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Dokumenttyp:
Konferenzbeitrag 
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz 
Autor(en):
Grigo, Constantin; Koutsourelakis, P.-S. 
Titel:
Probabilistic Reduced-Order Modeling for Stochastic Partial Differential Equations 
Seitenangaben Beitrag:
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...    »
 
Stichworte:
Reduced-order modeling, generative Bayesian model, SPDE, effective material properties 
Kongress- / Buchtitel:
UNCECOMP 17 
Kongress / Zusatzinformationen:
2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering 
Ausrichter der Konferenz:
Eccomas Thematic Conferences 
Konferenzort:
Rhodes Island, Greece 
Datum der Konferenz:
15 - 17 June 2017 
Jahr:
2017 
Reviewed:
ja 
Sprache:
en 
Erscheinungsform:
WWW 
WWW:
TUM Einrichtung:
Continuum Mechanics Group, Department of Mechanical Engineering 
Format:
Text