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Measurement uncertainty is essential for accurate comparison and decision-making in various fields. The ISO/IEC GUM standardizes uncertainty estimation, yet traditional methods like the Law of Propaga...tion of Uncertainties (LPU) face limitations. The Monte Carlo Method (MCM) offers a solution, especially for complex models. Our study explores MCM’s application in refriger-ator power measurement, overcoming challenges encountered with traditional methods. Three MCM methodologies— a priori, adaptive with 1 or 2 significant decimal digits—were tested. The findings reveal that while all three methods yield relatively similar results—51.3 𝑊 estimated measured power with a standard uncertainty of 1.44 𝑊—the a priori method with 𝑀=10^6 and the adaptive method with 2 significant decimal digits exhibit greater stability compared to the adaptive method with 1 significant decimal digit. This underscores MCM’s effectiveness in handling intricate uncertainties and its potential for advancing measurement reliability and quality.続きを見る
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Mendeley出力
p2468-2478