Abstract
The Allen-Cahn equation is a gradient system, where the free-energy functional decreases monotonically in time. We develop an energy stable reduced order model (ROM) for a gradient system, which inherits the energy decreasing property of the full order model (FOM). For the space discretization we apply a discontinuous Galerkin (dG) method and for time discretization the energy stable average vector field (AVF) method. We construct ROMs with proper orthogonal decomposition (POD)-greedy adaptive sampling of the snapshots in time and evaluating the nonlinear function with greedy discrete empirical interpolation method (DEIM). The computational efficiency and accuracy of the reduced solutions are demonstrated numerically for the parametrized Allen-Cahn equation with Neumann and periodic boundary conditions.
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References
Ali, M., Urban, K.: Reduced basis exact error estimates with wavelets. In: Karasözen, B., Manguğlu, M., Tezer-Sezgin, M., Göktepe, S., Uğur, Ö. (eds.) Numerical Mathematics and Advanced Applications ENUMATH 2015, Lecture Notes in Computational Science and Engineering, vol. 112, pp. 359–367. Springer International Publishing, Switzerland (2016)
Allen, M.S., Cahn, J.W.: A microscopic theory for antiphase boundary motion and its application to antiphase domain coarsening. Acta Metall. 27(6), 1085–1095 (1979)
Antil, H., Heinkenschloss, M., Sorensen, D.C.: Application of the discrete empirical interpolation method to reduced order modeling of nonlinear and parametric systems. In: Quarteroni, A., Rozza, G. (eds.) Reduced Order Methods for Modeling and Computational Reduction, MS and A. Model. Simul. Appl., vol. 9, pp. 101–136. Springer Italia, Milan (2014)
Arnold, D.N.: An interior penalty finite element method with discontinuous elements. SIAM J. Numer. Anal. 19, 724–760 (1982)
Arnold, D., Brezzi, F., Cockborn, B., Marini, L.: Unified analysis of discontinuous Galerkin methods for elliptic problems. SIAM J. Numer. Anal. 39, 1749–1779 (2002)
Barrault, M., Maday, Y., Nguyen, N.C., Patera, A.T.: An ‘empirical interpolation’ method: application to efficient reduced-basis discretization of partial differential equations. C. R. Math. 339(9), 667–672 (2004)
Barrett, J.W., Blowey, J.F.: Finite element approximation of the Cahn–Hilliard equation with concentration dependent mobility. Math. Comput. 68(226), 487–517 (1999)
Benner, P., Gugercin, S., Willcox, K.: A survey of projection-based model reduction methods for parametric dynamical systems. SIAM Rev. 57(4), 483–531 (2015)
Celledoni, E., Grimm, V., McLachlan, R., McLaren, D., O’Neale, D., Owren, B., Quispel, G.: Preserving energy resp. dissipation in numerical {PDEs} using the “average vector field” method. J. Comput. Phys. 231(20), 6770–6789 (2012)
Chaturantabut, S., Sorensen, D.C.: A state space error estimate for POD–DEIM nonlinear model reduction. SIAM J. Numer. Anal. 50(1), 46–63 (2012)
Chaturantabut, S., Sorensen, D.C.: Nonlinear model reduction via discrete empirical interpolation. SIAM J. Sci. Comput. 32(5), 2737–2764 (2010)
Choi, J.W., Lee, H.G., Jeong, D., Kim, J.: An unconditionally gradient stable numerical method for solving the Allen–Cahn equation. Phys. A Stat. Mech. Appl. 388(9), 1791–1803 (2009)
Christlieb, A., Jones, J., Promislow, K., Wetton, B., Willoughby, M.: High accuracy solutions to energy gradient flows from material science models. J. Comput. Phys. 257, 193–215 (2014)
Clenshaw, C.W., Curtis, A.R.: A method for numerical integration on an automatic computer. Numer. Math. 2(1), 197–205 (1960)
Drohmann, M., Haasdonk, B., Ohlberger, M.: Reduced basis approximation for nonlinear parametrized evolution equations based on empirical operator interpolation. SIAM J. Sci. Comput. 34(2), A937–A969 (2012)
Feng, X., Wu, H.j.: A posteriori error estimates and an adaptive finite element method for the Allen–Cahn equation and the mean curvature flow. J. Sci. Comput. 24(2), 121–146 (2005)
Feng, X., Song, H., Tang, T., Yang, J.: Nonlinear stability of the implicit–explicit methods for the Allen–Cahn equation. Inverse Problems Imaging 7(3), 679–695 (2013)
Feng, X., Tang, T., Yang, J.: Stabilized Crank-Nicolson/Adams-Bashforth schemes for phase field models. East Asian J. Appl. Math. 3, 59–80 (2013)
Grepl, M.A.: Model order reduction of parametrized nonlinear reaction-diffusion systems. Comput. Chem. Eng. 43, 33–44 (2012)
Grepl, M.A., Maday, Y., Nguyen, N.C., Patera, A.T.: Efficient reduced-basis treatment of nonaffine and nonlinear partial differential equations. ESAIM: M2AN 41(3), 575–605 (2007)
Guo, R., Ji, L., Xu, Y.: High order local discontinuous Galerkin methods for the Allen–Cahn equation: analysis and simulation. J. Comput. Math. 34, 135–158 (2016)
Hairer, E.: Energy-preserving variant of collocation methods. J. Numer. Anal. Ind. Appl. Math. 5, 73–84 (2010)
Ionita, A.C., Antoulas, A.C.: Data-driven parametrized model reduction in the loewner framework. SIAM J. Sci. Comput. 36(3), A984–A1007 (2014)
Kalashnikova, I., Barone, M.F.: Efficient non-linear proper orthogonal decomposition/Galerkin reduced order models with stable penalty enforcement of boundary conditions. Int. J. Numer. Methods Eng. 90(11), 1337–1362 (2012)
Karasözen, B., Kücükseyhan, T., Uzunca, M.: Structure preserving integration and model order reduction of skew-gradient reaction-diffusion systems. Ann. Oper. Res. 1–28 (2015)
Liu, F., Shen, J.: Stabilized semi-implicit spectral deferred correction methods for Allen–Cahn and Cahn–Hilliard equations. Math. Methods Appl. Sci. 38(18), 4564–4575 (2013)
Rivière, B.: Discontinuous Galerkin methods for solving elliptic and parabolic equations, Theory and implementation. SIAM (2008)
Shen, J., Yang, X.: An efficient moving mesh spectral method for the phase-field model of two-phase flows. J. Comput. Phys. 228(8), 2978–2992 (2009)
Shen, J., Yang, X.: Numerical approximations of Allen-Cahn and Cahn-Hilliard equations. Discret. Contin. Dyn. Syst. A 28, 1669–1691 (2010)
Shen, J., Tang, T., Yang, J.: On the maximum principle preserving schemes for the generalized Allen–Cahn equation. Commun. Math. Sci. 14, 1517–1534 (2016)
Song, H., Jiang, L., Li, Q.: A reduced order method for Allen–Cahn equations. J. Comput. Appl. Math. 292, 213–229 (2016)
Ullmann, S., Rotkvic, M., Lang, J.: POD-Galerkin reduced-order modeling with adaptive finite element snapshots. J. Comput. Phys. 235, 244–258 (2016)
Vemaganti, K.: Discontinuous Galerkin methods for periodic boundary value problems. Numerical Methods Partial Differ. Equ. 23(3), 587–596 (2007)
Volkwein, S.: Optimal control of a phase-field model using proper orthogonal decomposition. ZAMM - J. Appl. Math. Mech. / Zeitschrift für Angewandte Mathematik und Mechanik 81(2), 83–97 (2001)
Wirtz, D., Sorensen, D.C., Haasdonk, B.: A posteriori error estimation for DEIM reduced nonlinear dynamical systems. SIAM J. Sci. Comput. 36(2), A311–A338 (2014)
Yano, Masayuki: A minimum-residual mixed reduced basis method: exact residual certification and simultaneous finite-element reduced-basis refinement. ESAIM: M2AN 50(1), 163–185 (2016)
Zhang, J., Du, Q.: Numerical studies of discrete approximations to the Allen–Cahn equation in the sharp interface limit. SIAM J. Sci. Comput. 31(4), 3042–3063 (2009)
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Uzunca, M., Karasözen, B. (2017). Energy Stable Model Order Reduction for the Allen-Cahn Equation. In: Benner, P., Ohlberger, M., Patera, A., Rozza, G., Urban, K. (eds) Model Reduction of Parametrized Systems. MS&A, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-319-58786-8_25
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DOI: https://doi.org/10.1007/978-3-319-58786-8_25
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