Measurement Methodology Research Articles

Bioethanol burner operating parameters optimization: Effects of burner opening area modulation on heat output and flue gas composition

Bioethanol burners are significantly expanding devices in Europe, still considered preferably as the design element while its possible importance in the energy system of the household used to be neglected. The aim of this study was to determine the operating techno-environmental parameters as the heat output and the flue gas composition of the bioethanol fireplace with vortex flame. The measurement methodology was based on actual valid standard EN 16647 Fireplaces for Liquid Fuel. In general, three ethanol-based fuels were tested in combination with one bioethanol burner equipped with different regulation rings changing burner opening area. The average reached heat energy output ranged between 3.97 and 2.22 kW with maximal burner opening area (without the usage of regulation rings) for different fuels. By usage of the regulation rings, the heat energy output was reduced to 35 – 40 % of the nominal average heat output. Simultaneously the time of the burning of one fuel dose can be increased by regulation ring usage up to 195 % of the combustion time without the regulation ring. By placing the regulation rings on the burner bowl opening area, the flue gas composition was affected positively in terms of CO and negatively in terms of NOx.

A novel mirror-assisted method for full-field vibration measurement of a hollow cylinder using a three-dimensional continuously scanning laser Doppler vibrometer system

A novel general-purpose three-dimensional (3D) continuously scanning laser Doppler vibrometer (CSLDV) system was recently developed by the authors to measure 3D vibration of a structure with a curved surface. As a non-contact system, it can avoid the mass-loading problem in 3D vibration measurement using triaxial accelerometers. In previous studies, the 3D CSLDV system was used to measure 3D full-field vibration of a turbine blade with a curved surface and identify its operating deflection shapes (ODSs) and mode shapes. The 3D CSLDV system had the same level of accuracy as that with a commercial 3D scanning laser Doppler vibrometer system, but can measure many more points in much less time than the latter. However, the 3D CSLDV system can be limited by its field of view, which is a common problem for optical-based measurement devices. Moving the 3D CSLDV system to different positions to measure different parts of a test structure is not practical during 3D CSLDV measurement, since the system has to be re-calibrated once it has been moved, which can be time-consuming and introduce measurement errors. This work proposes a novel mirror-assisted testing methodology for 3D CSLDV measurement that aims to measure vibration of difficult-to-access areas of a structure without moving the 3D CSLDV system during the test, and stitch ODSs of its different parts together to obtain its panoramic 3D ODSs. The proposed methodology includes a novel scan trajectory design method that uses virtual areas of the structure behind the mirror to conduct continuous and synchronous scanning of three laser spots, and a novel velocity transformation method that uses virtual positions of three laser heads behind the mirror to stitch ODSs of different parts of the structure together. To demonstrate the proposed methodology, 3D CSLDV measurement is conducted on an aluminum hollow cylinder specimen, which has difficult-to-access areas such as its side and back surfaces, with the assistance of the mirror to obtain its panoramic 3D ODSs corresponding to its first two modes. Comparison between identified ODSs of the hollow cylinder specimen from the experiment and mode shapes from its finite element model is made and modal assurance criterion values are larger than 0.98.

Capacitance-based measurement of volume fraction, velocity, and mass flow rate of cryogenic nitrogen two-phase flow

Cryogenic fluid flow is a critical measurement parameter but is difficult to properly measure due to the extreme environmental conditions and the frequent presence of multiphase flow during saturated liquid transfers. Multiphase flow proves challenging for most flow measurement methodologies; furthermore, additional measurements of volume fraction, quality, and slip velocity are often required. In-line capacitance-based sensors have the potential to overcome these limitations. In this paper, a capacitance sensor in a multiphase cryogenic flow loop is evaluated for its ability to measure liquid volume fraction, gas phase velocity, and total mass flow rate for two-phase cryogenic nitrogen flow.

ALIGNING PROFIT WITH PLANET: STRATEGIES AND IMPLICATIONS OF SUSTAINABLE FINANCE IN THE MODERN ECONOMY

In the wake of escalating environmental concerns and the imperative to address climate change, the integration of sustainability principles into financial practices has emerged as a critical avenue for fostering a more environmentally conscious economy. This research paper delves into the strategies and implications of sustainable finance, aiming to align profit motives with planetary well-being. The paper explores the evolution of sustainable finance, tracing its roots from ethical investing to the contemporary landscape of Environmental, Social, and Governance (ESG) criteria integration. Drawing on a comprehensive review of existing literature and case studies, the paper elucidates various sustainable finance instruments and mechanisms, including green bonds, impact investing, and sustainability- linked loans. Furthermore, it examines the motivations driving businesses and financial institutions to embrace sustainable finance, ranging from risk mitigation and regulatory compliance to reputational enhancement and long-term value creation. Moreover, the paper investigates the challenges and opportunities associated with mainstreaming sustainable finance practices, highlighting issues such as data quality, measurement methodologies, and the need for standardized reporting frameworks. Additionally, it discusses the role of policymakers, regulators, and industry stakeholders in fostering an enabling environment for sustainable finance adoption. Finally, the paper concludes with reflections on the broader implications of sustainable finance for economic growth, social equity, and environmental stewardship, underscoring its potential to catalyze systemic change in the modern economy towards a more sustainable and resilient future. Keywords: sustainable finance, economy, environment, climate.

Role of Market Segmentation and the Impact on Alibaba Company Online Business

This study investigates the influence of market segmentation on Chinese internet companies, focusing on measurability, market demand, and entry barriers. It aims to fill a gap in the existing literature by analyzing how these factors affect segmentation methods, particularly in enterprises like Alibaba. Employing a quantitative approach, the research used surveys distributed to employees and senior managers from twenty randomly selected Chinese enterprises. The survey, developed with input from literature review and expert consultation, covered various aspects including measurement methodologies, market demand, entry barriers, and market segmentation. Data analysis involved statistical techniques such as Cronbach alpha, factor loading analysis, Pearson correlation analysis, and multiple linear regression analysis. Results indicated that market demand significantly influences segmentation strategies and decision-making, emphasizing the importance of understanding consumer preferences. Entry barriers were found to shape market segments and strategies, underscoring the need for firms to align their strategies with market demands to deliver tailored products. The study sheds light on the complexities of China's market dynamics and entry barriers, emphasizing the strategic importance of addressing these challenges and the impact of market demand on segmentation. These findings offer practical insights for navigating the Chinese market and contribute to academic understanding of the relationship between market segmentation, consumer behavior, and business strategy in Chinese online companies.

Methodology of Chip Temperature Measurement and Safety Machining Assessment in Dry Rough Milling of Magnesium Alloys Using Different Helix Angle Tools.

This paper presents the methodology of measuring chip temperature in the cutting zone in the rough milling of magnesium alloys. Infrared measurements are taken to determine the effect of variable cutting speed, feed per tooth, and depth of cut on the maximum temperature of chips. Thermal images of chip temperature for a generated collective frame and corresponding histograms are presented. Chip temperatures are presented in numerical terms as median and average values; maximum and minimum values; range; and standard deviation. Box plots are also shown for selected machining conditions. The problems arising during signal recording with a mean emissivity coefficient ε = 0.13, a value which is dedicated during machining magnesium alloys, are discussed in detail. Chip temperatures obtained in the tests do not exceed approx. 420 °C. Therefore, the dry rough milling process carried out with carbide tools with different blade geometries can be considered safe for a wide range of machining parameters. The proposed methodology of chip temperature measurement and result processing is a new and effective approach to safety assessment in the dry milling of magnesium alloys.

An uncertainty methodology for solar occultation flux measurements: ammonia emissions from livestock production

Abstract. Ammonia (NH3) emissions can negatively affect ecosystems and human health, so they should be monitored and mitigated. This study presents methodology for the estimation of uncertainties in NH3 emissions measurements using the solar occultation flux (SOF) method. The reactive nature of NH3 makes its measurement challenging, but SOF offers a reliable open-path passive method which utilizes solar spectrum data, thereby avoiding gas adsorption within the instrument. To compute NH3 gas fluxes, horizontal and vertical wind speed profiles, as well as plume height estimates and spatially resolved column measurements, are integrated. A unique aspect of this work is the first-time description of plume height estimations derived from ground and column NH3 concentration measurements aimed at uncertainty reduction. Initial validation tests indicated measurement errors between −31 % and +14 % on average, which was slightly larger than the estimated expanded uncertainty ranging from ± 12 % to ± 17 %. Application of the methodology to assess emission rates from farms of various sizes showed uncertainties between ± 21 % and ± 37 %, generally influenced by systematic wind uncertainties and random errors. The method demonstrates the capacity to measure NH3 emissions from both small (∼ 0.5–1 kg h−1) and large (∼ 100 kg h−1) sources in high-density farming areas. Generally, the SOF method provided an expanded uncertainty below 30 % in measuring NH3 emissions from livestock production, which could be further improved by adhering to best application practices. This paper's findings offer the potential for broader applications, such as measuring NH3 fluxes from fertilized fields and in the oil and gas sector. However, these applications would require further research to adapt and refine the methodologies for these specific contexts.

Investigation of the asymmetric flow structure in a hydrocyclone

AbstractThe flow field of a hydrocyclone was investigated using both computational fluid dynamics (CFD) and particle image velocimetry (PIV). A refractive index matching method was employed to improve the precision of the PIV measurements. The CFD results are in good agreement with PIV measurements. Detailed analysis reveals significant axial asymmetry in the velocity components, with the radial velocity component exhibiting notable disparities. This observation is supported by quantitative data comparing different sections of the hydrocyclone. It is further found that the asymmetry might be mainly attributed to the secondary vortexes with the single inlet of the hydrocyclone. And the secondary vortexes, superimposed on the primary flow rather than existing on its own, spiral downwards from near the inlet towards the underflow orifice. It is hypothesized that specific boundary effects and pressure gradients play a pivotal role in the formation of secondary flows. This assumption is grounded on both theoretical considerations and empirical observations, suggesting that these factors significantly influence the flow dynamics within the hydrocyclone. The insights gained from our measurement methodology and enhanced understanding of secondary flows within hydrocyclones are not only poised to serve as valuable references for fellow researchers but also have the potential to inform the design and operational optimization of hydrocyclones for improved efficiency and performance.

Integration into 3D Printing for Image Processing using AI ML

The challenges of physical measurement for prosthetic development and highlight how our integrated tool offers a remote solution to address these challenges, promoting accessibility, convenience, and active participation in the prosthetic design process. Our Measurement Module for Prosthetic Hand Dimensions is a comparison of Image Processing and Distance Measurement Methods The creation of a module to precisely measure finger dimensions for the creation of prosthetic hands is the main goal of this research project. The module provides distance measurement and image-based input as two different ways to get dimensions. Users place their hands at predetermined distances from a screen in the distance measurement option, while users submit photographs of their hands with reference objects for scale in the image based input option. In order To provide a proper fit and functionality, the collected dimensions are an essential component of the prosthetic hand construction process. The study contrasts the efficiency of distance measurement methods employing cameras or other cameras with image processing techniques like edge recognition and contour analysis. Accuracy, usability, and efficiency are among the factors that are assessed to identify the best method for acquiring dimensions. OpenCV for image processing, TensorFlow for machine learning-based analysis, Tkinter for UI design, Mediapipe for landmark identification and hand tracking, and NumPy for numerical operations are just a few of the open-source libraries that are used in this module. The module's possible influence on improving the creation and customization of prosthetic hands is also covered. By offering insights into effective and precise dimension measurement methodologies for customized prosthetic hand design, the study's findings advance the area of prosthetics

A Direct Assessment of Noninvasive Continuous Blood Pressure Monitoring in the Emergency Department and Intensive Care Unit

IntroductionNoninvasive continuous blood pressure monitoring has the potential to improve patient treatment in the hospital setting. Such noninvasive devices can be applied earlier in the treatment process to empower nurses and clinicians to react more quickly to patient deterioration with the added benefit of eliminating the risks associated with invasive monitoring. However, emerging technologies must be capable of reproducing current clinical measures for medical decision making. MethodsThis study aimed to determine the usability and willingness of nurses to implement a noninvasive continuous blood pressure monitoring device. The secondary aim directly compared the systolic blood pressure, diastolic blood pressure, and mean arterial pressure values recorded by the device (VitalStream; CareTaker Medical LLC, Charlottesville, VA) with the “gold standard” brachial cuff and arterial line measures recorded in the emergency department and intensive care unit settings. ResultsVitalStream was similarly received by nurses in the emergency department and intensive care setting, but ultimately had greater promotion from emergency nurses. Despite some statistical similarity between measurement methodologies, all direct comparisons were found to not meet the Association for the Advancement of Medical Instrumentation 2008 and Association for the Advancement of Medical Instrumentation / European Society of Hypertension / International Organization for Standardization 2019 consensus statement criteria for acceptable blood pressure measure differences between the VitalStream and “gold standard” clinical measures. In all instances, the standard deviation of the Bland-Altman bias exceeded 8 mm Hg with less than 85% of paired differences falling within 10 mm Hg of the “gold standard.” DiscussionTaken together, the tested device requires additional postprocessing for medical decision making in trauma or emergent care.

Experimental and numerical gust identification using deep learning models

Identifying gusts and turbulence events is of primary importance for designing future gust load alleviation systems, calculating airframe load, and analysing incidents. Due to the impossibility of their direct measurement, indirect methods are used and ad hoc experiments are necessary to validate the methodology. This paper employs Convolutional Neural Network and Long Short Term Memory (CNN-LSTM) as well as CNN models for in-flight gust identification. Two aeroelastic models, with different levels of fidelity, representative of a civil and commercial aircraft, are used to generate gust responses to train and test the Deep Learning (DL) models. The results highlight the capability of both LSTM-CNN and CNN models in reconstructing gusts across the entire flight envelope of a civil commercial aircraft. The CNN model demonstrated its ability to identify gusts and turbulence when they occur concurrently, similar to real-world scenarios, in a significantly shorter amount of time. Furthermore, its application to wind tunnel gust response measurements, where the inflow has previously been characterised, demonstrated the effectiveness of the proposed methodology for experimental measurements.

Global Assessment of Palliative Care Need: Serious Health-Related Suffering Measurement Methodology

ContextInequities and gaps in palliative care access are a serious impediment to health systems especially in low- and middle-income countries and the accurate measurement of need across health conditions is a critical step to understanding and addressing the issue. Serious Health-related Suffering (SHS) is a novel methodology to measure the palliative care need and was originally developed by The Lancet Commission on Global Access to Palliative Care and Pain Relief. In 2015, the first iteration – SHS 1.0 – was estimated at over 61 million people worldwide experiencing at least 6 billion days of SHS annually as a result of life-limiting and life-threatening conditions. ObjectivesIn this paper, an updated methodology - SHS 2.0 - is presented building on the work of the Lancet Commission and detailing calculations, data requirements, limitations, and assumptions. Methods and ResultsThe updates to the original methodology focus on measuring the number of people who die with (decedents) or live with (non-decedents) SHS in a given year to assess the number of people in need of palliative care across health conditions and populations. Detail on the methodology for measuring the number of days of SHS that was pioneered by the Lancet Commission, is also shared, as this second measure is essential for determining the health system responses that are necessary to address palliative care need and must be a priority for future methodological work on SHS. ConclusionsThe methodology encompasses opportunities for applying SHS to future policy making assessment of future research priorities particularly in light of the dearth of data from low- and middle-income countries, and sharing of directions for future work to develop SHS 3.0.

Multi-physical simulation of an inductive heat treatment process on 50CrMo4 steel rods and validation by HEXRD cross-sectional measurements

A multi-physical finite element model for the induction hardening of a 50CrMo4 steel rod was implemented in Abaqus, including an electromagnetic, thermal, mechanical, and metallurgical model describing the individual phenomena taking place during the process. For induction heating, a linearization scheme for the nonlinear permeability of steel was implemented. The model was validated by recreating a previously published experiment with the model and using the calculated residual stress data as a comparison to the measured stresses. To ensure a valid comparison, the sample preparation process and measurement methodology were considered for the simulation and a good agreement between the measured and calculated stress distributions was obtained. Thus the distribution and time evolution of several quantities such as temperature, phase fractions and plastic strain can be examined to gain insight into the formation of residual stresses.

Salivary High-Sensitivity C-Reactive Protein and Its Clinical Relevance in Modern Medicine: A Comprehensive Review.

High-sensitivity C-reactive protein (hsCRP) has emerged as a critical biomarker in inflammation, offering insights into various chronic diseases. However, traditional blood-based assays for hsCRP measurement pose limitations regarding invasiveness and cost. In recent years, saliva has garnered attention as an alternative diagnostic medium, presenting a noninvasive and easily accessible option for biomarker analysis. Salivary hsCRP has thus emerged as a promising avenue for research and clinical application, offering potential advantages over blood-based assays. This comprehensive review aims to elucidate the biological basis of salivary hsCRP, its clinical applications, and methodologies for measurement. By exploring its diagnostic potential, prognostic value, and implications for treatment monitoring, this review highlights the potential impact of salivary hsCRP in modern medicine. Moreover, it emphasizes the need for continued exploration, validation, and integration of salivary hsCRP into routine clinical practice to realize its full potential for enhancing patient care and advancing personalized medicine approaches.

Improving Aerosol Characterization Using an Optical Particle Counter Coupled with a Quartz Crystal Microbalance with an Integrated Microheater.

Aerosols, as well as suspended particulate matter, impact atmospheric pollution, the climate, and human health, directly or indirectly. Particle size, chemical composition, and other aerosol characteristics are determinant factors for atmospheric pollution dynamics and more. In the last decade, low-cost devices have been widely used in instrumentation to measure aerosols. However, they present some issues, such as the problem of discriminating whether the aerosol is composed of liquid particles or solid. This issue could lead to errors in the estimation of mass concentration in monitoring environments where there is fog. In this study, we investigate the use of an optical particle counter (OPC) coupled to a quartz crystal microbalance with an integrated microheater (H-QCM) to enhance measurement performances. The H-QCM was used not only to measure the collected mass on its surface but also, by using the integrated microheater, it was able to heat the collected mass by performing heating cycles. In particular, we tested the developed system with aerosolized saline solutions of sodium chloride (NaCl), with three decreasing concentrations of salt and three electronic cigarette solutions (e-liquid), with different concentrations of propylene glycol and glycerin mixtures. The results showed that the OPC coherently counted the salt dilution effects, and the H-QCM output confirmed the presence of liquid and solid particles in the aerosols. In the case of e-liquid aerosols, the OPC counted the particles, and the HQCM output highlighted that in the aerosol, there were no solid particles but a liquid phase only. These findings contribute to the refinement of aerosol measurement methodologies by low-cost sensors, fostering a more comprehensive understanding.

Benzene: A critical review on measurement methodology, certified reference material, exposure limits with its impact on human health and mitigation strategies.

Benzene is a carcinogenic pollutant with significant emission sources present in the atmosphere. The need for accurate and precise measurement of benzene in the atmosphere has become increasingly evident due to its toxicity and the adverse health effects associated with exposure to different concentrations. Certified reference material (CRM) is essential to establish the traceability of measurement results. The present review compiles the available national and international measurement methods, certified reference materials (CRMs) for benzene and the limit of benzene in fuel composition (v/v) worldwide. Overall, the review indicates the benzene level in the atmosphere and the resulting impacts on the environment and human health, which frequently exceed the exposure limits of different environment regulatory agencies. An extensive literature review was conducted to gather information on monitoring and analysis methods for benzene, revealing that the most preferred method, i.e. Gas Chromatography- Flame Ionization Detector and Mass Spectrometry, is neither cost-effective nor suitable for real-time continuous monitoring. By analysing existing literature and studies, this review will shed light on the understanding of the importance of benzene pollution monitoring in ambient air and its implications for public health. Additionally, it will reflect the mitigation strategies applied by regulators & need for future revisions of air quality guidelines.

The model of the value system of Russian youth based on Bayesian intellectual measurements

Purpose: of the article is to develop a model of the value system of Russian youth, which can form the basis for the formation of the orientations of young people necessary for the state, contributing to the sustainable development of the Russian Federation. Methods: the article used both traditional methods of scientifi c analysis and methods of Bayesian intelligent measurement methodology used in conditions of uncertainty, inaccuracy and incompleteness of data characteristic of social and socio-economic systems. Results: in the presented study, the extensible hierarchical information model of the value system of Russian youth has been developed. The methodology for processing questionnaire data has been developed, the results of which are presented on numerical and linguistic scales, which makes it possible to take into account the uncertainty of the information received. According to the results of the survey of university students of 10 subjects of the Russian Federation aged 17 to 30 years, a total of 1816 people obtained the values of factors characterizing the value world of Russian youth, which allowed her to form her portrait. Some value factors of young people of the Tula region are evaluated and analyzed. Conclusions and Relevance: the proposed model and methodology for processing personal data allows us to create the adequate holistic portrait of Russian youth in modern economic conditions. The formation of two groups of young people characterized by unfavorable and favorable value attitudes towards Russian society has been revealed, which in the future may lead to a confl ict of social and economic interests, thereby negatively aff ecting the pace of economic growth and sustainable development of the state. In order to reduce internal tension between youth groups and the formation of values inherent in Russian society, measures at the federal and regional levels are proposed.

Kiln-Furnace System: Validation of a Technology for Producing Charcoal with Less Environmental Impact in Brazil

Brazil is the world’s largest producer of charcoal. Therefore, there is need for improvement in the gravimetric yield of conversion and the reduction of gas emissions, including greenhouse gases (GHGs), released during carbonization. The objective was to apply the methodology of Measurement, Reporting and Verification (MRV) to evaluate the emission of GHG, mainly CO2 and CH4. The charcoal production kiln-furnace system used was composed of 4 kilns with a capacity of ~6 t of wood, each. The MRV cluster of coal gravimetric yield and gas burners were used to determine the gravimetric yield and burner efficiency and thus evaluate the emission of GHGs generated in the carbonization system. The carbonization was performed in an isolated way producing, in total, 3.34 t of charcoal, with an average gravimetric yield of 25.82%. The MRV methodology was effective for evaluating the GHG emissions. The wood burner reduced by 50% the methane burning and provided a reduction of 0.392 tCO2 eq (23.91%). The humidity of wood and high precipitation were the main limiting factors in this research, and responsible for the decrease in the gravimetric yield. The kiln-furnace system was effective for a sustainable production with the use of non-continuous carbonization gas burners.

A methodology for image-based measurement of plate movement in disengaged wet clutches

The drag loss behavior of a disengaged wet clutch is influenced, among other things, by the movement of the plates. Therefore, knowledge about the plate movement is essential for investigating and optimizing the drag loss behavior. This paper presents a methodology for image-based measurement of plate movement in disengaged wet clutches. A drag torque test rig is equipped with a camera to create the image series. The oil displacement from the measuring zone is crucial to obtain permanent optical access to the clutch pack. The rough plate positions are determined by segmentation using thresholding and template matching. Using the Canny edge detector significantly improves the accuracy of the position evaluation. The plate positions are finally converted into a metric unit based on the real plate thicknesses. The clearances are calculated from the determined positions of two adjacent plates. In the ideal case, an evaluation accuracy in the range of a few micrometers can be achieved. The image evaluation methodology is universally applicable to different clutch sizes, friction systems, plate types, and plate numbers. The methodology enables researchers to generate fundamental knowledge and derive design guidelines based on this, for example. In the development phase, it can also be used to optimize the design and operating parameters.

An Edge Cloud Based Coordination Platform for Multi-user AR Applications

Augmented Reality (AR) applications can reshape our society enabling novel ways of interactions and immersive experiences in many fields. However, multi-user and collaborative AR applications pose several challenges. The expected user experience requires accurate position and orientation information for each device and precise synchronization of the respective coordinate systems in real-time. Unlike mobile phones or AR glasses running on battery with constrained resource capacity, cloud and edge platforms can provide the computing power for the core functions under the hood. In this paper, we propose a novel edge cloud based platform for multi-user AR applications realizing an essential coordination service among the users. The latency critical, computation intensive Simultaneous Localization And Mapping (SLAM) function is offloaded from the device to the edge cloud infrastructure. Our solution is built on open-source SLAM libraries and the Robot Operating System (ROS). Our contribution is threefold. First, we propose an extensible, edge cloud based AR architecture. Second, we develop a proof-of-concept prototype supporting multiple devices and building on an AI-based SLAM selection component. Third, a dedicated measurement methodology is described, including energy consumption aspects as well, and the overall performance of the system is evaluated via real experiments.