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.

Základní údaje

Originální název

New framework for nanoindentation curve fitting and measurement uncertainty estimation

Autoři

CHARVÁTOVÁ CAMPBELL, A.; Zdeňka GERŠLOVÁ; Vojtěch ŠINDLÁŘ; R. ŠLESINGER a Gejza WIMMER

Vydání

Precision Engineering, Elsevier, 2024, 0141-6359

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10103 Statistics and probability

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 3.700

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14310/24:00139805

Organizační jednotka

Přírodovědecká fakulta

Klíčová slova anglicky

Nanoindentation; Statistical methods; Metrology; Computation

Štítky

14311010, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 30. 7. 2025 10:22, Mgr. Marie Novosadová Šípková, DiS.

Anotace

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.

Citovat

CHARVÁTOVÁ CAMPBELL, A.; Zdeňka GERŠLOVÁ; Vojtěch ŠINDLÁŘ; R. ŠLESINGER a Gejza WIMMER. New framework for nanoindentation curve fitting and measurement uncertainty estimation. Precision Engineering. Elsevier, 2024, roč. 85, January, s. 166-173. ISSN 0141-6359. Dostupné z: https://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 = {https://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 a Gejza WIMMER. New framework for nanoindentation curve fitting and measurement uncertainty estimation. \textit{Precision Engineering}. Elsevier, 2024, roč.~85, January, s.~166-173. ISSN~0141-6359. Dostupné z: https://doi.org/10.1016/j.precisioneng.2023.10.001.

Přehled o publikaci