Role of Random Factors in Nonlinear Regression: a Case Study for Estimation of Thermophysical Parameters

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Role of Random Factors in Nonlinear Regression: a Case Study for Estimation of Thermophysical Parameters

Popis výsledku v původním jazyce

Abstract: In order to design an optimal experimental setup the designers have to take into account uncertainties connected to the investigated system. The input random factors associated with for example values of loading, specimen dimensions or measurement errors influence behaviour of the system, which thus becomes also uncertain. From this point of view, the experiment design is a very important because it effects amount of information which can be obtained from the experiment. More specifically, accuracy of the identified parameters from indirect experimental measurements depends on experimental settings. In this contribution we demonstrate a role of random factors in a nonlinear model calibration on an illustrative example of one dimensional heat conduction. The thermophysical parameters such as thermal capacity and thermal conductivity are identified on a basis of noisy measurements from experiments with different setup. The experiments vary in a number of sensors and number of observed time steps. The presented statistical analysis shows dependence of the parameter estimation on the choice of measured quantities involving different uncertainties.

Název v anglickém jazyce

Role of Random Factors in Nonlinear Regression: a Case Study for Estimation of Thermophysical Parameters

Popis výsledku anglicky

Abstract: In order to design an optimal experimental setup the designers have to take into account uncertainties connected to the investigated system. The input random factors associated with for example values of loading, specimen dimensions or measurement errors influence behaviour of the system, which thus becomes also uncertain. From this point of view, the experiment design is a very important because it effects amount of information which can be obtained from the experiment. More specifically, accuracy of the identified parameters from indirect experimental measurements depends on experimental settings. In this contribution we demonstrate a role of random factors in a nonlinear model calibration on an illustrative example of one dimensional heat conduction. The thermophysical parameters such as thermal capacity and thermal conductivity are identified on a basis of noisy measurements from experiments with different setup. The experiments vary in a number of sensors and number of observed time steps. The presented statistical analysis shows dependence of the parameter estimation on the choice of measured quantities involving different uncertainties.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10102 - Applied mathematics

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

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Engineering Mechanics 2017 - Book of full texts

ISBN

978-80-214-5497-2

ISSN

1805-8248

e-ISSN

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Počet stran výsledku

4

Strana od-do

410-413

Název nakladatele

Brno University of Technology

Místo vydání

Brno

Místo konání akce

Svratka

Datum konání akce

15. 5. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000411657600092