Bayesian inference as a tool for improving estimates of effective elastic parameters of wood

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F19%3A00331211" target="_blank" >RIV/68407700:21110/19:00331211 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.compstruc.2019.03.006" target="_blank" >https://doi.org/10.1016/j.compstruc.2019.03.006</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.compstruc.2019.03.006" target="_blank" >10.1016/j.compstruc.2019.03.006</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Bayesian inference as a tool for improving estimates of effective elastic parameters of wood

Popis výsledku v původním jazyce

A simple approach to the identification of geometrical and material uncertainties of wood is presented.This stochastic mechanics problem combines classical micromechanics, computational homogenization and experimental measurements with Bayesian inference to estimate the model parameters including the characteristics of errors in macroscopic elastic properties of wood caused by randomness of microstructural details on the one hand and the experimental errors on the other hand. The former source of uncertainty includes, for example, variability in microfibril angle and growth ring density.Even such limiting consideration of random input illustrates the need for combined computational and experimental approach in a reliable prediction of the desired material properties. Tying the two approaches in the framework of Bayesian statistical method proves useful when addressing their limitations and as such giving better notion on the credibility of the prediction. This is demonstrated here on one particular example of spruce wood.

Název v anglickém jazyce

Bayesian inference as a tool for improving estimates of effective elastic parameters of wood

Popis výsledku anglicky

A simple approach to the identification of geometrical and material uncertainties of wood is presented.This stochastic mechanics problem combines classical micromechanics, computational homogenization and experimental measurements with Bayesian inference to estimate the model parameters including the characteristics of errors in macroscopic elastic properties of wood caused by randomness of microstructural details on the one hand and the experimental errors on the other hand. The former source of uncertainty includes, for example, variability in microfibril angle and growth ring density.Even such limiting consideration of random input illustrates the need for combined computational and experimental approach in a reliable prediction of the desired material properties. Tying the two approaches in the framework of Bayesian statistical method proves useful when addressing their limitations and as such giving better notion on the credibility of the prediction. This is demonstrated here on one particular example of spruce wood.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20102 - Construction engineering, Municipal and structural engineering

Projekt

<a href="/cs/project/GA18-05791S" target="_blank" >GA18-05791S: Požární odolnost lepených lamelových dřevěných nosníků se zahrnutím nejistot</a><br>

Návaznosti

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

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

Computers and Structures

ISSN

0045-7949

e-ISSN

1879-2243

Svazek periodika

218

Číslo periodika v rámci svazku

July

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

14

Strana od-do

94-107

Kód UT WoS článku

000467891600006

EID výsledku v databázi Scopus

2-s2.0-85063861080