CHARVÁTOVÁ CAMPBELL, A., Zdeňka GERŠLOVÁ, Vojtěch ŠINDLÁŘ, R. ŠLESINGER and Gejza WIMMER. New framework for nanoindentation curve fitting and measurement uncertainty estimation. Precision Engineering. Elsevier, 2024, vol. 85, January, p. 166-173. ISSN 0141-6359. Available from: https://dx.doi.org/10.1016/j.precisioneng.2023.10.001.
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Basic information
Original name New framework for nanoindentation curve fitting and measurement uncertainty estimation
Authors CHARVÁTOVÁ CAMPBELL, A., Zdeňka GERŠLOVÁ (203 Czech Republic, belonging to the institution), Vojtěch ŠINDLÁŘ (203 Czech Republic, belonging to the institution), R. ŠLESINGER and Gejza WIMMER (703 Slovakia, belonging to the institution).
Edition Precision Engineering, Elsevier, 2024, 0141-6359.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10103 Statistics and probability
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 3.600 in 2022
Organization unit Faculty of Science
Doi http://dx.doi.org/10.1016/j.precisioneng.2023.10.001
UT WoS 001098374000001
Keywords in English Nanoindentation; Statistical methods; Metrology; Computation
Tags rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Marie Šípková, DiS., učo 437722. Changed: 31/1/2024 12:47.
Abstract
Uncertainty quantification is a vital component of any measurement process and is indispensable for comparing results obtained by different methods, instruments, or laboratories. The processing of the measured data often relies on fitting the data by a given function. Common methods such as ordinary nonlinear least squares are not capable of treating general uncertainties and correlations in both dependent and independent variables. A new computation method for nonlinear curve fitting to data with a general covariance structure is introduced. This method is applied to the Oliver-Pharr analysis of unloading curves and differences between different regression methods are addressed. Numerical simulations show that the new method yields parameter estimates in agreement with other methods for simple covariance structures. The obtained uncertainty estimates are in agreement with Monte Carlo studies.
Links
TJ02000203, research and development projectName: Pokročilé matematické a statistické metody ve vyhodnocování měření instrumentovanou indentací
Investor: Technology Agency of the Czech Republic
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