This paper proposes to address the issue of complexity reduction for the numerical simulation of multiscale media in a quasi-periodic setting. We consider a stationary elliptic diffusion equation defined on a domain such that is the union of cells and we introduce a two-scale representation by identifying any function defined on with a bi-variate function , where relates to the index of the cell containing the point and relates to a local coordinate in a reference cell . We introduce a weak formulation of the problem in a broken Sobolev space using a discontinuous Galerkin framework. The problem is then interpreted as a tensor-structured equation by identifying with a tensor product space of functions defined over the product set . Tensor numerical methods are then used in order to exploit approximability properties of quasi-periodic solutions by low-rank tensors.
Mots clés : Quasi-periodicity, tensor approximation, discontinuous Galerkin, multiscale, heterogeneous diffusion
@article{M2AN_2018__52_3_869_0, author = {Ayoul-Guilmard, Quentin and Nouy, Anthony and Binetruy, Christophe}, title = {Tensor-based multiscale method for diffusion problems in quasi-periodic heterogeneous media}, journal = {ESAIM: Mathematical Modelling and Numerical Analysis }, pages = {869--891}, publisher = {EDP-Sciences}, volume = {52}, number = {3}, year = {2018}, doi = {10.1051/m2an/2018022}, mrnumber = {3865552}, zbl = {1407.65279}, language = {en}, url = {http://www.numdam.org/articles/10.1051/m2an/2018022/} }
TY - JOUR AU - Ayoul-Guilmard, Quentin AU - Nouy, Anthony AU - Binetruy, Christophe TI - Tensor-based multiscale method for diffusion problems in quasi-periodic heterogeneous media JO - ESAIM: Mathematical Modelling and Numerical Analysis PY - 2018 SP - 869 EP - 891 VL - 52 IS - 3 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/m2an/2018022/ DO - 10.1051/m2an/2018022 LA - en ID - M2AN_2018__52_3_869_0 ER -
%0 Journal Article %A Ayoul-Guilmard, Quentin %A Nouy, Anthony %A Binetruy, Christophe %T Tensor-based multiscale method for diffusion problems in quasi-periodic heterogeneous media %J ESAIM: Mathematical Modelling and Numerical Analysis %D 2018 %P 869-891 %V 52 %N 3 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/m2an/2018022/ %R 10.1051/m2an/2018022 %G en %F M2AN_2018__52_3_869_0
Ayoul-Guilmard, Quentin; Nouy, Anthony; Binetruy, Christophe. Tensor-based multiscale method for diffusion problems in quasi-periodic heterogeneous media. ESAIM: Mathematical Modelling and Numerical Analysis , Tome 52 (2018) no. 3, pp. 869-891. doi : 10.1051/m2an/2018022. http://www.numdam.org/articles/10.1051/m2an/2018022/
[1] Reduced basis finite element heterogeneous multiscale method for high-order discretizations of elliptic homogenization problems. J. Comput. Phys. 231 (2012) 7014–7036. | DOI | MR | Zbl
and ,[2] The heterogeneous multiscale method. Acta Numer. 21 (2012). | DOI | MR | Zbl
, , and ,[3] A multiscale finite element method for numerical homogenization. Multiscale Model. Simul. 4 (2005) 790–812. | DOI | MR | Zbl
and ,[4] Introduction to Numerical Stochastic Homogenization 311 and the Related Computational Challenges: Some Recent Developments, Vol. 22. World Scientific, Singapore (2011). | MR
, , , and ,[5] Corrector theory for MsFEM and HMM in random media. Multiscale Model. Simul. 9 (2011) 1549–1587. | DOI | MR | Zbl
, and ,[6] Une variante de la théorie de l’homogénéisation stochastique des opérateurs elliptiques. C. R. Math. 343 (2006) 717–724. | DOI | MR | Zbl
, and ,[7] Variance reduction in stochastic homogenization using antithetic variables. Markov Processes Relat. Fields 66 (2012) 31–66. | MR | Zbl
, , and ,[8] Reduced-basis approach for homogenization beyond the periodic setting. Multiscale Model. Simul. 7 (2008). | DOI | MR | Zbl
,[9] A multiscale method with patch for the solution of stochastic partial differential equationswith localized uncertainties. Comput. Methods Appl. Mech. Eng. 255 (2013) 255–274. | DOI | MR | Zbl
, and ,[10] Mathematical Aspects of Discontinuous Galerkin Methods, Vol. 69. Springer Science & Business Media (2011). | MR | Zbl
and ,[11] Heterogeneous multiscale methods: a review. Commun. Comput. Phys. 2 (2007) 367–450. | MR | Zbl
, , , and ,[12] Multiscale Finite Element Methods. Surveys and Tutorials in the Applied Mathematical Sciences. Springer, New York, NY (2009). | MR | Zbl
and ,[13] Estimation of penalty parameters for symmetric interior penalty Galerkin methods. J. Comput. Appl. Math. 206 (2007) 843–872. | DOI | MR | Zbl
and ,[14] Theory and Practice of Finite Elements. Applied Mathematical Sciences. Springer, New York (2004). | DOI | MR | Zbl
and ,[15] Partial Differential Equations. Graduate Studies in Mathematics. American Mathematical Society (1998). | MR | Zbl
,[16] Proper generalized decomposition for nonlinear convex problems in tensor Banach spaces. Numer. Math. 121 (2012) 503–530. | DOI | MR | Zbl
and ,[17] A two-scale approximation of the Schur complement and its use for non-intrusive coupling. Int. J. Numer. Methods Eng. 87 (2011) 889–905. | DOI | MR | Zbl
, and ,[18] Approximation of multi-scale elliptic problems using patches of finite elements. C. R. Math. 337 (2003) 679–684. | DOI | MR | Zbl
, , and ,[19] A literature survey of low-rank tensor approximation techniques. GAMM-Mitteilungen 36 (2013) 53–78. | DOI | MR | Zbl
, and ,[20] Tensor Spaces and Numerical Tensor Calculus. Vol. 42 of Springer Series in Computational Mathematics. Springer, Heidelberg (2012). | MR | Zbl
,[21] High-dimensional finite elements for elliptic problems with multiple scales. Multiscale Model. Simul. 3 (2005). | MR | Zbl
and ,[22] A multiscale finite element method for elliptic problems in composite materials and porous media. J. Comput. Phys. 134 (1997) 169–189. | DOI | MR | Zbl
and ,[23] Tensors-structured numerical methods in scientific computing: survey on recent advances. Chemom. Intell. Lab. Syst. 110 (2012) 1–19. | DOI
,[24] Some numerical approaches for weakly random homogenization, in Numerical Mathematics and Advanced Applications, edited by , , and Springer, Berlin, Heidelberg (2009) 29–45. | Zbl
,[25] Special quasirandom structures: a selection approach for stochastic homogenization. Monte Carlo Methods Appl. 22 (2016) 25–54. | DOI | MR | Zbl
, and ,[26] Multiscale finite element approach for “weakly” random problems and related issues. ESAIM: M2AN 48 (2014) 815–858. | DOI | Numdam | MR | Zbl
, and ,[27] A reduced basis approach for some weakly stochastic multiscale problems. Chin. Ann. Math. Ser. B 33 (2012) 657–672. | DOI | MR | Zbl
and ,[28] A control variate approach based on a defect-type theory for variance reduction in stochastic homogenization. Multiscale Model. Simul. 13 (2015). | DOI | MR | Zbl
and ,[29] Variance reduction using antithetic variables for a nonlinear convex stochastic homogenization problem. Discrete Contin. Dyn. Syst. Ser. S 8 (2015) 1–27. | MR | Zbl
and ,[30] A posteriori error estimates for discontinuous Galerkin methods using non-polynomial basis functions. Part I: Second order linear PDE. ESAIM: M2AN 50 (2016) 1193–1222. | DOI | Numdam | MR | Zbl
and ,[31] Reduced basis method for the rapid and reliable solution of partial differential equations, in International Congress of Mathematicians, Madrid. European Mathematical Society (2006). 1255–1270. | MR | Zbl
,[32] A general multipurpose interpolation procedure: the magic points. Commun. Pure Appl. Anal. 8 (2009) 383–404. | DOI | MR | Zbl
, , and ,[33] Low-rank methods for high-dimensional approximation and model order reduction, in Chapter 4 of Model Reduction and Approximation. SIAM (2017) 171–226. | DOI | MR
,[34] Domain decomposition methods for CAD. C. R. Acad. Sci. Ser. I – Math. 328 (1999) 73–80. | MR | Zbl
and ,[35] Multiscale algorithm with patches of finite elements. Math. Comput. Simul. 76 (2007) 181–187. | DOI | MR | Zbl
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