Metrology, Volume 5, Issue 3 (September 2025) – 15 articles

This paper proposes using provenance information to describe processes in metrology. The PROV data model is used as an example to showcase a conceptual analysis about how to improve quality, reliability, and overall interoperability within cross-domain applications that require communicating measurement data and traceability information. The analysis considers various metrological processes and outputs that support traceability. The conceptual analysis will be used as a foundation for further contributions to the topic of improving the documentation of metrological traceability with provenance data models. Several use cases illustrate how provenance information can provide context for traceability claims, especially when the measurement result is the focal object of interest. The PROV family of specifications provides machine-actionable metadata and semantic interoperability when communicating measurement information in traceability chains. PROV supports various perspectives that arise in the context of metrological traceability. Full article

This article investigates the acoustic properties of artificial discontinuities in reference specimens for the ultrasonic testing of welded joints in polyethylene pipes. An analysis is conducted on the reflectivity of various materials (air, sand, heat-resistant silicate-based sealant, and aluminum foil) and their correspondence to real defects occurring in weld seams. A theoretical analysis of reflection coefficients is performed, along with laboratory studies using digital radiography and ultrasonic testing. The results demonstrate that heat-resistant silicate sealant is the most suitable material for simulating defects, as its acoustic properties closely match those of real inclusions, and its geometric parameters remain stable during the welding process. The use of such specimens enhances the reliability of ultrasonic testing and reduces the likelihood of errors in defect classification. Full article

Accurate characterization of 3D surface topography is essential for assessing the quality of machined components. This study investigates the influence of measurement area selection on the evaluation of roughness parameters in high-feed tangential turning of 42CrMo4 alloy steel. Cylindrical surfaces were machined using different process parameters, and their surface topography was analyzed by varying the size of the areal measurement region. Key roughness parameters were examined to determine the impact on the reliability and consistency of surface characterization. The results highlight how different measurement areas influence roughness values and their variations. The findings contribute to improved metrological practices in tangential turning, and they are particularly relevant for precision machining applications where surface integrity plays a critical role. The area width of the measurement area was shown to play a critical role in data reliability. The results showed that S_a and S_k stabilized after 5.5–6.0 mm, while S_sk and S_ku stabilized earlier, at approximately 5.0 mm. S_pk and S_vk required the longest evaluation area widths, up to 6.0 mm, to achieve consistent values. Full article

Background: Velocity-based training (VBT) requires precise measurement devices to monitor neuromuscular performance. PowerTrack^TM is a novel optoelectronic device designed to assess movement velocity in resistance training. This study aimed to evaluate the validity and reliability of PowerTrack^TM during the Smith machine back squat. Methods: Twenty experienced-trained men performed three repetitions at three submaximal loads (20, 50, and 70 kg) across two sessions. Velocity metrics—mean velocity (MV), mean propulsive velocity (MPV), and maximum velocity (Vmax)—were simultaneously recorded by PowerTrack^TM and the criterion device (MuscleLab^TM). Validity was assessed via ordinary least products (OLP) regression, Lin’s concordance correlation coefficient (CCC), and Bland–Altman plots. Reliability was determined using intraclass correlation coefficients (ICCs), standard error of measurement (SEM), coefficient of variation (CV), and minimum detectable change (MDC). Results: PowerTrack showed high agreement with MuscleLab^TM for MPV and Vmax (slope ≈ 1.00; CCC = 0.95–0.97), while MV presented a proportional bias (slope = 0.83). ICCs ranged from 0.78 to 0.91 across loads, and SEM remained <0.09 m/s for all metrics, indicating excellent relative reliability and acceptable absolute precision. Conclusion: Despite a slight underestimation of MV at light loads, PowerTrack^TM proved to be a valid and reliable device for velocity monitoring in VBT contexts. Full article

Cone Penetration Tests with pore pressure measurements (CPTu) are widely used in geotechnical site investigations due to their high-resolution profiling capabilities. However, traditional interpretation methods—such as the Soil Behavior Type Index ($I_c$)—often fail to capture the internal heterogeneity typical of mining tailings deposits. This study presents a machine learning-based approach to enhance stratigraphic interpretation from CPTu data. Four unsupervised clustering algorithms—k-means, DBSCAN, MeanShift, and Affinity Propagation—were evaluated using a dataset of 12 CPTu soundings collected over a 19-year period from an iron tailings dam in Brazil. Clustering performance was assessed through visual inspection, stratigraphic consistency, and comparison with $I_c$-based profiles. k-means and MeanShift produced the most consistent stratigraphic segmentation, clearly delineating depositional layers, consolidated zones, and transitions linked to dam raising. In contrast, DBSCAN and Affinity Propagation either over-fragmented or failed to identify meaningful structures. The results demonstrate that clustering methods can reveal behavioral trends not detected by $I_c$ alone, offering a complementary perspective for understanding depositional and mechanical evolution in tailings. Integrating clustering outputs with conventional geotechnical indices improves the interpretability of CPTu profiles, supporting more informed geomechanical modeling, dam monitoring, and design. The approach provides a replicable methodology for data-rich environments with high spatial and temporal variability. Full article

Optical fringe projection is an outstanding technology that significantly enhances three-dimensional (3D) metrology in numerous applications in science and engineering. Although the complexity of fringe projection systems may be overwhelming, current scientific advances bring improved models and methods that simplify the design and calibration of these systems, making 3D metrology less complicated. This paper provides an overview of the fundamentals of fringe projection profilometry, including imaging, stereo systems, phase demodulation, triangulation, and calibration. Some applications are described to highlight the usefulness and accuracy of modern optical fringe projection profilometers, impacting 3D metrology in different fields of science and engineering. Full article

Thermal management is an area of study in electronics focused on managing temperature to improve reliability and efficiency. When temperatures are too high, cooling systems are activated to prevent overheating, which can lead to reliability issues. To monitor the temperatures, sensors are often placed on-chip near hotspot locations. These sensors should be very small to allow them to be placed among compact, high-activity circuits. Often, they are connected to a central control circuit located far away from the hot spot locations where more area is available. This paper proposes sensing units for a novel temperature sensing architecture in the TSMC 180 nm process. This architecture functions by approximating the current through the sensing unit at a reference voltage, which is used to approximate the temperature in the digital back end using fitting functions. Sensing units are selected based on how well its temperature–current relationship can be modeled, sensing unit area, and power consumption. Many sensing units will be experimented with at different reference voltages. These temperature–current curves will be modeled with various fitting functions. The sensing unit selected is a diode-connected p-type MOSFET (Metal Oxide Semiconductor Field Effect Transistor) with a size of W = 400 nm, L = 180 nm. This sensing unit is exceptionally small compared to existing work because it does not rely on multiple devices at the sensing unit location to generate a PTAT or IPTAT signal like most work in this area. The temperature–current relationship of this device can also be modeled using a 2nd order polynomial, requiring a minimal number of trim temperatures. Its temperature error is small, and the power consumption is low. The range of currents for this sensing unit could be reasonably made on an IDAC. Full article

Articulated arm coordinate measuring machines are designed for in situ use directly in manufacturing environments, enabling efficient dimensional control outside of climate-controlled laboratories. This study investigates the influence of ambient temperature variation on the accuracy of length measurements performed with the Hexagon Absolute Arm 8312. The experiment was carried out in a laboratory setting simulating typical shop floor conditions through controlled temperature changes in the range of approximately 20–31 °C. A calibrated steel gauge block was used as a reference standard, allowing separation of the influence of the measuring system from that of the measured object. The results showed that the gauge block length changed in line with the expected thermal expansion, while the articulated arm coordinate measuring machine exhibited only a minor residual thermal drift and stable performance. The experiment also revealed a constant measurement offset of approximately 22 µm, likely due to calibration deviation. As part of the study, an uncertainty budget was developed, taking into account all relevant sources of influence and enabling a more realistic estimation of accuracy under operational conditions. The study confirms that modern carbon composite articulated arm coordinate measuring machines with integrated compensation can maintain stable measurement behavior even under fluctuating temperatures in controlled environments. Full article

Current temperature sensors require regular recalibration to maintain reliable temperature measurement. Photonic/quantum-based approaches have the potential to radically change the practice of thermometry through provision of in situ traceability, potentially through practical primary thermometry, without the need for sensor recalibration. This article gives an overview of the European Partnership in Metrology (EPM) project: Photonic and quantum sensors for practical integrated primary thermometry (PhoQuS-T), which aims to develop sensors based on photonic ring resonators and optomechanical resonators for robust, small-scale, integrated, and wide-range temperature measurement. The different phases of the project will be presented. The development of the integrated optical practical primary thermometer operating from 4 K to 500 K will be reached by a combination of different sensing techniques: with the optomechanical sensor, quantum thermometry below 10 K will provide a quantum reference for the optical noise thermometry (operating in the range 4 K to 300 K), whilst using the high-resolution photonic (ring resonator) sensor the temperature range to be extended from 80 K to 500 K. The important issues of robust fibre-to-chip coupling will be addressed, and application case studies of the developed sensors in ion-trap monitoring and quantum-based pressure standards will be discussed. Full article

The determination of precise and reliable interior (IO) and relative (RO) orientation parameters for thermal infrared (TIR) cameras is critical for their subsequent use in photogrammetric processes. Although 2D calibration boards have become the predominant approach for TIR geometric calibration, these targets are susceptible to projective coupling and often introduce error through manual construction methods, necessitating the development of 3D targets tailored to TIR geometric calibration. Therefore, this paper evaluates TIR geometric calibration results obtained from 2D board and 3D field calibration approaches, documenting the construction, observation, and calculation of IO and RO parameters. This includes a comparative analysis of values derived from three popular commercial software packages commonly used for geometric calibration: MathWorks’ MATLAB, Agisoft Metashape, and Photometrix’s Australis. Furthermore, to assess the validity of derived parameters, two InfraRed Thermography 3D-Data Fusion (IRT-3DDF) methods are developed to model historic building façades and medieval frescoes. The results demonstrate the success of the proposed 3D field calibration targets for the calculation of both IO and RO parameters tailored to photogrammetric data fusion. Additionally, a novel combined TIR-RGB bundle block adjustment approach demonstrates the success of applying ‘out-of-the-box’ deep-learning neural networks for multi-modal image matching and thermal modelling. Considerations for the development of TIR geometric calibration approaches and the evolution of proposed IRT-3DDF methods are provided for future work. Full article

The rapid advancement of materials science is driving the development of emerging advanced materials, such as nanomaterials, composites, biomaterials, and high-performance metals. These materials possess unique properties and offer significant potential for innovative applications across industries. Standardization plays a crucial role in ensuring the reliability, consistency, and comparability of material quality assessments. Although typical material specification standards, which rigidly define allowable characteristic ranges, are well-suited for established materials like steel, they may not be directly applicable to emerging advanced materials due to their novelty and evolving nature. To address this challenge, a distinct approach is required—flexible yet robust testing standards for assessing material quality. This paper introduces scenario-based methodologies, a structured approach to developing such standards, with a particular focus on metrological aspects of measurement methods and procedures. Additionally, self-assessment processes aimed at verifying measurement reliability are integrated into the methodology. These methodologies involve defining target materials and their applications, identifying critical material characteristics, specifying appropriate measurement methods and procedures, and promoting adaptable yet reliable guidelines. To maintain relevance with metrological advancements and evolving market demands, these quality testing standards should undergo periodic review and updates. This approach enhances industrial confidence and facilitates market integration. Full article

Thermal mass flow sensors (TMFS) are used to detect the flow rates of gases. TMFS elements are available in different technologies and, depending on the one used, the material choice of substrate, heater, and temperature sensors can limit their performance. In this work, a sensor element based on the Ensinger Microsystems Technology (EMST) is presented that uses PEEK as the substrate, nickel-chromium as the heater, and nickel as the temperature sensor material. The fabrication process of the element is described, the completion to a flow sensor with a control and readout circuit based on discharge time measurement with picosecond resolution is presented, and measurement results are shown, which are compared to sensors with a commercially available element based on thin film technology on ceramic and an element built with discrete components, all using the same electronics. It is shown that the operation of all sensor elements with the proposed readout circuit was successful, flow-dependent signals were achieved, and the performance of TMFS in EMST improved. Its heater shows better results compared to the commercial element due to material choice with a smaller temperature coefficient of resistance. In its current state, the TMFS in EMST is suitable to detect flow rates > 20 SLPM. The performance needs to be improved further, since the temperature sensors still differ too much from another. Full article

Access to significant amounts of data is typically required to develop structural health monitoring (SHM) systems. In this study, a novel SHM approach was evaluated, with all training data collected solely from a validated finite element analysis (FEA) of a reinforced concrete (RC) beam and the structural health based on the tension side of a rebar under flexural loading. The developed SHM system was verified by four-point bending experiments on three RC beams cast in the dimensions of 4000 mm × 200 mm × 400 mm. Distributed optical fibre sensors (DOFS) were mounted on the concrete surface and on the bottom rebar to maximise sample points and investigate the reliability of the strain data. The FEA model was validated using a single beam and subsequently used to generate labelled SHM strain data by altering the dilation angle and rebar sizes. The generated strain data were then used to train an artificial neural network (ANN) classifier using deep learning (DL). Training and validation accuracy greater than 98.75% were recorded, and the model was trained to predict the tension state up to 90% of the steel yield limit. The developed model predicts the health condition with the input of strain data acquired from the concrete surface of reinforced concrete beams under various loading regimes. The model predictions were accurate for the experimental DOFS data acquired from the tested beams. Full article

Over recent years, ultrasonic atomization, especially with regard to liquid metals, has become an object of increased interest, mainly from industry, for additive manufacturing, but also from investigators, for research purposes. A strong correlation between the average particle size, distribution of particle sizes, and other process parameters like frequency and vibration amplitude was noted based on the analysis of available theoretical studies, simulations and experiments. The influence of parameters of the atomized fluid-like viscosity and surface tension on process parameters was also mentioned. The objective of this study is further research on the feasibility of using ultrasonic atomization to examine the properties of liquids, especially metals in liquid state. It attempts to close a gap in existing knowledge in searching for a new, possibly simple and cost-effective method to study the properties of liquid metals and further clarify the relationship between ultrasonic atomization parameters (amplitude, frequency, characteristics of metal being spilled on a vibrating surface) and obtained atomization results meant by average particle size and atomization time. Using numerical modeling (finite element method and computational fluid dynamics) as a methodology, combined with tests of using ultrasonic atomization as an instrument to determine properties of liquid metals, was considered as an introduction to a series of experiments. These tests were followed by real experiments that are also presented. At the first stage, numerical modeling was applied to a case of a specific liquid being spilled over a vibrating surface of different angles of inclination and specified, constant frequency and amplitude. The results of the simulation are in line with the current state of knowledge about ultrasonic atomization. Moreover, they can provide some more information on scalability, thus easing the comparison of the results of other experiments presented in the available literature. As a result, the relationship between fluid properties and the average size of atomized particles was demonstrated independently of the surface inclination angle. In the same way, the dependence of successful atomization on a sufficiently thin layer of a liquid was demonstrated. Thirdly, a correlation between the aforementioned layer thickness and the value of vibration amplitude has also been shown. Taking all the above into consideration, ultrasonic atomization can also be considered a research method and can be applied to study the properties of liquid metals. Further research, simulations and experimentation will be conducted to verify, develop and describe this method in full. Full article

Slight changes in the local properties of a transmission line, dipped in a liquid, can be used to estimate its level through two different determination techniques, involving the capacitance and electromagnetic wave speed, measured by the time of flight. Indeed, the overall capacitance of a transmission line varies linearly with the liquid level, as well as the time of flight of the electromagnetic wave. Both quantities can be estimated via the measurement of a phase shift at radio frequencies, and the simultaneous measurements can be realized using a compact and low-cost design working at a few megahertz. This paper presents a further improvement in sensitivity to challenge the performance of this kind of level sensor, dealing with liquids with low dielectric constants. To better describe this effect, a study on the overall capacitance of different transmission path segments was conducted in COMSOL Multiphysics. The level measurement was performed experimentally on the realized prototype while considering the measured phase shift as a function of the liquid level, for both an unshielded twisted-pair and magnet wires. As the results showed, with the magnet wires the sensitivity was improved by a factor of about 4, consistently aligning with the simulation results and providing a predictable phase shift response with increasing liquid levels. Consequently, magnet wire is a good choice for precise level measurements through RF phase shifts, especially in the case of low relative permittivity liquids. Full article