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Document type:
Konferenzbeitrag 
Contribution type:
Textbeitrag / Aufsatz 
Author(s):
Grigo, Constantin; Koutsourelakis, P.-S. 
Title:
Probabilistic Reduced-Order Modeling for Stochastic Partial Differential Equations 
Pages contribution:
19 
Abstract:
We discuss a Bayesian formulation to coarse-graining (CG) of PDEs where the coefficients (e.g. material parameters) exhibit random, fine scale variability. The direct solution to such problems requires grids that are small enough to resolve this fine scale variability which unavoidably requires the repeated solution of very large systems of algebraic equations. We establish a physically inspired, data-driven coarse-grained model which learns a low- dimensional set of microstructural fe...    »
 
Keywords:
Reduced-order modeling, generative Bayesian model, SPDE, effective material properties 
Book / Congress title:
UNCECOMP 17 
Congress (additional information):
2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering 
Organization:
Eccomas Thematic Conferences 
Date of congress:
15 - 17 June 2017 
Year:
2017 
Reviewed:
ja 
Language:
en 
Publication format:
WWW 
WWW:
TUM Institution:
Continuum Mechanics Group, Department of Mechanical Engineering 
Format:
Text