Industrial applications of power electronics

Electronic applications use a wide variety of materials, knowledge, and devices, which pave the road to creative design, development, and the creation of countless electronic circuits with the purpose of incorporating them in electronic products. Therefore, power electronics have been fully introduced in industry, in applications such as power supplies, converters, inverters, battery chargers, temperature control, variable speed motors, by studying the effects and the adaptation of electronic power systems to industrial processes. Recently, the role of power electronics has been gaining special significance regarding energy conservation and environmental control. The reality is that the demand for electrical energy grows in a directly proportional manner with the improvement in quality of life. Consequently, the design, development, and optimization of power electronics and controller devices are essential to face forthcoming challenges. In this Special Issue, 19 selected and peer-reviewed papers discussing a wide range of topics contribute to addressing a wide variety of themes, such as motor drives, AC-DC and DC-DC converters, electromagnetic compatibility and multilevel converters.publishersversionpublishe

A review of data mining applications in semiconductor manufacturing

The authors acknowledge Fundacao para a Ciencia e a Tecnologia (FCT-MCTES) for its financial support via the project UIDB/00667/2020 (UNIDEMI).For decades, industrial companies have been collecting and storing high amounts of data with the aim of better controlling and managing their processes. However, this vast amount of information and hidden knowledge implicit in all of this data could be utilized more efficiently. With the help of data mining techniques unknown relationships can be systematically discovered. The production of semiconductors is a highly complex process, which entails several subprocesses that employ a diverse array of equipment. The size of the semiconductors signifies a high number of units can be produced, which require huge amounts of data in order to be able to control and improve the semiconductor manufacturing process. Therefore, in this paper a structured review is made through a sample of 137 papers of the published articles in the scientific community regarding data mining applications in semiconductor manufacturing. A detailed bibliometric analysis is also made. All data mining applications are classified in function of the application area. The results are then analyzed and conclusions are drawn.publishersversionpublishe

Reliability assessment of the ocean thermal energy conversion systems through Monte Carlo simulation considering outside temperature variation

Open access funding provided by FCT|FCCN (b-on). Publisher Copyright: © 2023, The Author(s).The ocean thermal energy conversion (OTEC) systems, as renewable energy-based power plants, have the potential to play a significant role in meeting future electricity demands due to the vast expanse of the world's oceans. These systems employ the temperature difference between surface ocean waters and deep ocean waters to drive a thermodynamic cycle and produce electricity. The temperature of deep ocean waters, approximately 1000 m below the surface, is approximately 4 °C, while surface ocean temperatures typically range between 20 and 30 °C. The generated power of OTEC systems is dependent on these temperature differences and may vary with changes in surface ocean temperatures. In this study, the main focus is to find the impact of temperature variation on the failure rates of OTEC system components and the generated power output of these plants. The findings indicate that as the demand for the power system increases, its reliability decreases. In order to improve the reliability of the power system, the integration of a new generation unit, such as the close cycle OTEC power plant under investigation, could be necessary. The findings also indicate the importance of considering temperature variation in the evaluation of the reliability of such types of power plants based on renewable energy.publishersversionepub_ahead_of_prin

Energy management of virtual power plant considering distributed generation sizing and pricing

UID/EMS/00667/2019The energy management of virtual power plants faces some fundamental challenges that make it complicated compared to conventional power plants, such as uncertainty in production, consumption, energy price, and availability of network components. Continuous monitoring and scaling of network gain status, using smart grids provides valuable instantaneous information about network conditions such as production, consumption, power lines, and network availability. Therefore, by creating a bidirectional communication between the energy management system and the grid users such as producers or energy applicants, it will afford a suitable platform to develop more efficient vector of the virtual power plant. The paper is treated with optimal sizing of DG units and the price of their electricity sales to achieve security issues and other technical considerations in the system. The ultimate goal in this study to determine the active demand power required to increase system loading capability and to withstand disturbances. The effect of different types of DG units in simulations is considered and then the efficiency of each equipment such as converters, wind turbines, electrolyzers, etc., is achieved to minimize the total operation cost and losses, improve voltage profiles, and address other security issues and reliability. The simulations are done in three cases and compared with HOMER software to validate the ability of proposed model.publishersversionpublishe

Power quality improvement with a pulse width modulation control method in modular multilevel converters under varying nonlinear loads

UIDB/00667/2020 POCI-01-0145-FEDER-029803 (02/SAICT/2017) POCI-01-0145-FEDER-006961 (UID/EEA/50014/2019)In order to reach better results for pulse width modulation (PWM)-based methods, the reference waveforms known as control laws have to be achieved with good accuracy. In this paper, three control laws are created by considering the harmonic components of modular multilevel converter (MMC) state variables to suppress the circulating currents under nonlinear load variation. The first control law consists of only the harmonic components of the MMC's output currents and voltages. Then, the second-order harmonic of circulating currents is also involved with both upper and lower arm currents in order to attain the second control law. Since circulating current suppression is the main aim of this work, the third control law is formed by measuring all harmonic components of circulating currents which impact on the arm currents as well. By making a comparison between the switching signals generated by the three proposed control laws, it is verified that the second-order harmonic of circulating currents can increase the switching losses. In addition, the existence of all circulating current harmonics causes distributed switching patterns, which is not suitable for the switches' lifetime. Each upper and lower arm has changeable capacitors, named "equivalent submodule (SM) capacitors" in this paper. To further assess these capacitors, eliminating the harmonic components of circulating currents provides fluctuations with smaller magnitudes, as well as a smaller average value for the equivalent capacitors. Moreover, the second-order harmonic has a dominant role that leads to values higher than 3 F for equivalent capacitors. In comparison with the first and second control laws, the use of the third control-law-based method will result in very small circulating currents, since it is trying to control and eliminate all harmonic components of the circulating currents. This result leads to very small magnitudes for both the upper and lower arm currents, noticeably decreasing the total MMC losses. All simulation results are verified using MATLAB software in the SIMULINK environment.publishersversionpublishe

Liquid Mixtures Involving Hydrogenated and Fluorinated Chains: (p, ρ, T, x) Surface of (Ethanol + 2,2,2-Trifluoroethanol), Experimental and Simulation

The effect of mixing hydrogenated and fluorinated molecules that simultaneously interact through strong hydrogen bonding was investigated: (ethanol + 2,2,2-trifluoroethanol) binary mixtures were studied both experimentally and by computer simulation. This mixture displays a very complex behavior when compared with mixtures of hydrogenated alcohols and mixtures of alkanes and perfluoroalkanes. The excess volumes are large and positive (unlike those of mixtures of hydrogenated alchools), while the excess enthalpies are large and negative (contrasting with those of mixtures of alkanes and perfluoroalkanes). In this work, the liquid density of the mixtures was measured as a function of composition, at several temperatures from 278.15 to 353.15 K and from atmospheric pressure up to 70 MPa. The corresponding excess molar volumes, compressibilities, and expansivities were calculated over the whole (p, ρ, T, x) surface. In order to obtain molecular level insight, the behavior of the mixture was also studied by molecular dynamics simulation, using the OPLS-AA force field. The combined analysis of the experimental and simulation results indicates that the peculiar phase behavior of this system stems from a balance between the weak dispersion forces between the hydrogenated and fluorinated groups and a preferential hydrogen bond between ethanol and 2,2,2-trifluoroethanol. Additionally, it was observed that a 25% reduction of the F−H dispersive interaction in the simulations brings agreement between the experimental and simulated excess enthalpy but produces no effect in the excess volumes. This reveals that the main reason causing the volume increase in these systems is not entirely related to the weak dispersive interactions, as it is usually assumed, and should thus be connected to the repulsive part of the intermolecular potential

Modeling of Soybean under Present and Future Climates in Mozambique

Citation: Talacuece, M. A. D., Justino, F. B., Rodrigues, R. D., Flores, M. E. P., Nascimento, J. G., & Santos, E. A. (2016). Modeling of Soybean under Present and Future Climates in Mozambique. Climate, 4(2), 14. doi:10.3390/cli4020031This study aims to calibrate and validate the generic crop model (CROPGRO-Soybean) and estimate the soybean yield, considering simulations with different sowing times for the current period (1990-2013) and future climate scenario (2014-2030). The database used came from observed data, nine climate models of CORDEX (Coordinated Regional climate Downscaling Experiment)-Africa framework and MERRA (Modern Era Retrospective-Analysis for Research and Applications) reanalysis. The calibration and validation data for the model were acquired in field experiments, carried out in the 2009/2010 and 2010/2011 growing seasons in the experimental area of the International Institute of Tropical Agriculture (IITA) in Angonia, Mozambique. The yield of two soybean cultivars: Tgx 1740-2F and Tgx 1908-8F was evaluated in the experiments and modeled for two distinct CO2 concentrations. Our model simulation results indicate that the fertilization effect leads to yield gains for both cultivars, ranging from 11.4% (Tgx 1908-8F) to 15% (Tgx 1740-2Fm) when compared to the performance of those cultivars under current CO2 atmospheric concentration. Moreover, our results show that MERRA, the RegCM4 (Regional Climatic Model version 4) and CNRM-CM5 (Centre National de Recherches Meteorologiques - Climatic Model version 5) models provided more accurate estimates of yield, while others models underestimate yield as compared to observations, a fact that was demonstrated to be related to the model's capability of reproducing the precipitation and the surface radiation amount

Permeability coefficients and vapor pressure determination for fragrance materials

Objective This study aims to correlate new experimental data relevant to the description of the combined evaporation/permeation process of a perfume applied onto the skin. Methods The vapor pressure data was measured by thermogravimetric analysis (TG‐DTA). The Antoine constants and the Clarke & Glew parameters were determined for the same set of fragrance molecules to describe its low vapor pressures at new temperature ranges. The permeability coefficient of a set of 14 fragrance molecules in ethanolic solution was determined by Franz diffusion cell experiments, using porcine skin. The samples were analyzed by gas chromatography with a flame ionization detector (GC/FID) and high‐performance liquid chromatography with UV visible detector (HPLC/UV). A QSAR model was proposed to correlate the experimental data. Results The Antoine constants were determined and presented low standard deviations. The Clarke & Glew physically significant parameters were obtained along with its statistical analysis. The fitting is good since the magnitude order is in accordance with the literature, associated with the low correlation between the estimated parameters and low standard deviations. The presented correlation, based on a mixture using only ethanol as solvent, showed better results than previous QSAR models with a standard relative deviation (σr) of 0.190, a standard error (SE) of 0.397, and a determination coefficient (R2) of 0.7786. Conclusion The dataset is still small compared to larger and more general QSAR models; however, it is much more specific as to the type of solvent and class of materials studied. This work represents an advance for the modeling of the perfume diffusion process since it specifies important properties that until then had been treated in a more general way.info:eu-repo/semantics/acceptedVersio

a cross-sectional population-based study

Funding Information: We thank Prof. Carla Nunes (NOVA National School of Public Health – Universidade NOVA de Lisboa) for the valuable insights and discussions in the conceptualization of this project. We thank the EpiDoc Unit and EpiReumaPt team for conceptualizing, planning, and implementing the main research project. We also acknowledge the support of CHRC (UIDP/04923/2020), granted by national funds through Fundação Ciência e Tecnologia, IP. Funding Information: This study received funding from an independent research grant (ID: 64165707) by Pfizer, and the first author received a grant from Fundação Ciência e Tecnologia, IP under the PhD grant SFRH/BD/148420/2019. The funders were not involved in study design; collection, analysis, or interpretation of data; or writing this article or the decision to submit it for publication. Publisher Copyright: © 2023, The Author(s).Background: Pain due to knee and / or hip osteoarthritis (HKOA) is the most common symptom for seeking healthcare. Pain interferes on daily activities, social and occupational participation in people with HKOA. The goal of this study is to estimate the prevalence of unmanageable pain levels (UPL) among people with HKOA), characterize this population and identify factors associated with UPL, and compare therapeutic strategies used by people with UPL versus manageable pain levels (MPL). Methods: We analysed data from the EpiReumaPt study (n = 10,661), that included a representative sample of the Portuguese population. Among these, 1081 participants had a validated diagnosis of HKOA by a rheumatologist. Sociodemographic, lifestyle and health-related data were collected in a structured interview. Pain intensity (NPRS) data were collected in a medical appointment. Painmedication (last month), physiotherapy and surgery were considered as therapies for pain management. UPL was defined as a mean pain intensity in the previous week of ≥5 points on 11-point numeric pain rating scale. The factors associated with UPL were analyzed with logistic regression (p < 0.05, 95%CI). The effect of unmanageable pain levels was assessed by the HOOS/KOOS activities of daily living and quality of life subscales. Symptoms of anxiety and depression were assessed by the Hospital Anxiety and Depression Scale (HADS). Analysis was completed with linear and logistic regression. All analysis were weighted. Results: The estimated prevalence of UPL among people with HKOA was 68.8%. UPL was associated with being female (odds ratio (OR) = 2.36, p < 0.001), being overweight (OR = 1.84, p = 0.035) or obese (OR = 2.26, p = 0.006), and having multimorbidity (OR = 2.08, p = 0.002). People with UPL reported worse performance in activities of daily living and lower quality of life (β = − 21.28, p < 0.001 and β = − 21.19, p < 0.001, respectively) than people with MPL. People with UPL consumed more NSAIDs (22.0%, p = 0.003), opioids (4.8%, p = 0.008), paracetamol (2.7%, p = 0.033), and overall analgesics (7.3%, p = 0.013) than people with MPL. A higher proportion of people with UPL underwent physiotherapy (17.5%, p = 0.002) than people with MPL. Conclusion: Two-thirds of people with HKOA in Portugal have poor management of their pain levels. Clinical and lifestyle factors, that are highly presented in individuals with HKOA, are associated with unmanageable pain. Our results highlighting the need for further research and implementation of effective interventions to improve pain, function and quality of life in people with HKOA.publishersversionpublishe

Herramienta de modelado y análisis estocástico de sistemas biológicos

Los sistemas híbridos cuentan con la atención de gran parte de la comunidad científica por lo atractivo del estudio de sus dinámicas, las continuas y las discretas, y la comprensión de sus interacciones. Entre las más comunes se encuentran aquellas que cambian de estado entre diferentes procesos continuos. También se pueden encontrar formas de interacción que incluyen transiciones discretas supeditadas a evoluciones continuas, u otras como resultados de una decisión, o por la ocurrencia de determinados eventos. El estudio de la distribución probabilísticas de la dinámica discreta y la continua se lleva a cavo por medio del análisis del sistema híbrido estocástico (SHE) que lo modela. Debido a que el modelo numérico, de un SH, es afectado por el problema de la explosión de estados y de ser sumamente exigente en lo que a recursos se refiere, aparece como una opción aceptable la formulación del mismo sistema por medio de un SHP. Estos tipos de sistemas pueden ser analizados por medio de herramientas informáticas con solida base matemática como son los Model Checkers Probabilísticos. Los sistemas biológicos encuadran perfectamente en la clasificación de SHE. En el ámbito de estudio de SB no se cuenta con herramientas que permitan una traducción directa de un SHE, como por ejemplo un sistema de reacciones, a un modelo estocástico factible de ser analizado por herramientas informáticas disponibles en la actualidad como son los model checkers antes mencionados. En nuestra línea de investigación proponemos el estudio de factibilidad y de propuesta de desarrollo de una herramienta de análisis de SB basado en su formulación estocástica. Tenemos como hipótesis de trabajo que el desarrollo de este prototipo de herramienta que permite la obtención de un modelo estocástico a partir de su formulación por medio de reacciones que permitirá analizar el sistema e incrementar la productividad en el estudio de SBs habilitando a su verificación y validación con herramientas novedosas en el área biológica. En una primera etapa se centrará en la obtención de modelos estocásticos de un sistema de reacciones para luego habilitar el análisis basado en probabilidades y en simulaciones probabilísticas basadas en su semántica estocástica.Eje: Innovación en Sistemas de Software.Red de Universidades con Carreras en Informática (RedUNCI