2,240 research outputs found
The Periodic Unfolding Method in Homogenization
International audienceThe periodic unfolding method was introduced in 2002 in [Cioranescu, Damlamian, and Griso, C. R. Acad. Sci. Paris, Ser. 1, 335 (2002), pp. 99-104] (with the basic proofs in [Proceedings of the Narvik Conference 2004, GAKUTO Internat. Ser. Math. Sci. Appl. 24, Gakkotosho, Tokyo, 2006, pp. 119-136]). In the present paper we go into all the details of the method and include complete proofs, as well as several new extensions and developments. This approach is based on two distinct ideas, each leading to a new ingredient. The first idea is the change of scale, which is embodied in the unfolding operator. At the expense of doubling the dimension, this allows one to use standard weak or strong convergence theorems in L(p) spaces instead of more complicated tools (such as two-scale convergence, which is shown to be merely the weak convergence of the unfolding; cf. Remark 2.15). The second idea is the separation of scales, which is implemented as a macro-micro decomposition of functions and is especially suited for the weakly convergent sequences of Sobolev spaces. In the framework of this method, the proofs of most periodic homogenization results are elementary. The unfolding is particularly well-suited for multiscale problems (a simple backward iteration argument suffices) and for precise corrector results without extra regularity on the data. A list of the papers where these ideas appeared, at least in some preliminary form, is given with a discussion of their content. We also give a list of papers published since the publication [Cioranescu, Damlamian, and Griso, C. R. Acad. Sci. Paris, Ser. 1, 335 (2002), pp. 99-104], and where the unfolding method has been successfully applied
Stochastic unfolding and homogenization
The notion of periodic two-scale convergence and the method of periodic unfolding are prominent and useful tools in multiscale modeling and analysis of PDEs with rapidly oscillating periodic coefficients. In this paper we are interested in the theory of stochastic homogenization for continuum mechanical models in form of PDEs with random coefficients, describing random heterogeneous materials. The notion of periodic two-scale convergence has been extended in different ways to the stochastic case. In this work we introduce a stochastic unfolding method that features many similarities to periodic unfolding. In particular it allows to characterize the notion of stochastic two-scale convergence in the mean by mere convergence in an extended space. We illustrate the method on the (classical) example of stochastic homogenization of convex integral functionals, and prove a stochastic homogenization result for an non-convex evolution equation of Allen-Cahn type. Moreover, we discuss the relation of stochastic unfolding to previously introduced notions of (quenched and mean) stochastic two-scale convergence. The method introduced in this paper extends extitdiscrete stochastic unfolding, as recently introduced by the second and third author in the context of discrete-to-continuum transition
Stochastic homogenization of -convex gradient flows
In this paper we present a stochastic homogenization result for a class of
Hilbert space evolutionary gradient systems driven by a quadratic dissipation
potential and a -convex energy functional featuring random and rapidly
oscillating coefficients. Specific examples included in the result are
Allen-Cahn type equations and evolutionary equations driven by the -Laplace
operator with . The homogenization procedure we apply is based
on a stochastic two-scale convergence approach. In particular, we define a
stochastic unfolding operator which can be considered as a random counterpart
of the well-established notion of periodic unfolding. The stochastic unfolding
procedure grants a very convenient method for homogenization problems defined
in terms of (-)convex functionals.Comment: arXiv admin note: text overlap with arXiv:1805.0954
Stochastic unfolding and homogenization
The notion of periodic two-scale convergence and the method of periodic
unfolding are prominent and useful tools in multiscale modeling and analysis of
PDEs with rapidly oscillating periodic coefficients. In this paper we are
interested in the theory of stochastic homogenization for continuum mechanical
models in form of PDEs with random coefficients, describing random
heterogeneous materials. The notion of periodic two-scale convergence has been
extended in different ways to the stochastic case. In this work we introduce a
stochastic unfolding method that features many similarities to periodic
unfolding. In particular it allows to characterize the notion of stochastic
two-scale convergence in the mean by mere weak convergence in an extended
space. We illustrate the method on the (classical) example of stochastic
homogenization of convex integral functionals, and prove a new result on
stochastic homogenization for a non-convex evolution equation of Allen-Cahn
type. Moreover, we discuss the relation of stochastic unfolding to previously
introduced notions of (quenched and mean) stochastic two-scale convergence. The
method described in the present paper extends to the continuum setting the
notion of discrete stochastic unfolding, as recently introduced by the second
and third author in the context of discrete-to-continuum transition.Comment: 46 page
HOMOGENIZATION OF A NON-PERIODIC OSCILLATING BOUNDARY VIA PERIODIC UNFOLDING
This paper deals with the homogenization of an elliptic model problem in a two-dimensional domain with non-periodic oscillating boundary by the method of periodic unfolding. For the non-periodic oscillations, a modulated unfolding is used. The L-2 convergence of the solutions and their fluxes are shown, under natural hypotheses on the domain
Stochastic unfolding and homogenization
The notion of periodic two-scale convergence and the method of periodic un- folding are prominent and useful tools in multiscale modeling and analysis of PDEs with rapidly oscillating periodic coe cients. In this paper we are interested in the theory of stochastic homogenization for continuum mechanical models in form of PDEs with random coe cients, describing random heterogeneous materials. The notion of periodic two-scale convergence has been extended in di erent ways to the stochastic case. In this work we introduce a stochastic unfolding method that fea- tures many similarities to periodic unfolding. In particular it allows to characterize the notion of stochastic two-scale convergence in the mean by mere convergence in an extended space. We illustrate the method on the (classical) example of stochastic homogenization of convex integral functionals, and prove a stochastic homogeniza- tion result for an non-convex evolution equation of Allen-Cahn type. Moreover, we discuss the relation of stochastic unfolding to previously introduced notions of (quenched and mean) stochastic two-scale convergence. The method descibed in the present paper extends to the continuum setting the notion of discrete stochastic unfolding, as recently introduced by the second and third author in the context of discrete-to-continuum transition
Stochastic unfolding and homogenization of evolutionary gradient systems
The mathematical theory of homogenization deals with the rigorous derivation of effective models from partial differential equations with rapidly-oscillating coefficients. In this thesis we deal with modeling and homogenization of random heterogeneous media. Namely, we obtain stochastic homogenization results for certain evolutionary gradient systems. In particular, we derive continuum effective models from discrete networks consisting of elasto-plastic springs with random coefficients in the setting of evolutionary rate-independent systems. Also, we treat a discrete counterpart of gradient plasticity. The second type of problems that we consider are gradient flows. Specifically, we study continuum gradient flows driven by λ-convex energy functionals. In stochastic homogenization the derived deterministic effective equations are typically hardly-accessible for standard numerical methods. For this reason, we study approximation schemes for the effective equations that we obtain, which are well-suited for numerical analysis. For the sake of a simple treatment of these problems, we introduce a general procedure for stochastic homogenization â the stochastic unfolding method. This method presents a stochastic counterpart of the well-established periodic unfolding procedure which is well-suited for homogenization of media with periodic microstructure. The stochastic unfolding method is convenient for the treatment of equations driven by integral functionals with random integrands. The advantage of this strategy in regard to other methods in homogenization is its simplicity and the elementary analysis that mostly relies on basic functional analysis concepts, which makes it an easily accessible method for a wide audience. In particular, we develop this strategy in the setting that is suited for problems involving discrete-to-continuum transition as well as for equations defined on a continuum physical space. We believe that the stochastic unfolding method may also be useful for problems outside of the scope of this work
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