Analyticity, regularity, and generalized polynomial chaos approximation of stochastic, parametric parabolic two-scale partial differential equations

We study two-scale parabolic partial differential equations whose coefficient is stochastic and depends linearly on a sequence of pairwise independent random variables which are uniformly distributed in a compact interval. We cast the problem into a deterministic two-scale parabolic problem which de...

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Main Author: Hoang, Viet Ha
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/155098
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1550982022-02-11T07:17:50Z Analyticity, regularity, and generalized polynomial chaos approximation of stochastic, parametric parabolic two-scale partial differential equations Hoang, Viet Ha School of Physical and Mathematical Sciences Science::Mathematics Stochastic Parabolic Two-Scale Pdes Generalized Polynomial Chaos Approximation We study two-scale parabolic partial differential equations whose coefficient is stochastic and depends linearly on a sequence of pairwise independent random variables which are uniformly distributed in a compact interval. We cast the problem into a deterministic two-scale parabolic problem which depends on a sequence of real parameters in a compact interval. Passing to the limit when the microscale tends to zero, using two-scale homogenization, we obtain the parametric two-scale homogenized problem. This problem contains the solution to the homogenized equation which describes the solution to the original two-scale parabolic problem macroscopically, and the corrector which encodes the microscopic information. The solution of this two-scale homogenized equation is represented as a generalized polynomial chaos (gpc) expansion according to a polynomial basis of the L2 space of the parameters. We use a semidiscrete Galerkin approximation which projects the solution into a space of parametric functions which contain a finite number of pre-chosen gpc modes. Analyticity of the solution of the two-scale homogenized equation with respect to the parameters is established. Under mild assumptions, we show the summability of the coefficients of the solution’s gpc expansion. From this, an explicit error estimate for the semidiscrete Galerkin approximation in terms of the number of the chosen gpc modes is derived when these gpc modes are chosen as the N best ones according to the norms of the gpc coefficients. Regularity of the gpc coefficients and summability of their norms in the regularity spaces are also established. Using the solution of the best N term semidiscrete Galerkin approximation, we derive an approximation for the solution of the original two-scale problem, with an explicit convergence rate in terms of the microscopic scale and the number of gpc modes in the Galerkin approximation. Ministry of Education (MOE) The research is supported by the Singapore MOE AcRF Tier 1 grant RG30/16 and the MOE Tier 2 grant MOE2017-T2-2-144. 2022-02-11T07:17:50Z 2022-02-11T07:17:50Z 2020 Journal Article Hoang, V. H. (2020). Analyticity, regularity, and generalized polynomial chaos approximation of stochastic, parametric parabolic two-scale partial differential equations. Acta Mathematica Vietnamica, 45(1), 217-247. https://dx.doi.org/10.1007/s40306-019-00345-2 0251-4184 https://hdl.handle.net/10356/155098 10.1007/s40306-019-00345-2 2-s2.0-85070785764 1 45 217 247 en RG30/16 MOE2017-T2-2-144 Acta Mathematica Vietnamica © 2019 Institute of Mathematics, Vietnam Academy of Science and Technology (VAST) and Springer Nature Singapore Pte Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Mathematics
Stochastic Parabolic Two-Scale Pdes
Generalized Polynomial Chaos Approximation
spellingShingle Science::Mathematics
Stochastic Parabolic Two-Scale Pdes
Generalized Polynomial Chaos Approximation
Hoang, Viet Ha
Analyticity, regularity, and generalized polynomial chaos approximation of stochastic, parametric parabolic two-scale partial differential equations
description We study two-scale parabolic partial differential equations whose coefficient is stochastic and depends linearly on a sequence of pairwise independent random variables which are uniformly distributed in a compact interval. We cast the problem into a deterministic two-scale parabolic problem which depends on a sequence of real parameters in a compact interval. Passing to the limit when the microscale tends to zero, using two-scale homogenization, we obtain the parametric two-scale homogenized problem. This problem contains the solution to the homogenized equation which describes the solution to the original two-scale parabolic problem macroscopically, and the corrector which encodes the microscopic information. The solution of this two-scale homogenized equation is represented as a generalized polynomial chaos (gpc) expansion according to a polynomial basis of the L2 space of the parameters. We use a semidiscrete Galerkin approximation which projects the solution into a space of parametric functions which contain a finite number of pre-chosen gpc modes. Analyticity of the solution of the two-scale homogenized equation with respect to the parameters is established. Under mild assumptions, we show the summability of the coefficients of the solution’s gpc expansion. From this, an explicit error estimate for the semidiscrete Galerkin approximation in terms of the number of the chosen gpc modes is derived when these gpc modes are chosen as the N best ones according to the norms of the gpc coefficients. Regularity of the gpc coefficients and summability of their norms in the regularity spaces are also established. Using the solution of the best N term semidiscrete Galerkin approximation, we derive an approximation for the solution of the original two-scale problem, with an explicit convergence rate in terms of the microscopic scale and the number of gpc modes in the Galerkin approximation.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Hoang, Viet Ha
format Article
author Hoang, Viet Ha
author_sort Hoang, Viet Ha
title Analyticity, regularity, and generalized polynomial chaos approximation of stochastic, parametric parabolic two-scale partial differential equations
title_short Analyticity, regularity, and generalized polynomial chaos approximation of stochastic, parametric parabolic two-scale partial differential equations
title_full Analyticity, regularity, and generalized polynomial chaos approximation of stochastic, parametric parabolic two-scale partial differential equations
title_fullStr Analyticity, regularity, and generalized polynomial chaos approximation of stochastic, parametric parabolic two-scale partial differential equations
title_full_unstemmed Analyticity, regularity, and generalized polynomial chaos approximation of stochastic, parametric parabolic two-scale partial differential equations
title_sort analyticity, regularity, and generalized polynomial chaos approximation of stochastic, parametric parabolic two-scale partial differential equations
publishDate 2022
url https://hdl.handle.net/10356/155098
_version_ 1724626871454269440