New framework for nanoindentation curve fitting and measurement
uncertainty estimation

J 2024

New framework for nanoindentation curve fitting and measurement uncertainty estimation

CHARVÁTOVÁ CAMPBELL, A., Zdeňka GERŠLOVÁ, Vojtěch ŠINDLÁŘ, R. ŠLESINGER, Gejza WIMMER et. al.

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

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10103 Statistics and probability

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

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

Abstract

V originále

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 project

Name: Pokročilé matematické a statistické metody ve vyhodnocování měření instrumentovanou indentací

Investor: Technology Agency of the Czech Republic

Citovat

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.

@article{2368114,
   author = {Charvátová Campbell, A. and Geršlová, Zdeňka and Šindlář, Vojtěch and Šlesinger, R. and Wimmer, Gejza},
   article_number = {January},
   doi = {http://dx.doi.org/10.1016/j.precisioneng.2023.10.001},
   keywords = {Nanoindentation; Statistical methods; Metrology; Computation},
   language = {eng},
   issn = {0141-6359},
   journal = {Precision Engineering},
   title = {New framework for nanoindentation curve fitting and measurement uncertainty estimation},
   url = {https://www.sciencedirect.com/science/article/pii/S0141635923001848},
   volume = {85},
   year = {2024}
}

TY  - JOUR
ID  - 2368114
AU  - Charvátová Campbell, A. - Geršlová, Zdeňka - Šindlář, Vojtěch - Šlesinger, R. - Wimmer, Gejza
PY  - 2024
TI  - New framework for nanoindentation curve fitting and measurement uncertainty estimation
JF  - Precision Engineering
VL  - 85
IS  - January
SP  - 166-173
EP  - 166-173
PB  - Elsevier
SN  - 01416359
KW  - Nanoindentation
KW  - Statistical methods
KW  - Metrology
KW  - Computation
UR  - https://www.sciencedirect.com/science/article/pii/S0141635923001848
N2  - 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.
ER  -

CHARVÁTOVÁ CAMPBELL, A., Zdeňka GERŠLOVÁ, Vojtěch ŠINDLÁŘ, R. ŠLESINGER and Gejza WIMMER. New framework for nanoindentation curve fitting and measurement uncertainty estimation. \textit{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.

Detailed Information on Publication Record