Metrology

Advanced coupled resonance sensors (ACRS), built by integrating micropillar arrays onto quartz crystal microbalance (QCM) substrates, have emerged as a powerful platform for high-sensitivity measurement of viscosity, water contamination, temperature, and purification in liquid environments. Despite their demonstrated performance, the systematic role of pillar geometry, material properties, and fabrication tolerances on device behavior has not been investigated. This work presents a three-dimensional finite element digital twin of an ACRS device operating in air and liquid, in which pillar height, cross-sectional shape, elastic modulus, density, and internal loss factor are treated as independent input parameters. The model resolves the full coupled fluid–structure interaction using the linearized Navier–Stokes equations in the liquid domain, viscoelastic damping inside the pillar, and the periodic acoustic loading imposed by the QCM substrate. The framework was validated against pillar-height-dependent response in air and in deionized water for square (critical height 15 µm in air, 13 µm in water) and circular (11 µm in air, 9.5 µm in water) cross-sections, and against bulk-liquid viscosity loading across a sucrose–water series spanning approximately 1–15 cP, in which the model reproduced frequency shifts up to 85 kHz. Sensitivity enhancement exceeded a factor of 22 for both geometries near their critical heights, and the normalized peak shear displacement peaked at the critical height for both cross-sections in air and in water, exceeding the substrate amplitude by more than an order of magnitude. A Monte Carlo uncertainty propagation analysis demonstrated that operation at the critical height amplifies the standard uncertainty in resonance frequency by more than an order of magnitude relative to sub-critical operation, with geometric tolerances dominating over material property variability by a factor of two to four. The analysis recommends sub-critical operation for quantitative measurement, where the fabrication-driven combined coefficient of variation stays below 0.2% under realistic fabrication conditions. The model is validated for Newtonian liquids under fully wetted conditions and against the frequency response only. The viscosity response is validated over approximately 1–15 cP, and use outside this interval is an extrapolation of the calibration. The digital twin provides a metrologically grounded basis for ACRS design and material selection.

Ammonia (NH₃) is emerging as a key energy carrier in the context of the European Union’s drive towards decarbonisation, serving as a hydrogen carrier and direct fuel in maritime and power generation sectors. Accurate and traceable measurement of NH₃ purity is essential across the entire ammonia value chain. This article describes the work carried out by the Reference Gas Laboratory (LGR) of the Instituto Português da Qualidade (IPQ) within the framework of the European Partnership on Metrology project MetNH3Energy. This work presents the calibration of NH₃ reference gas mixtures according to ISO 6143 using a first-order linear fit with three certified reference gas standards in nitrogen matrix at nominal mole fractions from 25 µmol/mol to 1001 µmol/mol. While the ISO 6143 comparative approach is well established, its systematic application to NH₃ across this concentration range, together with an assessment of the nitrogen-to-air matrix effect relevant to IPQ’s air-matrix reference mixtures, has not previously been reported and extends the NH₃ measurement capabilities currently available through the BIPM Key Comparison Database. The validation of the NH₃ calibration method was carried out on three consecutive days using the normalised error (En) statistical tool and repeatability and intermediate precision studies. All En values obtained were within the acceptance criterion |En| ≤ 1, confirming the validity of the calibration method. Repeatability and intermediate precision components were found to be well below the calibration uncertainty, demonstrating the robustness of the measurement procedure. These results support the establishment of new Calibration and Measurement Capabilities (CMCs) for NH₃ at IPQ, contributing to the metrological infrastructure for ammonia in emerging energy applications. This work therefore represents the first rigorous validation of the NH₃ calibration method at IPQ, providing the metrological foundation needed to support the emerging ammonia energy sector.

Transmission line monitoring is undergoing a significant transformation driven by the increasing demand for enhanced grid utilization, Dynamic Line Rating (DLR), and cost-effective monitoring solutions. However, the large-scale deployment of physical monitoring devices remains constrained by installation and maintenance time and costs. This paper presents the development and validation of an artificial neural network (ANN)-based Digital Twin (DT) framework for conductor temperature monitoring through virtual sensing. The investigated approach is part of a multi-layer Digital Twin architecture that integrates data preparation, virtual sensing, and DLR applications into a unified monitoring concept. The research was conducted within the Horizon Europe TwinEU project using datasets collected from three power system operators operating overhead lines at voltage levels between 132 kV and 400 kV. The developed ANN models applied weather observations and SCADA-derived loading data as inputs, while conductor temperature measurements obtained from physical sensors served as training and validation targets. To enhance robustness and generalization, different data-splitting methodologies, normalization techniques, and site-specific hyperparameter optimization strategies were investigated using a Bayesian optimization framework. The results demonstrate that ANN-based virtual sensors can reproduce conductor temperature measurements with high accuracy, achieving RMSE values of 0.791–1.087 °C, when sufficient high-quality training data are available. The study also highlights the importance of local weather measurements and seasonally representative datasets for reliable model performance. The findings confirm that DT technologies can partially substitute physical monitoring assets without significant loss of accuracy, reducing monitoring complexity and operational costs. The proposed approach offers a practical pathway toward scalable transmission line monitoring and provides a foundation for future applications in DLR, ampacity calculation, market-oriented grid operation, and asset management.