Pregled bibliografske jedinice broj: 852323
Examples of measurement uncertainty evaluations in accordance with the revised GUM
Examples of measurement uncertainty evaluations in accordance with the revised GUM // Journal of Physics: Conference Series Metrology across the Sciences: Wishful Thinking?
Berkeley (CA), 2016. str. 128-142 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 852323 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Examples of measurement uncertainty evaluations in accordance with the revised GUM
Autori
Runje, Biserka ; Horvatić Novak, Amalija ; Alar, Vesna ; Medić, Srđan ; Bošnjaković, Alen
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Journal of Physics: Conference Series Metrology across the Sciences: Wishful Thinking?
/ - Berkeley (CA), 2016, 128-142
Skup
2016 Joint IMEKO TC1-TC7-TC13 Symposium: Metrology Across the Sciences: Wishful Thinking?
Mjesto i datum
Berkeley (CA), Sjedinjene Američke Države, 03.08.2016. - 05.08.2016
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
measurement uncertainty ; GUM ; Bayesian approach
Sažetak
The paper presents examples of the evaluation of uncertainty components in accordance with the current and revised Guide to the expression of uncertainty in measurement (GUM). In accordance with the proposed revision of the GUM a Bayesian approach was conducted for both type A and type B evaluations.The law of propagation of uncertainty (LPU)and the law of propagation of distribution applied through the Monte Carlo method, (MCM) were used to evaluate associated standard uncertainties, expanded uncertainties and coverage intervals. Furthermore, the influence of the non-Gaussian dominant input quantity and asymmetric distribution of the output quantity y on the evaluation of measurement uncertainty was analyzed. In the case when the probabilistically coverage interval is not symmetric, the coverage interval for the probability P is estimated from the experimental probability density function using the Monte Carlo method. Key highlights of the proposed revision of the GUM were analyzed through a set of examples.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb
Profili:
Biserka Runje
(autor)
Amalija Horvatić Novak
(autor)
Vesna Alar
(autor)
Alen Bošnjaković
(autor)
Srđan Medić
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Conference Proceedings Citation Index - Science (CPCI-S)
- Scopus