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Reduced-order extrapolation spectral-finite difference scheme based on POD method and error estimation for three-dimensional parabolic equation

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Abstract

In this study, a classical spectral-finite difference scheme (SFDS) for the three-dimensional (3D) parabolic equation is reduced by using proper orthogonal decomposition (POD) and singular value decomposition (SVD). First, the 3D parabolic equation is discretized in spatial variables by using spectral collocation method and the discrete scheme is transformed into matrix formulation by tensor product. Second, the classical SFDS is obtained by difference discretization in time-direction. The ensemble of data are comprised with the first few transient solutions of the classical SFDS for the 3D parabolic equation and the POD bases of ensemble of data are generated by using POD technique and SVD. The unknown quantities of the classical SFDS are replaced with the linear combination of POD bases and a reduced-order extrapolation SFDS with lower dimensions and sufficiently high accuracy for the 3D parabolic equation is established. Third, the error estimates between the classical SFDS solutions and the reduced-order extrapolation SFDS solutions and the implementation for solving the reduced-order extrapolation SFDS are provided. Finally, a numerical example shows that the errors of numerical computations are consistent with the theoretical results. Moreover, it is shown that the reduced-order extrapolation SFDS is effective and feasible to find the numerical solutions for the 3D parabolic equation.

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References

  1. Afanasiev K, Hinze M. Adaptive control of a wake flow using proper orthogonal decomposition. Lect Notes Pure Appl Math, 2001, 216: 317–332

    MathSciNet  Google Scholar 

  2. Algazi V, Sakrison D. On the optimality of Karhunen-Loève expansion. IEEE Trans Inform Theory, 1969, 15: 319–321

    Article  MATH  MathSciNet  Google Scholar 

  3. Arian E, Fahl M, Sachs E W. Trust-region proper orthogonal decomposition models by optimization method. In: Proceedings of the 41st IEEE Conference on Decision and Control, Las Vegas, Nevada, 2002. 2002, 3300–3305

    Chapter  Google Scholar 

  4. Aubry N, Holmes P, Lumley J L, Stone E. The dynamics of coherent structures in the wall region of a turbulent boundary layer. J Fluid Dynamics, 1988, 192: 115–173

    MATH  MathSciNet  Google Scholar 

  5. Cao Y H, Zhu J, Luo Z H, Navon I M. Reduced order modeling of the upper tropical Pacific Ocean model using proper orthogonal decomposition. Comput Math Appl, 2006, 52: 1373–1386

    Article  MATH  MathSciNet  Google Scholar 

  6. Cao Y H, Zhu J, Navon I M, Luo Z D. A reduced order approach to four-dimensional variational data assimilation using proper orthogonal decomposition. Int J Numer Meth Fluids, 2007, 53: 1571–1583

    Article  MATH  Google Scholar 

  7. Fox L, Parker I B. Chebyshev Polynomials in Numerical Analysis. Oxford: Oxford University Press, 1968

    Google Scholar 

  8. Fukunaga K. Introduction to Statistical Recognition. New York: Academic Press, 1990

    MATH  Google Scholar 

  9. Graham M, Kevrekidis I. Alternative approaches to the Karhunen-Loève decomposition for model reduction and data analysis. Comput Chem Eng, 1996, 20: 495–506

    Article  Google Scholar 

  10. Holmes P, Lumley J L, Berkooz G. Turbulence, Coherent Structures, Dynamical Systems and Symmetry. Cambridge: Cambridge University Press, 1996

    Book  MATH  Google Scholar 

  11. Jolliffe I T. Principal Component Analysis. Berlin: Springer-Verlag, 2002

    MATH  Google Scholar 

  12. Joslin R D, Gunzburger M D, Nicolaides R, Erlebacher G, Hussaini M Y. A selfcontained automated methodology for optimal flow control validated for transition delay. AIAA Journal, 1997, 35: 816–824

    Article  MATH  Google Scholar 

  13. Kunisch K, Volkwein S. Galerkin proper orthogonal decomposition methods for parabolic problems. Numer Math, 2001, 90: 117–148

    Article  MATH  MathSciNet  Google Scholar 

  14. Kunisch K, Volkwein S. Galerkin proper orthogonal decomposition methods for a general equation in fluid dynamics. SIAM J Numer Anal, 2002, 40(2): 492–515

    Article  MATH  MathSciNet  Google Scholar 

  15. Kunisch K, Volkwein S. Proper orthogonal decomposition for optimality systems. ESAIM: Math Model Numer Anal, 2008, 42(1): 1–23

    Article  MATH  MathSciNet  Google Scholar 

  16. Lanczos C. Trigonometric interpolation of empirical and analytical functions. J Math Phys, 1938, 17: 123–199

    Google Scholar 

  17. Li H R, Luo Z D, Chen J. Numerical simulation based on proper orthogonal decomposition for two-dimensional solute transport problems. Appl Math Model, 2011, 35(5): 2489–2498

    Article  MATH  MathSciNet  Google Scholar 

  18. Lumley J L. Coherent structures in turbulence. In: Meyer R E, ed. Transition and Turbulence. Proceedings of the Symposium on Transition and Turbulence in Fluids, Madison, WI, October 13–15, 1980. New York: Academic Press, 1981, 215–242

    Google Scholar 

  19. Luo Z D, Chen J, Navon I M, Yang X Z. Mixed finite element formulation and error estimates based on proper orthogonal decomposition for the non-stationary Navier-Stokes equations. SIAM J Numer Anal, 2008, 47(1): 1–19

    Article  MATH  MathSciNet  Google Scholar 

  20. Luo Z D, Chen J, Navon I M, Zhu J. An optimizing reduced PLSMFE formulation for non-stationary conduction-convection problems. Int J Numer Meth Fluids, 2009, 60(4): 409–436

    Article  MATH  MathSciNet  Google Scholar 

  21. Luo Z D, Chen J, Sun P, Yang X Z. Finite element formulation based on proper orthogonal decomposition for parabolic equations. Sci China Ser A: Math, 2009, 52(3): 585–596

    Article  MATH  MathSciNet  Google Scholar 

  22. Luo Z D, Chen J, Zhu J, Wang R W, Navon I M. An optimizing reduced order FDS for the tropical Pacific Ocean reduced gravity model. Int J Numer Meth Fluids, 2007, 55(2): 143–161

    Article  MATH  MathSciNet  Google Scholar 

  23. Luo Z D, Du J, Xie Z H, Guo Y. A reduced stabilized mixed finite element formulation based on proper orthogonal decomposition for the no-stationary Navier-Stokes equations. Int J Numer Meth Eng, 2011, 88(1): 31–46

    Article  MATH  MathSciNet  Google Scholar 

  24. Luo Z D, Li H, Zhou Y J, Huang X M. A reduced FVE formulation based on POD method and error analysis for two-dimensional viscoelastic problem. J Math Anal Appl, 2012, 385: 310–321

    Article  MATH  MathSciNet  Google Scholar 

  25. Luo Z D, Li H, Zhou Y J, Xie Z H. A reduced finite element formulation and error estimates based on POD method for two-dimensional solute transport problems. J Math Anal Appl, 2012, 385: 371–383

    Article  MATH  MathSciNet  Google Scholar 

  26. Luo Z D, Ou Q L, Xie Z X. A reduced finite difference scheme and error estimates based on POD method for the non-stationary Stokes equation. Appl Math Mech, 2011, 32(7): 847–858

    Article  MATH  MathSciNet  Google Scholar 

  27. Luo Z D, Wang R W, Zhu J. Finite difference scheme based on proper orthogonal decomposition for the non-stationary Navier-Stokes equations. Sci China Ser A: Math, 2007, 50(8): 1186–1196

    Article  MATH  MathSciNet  Google Scholar 

  28. Luo Z D, Xie Z H, Chen J. A reduced MFE formulation based on POD for the nonstationary conduction-convection problems. Acta Math Sci Ser B Engl Ed, 2011, 31(5): 1765–1785

    MATH  MathSciNet  Google Scholar 

  29. Luo Z D, Xie Z H, Shang Y Q, Chen J. A reduced finite volume element formulation and numerical simulations based on POD for parabolic equations. J Comput Appl Math, 2011, 235(8): 2098–2111

    Article  MATH  MathSciNet  Google Scholar 

  30. Luo Z D, Yang X Z, Zhou Y J. A reduced finite difference scheme based on singular value decomposition and proper orthogonal decomposition for Burgers equation. J Comput Appl Math, 2009, 229(1): 97–107

    Article  MATH  MathSciNet  Google Scholar 

  31. Luo Z D, Zhou Y J, Yang X Z. A reduced finite element formulation based on proper orthogonal decomposition for Burgers equation. Appl Numer Math, 2009, 59(8): 1933–1946

    Article  MATH  MathSciNet  Google Scholar 

  32. Luo Z D, Zhu J, Wang R W, Navon I M. Proper orthogonal decomposition approach and error estimation of mixed finite element methods for the tropical Pacific Ocean reduced gravity model. Comput Meth Appl Mech Eng, 2007, 196(41–44): 4184–4195

    Article  MATH  MathSciNet  Google Scholar 

  33. Rajaee M, Karlsson S K F, Sirovich L. Low dimensional description of free sheer flow coherent structures and their dynamical behavior. J Fluid Mech, 1994, 258: 1401–1402

    Article  Google Scholar 

  34. Selten F. Baroclinic empirical orthogonal functions as basis functions in an atmospheric model. J Atmospheric Sci, 1997, 54: 2100–2114

    Google Scholar 

  35. Shvartsman S, Kevrekisis I. Low-dimensional approximation and control of periodic solutions in spatially extended systems. Phys Rev E, 1998, 58(3): 361–368

    Article  Google Scholar 

  36. Sirovich L. Turbulence and the dynamics of coherent sructures: part I–III. Quart Appl Math, 1987, 45(3): 561–590

    MATH  MathSciNet  Google Scholar 

  37. Sun P, Luo Z D, Zhou Y J. Some reduced finite difference schemes based on a proper orthogonal decomposition technique for parabolic equations. Appl Numer Math, 2010, 60(1–2): 154–164

    Article  MATH  MathSciNet  Google Scholar 

  38. Trefethen L N. Spectral Method in MATLAB. Philadephia: SIAM, 2000

    Book  Google Scholar 

  39. Trültzsch F, Volkwein S. POD a-posteriori error estimates for linear-quadratic optimal control problems. Comput Optim Appl, 2009, 44(1): 83–115

    Article  MathSciNet  Google Scholar 

  40. Weideman J A C, Reddy S C. A Matlab differentiation matrix suite. ACM Trans Math Software, 2000, 26: 465–511

    Article  MathSciNet  Google Scholar 

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An, J., Luo, Z., Li, H. et al. Reduced-order extrapolation spectral-finite difference scheme based on POD method and error estimation for three-dimensional parabolic equation. Front. Math. China 10, 1025–1040 (2015). https://doi.org/10.1007/s11464-015-0469-8

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  • DOI: https://doi.org/10.1007/s11464-015-0469-8

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