perot, B., Nallapati, R.: A moving unstructured staggered mesh method for the simulation of incompressible free-surface flows. J. Comput. Phys. 184, 192–214 (2003)

    MATH  Google Scholar 

  45. Popinet, S.: An accurate adaptive solver for surface-tension-driven interfacial flows. J. Comput. Phys. 228, 5838–5866 (2009)

    MathSciNet  MATH  Google Scholar 

  46. Quan, S., Schmidt, D.P.: A moving mesh interface tracking method for 3D incompressible two-phase flows. J. Comput. Phys. 221, 761–780 (2007)

    MathSciNet  MATH  Google Scholar 

  47. Rayleigh, L., et al.: On the capillary phenomena of jets. Proc. R. Soc. Lond. 29, 71–97 (1879)

    Google Scholar 

  48. Renardy, Y., Renardy, M.: PROST: a parabolic reconstruction of surface tension for the volume-of-fluid method. J. Comput. Phys. 183, 400–421 (2002)

    MathSciNet  MATH  Google Scholar 

  49. Schmidt, A., Siebert, K.G.: Design of Adaptive Finite Element Software: The Finite Element Toolbox ALBERTA. Lecture Notes in Computational Science and Engineering, vol. 42. Springer, Berlin (2005)

    MATH  Google Scholar 

  50. Sethian, J.A.: Level set methods and fast marching methods: evolving interfaces in computational geometry, fluid mechanics, computer vision, and materials science, vol. 3. Cambridge University Press, Cambridge (1999)

    MATH  Google Scholar 

  51. Styles, V., Kay, D., Welford, R.: Finite element approximation of a Cahn–Hilliard–Navier–Stokes system. Interfaces Free Bound. 10, 15–43 (2008)

    MathSciNet  Google Scholar 

  52. Sussman, M., Puckett, E.G.: A coupled level set and volume-of-fluid method for computing 3D and axisymmetric incompressible two-phase flows. J. Comput. Phys. 162, 301–337 (2000)

    MathSciNet  MATH  Google Scholar 

  53. Sussman, M., Smereka, P., Osher, S.: A level set approach for computing solutions to incompressible two-phase flow. J. Comput. Phys. 114, 146–159 (1994)

    MATH  Google Scholar 

  54. Tryggvason, G., Bunner, B., Esmaeeli, A., Juric, D., Al-Rawahi, N., Tauber, W., Han, J., Nas, S., Jan, Y.J.: A front-tracking method for the computations of multiphase flow. J. Comput. Phys. 169, 708–759 (2001)

    MathSciNet  MATH  Google Scholar 

  55. Unverdi, S.O., Tryggvason, G.: A front-tracking method for viscous, incompressible multi-fluid flows. J. Comput. Phys. 100, 25–37 (1992)

    MATH  Google Scholar 

  56. Velentine, R., Sather, N., Heideger, W.: The motion of drops in viscous media. Chem. Engrg. Sci. 20, 719–728 (1965)

    Google Scholar 

  57. Zhao, Q., Ren, W.: An energy-stable finite element method for the simulation of moving contact lines in two-phase flows. J. Comput. Phys. 417, 109582 (2020)

    MathSciNet  MATH  Google Scholar 

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The work of Zhao was supported by the Alexander von Humboldt Foundation.

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Appendix: Derivation of (3.11)

Appendix: Derivation of (3.11)

Let \(\vec x= (x,y,z)\) be the Cartesian coordinates, and \((r,z,\varphi )\) be the cylindrical coordinates such that

$$\begin{aligned} x = r\cos \varphi ,\qquad y = r\sin \varphi , \end{aligned}$$

where \(r=\sqrt{x^2+y^2}\) is the radial distance and \(\varphi \) is the azimuthal angle. This gives rise to the basis vectors \(\big \{\vec e_r,\vec e_\varphi ,\vec e_z\big \}\)

$$\begin{aligned} \vec e_r = (\cos \varphi ,\sin \varphi , 0)^T,\qquad \vec e_\varphi = (-\sin \varphi ,\cos \varphi , 0)^T,\qquad \vec e_z=(0,0,1)^T, \end{aligned}$$
(A.1)

which satisfy

$$\begin{aligned} \frac{\partial \vec e_r}{\partial \varphi } = \vec e_\varphi ,\qquad \frac{\partial \vec e_\varphi }{\partial \varphi } = -\vec e_r,\qquad \frac{\partial \vec e_z}{\partial \varphi } = \vec 0,\qquad \frac{\partial \vec e_r}{\partial r} = \frac{\partial \vec e_\varphi }{\partial r}=\frac{\partial \vec e_z}{\partial r}=\vec {0}. \end{aligned}$$
(A.2)

For any scalar function \(\breve{b}(\vec x)\), we write in cylindrical coordinates \(b(r,\varphi ,z) = \breve{b}(\vec x)\). Then we have

$$\begin{aligned} \nabla \breve{b}(\vec x) = \frac{\partial b}{\partial r}\,\vec e_r + \frac{1}{r}\frac{\partial b}{\partial \varphi }\,\vec e_\varphi + \frac{\partial b}{\partial z}\,\vec e_z. \end{aligned}$$
(A.3)

For any vector-valued function \(\breve{\vec b}(\vec x, t)\), similarly we write \(\breve{\vec b}(\vec x)=\vec b(r,\varphi , z) = b^r\,\vec e_r + b^\varphi \,\vec e_\varphi + b^z\,\vec e_z\). Then using the relations in (A.2) gives

$$\begin{aligned} \nabla \breve{\vec b} =[\vec e_r\quad \vec e_\varphi \quad \vec e_z]\left[ \begin{array}{lll} \frac{\partial b^r}{\partial r} &{}\frac{1}{r}\frac{\partial b^r}{\partial \varphi }-\frac{b^\varphi }{r} &{}\frac{\partial b^r}{\partial z}\\ \frac{\partial b^\varphi }{\partial r}&{}\frac{b^r}{r}+ \frac{1}{r}\frac{\partial b^\varphi }{\partial \varphi } &{}\frac{\partial b^\varphi }{\partial z}\\ \frac{\partial b^z}{\partial r}&{}\frac{1}{r}\frac{\partial b^z}{\partial \varphi } &{}\frac{\partial b^z}{\partial z} \end{array}\right] \left[ \begin{array}{l} (\vec e_r)^T\\ (\vec e_\varphi )^T\\ (\vec e_z)^T \end{array} \right] . \end{aligned}$$
(A.4)

Moreover, for the divergence of \(\breve{\vec b}\) it holds that

$$\begin{aligned} \nabla \cdot \breve{\vec b} = \frac{\partial \vec b}{\partial r}\cdot \vec e_r + \frac{1}{r}\frac{\partial \vec b}{\partial \varphi }\cdot \vec e_\varphi + \frac{\partial \vec b}{\partial z}\cdot \vec e_z = \frac{\partial b^r}{\partial r} + \frac{b^r}{r}+\frac{1}{r}\frac{\partial b^\varphi }{\partial \varphi } +\frac{\partial b^z}{\partial z}. \end{aligned}$$
(A.5)

We now follow the axisymmetric setting in Sect. 3.1 and denote

$$\begin{aligned} \breve{\vec u}(\vec x, t)=u^r(r,z,t)\,\vec e_r + u^z(r,z,t)\,\vec e_z,\qquad \breve{{\vec {\chi }}}(\vec x, t) =\chi ^r(r,z,t)\,\vec e_r + \chi ^z(r,z,t)\,\vec e_z. \end{aligned}$$

Then it follows from (3.12a) that

$$\begin{aligned} \Bigl (\rho \breve{\vec u},~\breve{{\vec {\chi }}}\Bigr )_\varOmega&= 2\pi \int _{\mathcal {R}_-(t)}\rho _-(u^r\,\chi ^r + u^z\,\chi ^z)r\,\textrm{d}r\textrm{d}z+ 2\pi \int _{\mathcal {R}_+(t)}\rho _+(u^r\,\chi ^r + u^z\,\chi ^z)r\,\textrm{d}r\textrm{d}z\nonumber \\&=2\pi \int _{\mathcal {R}}\rho _{_c}(u^r\,\chi ^r + u^z\,\chi ^z)r\,\textrm{d}r\textrm{d}z=2\pi \,\Bigl (\rho _{_c}\vec u,~{\vec {\chi }}\,r\Bigr ), \end{aligned}$$
(A.6)

where \(\vec u = (u^r, u^z)^T\) and \({\vec {\chi }} = (\chi ^r,\chi ^z)^T\) are vectors in the 2d-meridian halfplane \(\mathcal {R}\). Similarly we have

$$\begin{aligned} \Bigl (\rho \partial _t\breve{\vec u},~\breve{{\vec {\chi }}}\Bigr )_\varOmega = 2\pi \,\Bigl (\rho _{_c}\partial _t\vec u,~{\vec {\chi }}\,r\bigr ),\qquad \Bigl (\rho \breve{\vec u},~\partial _t\breve{{\vec {\chi }}}\Bigr )_\varOmega = 2\pi \,\Bigl (\rho _{_c}\vec u,~\partial _t{\vec {\chi }}\,r\Bigr ). \end{aligned}$$
(A.7)

On recalling (A.5) and (3.8), it holds that

$$\begin{aligned} \Bigl (\breve{q},\,\nabla \cdot \breve{\vec u}\Bigr ) = 2\pi \int _\mathcal {R}\left( \frac{\partial u^r}{\partial r} + \frac{u^r}{r} + \frac{\partial u^z}{\partial z}\right) q\,r\textrm{d}r\textrm{d}z= 2\pi \,\Bigl (\nabla _c\cdot ([r\vec u],~q\Bigr ). \end{aligned}$$
(A.8)

Using (A.4) for \(\breve{\vec u}\) and \(\breve{{\vec {\chi }}}\), it is not difficult to show that

$$\begin{aligned} \int _{\varOmega _\pm (t)}\left( [\breve{\vec u}\cdot \nabla ]\breve{\vec u}\cdot \breve{{\vec {\chi }}} -[\breve{\vec u}\cdot \nabla ]\breve{{\vec {\chi }}}\cdot \breve{\vec u}\right) \,\textrm{d}V= 2\pi \int _{\mathcal {R}_\pm (t)}\,\bigl ([\vec u\cdot \nabla _c]\vec u\cdot {\vec {\chi }} - [\vec u\cdot \nabla _c]{\vec {\chi }}\cdot \vec u\bigr )\,r\,\textrm{d}r\textrm{d}z. \end{aligned}$$
(A.9)

Multiplying (A.9) with \(\rho _\pm \) and combining these two equations gives rise to

$$\begin{aligned} \Bigl (\rho ,~[\breve{\vec u}\cdot \nabla ]\breve{\vec u}\cdot \breve{{\vec {\chi }}} -[\breve{\vec u}\cdot \nabla ]\breve{{\vec {\chi }}}\cdot \breve{\vec u}\Bigr )_\varOmega =2\pi \, \Bigl (\rho _{_c}r,~[\vec u\cdot \nabla _c]\vec u\cdot {\vec {\chi }} - [\vec u\cdot \nabla _c]{\vec {\chi }}\cdot \vec u\Bigr ). \end{aligned}$$
(A.10)

Similarly we can compute

$$\begin{aligned} \underline{\underline{\mathbb {D}}}(\breve{\vec u}) = \frac{1}{2}\left( \nabla \breve{\vec u}+ (\nabla \breve{\vec u})^T\right) =[\vec e_r\quad \vec e_\varphi \quad \vec e_z]\left[ \begin{array}{lll} \frac{\partial u^r}{\partial r} &{}0 &{}\frac{1}{2}\left( \frac{\partial u^r}{\partial z}+\frac{\partial u^z}{\partial r}\right) \\ 0&{}\frac{u^r}{r} &{}0\\ \frac{1}{2}\left( \frac{\partial u^r}{\partial z}+\frac{\partial u^z}{\partial r}\right) &{}0 &{}\frac{\partial u^z}{\partial z} \end{array}\right] \left[ \begin{array}{l} (\vec e_r)^T\\ (\vec e_\varphi )^T\\ (\vec e_z)^T \end{array} \right] . \end{aligned}$$

This implies that

$$\begin{aligned}&\int _{\varOmega _\pm (t)}\underline{\underline{\mathbb {D}}}(\breve{\vec u}):\underline{\underline{\mathbb {D}}}(\breve{{\vec {\chi }}})\,\textrm{d}V\nonumber \\&\quad =2\pi \int _{\mathcal {R}_\pm (t)}\left\{ \frac{\partial u^r}{\partial r}\frac{\partial \chi ^r}{\partial r} + \frac{1}{2}\left[ \frac{\partial u^r}{\partial z} + \frac{\partial u^z}{\partial r}\right] \left[ \frac{\partial \chi ^r}{\partial z} + \frac{\partial \chi ^z}{\partial r}\right] + \,\frac{\partial u^z}{\partial z}\frac{\partial \chi ^z}{\partial z} + \frac{u^r\,\chi ^r}{r^2}\right\} r\,\textrm{d}r\textrm{d}z\nonumber \\&\quad =2\pi \int _{\mathcal {R}_\pm (t)}\underline{\underline{\mathbb {D}_c}}(\vec u):\underline{\underline{\mathbb {D}_c}}({\vec {\chi }})\,r\textrm{d}r\textrm{d}z+2\pi \int _{\mathcal {R}_\pm (t)}(\vec u\cdot \vec e_1)({\vec {\chi }}\cdot \vec e_1)\,r^{-1}\,\textrm{d}r\textrm{d}z. \end{aligned}$$
(A.11)

Multiplying (A.11) with \(\mu _\pm \) and combining these two equations yields that

$$\begin{aligned} \Bigl (\mu \,\underline{\underline{\mathbb {D}}}(\breve{\vec u}),~\underline{\underline{\mathbb {D}}}(\breve{{\vec {\chi }}})\Bigr )_\varOmega = 2\pi \,\Bigl (\mu _{_c}r\,\underline{\underline{\mathbb {D}_c}}(\vec u),~\underline{\underline{\mathbb {D}_c}}({\vec {\chi }})\Bigr ) +2\pi \, \Bigl (\mu _{_c}r^{-1}(\vec u\cdot \vec e_1),~({\vec {\chi }}\cdot \vec e_1)\Bigr ).\nonumber \\ \end{aligned}$$
(A.12)

On the axisymmetric surface \(S(t)\), by (3.1) we can set

$$\begin{aligned} \mathcal {\vec {\hspace{0.0pt}V}}(\vec x, t) = {\mathfrak {X}}^r_t\,\vec e_r + {\mathfrak {X}}^z_t\,\vec e_z,\qquad \vec n_{_S}(\vec x, t) = -{\mathfrak {X}}^z_s\,\vec e_r + {\mathfrak {X}}^r_s\,\vec e_z,\nonumber \\ \breve{{\vec {\eta }}}(\vec x) = \eta ^r\vec e_r + \eta ^z\vec e_z\quad \text{ for }\quad \vec x\in S(t). \end{aligned}$$
(A.13)

Denote \(\zeta (\alpha , t) = \breve{\zeta }(\vec x, t)\) for \(\vec x\in S(t)\), \(\alpha \in \mathbb {I}\). Then it is easy to get

$$\begin{aligned} \int _{S(t)}(\mathcal {\vec {\hspace{0.0pt}V}}-\breve{\vec u})\cdot \vec n_{_S}\,\breve{\zeta }\,\;\textrm{d}S= & {} 2\pi \int _{\varGamma (t)}({\vec {{\mathfrak {X}}}}_t - \vec u)\cdot {\vec {\nu }}\,\zeta \,({\vec {{\mathfrak {X}}}}\cdot \vec e_1)\;\textrm{d}s \nonumber \\= & {} 2\pi \,\Big \langle ({\vec {{\mathfrak {X}}}}\cdot \vec e_1)({\vec {{\mathfrak {X}}}}_t-\vec u)\cdot {\vec {\nu }},\,\zeta \,|{\vec {{\mathfrak {X}}}}_\alpha |\Big \rangle . \end{aligned}$$
(A.14)

Similarly, it is straightforward to obtain

$$\begin{aligned} \int _{S(t)}\mathcal {H}\,\vec n_{_S}\cdot \breve{{\vec {\eta }}}\,\;\textrm{d}S =2\pi \int _{\varGamma (t)}\varkappa \,{\vec {\nu }}\cdot {\vec {\eta }}\;({\vec {{\mathfrak {X}}}}\cdot \vec e_1)\;\textrm{d}s = 2\pi \,\Big \langle ({\vec {{\mathfrak {X}}}}\cdot \vec e_1)\,\varkappa \,{\vec {\nu }},~{\vec {\eta }} \,|{\vec {{\mathfrak {X}}}}_\alpha |\Big \rangle ,\nonumber \\ \end{aligned}$$
(A.15)

where \({\vec {\eta }}=(\eta ^r,~\eta ^z)^T\) is the vector in the 2d-meridian plane. Finally, we have

$$\begin{aligned} \int _{S(t)}\nabla _s{\vec {\textrm{id}}}:\nabla _s\breve{{\vec {\eta }}}\,\;\textrm{d}S&= \int _{S(t)}\nabla _s\cdot \breve{{\vec {\eta }}}\,\;\textrm{d}S = 2\pi \int _{\varGamma (t)}({\vec {{\mathfrak {X}}}}\cdot \vec e_1)\left( {\vec {{\mathfrak {X}}}}_s\cdot {\vec {\eta }}_s + \frac{{\vec {\eta }}\cdot \vec e_1}{{\vec {{\mathfrak {X}}}}\cdot \vec e_1}\right) \;\textrm{d}s\nonumber \\&= 2\pi \int _{\mathbb {I}}({\vec {{\mathfrak {X}}}}\cdot \vec e_1){\vec {{\mathfrak {X}}}}_s\cdot {\vec {\eta }}_s\,|{\vec {{\mathfrak {X}}}}_\alpha | + ({\vec {\eta }}\cdot \vec e_1)\,|{\vec {{\mathfrak {X}}}}_\alpha |\,\;\textrm{d}\alpha , \end{aligned}$$
(A.16)

where we used the fact

$$\begin{aligned} \nabla _s\cdot \breve{{\vec {\eta }}} = {\mathfrak {X}}^r_s\eta ^r_s + {\mathfrak {X}}^z_s\eta ^z_s + \frac{\eta ^r}{{\vec {{\mathfrak {X}}}}\cdot \vec e_1}. \end{aligned}$$
(A.17)

Collecting the above results, we obtain (3.11) from (2.5).

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Garcke, H., Nürnberg, R. & Zhao, Q. Unfitted Finite Element Methods for Axisymmetric Two-Phase Flow. J Sci Comput 97, 14 (2023). https://doi.org/10.1007/s10915-023-02325-z

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  • DOI: https://doi.org/10.1007/s10915-023-02325-z

Keywords

Mathematics Subject Classification

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