We consider a finite element discretization for the reconstruction of the final state of the heat equation, when the initial data is unknown, but additional data is given in a sub domain in the space time. For the discretization in space we consider standard continuous affine finite element approximation, and the time derivative is discretized using a backward differentiation. We regularize the discrete system by adding a penalty on the H2-semi-norm of the initial data, scaled with the mesh-parameter. The analysis of the method uses techniques developed in E. Burman and L. Oksanen [Numer. Math. 139 (2018) 505–528], combining discrete stability of the numerical method with sharp Carleman estimates for the physical problem, to derive optimal error estimates for the approximate solution. For the natural space time energy norm, away from t = 0, the convergence is the same as for the classical problem with known initial data, but contrary to the classical case, we do not obtain faster convergence for the L2-norm at the final time.
Accepté le :
DOI : 10.1051/m2an/2018030
Mots clés : Heat equation, inverse problem, data assimilation, stabilized finite elements
@article{M2AN_2018__52_5_2065_0, author = {Burman, Erik and Ish-Horowicz, Jonathan and Oksanen, Lauri}, title = {Fully discrete finite element data assimilation method for the heat equation}, journal = {ESAIM: Mathematical Modelling and Numerical Analysis }, pages = {2065--2082}, publisher = {EDP-Sciences}, volume = {52}, number = {5}, year = {2018}, doi = {10.1051/m2an/2018030}, mrnumber = {3893359}, zbl = {1420.65124}, language = {en}, url = {http://www.numdam.org/articles/10.1051/m2an/2018030/} }
TY - JOUR AU - Burman, Erik AU - Ish-Horowicz, Jonathan AU - Oksanen, Lauri TI - Fully discrete finite element data assimilation method for the heat equation JO - ESAIM: Mathematical Modelling and Numerical Analysis PY - 2018 SP - 2065 EP - 2082 VL - 52 IS - 5 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/m2an/2018030/ DO - 10.1051/m2an/2018030 LA - en ID - M2AN_2018__52_5_2065_0 ER -
%0 Journal Article %A Burman, Erik %A Ish-Horowicz, Jonathan %A Oksanen, Lauri %T Fully discrete finite element data assimilation method for the heat equation %J ESAIM: Mathematical Modelling and Numerical Analysis %D 2018 %P 2065-2082 %V 52 %N 5 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/m2an/2018030/ %R 10.1051/m2an/2018030 %G en %F M2AN_2018__52_5_2065_0
Burman, Erik; Ish-Horowicz, Jonathan; Oksanen, Lauri. Fully discrete finite element data assimilation method for the heat equation. ESAIM: Mathematical Modelling and Numerical Analysis , Tome 52 (2018) no. 5, pp. 2065-2082. doi : 10.1051/m2an/2018030. http://www.numdam.org/articles/10.1051/m2an/2018030/
[1] A review of forecast error covariance statistics in atmospheric variational data assimilation. II: modelling the forecast error covariance statistics. Quaterly J. Roy. Meteorol. Soc. 134 (2008) 1971–1996. | DOI
,[2] Application of mixed formulations of quasi-reversibility to solve ill-posed problems for heat and wave equations: the 1D case. Inverse Probl. Imaging 9 (2015) 971–1002. | DOI | MR | Zbl
, , and ,[3] Uniform controllability properties for space/time-discretized parabolic equations. Numer. Math. 118 (2011) 601–661. | DOI | MR | Zbl
, and ,[4] Stabilized finite element methods for nonsymmetric, noncoercive, and ill-posed problems. Part I: Elliptic equations. SIAM J. Sci. Comput. 35 (2013) A2752–A2780. | DOI | MR | Zbl
,[5] Error estimates for stabilized finite element methods applied to ill-posed problems. C. R. Math. Acad. Sci. Paris 352 (2014) 655–659. | DOI | MR | Zbl
,[6] Stabilised finite element methods for ill-posed problems with conditional stability, in Building Bridges: Connections and Challenges in Modern Approaches to Numerical Partial Differential Equations. Vol. 114 of Lect. Notes Comput. Sci. Eng. Springer, Cham (2016) 93–127. | MR | Zbl
,[7] Data Assimilation for the Heat Equation Using Stabilized Finite Element Methods. Numer. Math. 139 (2016) 505–528. | DOI | MR | Zbl
and ,[8] Solving ill-Posed Control Problems by Stabilized Finite Element Methods: An Alternative to Tikhonov Regularization. Technical report (2016) | MR
, and ,[9] Controllability of the linear one-dimensional wave equation with inner moving forces. SIAM J. Control Optim. 52 (2014) 4027–4056. | DOI | MR | Zbl
, and ,[10] Inverse problems for linear hyperbolic equations using mixed formulations. Inverse Probl. 31 (2015) 075001. | DOI | MR | Zbl
and ,[11] A mixed formulation for the direct approximation of the control of minimal L2-norm for linear type wave equations. Calcolo 52 (2015) 245–288. | DOI | MR | Zbl
and ,[12] Simultaneous reconstruction of the solution and the source of hyperbolic equations from boundary measurements: a robust numerical approach. Inverse Probl. 32 (2016) 115020. | DOI | MR | Zbl
and ,[13] Numerical controllability of the wave equation through primal methods and Carleman estimates. ESAIM: COCV. 19 (2013) 1076–1108. | Numdam | MR | Zbl
, and ,[14] A strategy for operational implementation of 4D-Var, using an incremental approach. Quaterly J. Roy. Meteorol.Soc. 120 (1994) 1367–1387.
et al.,[15] Controllability of parabolic equations. Mat. Sb. 186 (1995) 109–132. | MR | Zbl
,[16] Theory and Practice of Finite Elements. Vol. 159 of Applied Mathematical Sciences. New York (2004). | DOI | MR | Zbl
and ,[17] Inverse Problems For Partial Differential Equations, 2nd edn. Vol. 127 of Applied Mathematical Sciences. Springer, New York (2006). | MR | Zbl
,[18] The effect of numerical model error on data assimilation. J. Comput. Appl. Math. 290 (2015) 567–588. | DOI | MR | Zbl
, , and ,[19]
, , et al., SciPy: open source scientific tools for python (2001). Online; version 0.19.1 [accessed 19/07/17].[20] Estimates of initial conditions of parabolic equations and inequalities via lateral Cauchy data. Inverse Probl. 22 (2006) 495–514. | DOI | MR | Zbl
,[21] Carleman estimates for global uniqueness, stability and numerical methods for coefficient inverse problems. J. Inverse Ill-Posed Probl. 21 (2013) 477–560. | DOI | MR | Zbl
,[22] Carleman estimates for the regularization of ill-posed Cauchy problems. Appl. Numer. Math. 94 (2015) 46–74. | DOI | MR | Zbl
,[23] Solution of coefficient inverse problems by the method of quasi-reversibility. Dokl. Akad. Nauk SSSR 310 (1990) 528–532. | MR | Zbl
and ,[24] Méthode de quasi-réversibilité et applications. Travaux et Recherches Mathématiques, No. 15. Dunod, Paris (1967). | MR | Zbl
and ,[25] Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects. Tellus A 38 (1986) 97–110. | DOI
and ,[26] Équations différentielles opérationnelles et problèmes aux limites. Die Grundlehren der mathematischen Wissenschaften, Bd.111, Springer-Verlag, Berlin-Göttingen-Heidelberg (1961). | MR | Zbl
,[27] A mixed formulation for the direct approximation of L2-weighted controls for the linear heat equation. Adv. Comput. Math. 42 (2016) 85–125. | DOI | MR | Zbl
and ,[28] Solutions of sparse indefinite systems of linear equations. SIAM J. Numer. Anal. 12 (1975) 617–629. | DOI | MR | Zbl
and ,[29] Some basic formalisms in numerical variational analysis. Mon. Weather Rev. 98 (1970). | DOI
,[30] An inversion method for parabolic equations based on quasireversibility. Comput. Math. Appl. 43 (2002) 927–941. | DOI | MR | Zbl
, and ,[31] Initialisation d’un modèle numérique d’atmosphère à partir de données distribuées dans le temps, in Computing Methods in Applied Sciences and Engineering, in Proc. Third Internat. Sympos., Versailles, 1977, II. Vol. 91 of Lecture Notes in Physics. Springer, Berlin-New York (1979) 217–231. | MR | Zbl
,[32] On the mathematics of data assimilation. Tellus 33 (1981) 321–339. | DOI | MR
,[33] Variational assimilation of meteorological observations with the adjoint vorticity equation. i: theory. Q. J. Royal Meteorol. Soc. 113 (1987) 1311–1328. | DOI
and ,[34] Galerkin Finite Element Methods for Parabolic Problems. Vol. 25 of Springer Series in Computational Mathematics. Springer-Verlag, Berlin (1997). | MR | Zbl
,[35] A numerical method for solving the inverse heat conduction problem without initial value. Inverse Probl. Sci. Eng. 18 (2010) 655–671. | DOI | MR | Zbl
, , and[36] Carleman estimates for parabolic equations and applications. Inverse Probl. 25 123013 (2009). | DOI | MR | Zbl
,Cité par Sources :