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New framework for nanoindentation curve fitting and measurement uncertainty estimation

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

Rok publikování 2024
Druh Článek v odborném periodiku
Časopis / Zdroj Precision Engineering
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
www https://www.sciencedirect.com/science/article/pii/S0141635923001848
Doi http://dx.doi.org/10.1016/j.precisioneng.2023.10.001
Klíčová slova Nanoindentation; Statistical methods; Metrology; Computation
Popis 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.
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