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Uncertainty quantification in engineering and energy instrumentation: Linking bibliometric insights and practical methods Nanang Apriandi; Sumantri Hatmoko; Berkah Fajar Tamtomo Kiono; Mukhsinun Hadi Kusuma; Khoiri Rozi; Yoyok Setiyo Pambudi; Lily Maysari Angraini; Rani Raharjanti; Muhammad Yunus; Anhar Riza Antariksawan; Sofia Loren Butarbutar; Aris Fiatno; Afifa Pramesywari
Jurnal Polimesin Vol 24, No 4 (2026): August
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i4.7746

Abstract

Reliable quantification of measurement uncertainty is essential for validating thermal performance in engineering systems, particularly in heat pipe experimentation where derived parameters such as heat input and thermal resistance are highly sensitive to instrument variability. Despite the availability of the Guide to the Expression of Uncertainty in Measurement (GUM), practical implementation in laboratory-scale settings remains uneven. This study integrates bibliometric mapping and experimental validation to bridge this gap. A bibliometric analysis of 183 Scopus-indexed publications (1987–2025) identifies dominant research themes centered on high-precision calibration, simulation-based propagation, and intelligent modeling, with comparatively limited emphasis on structured frameworks for resource-constrained laboratories. An experimental uncertainty evaluation was then conducted on five instruments commonly used in heat pipe systems: thermocouples, pressure transducers, a voltage regulator, a digital clamp meter, and a rotameter. Instrument-level accuracy and precision were quantified, and system-level uncertainty was propagated using a GUM-aligned Root-Sum-of-Squares (RSS) method. The system achieved a combined uncertainty of ±2.51 and an expanded uncertainty of ±5.02 at a 95% confidence level. Uncertainty decomposition indicates that electrical input variability, particularly voltage regulation, is the dominant contributor to propagated thermal performance uncertainty. The findings establish a technically grounded and implementable uncertainty framework for laboratory-scale thermal systems, providing quantitative guidance for prioritizing instrumentation improvements and strengthening experimental reliability under constrained resource conditions.