scholarly journals Use of Pooled Standard Deviation of Paired Samples in Calculating the Measurement Uncertainty by the Monte Carlo Method

2013 ◽  
Author(s):  
Sueli Fischer Beckert ◽  
Gustavo Domeneghetti ◽  
Danielle Bond
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Monte Carlo Method ◽  
Measurement Uncertainty ◽  
Paired Samples ◽  
The Monte Carlo Method

A Simplified Software for Uncertainty Estimation Using Monte Carlo Method

2020 ◽  
Vol 12 (8) ◽  
pp. 1050-1053
Author(s):  
Jasveer Singh ◽  
L. A. Kumaraswamidhas ◽  
Neha Bura ◽  
Kapil Kaushik ◽  
Nita Dilawar Sharma
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Monte Carlo Method ◽  
Measurement Uncertainty ◽  
Standard Uncertainty ◽  
Uncertainty Estimation ◽  
End Points ◽  
The Monte Carlo Method ◽  
Adaptive Trials ◽  
Coverage Interval

The current paper discusses about the application of Monte Carlo method for the evaluation of measurement uncertainty using in-house developed program on C++ platform. The Monte Carlo method can be carried out by fixed trials as well as adaptive trials using this program. The program provides the four parameters viz. estimate of measurand, standard uncertainty in the form of standard deviation and end points of coverage interval as an output.

scholarly journals Analysis of the Accuracy of the Calculation of the Diaphragm Area by the Monte Carlo Method

2020 ◽  
pp. 22-26
Author(s):  
O. D. Kupko
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Monte Carlo Method ◽  
Probability Distribution ◽  
Circular Aperture ◽  
The Monte Carlo Method ◽  
Relative Standard ◽  
Uniform Probability Distribution ◽  
Standard Deviations ◽  
The Difference

The process of measuring the area of a circular diaphragm using a device that determines the coordinates of the boundary of the diaphragm is theoretically considered. The Monte Carlo method with a small number of implementations was used. The procedure for calculating the area is described in detail. We considered a circular aperture with a precisely known radius. On the circumference of the diaphragm, the coordinate measuring points vibrated through 0.1, 0.3, 0.6, and π/2 radians vibrated. To simulate random deviations (uncertainties) when measuring coordinates, random additives were used with a uniform probability distribution and a given standard deviation. For each case, the areas were calculated in accordance with the proposed procedure. The difference in the results of calculating the area from the true area depending on the number of measurement points and the standard deviation of random additives is analyzed. It is shown that the ratio of the relative standard deviations of the area to the relative standard deviations of the coordinates is approximately the same for each number of measurements. The dependence of this relationship on the number of measurements is determined. The results obtained are analyzed.

scholarly journals Verification of the Indicating Measuring Instruments Taking into Account their Instrumental Measurement Uncertainty

2017 ◽  
Vol 17 (6) ◽  
pp. 269-272
Author(s):  
Igor Zakharov ◽  
Pavel Neyezhmakov ◽  
Olesia Botsiura
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Measurement Uncertainty ◽  
Measuring Instruments ◽  
Legal Metrology ◽  
The Monte Carlo Method ◽  
Uncertainty Of Measurements ◽  
Instrumental Measurement ◽  
Probability Of Compliance

Abstract The specific features of the measuring instruments verification based on the results of their calibration are considered. It is noted that, in contrast to the verification procedure used in the legal metrology, the verification procedure for calibrated measuring instruments has to take into account the uncertainty of measurements into account. In this regard, a large number of measuring instruments, considered as those that are in compliance after verification in the legal metrology, turns out to be not in compliance after calibration. In this case, it is necessary to evaluate the probability of compliance of indicating measuring instruments. The procedure of compliance probability determination on the basis of the Monte Carlo method is considered. An example of calibration of a Vernier caliper is given.

scholarly journals MEASUREMENT UNCERTAINTY EVALUATION OF BRINELL HARDNESS TEST: GUM AND MONTE CARLO METHOD

2018 ◽  
Vol 15 (30) ◽  
pp. 252-258
Author(s):  
L. TREVISAN ◽  
D. A. K. FABRICIO
Keyword(s):  
Mathematical Method ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Measurement Uncertainty ◽  
Brinell Hardness ◽  
Hardness Test ◽  
Mechanical Tests ◽  
Uncertainty Evaluation ◽  
The Monte Carlo Method ◽  
Measurement Uncertainty Evaluation

The Brinell hardness test is one of the most used mechanical tests in the industry to assure the quality of metallurgical processes. Based on the measured values, it is necessary to describe the measurement uncertainty values associated with the mathematical method used. Thus, measurement uncertainty values describe the reliability of the experimental results. The calculation of measurement uncertainty can be performed in several ways, and the method described by ISO/GUM is the most used by ISO/IEC 17025 accredited laboratories. The main objective of this work is to compare measurement uncertainty values based on different sources of uncertainty used in the measurement uncertainty evaluation for two Brazilian laboratories accredited by Cgcre/INMETRO. In addition, uncertainty values obtained by the GUM method and by the Monte Carlo method were compared. The results show that there is no great variation in the measurement uncertainty values as a function of the mathematical method used.

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