<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The paper presents the comparison of uncertainty measurement estimations of the energy performances of gas stoves. The Guide to the Expression of Uncertainty in Measurement (GUM) framework and two Monte Carlo Simulation (MCM) approaches: ordinary and adaptive MCM were applied for the energy performance uncertainty: thermal energy and efficiency measurement uncertainties. The validation of the two MCMs is performed by comparing the MCM estimations to the GUM estimations for the thermal energy and efficiency measurement results. A test method designed in Indonesia National Standard SNI 7368:2011 was employed for the thermal energy and efficiency determinations. The results of the GUM and two MCM methods are in good agreement for the estimation of the thermal energy value. Significant differences of the uncertainty estimations for the thermal energy and efficiency results are observed for both GUM and MCM methods. Both the ordinary and adaptive MCM estimations give larger coverage interval compared to the GUM method. The adaptive MCM can give similar estimations with a much lower number of iterations compared to the ordinary MCM. From the estimation difference between the GUM and MCM methods, suggestions are needed for the improvement in measurement models for thermal energy and efficiency of the standard.</p>
</abstract>

The paper presents the comparison of uncertainty measurement estimations of the energy performances of gas stoves. The Guide to the Expression of Uncertainty in Measurement (GUM) framework and two Monte Carlo Simulation (MCM) approaches: ordinary and adaptive MCM were applied for the energy performance uncertainty: thermal energy and efficiency measurement uncertainties. The validation of the two MCMs is performed by comparing the MCM estimations to the GUM estimations for the thermal energy and efficiency measurement results. A test method designed in Indonesia National Standard SNI 7368:2011 was employed for the thermal energy and efficiency determinations. The results of the GUM and two MCM methods are in good agreement for the estimation of the thermal energy value. Significant differences of the uncertainty estimations for the thermal energy and efficiency results are observed for both GUM and MCM methods. Both the ordinary and adaptive MCM estimations give larger coverage interval compared to the GUM method. The adaptive MCM can give similar estimations with a much lower number of iterations compared to the ordinary MCM. From the estimation difference between the GUM and MCM methods, suggestions are needed for the improvement in measurement models for thermal energy and efficiency of the standard.

Comparison of GUM and Monte Carlo Methods for Measurement Uncertainty Estimation of the Energy Performance Measurements of Gas Stoves

Measurement Science Review

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The paper presents the comparison of uncertainty measurement estimations of the energy performances of gas stoves. The Guide to the Expression of Uncertainty...

Comparison of GUM and Monte Carlo Methods for Measurement Uncertainty Estimation of the Energy Performance Measurements of Gas Stoves

Published Online: May 14, 2022

Page range: 160 - 169

Received: Dec 28, 2021

Accepted: Mar 21, 2022

DOI: https://doi.org/10.2478/msr-2022-0020

Keywords
measurement uncertainty, national standard, GUM framework, Monte Carlo, thermal energy, efficiency

© 2022 Bayu Utomo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Comparison of GUM and Monte Carlo Methods for Measurement Uncertainty Estimation of the Energy Performance Measurements of Gas Stoves

Published Online: May 14, 2022

Page range: 160 - 169

Received: Dec 28, 2021

Accepted: Mar 21, 2022

DOI: https://doi.org/10.2478/msr-2022-0020

Keywordsmeasurement uncertainty, national standard, GUM framework, Monte Carlo, thermal energy, efficiency

© 2022 Bayu Utomo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
measurement uncertainty, national standard, GUM framework, Monte Carlo, thermal energy, efficiency