Indian Journal of Engineering & Materials Sciences

Open Access Open Access  Restricted Access Subscription Access

Comprehensive Exordium of Monte Carlo Simulation Technique : An Alternative Approach for Measurement Uncertainty Evaluation


Affiliations
1 Academy of Scientific and Innovative Research, Ghaziabad 201 002, India
2 National Institute of Technology, Delhi 110 036, India
 

Precise and accurate measurements are essential for reliable experimental investigations and establishments of immaculate scientific theories. It has been realized that the measurement observations are always accompanied by certain reservations, hence to provide quality measurements, systematic assessment of these uncertainties is of much significance. This article attempts to demonstrate the detailed procedure for measurement uncertainty evaluation using Monte Carlo Simulation (MCS) technique as per the recommendations of JCGM 101: 2008 using Microsoft Excel. Interestingly, it has been perceived that the expanded uncertainty values and histograms acquired using Law of Propagation of Uncertainties (LPU) and Monte Carlo Simulation (MCS) are distinctive.

Keywords

Metrology, Measurement, Uncertainty, Law of Propagation of Uncertainties, Probability Distribution Function, Monte Carlo Simulation, Random Number Generation.
User
Notifications
Font Size

  • Joint Committee for Guides in Metrology, “Guide to the Expression of Uncertainty in Measurement”, Geneva, International Organization for Standardization, 1st edition, BIPM, Sevres-France, 2008.

  • Joint Committee for Guides in Metrology, Evaluation of Measurement Data Supplement 1 to the “Guide to the Expression of Uncertainty in Measurement Propagation of Distribution Using a Monte Carlo Method” 1st edition, BIPM, Sevres-France, 2008.

  • Veen A M H & Cox M G, Accreditation Qual Assur, 26 (2021) 129.

  • Singh J, Bura N, Kaushik K, Kumarswamidhas L A & Sharma N, Trans Inst Meas, 43 (16) (2021) 3615.

  • Willink R, Metrologia, 43 (2006) L39.

  • Cox M, Harris P, & Siebert B R L, Meas Tech, 46 (2003) 824.

  • Cox M G, Dainton M P, Forbes A B, Harris P M, Schwenke H, Siebert B R L & Wöger W, Advanced Mathematical and Computational Tools in Metrology, Series of Advances in Mathematics for Applied Sciences, ISBN/ISSN 981-0244-94-0, 2001, 57, 93–105.

  • Moona G, Kumar V, Jewariya M, Sharma &, Kumar H, JMSI Mapan, 34(3) (2019) 325


Abstract Views: 96

PDF Views: 97




  • Comprehensive Exordium of Monte Carlo Simulation Technique : An Alternative Approach for Measurement Uncertainty Evaluation

Abstract Views: 96  |  PDF Views: 97

Authors

Girija Moona
Academy of Scientific and Innovative Research, Ghaziabad 201 002, India
Harish Kumar
National Institute of Technology, Delhi 110 036, India

Abstract


Precise and accurate measurements are essential for reliable experimental investigations and establishments of immaculate scientific theories. It has been realized that the measurement observations are always accompanied by certain reservations, hence to provide quality measurements, systematic assessment of these uncertainties is of much significance. This article attempts to demonstrate the detailed procedure for measurement uncertainty evaluation using Monte Carlo Simulation (MCS) technique as per the recommendations of JCGM 101: 2008 using Microsoft Excel. Interestingly, it has been perceived that the expanded uncertainty values and histograms acquired using Law of Propagation of Uncertainties (LPU) and Monte Carlo Simulation (MCS) are distinctive.

Keywords


Metrology, Measurement, Uncertainty, Law of Propagation of Uncertainties, Probability Distribution Function, Monte Carlo Simulation, Random Number Generation.

References