Probabilistic modelling of heterogeneous materials based on image analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F14%3A00223509" target="_blank" >RIV/68407700:21110/14:00223509 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.esco2014.femhub.com/docs/ESCO2014_Book_of_Abstracts.pdf" target="_blank" >http://www.esco2014.femhub.com/docs/ESCO2014_Book_of_Abstracts.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Probabilistic modelling of heterogeneous materials based on image analysis

Popis výsledku v původním jazyce

Macroscopically heterogeneous materials, characterized mostly by comparable heterogeneity lengthscale and structural sizes, can no longer be modelled by deterministic approach. It is convenient to introduce stochastic approach with uncertain material parameters quantified as random fields. Nevertheless, introduction of random fields brings higher demands on quality of input data, especially on inputs of covariance kernels representing the spatial randomness. The present contribution is devoted to the construction of random fields based on image analysis utilizing statistical descriptors, which were developed to describe the different morphology structure of multi-phase random material. The whole concept is demonstrated on a simple numerical example ofheat conduction where interesting phenomena can be clearly understood.

Název v anglickém jazyce

Probabilistic modelling of heterogeneous materials based on image analysis

Popis výsledku anglicky

Macroscopically heterogeneous materials, characterized mostly by comparable heterogeneity lengthscale and structural sizes, can no longer be modelled by deterministic approach. It is convenient to introduce stochastic approach with uncertain material parameters quantified as random fields. Nevertheless, introduction of random fields brings higher demands on quality of input data, especially on inputs of covariance kernels representing the spatial randomness. The present contribution is devoted to the construction of random fields based on image analysis utilizing statistical descriptors, which were developed to describe the different morphology structure of multi-phase random material. The whole concept is demonstrated on a simple numerical example ofheat conduction where interesting phenomena can be clearly understood.

Druh

O - Ostatní výsledky

CEP obor

JM - Inženýrské stavitelství

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů