En el presente trabajo se expone una propuesta para el diseño de Objetos de Aprendizaje (OA), que abarca la perspectiva pedagógica y computacional, que permite componer materiales educativos basados en competencias en carreras de ingeniería de acuerdo con los estándares y lineamientos propuestos por CONFEDI. Desde el punto de vista pedagógico se analiza el enfoque de formación por competencias próximo a implementarse en las universidades de Argentina. A partir de la perspectiva computacional, se presenta un patrón de arquitectura modelado a través de una ontología, para la producción de OAs que sigan el enfoque considerado. Como resultado se obtiene un modelo consistente que integra los elementos propuestos, y que además es legible por computadora, lo cual permite su automatizacion.
In this paper, a smart load shedding scheme with a new criterion for a faster load restoration is tested against a genset stalling scenario. Simulation results are presented to prove the concept behind the criterion, which is based on the fundamentals that explain the causes of genset stalling due to abrupt load steps in a microgrid. The criterion allows disconnection times for shed loads to go from a couple of seconds to less than a second compared to previous smart shedding schemes. Thus, it reduces the duration of disturbances in the microgrid and makes place to new possibilities in terms of the load shedding system design. Obtained results show that is possible to improve the restoration time in the smart load shedding scheme for genset in a microgrid.
This paper presents a control based on feedback linearization technique to control a Dual Active Bridge (DAB) Converter feeding a constant power load (CPL). The proposed control law requires knowledge of the load power and its time derivative, for which a non-linear reduced-order observer is designed to estimate these variables. Simulation results are presented to validate the proposed control, showing a good dynamic response of the system under significant variations in the transferred power and changes in the direction of the energy flow.
En este trabajo se propone una estrategia para el control de la diferencia de fase y el balance de las corrientes de rama en convertidores buck con interleaving y control por modos deslizantes. La propuesta consiste en la determinación de la fase de la componente fundamental de la función de deslizamiento mediante lazos de enganche de fase ePLL (enhanced Phased-Locked Loop) y el control de la amplitud de la region de deslizamiento. El balance de valor medio de las corrientes de rama se implementa mediante un control asimétrico de la amplitud de la region deslizamiento. La estrategia admite la reconfiguración del número de ramas, la secuencia y la diferencia de fase con el propósito de lograr tolerancia a fallas, incrementar la eficiencia y reducir el ripple de tension a bornes de la carga. La propuesta se verifica mediante simulación para un convertidor buck de tres ramas y topología maestro–esclavo.
Sporobolus spartinus (Trin.) P.M. Peterson & Saarela (=Spartina argentinensis Parodi, common name: espartillo) is a perennial C4 grass that dominates in many communities from a region named "Bajos Submeridionales" in the northern part of Santa Fe province. It produces high quantity of biomass but, due to its low digestibility, cattle risers often burn it in order to stimulate the growth of more tender leaves. This burnt biomass could be used in order to produce bioenergy, thus knowing its availability is mandatory in order to select areas with higher biomass. In this research, S. spartinus biomass reflectance from a farm near the town of Galvez was measured with i: a multispectral camera mounted in a Drone and ii: a hyperspectral camera in a spectrometer in two different dates, one in October of 2019 and the other in March of 2020. S. spartinus biomass presented higher total biomass (average of 7700 kg of dry matter per hectare) in October and most of it (67%) was senescent biomass while in March, total biomass accounted for 5300 kg per hectare and only 38% of it was standing dead biomass. A Normalized index was able to explain 33% of total biomass variability with both instruments. Due to the fact that either green or senescent biomass can be used for bioenergy, our aim was to estimate those using remotely sensed multispectral images.
This paper exposes the creation of a strategic virtual learning object (VLO) for the teaching and learning of Physics I, more properly Kinematics, applied to engineering and biology degree courses at the National University of San Juan. It is emphasized that it is not an elementary OVA, since it covers most of the content of that learning unit, with a certain pre-established level of depth; it also contains a significant amount of reused objects and resources.Its purpose is to resignify the offer of a hybrid learning experience, based on the Theory of Significant Learning, and methodologically structured from notions of training days in cycles and learning arcs, in order to contemplate greater pedagogical flexibility. It has sought to contribute to the construction of a path for other experiences and reflections on educational strategies in a context of digital and post-pandemic culture.Its implementation was recently carried out in two virtual classrooms as a prototype (and in beta phase) showing very good acceptance by students. It is expected to expand the range of use in the second semester and subsequent years. This offers the student the opportunity to carry out interactive, autonomous, dynamic and personalized learning.
Este trabajo propone un modelo electromecánico no estacionario para simular el comportamiento de propulsores de plasma pulsantes ablativos, con el objetivo de caracterizar el desempeño del propulsor. Además de la ecuación circuital y la ecuación que modela la aceleración de la lámina de plasma, el modelo introduce una ecuación empírica para estimar la masa ablacionada, así como un sistema de ecuaciones basado en la ecuación de Saha, el cual permite modelar la evolución de la densidad del plasma. La introducción de este sistema de ecuaciones requiere de considerar que el sistema se encuentra localmente en equilibrio termodinámico, lo cual se verifica según el criterio de McWhirter. Además, se modela la evolución de la temperatura del plasma mediante la aplicación de la conservación de la energía de la lámina de plasma, considerando el calentamiento por efecto Joule, las pérdidas por radiación y la energía asociada a la fuerza de Lorentz. Al modelo se lo implementa numéricamente, lo que permite estimar parámetros de rendimiento, como la masa ablacionada, el bit de impulso, el impulso específico y la eficiencia propulsiva, entre otros. El modelo ha sido comparado y validado con resultados experimentales de la literatura, demostrando ser capaz de reproducir las variables de desempeño de los APPT dentro de un margen de error del 15 %.
The Serrano forest is the least extensive type of forest in the South American Gran Chaco with a long history of human disturbance that has altered the natural vegetation. This work aims to determine and quantify the changes in Serrano forest cover in the last 30 years based on supervised classifications in three periods (1989, 2004, 2019), with main attention to native forest cover. Supervised land cover classification was performed using Landsat 5 TM and Sentinel-2A images and a spectral indices set. This classification showed a correct differentiation of the evaluated classes, resulting in adequate maps to be used in future studies on the region. Throughout the study period, substantial changes in land use and land cover were found, estimating a 22% loss of native forest in the last 30 years. The main drivers responsible to land cover changes were urbanization, expansion of exotic trees and forest fires.
As unconventional renewable generation is increasingly introduced and the grid becomes more extensive, the task of planning the future transmission facilities required becomes an assignment of growing complexity. In developing economies with limited resources for investment, such as the case of Latin American countries, expanding the network often involves reconfigurations of the grid using existing infrastructure, a situation that is difficult to capture with conventional planning considering only new transmission corridors. Faced with these challenges, selecting and prioritizing candidate facilities is a task that must be analyzed from various angles, such as investment cost, social benefit of the work, system reliability, environmental impact, among others. This paper proposes a methodology for the analysis and prioritization of infrastructure projects in the National Electricity Administration’s Transmission Master Plan based on system reliability indices measured by the expected energy not supplied for N-1 contingencies. To consider the expected value, the probabilities of occurrence of each fault and the average repair time are taken and the energy not supplied, among other reliability index, are calculated. This methodology is applied to an equivalent system of the National Interconnected System considering the inclusion of works and load levels in the year 2030. Finally, with the results obtained from the simulations, it is possible to prioritize the works analyzed according to their impact on the reliability of the Paraguayan electricity system.
Coronary Artery Calcium (CAC) constitutes a highly specific feature of ‘coronary’ atherosclerosis. The aim of this study is to explore the combination of arterial biomechanical parameters, used for general atherosclerosis evaluation, in CAC score assessment, stratified by year of age. Three hundred and fifty individuals participated in the study, with no history of cardiovascular disease. CAC score jointly with ascending aortic diameter (AAD) were determined through multislice computer tomography. Carotid intima-media thickness (cIMT) and presence of carotid and femoral plaques (PAB) were also assessed using B-mode ultrasound. Aortic stiffness was calculated by means of Pulse Wave Velocity (aPWV). Data were grouped by age, thus becoming a stratification factor. Univariate and multiple linear regression (MLR) analysis were applied for CAC score quantification. Univariate analysis evidenced a linear association between log-transformed levels of CACs stratified by age (LCACs) and aPWV (R 2 =0.43, P<0.05), cIMT (R 2 =0.52, P<0.05), AAD (R 2 =0.53, P<0.05), PAB (R 2 =0.46, P<0.05) and SBP (R 2 =0.10, P<0.05). An adjusted determination coefficient (adj. R 2 ) of 0.89 was obtained for MLR, where AAD, cIMT, PAB, SBP and BMI were significantly correlated with LCACs (P<0.05). This analysis provides a holistic description in terms of the contribution of atherosclerosis/arteriosclerosis markers (such as cIMT and aortic diameters) that may suggest the existence of increased levels of age-stratified CAC.
A low power voltage reference with low temperature dependence and multiple outputs is designed and simulated in a CMOS 180 nm process. This circuit is required by the transducer of a gas sensor project planned to be integrated in the same chip. The design is divided in two main parts. One, is a self-biased single output voltage reference with a temperature coefficient of 27ppm/°C obtained by compensating opposite thermal coefficients in the circuit. Employing Montecarlo’s method, the estimated mean value is 828.49mV with standard deviation of 11.25mV at room temperature. Line sensitivity is 0.51%/V from 0.94V to 1.80V and total noise is 180µV RMS . The second part is a circuit that allows generating auxiliary voltages with specifically required values of 0.55V and 1.10V for different stages of the transducer. Total noise for each of these signals are 202µV RMS and 382µV RMS . Total power consumption is about 485nW.
In the state of the art of non-invasive load monitoring study, there are several proposals for the elaboration of datasets of electrical appliance consumption at different test frequencies, which allow the implementation of strategies and algorithms for energy monitoring. This paper presents an high-frequency electrical energy measurement system and digital signal processing to obtain non-conventional features that may be relevant for the study of energy disaggregation in real time. The system consists of the Atmel-DB board, based on the Atmel M90E36A integrated circuit, with channels for three-phase voltage and current measurement, a data acquisition board with an Arduino DUE for communication and a Raspberry Pi running the user interface and high frequency DSP. After a detailed description of the system, an application example is presented where high frequency signal processing is developed.
En este artículo se presenta un algoritmo para la búsqueda manual del tap del transformador de distribución y la búsqueda de los valores óptimos para la configuración de los inversores inteligentes de la generación distribuida fotovoltaica (GD-FV). Mediante esta configuración optima se logra mitigar los problemas de tensión que se producen debido a una alta penetración de GD-FV en redes de distribución. Los inversores inteligentes tienen la capacidad de gestionar la potencia activa y reactiva usando curvas configurables con valores por defecto y mediante un rango de valores establecidos en la norma IEEE 1547-2018. El algoritmo de optimización está basado en el algoritmo genético y permite realizar la búsqueda del óptimo de entre el rango de valores establecidos en la norma. De las simulaciones obtenidas se muestra que el uso de valores optimizados juntamente con una selección adecuada del tap pueden llegar a reducir a cero los problemas de tensión frente al uso de los valores por defecto que recomienda la norma IEEE1547-2018.
Tomando como ejemplo de aplicación, un vehículo aéreo no tripulado con dos brazos y cuatro rotores, en el presente trabajo se lleva cabo una comparación del desempeño de dos sistemas de control. Uno de estos controles fue diseñado mediante técnicas lineales de parámetros variantes, mientras que el otro se basa en la estrategia denominada PID inteligente, técnica adaptativa basada en controles libres de modelo. Ambos controles atacan el problema de tolerancia a fallas con diferentes enfoques para adaptarse a dos casos de fallas, en uno y en dos rotores. Las fallas consideradas son de tipo total y se conocen de ellas el momento en que se producen y el actuador en el cual ocurrió la falla. En este escenario, se lleva a cabo la comparación.
La creciente complejidad de los sistemas industri-ales ha fomentado el surgimiento de nuevas técnicas de análisis de datos para apoyar a los procesos de toma de decisiones. Concretamente, los modelos basados en redes neuronales pro-fundas constituyen una alternativa promisoria para diversas aplicaciones de detección, clasificación y predicción de defectos o fallas que abarca aplicaciones desde el control de calidad de los productos, identificación de defectos en los procesos en una línea de producción hasta predicción de fallas de los equipos tecnologicós. Sin embargo, el exitó de dichos modelos depende sensiblemente de la elección de sus hiper-parametrós para lo cual se requiere de un exhaustivo proceso de configuración que, hoy en día, demanda un alto grado de conocimiento experto. En este contexto, el presente trabajo propone un Sistema Inteligente basado en redes neuronales profundas, dotado con un sistema de auto-ajuste de sus hiper-parametrós, para la detección de defectos y fallas. Dicho sistema integra un algoritmo de Optimización Bayesiana para encontrar la combinación optima de los hiper- párametros que permita alcanzar el mejor desempeño posible del sistema. El sistema inteligente propuesto se prueba en dos casos de estudio de diferente naturaleza y los resultados alcanzado demuestran la efectividad de la propuesta.
The context and trends of Industry 4.0, together with the advancement of cyber-physical systems (CPS) technology, are transforming the way people interact with engineered systems, just as the Internet has transformed the way people interact with information. Progress in the design and development of these CPS is aimed at achieving greater adaptability, resource efficiency, scalability, robustness, security, and ease of design. Moreover, considering the reduced time-to-market, it is necessary to minimize development times. Considering that Petri Nets are a recognized and adequate modeling, analysis, and execution language for reactive, parallel, and concurrent systems, to favor the modeling efforts it is desirable to use the model to automatically obtain part of the system implementation. In this paper we present an algorithm from a modeled system with Petri Nets, to automatically determines the conflict control policies to achieve productivity by the pre-established requirements. Since these CPS interact with dynamic and changing environments, this objective is achieved by making use of learning automata. This paper presents the proposed algorithm, the results obtained from the application to a set of networks, and the analysis of an application case.
This paper presents the design of an IF (Intermediate Frequency) signal receptor in order to modernize the one included on the Vitro RIR-778C tracking radar.The radar’s technique for doing the object tracking is the one called monopulse, therefore this new system has to process the signals according to this method.For a proper signal processing, the IF analog signals are converted to a digital form by undersampling them.The physical device chosen for accomplish this is an FPGA programmed by a hardware description language.Despite the fact that it wasn’t possible to perform real tests in the radar’s environment, final results are promising, being very similar to those who’d been simulated.
False data injection attacks (FDIAs), in which an attacker has access to a number of meters and can corrupt their measurements, is a critical cybersecurity issue in smart grids. In this work, we consider the effectiveness of FDIAs against the Argentine Interconnection System (SADI). We consider a situation in which the attacker is able to influence a small number of devices. Inspired by [1], the problem is examined from the point of view of the grid operator and the attacker. For the control center, we examine the performance of classical LNR and ℐ(x) detectors against FDIAs. From the point of view of the attacker we consider the maximal estimation error that he can induce at the control center subject to a bound on the detection probability of the attack. In addition, we analyze the influence of the grid state covariance matrix in the above problem. Using real and public data for the for the SADI we provides a estimation technique of the state covariance matrix exploiting is low rank structure. Then the resulting estimated covariance matrix is included in our analysis of the FDIAs in the SADI. The results of experiments demonstrate, at least for the SADI, the importance of the structure of the covariance matrix of the states for in the above mentioned trade-offs between the harmfulness of the attacks and the detection performance for the detectors at the control center. In fact, we show that a sufficiently informed attacker can leverage this information to generate stronger attacks.
Population growth in metropolitan areas and the need for infrastructure leads to a rapid and unplanned urbanization process. In Córdoba, Argentina, infrastructure problems have been recognized, such as breakage of houses and buildings, due to a combination of natural (soil instability) and anthropic factors (saturation of wastewater wells). In this study, Ground Surface Subsidence (GSS) was detected through multitemporal SAR (Synthetic Aperture Radar) Interferometry. Specifically, the Parallel Small BAseline Subset (P-SBAS) algorithm was used to process Sentinel 1 images acquired between 2015 and 2021. Main goal was to discover active subsidences for the first time, in places where deformations have already been detected only by cracking and rupture of infrastructure. Velocities of 3-7 cm/year were detected in peripheral neighborhoods such as Villa Libertador and Parque República, located in highly collapsible soils according to geotechnical reports. Results have revealed the magnitude of the problem and its impact on the structure of family homes. The applicability of this technique can be a complement to classical geotechnical approaches. Its relevance in the detection of latent geological hazards for decision-making by local actors is also discussed.
