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Flow control device modeling is an engaging research field for wind turbine optimization, since in recent years wind turbines have grown in proportions and weight. The purpose of the present work was to study the performance and effects generated by a rotating microtab (MT) implemented on the trailing edge of a DU91W250 airfoil through the novel cell-set (CS) model for the first time via CFD techniques. The CS method is based on the reutilization of an already calculated mesh for the addition of new geometries on it. To accomplish that objective, the required region is split from the main domain, and new boundaries are assigned to the mentioned construction. Three different MT lengths were considered: h = 1%, 1.5% and 2% of the airfoil chord length, as well as seven MT orientations (β): from 0° to −90° regarding the horizontal axis, for five angles of attack: 0°, 2°, 4°, 6° and 9°. The numerical results showed that the increases of the β rotating angle and the MT length (h) led to higher aerodynamic performance of the airfoil, CL/CD = 164.10 being the maximum ratio obtained. All the performance curves showed an asymptotic trend as the β angle reduced. Qualitatively, the model behaved as expected, proving the relationship between velocity and pressure. Taking into consideration resulting data, the cell-set method is appropriate for computational testing of trailing edge rotating microtab geometry.
Alejandro Ballesteros-Coll; Koldo Portal-Porras; Unai Fernandez-Gamiz; Ekaitz Zulueta; Jose Manuel Lopez-Guede. Rotating Microtab Implementation on a DU91W250 Airfoil Based on the Cell-Set Model. Sustainability 2021, 13, 9114 .
AMA StyleAlejandro Ballesteros-Coll, Koldo Portal-Porras, Unai Fernandez-Gamiz, Ekaitz Zulueta, Jose Manuel Lopez-Guede. Rotating Microtab Implementation on a DU91W250 Airfoil Based on the Cell-Set Model. Sustainability. 2021; 13 (16):9114.
Chicago/Turabian StyleAlejandro Ballesteros-Coll; Koldo Portal-Porras; Unai Fernandez-Gamiz; Ekaitz Zulueta; Jose Manuel Lopez-Guede. 2021. "Rotating Microtab Implementation on a DU91W250 Airfoil Based on the Cell-Set Model." Sustainability 13, no. 16: 9114.
In this work, a maximum power point tracking (MPPT) system for its application to a new piezoelectric wind energy harvester (PWEH) has been designed and implemented. The motivation for such MPPT unit comes from the power scales of the piezoelectric layers being in the order of μW. In addition, the output generates highly disturbed voltage waveforms with high total harmonic distortion (THD), thereby high THD values cause a certain power loss at the output of the PWEH system and an intense motivation is given to design and implement the system. The proposed MPPT system is widely used for many different harvesting studies, however, in this paper it has been used at the first time for such a distorted waveform to our best knowledge. The MPPT consists of a rectifier unit storing the rectified energy into a capacitor with a certain voltage called VOC (i.e., the open circuit voltage of the harvester), then a dc-dc converter is used with the help of the MPPT unit using the half of VOC as the critical value for the performance of the control. It has been demonstrated that the power loss is nearly half of the power for the MPPT-free system, the efficiency has been increased with a rate of 98% and power consumption is measured as low as 5.29 μW.
Erol Kurt; Davut Özhan; Nicu Bizon; Jose Lopez-Guede. Design and Implementation of a Maximum Power Point Tracking System for a Piezoelectric Wind Energy Harvester Generating High Harmonicity. Sustainability 2021, 13, 7709 .
AMA StyleErol Kurt, Davut Özhan, Nicu Bizon, Jose Lopez-Guede. Design and Implementation of a Maximum Power Point Tracking System for a Piezoelectric Wind Energy Harvester Generating High Harmonicity. Sustainability. 2021; 13 (14):7709.
Chicago/Turabian StyleErol Kurt; Davut Özhan; Nicu Bizon; Jose Lopez-Guede. 2021. "Design and Implementation of a Maximum Power Point Tracking System for a Piezoelectric Wind Energy Harvester Generating High Harmonicity." Sustainability 13, no. 14: 7709.
The protection provided by wearing masks has been a guideline worldwide to prevent the risk of COVID-19 infection. The current work presents an investigation that analyzes the effectiveness of face shields as personal protective equipment. To that end, a multiphase computational fluid dynamic study based on Eulerian–Lagrangian techniques was defined to simulate the spread of the droplets produced by a sneeze. Different scenarios were evaluated where the relative humidity, ambient temperature, evaporation, mass transfer, break up, and turbulent dispersion were taken into account. The saliva that the human body generates was modeled as a saline solution of 8.8 g per 100 mL. In addition, the influence of the wind speed was studied with a soft breeze of 7 km/h and a moderate wind of 14 km/h. The results indicate that the face shield does not provide accurate protection, because only the person who is sneezed on is protected. Moreover, with a wind of 14 km/h, none of the droplets exhaled into the environment hit the face shield, instead, they were deposited onto the neck and face of the wearer. In the presence of an airflow, the droplets exhaled into the environment exceeded the safe distance marked by the WHO. Relative humidity and ambient temperature play an important role in the lifetime of the droplets.
Ainara Ugarte-Anero; Unai Fernandez-Gamiz; Iñigo Aramendia; Ekaitz Zulueta; Jose Lopez-Guede. Numerical Modeling of Face Shield Protection against a Sneeze. Mathematics 2021, 9, 1582 .
AMA StyleAinara Ugarte-Anero, Unai Fernandez-Gamiz, Iñigo Aramendia, Ekaitz Zulueta, Jose Lopez-Guede. Numerical Modeling of Face Shield Protection against a Sneeze. Mathematics. 2021; 9 (13):1582.
Chicago/Turabian StyleAinara Ugarte-Anero; Unai Fernandez-Gamiz; Iñigo Aramendia; Ekaitz Zulueta; Jose Lopez-Guede. 2021. "Numerical Modeling of Face Shield Protection against a Sneeze." Mathematics 9, no. 13: 1582.
In this article, a control strategy approach is proposed for a system consisting of a quadrotor transporting a double pendulum. In our case, we attempt to achieve a swing free transportation of the pendulum, while the quadrotor closely follows a specific trajectory. This dynamic system is highly nonlinear, therefore, the fulfillment of this complex task represents a demanding challenge. Moreover, achieving dampening of the double pendulum oscillations while following a precise trajectory are conflicting goals. We apply a proportional derivative (PD) and a model predictive control (MPC) controllers for this task. Transportation of a multiple pendulum with an aerial robot is a step forward in the state of art towards the study of the transportation of loads with complex dynamics. We provide the modeling of the quadrotor and the double pendulum. For MPC we define the cost function that has to be minimized to achieve optimal control. We report encouraging positive results on a simulated environmentcomparing the performance of our MPC-PD control circuit against a PD-PD configuration, achieving a three fold reduction of the double pendulum maximum swinging angle.
Julian Estevez; Jose Lopez-Guede; Gorka Garate; Manuel Graña. A Hybrid Control Approach for the Swing Free Transportation of a Double Pendulum with a Quadrotor. Applied Sciences 2021, 11, 5487 .
AMA StyleJulian Estevez, Jose Lopez-Guede, Gorka Garate, Manuel Graña. A Hybrid Control Approach for the Swing Free Transportation of a Double Pendulum with a Quadrotor. Applied Sciences. 2021; 11 (12):5487.
Chicago/Turabian StyleJulian Estevez; Jose Lopez-Guede; Gorka Garate; Manuel Graña. 2021. "A Hybrid Control Approach for the Swing Free Transportation of a Double Pendulum with a Quadrotor." Applied Sciences 11, no. 12: 5487.
Obtaining tools to analyze and predict the performance of batteries is a non-trivial challenge because it involves non-destructive evaluation procedures. At the research level, the development of sensors to allow cell-level monitoring is an innovative path, and electrochemical impedance spectrometry (EIS) has been identified as one of the most promising tools, as is the generation of advanced multivariable models that integrate environmental and internal-battery information. In this article, we describe an algorithm that automatically identifies a battery-equivalent electrochemical model based on electroscopic impedance data. This algorithm allows in operando monitoring of variations in the equivalent circuit parameters that will be used to further estimate variations in the state of health (SoH) and state of charge (SoC) of the battery based on a correlation with experimental aging data corresponding to states of failure or degradation. In the current work, the authors propose a two-step parameter identification algorithm. The first consists of a rough differential evolution algorithm-based identification. The second is based on the Nelder–Mead Simplex search method, which gives a fine parameter estimation. These algorithm results were compared with those of the commercially available Z-view, an equivalent circuit tool estimation that requires expert human input.
Javier Olarte; Jaione Martínez de Ilarduya; Ekaitz Zulueta; Raquel Ferret; Unai Fernández-Gámiz; Jose Lopez-Guede. Automatic Identification Algorithm of Equivalent Electrochemical Circuit Based on Electroscopic Impedance Data for a Lead Acid Battery. Electronics 2021, 10, 1353 .
AMA StyleJavier Olarte, Jaione Martínez de Ilarduya, Ekaitz Zulueta, Raquel Ferret, Unai Fernández-Gámiz, Jose Lopez-Guede. Automatic Identification Algorithm of Equivalent Electrochemical Circuit Based on Electroscopic Impedance Data for a Lead Acid Battery. Electronics. 2021; 10 (11):1353.
Chicago/Turabian StyleJavier Olarte; Jaione Martínez de Ilarduya; Ekaitz Zulueta; Raquel Ferret; Unai Fernández-Gámiz; Jose Lopez-Guede. 2021. "Automatic Identification Algorithm of Equivalent Electrochemical Circuit Based on Electroscopic Impedance Data for a Lead Acid Battery." Electronics 10, no. 11: 1353.
This work presents a battery management system for lead–acid batteries that integrates a battery-block (12 V) sensor that allows the online monitoring of a cell’s temperature, voltage, and impedance spectra. The monitoring and diagnostic capabilities enable the implementation of improved battery management algorithms in order to increase the life expectancy of lead–acid batteries and report the battery health conditions. The novelty is based on the online monitoring of the evolution of electrochemical impedance spectroscopy (EIS) over a battery’s life as a way to monitor the battery’s performance. Active cell balancing is also proposed as an alternative to traditional charge equalization to minimize excessive electrolyte consumption. A battery-block sensor (VTZ) was validated by using the correlation between experimental data collected from electrochemical impedance spectroscopy lab-testing equipment and sensors that were implemented in a series of 12 V lead–acid battery blocks. The modular design and small size allow easy and direct integration into different commercial cell formats, and the proposed methodology can be used for applications ranging from automotive to stationary energy storage.
Javier Olarte; Jaione Martínez de Ilarduya; Ekaitz Zulueta; Raquel Ferret; Unai Fernández-Gámiz; Jose Lopez-Guede. A Battery Management System with EIS Monitoring of Life Expectancy for Lead–Acid Batteries. Electronics 2021, 10, 1228 .
AMA StyleJavier Olarte, Jaione Martínez de Ilarduya, Ekaitz Zulueta, Raquel Ferret, Unai Fernández-Gámiz, Jose Lopez-Guede. A Battery Management System with EIS Monitoring of Life Expectancy for Lead–Acid Batteries. Electronics. 2021; 10 (11):1228.
Chicago/Turabian StyleJavier Olarte; Jaione Martínez de Ilarduya; Ekaitz Zulueta; Raquel Ferret; Unai Fernández-Gámiz; Jose Lopez-Guede. 2021. "A Battery Management System with EIS Monitoring of Life Expectancy for Lead–Acid Batteries." Electronics 10, no. 11: 1228.
This work presents the results of experimental analysis of the correlation between open-circuit voltage at 0% and the state of charge of a set (3 × 6) of high-temperature valve-regulated lead acid batteries, which provides a valuable health diagnosis tool when performing predictive maintenance actions. The proposed test could be executed after any emergency event in the battery system. It offers an alternative to the integration ampere hours, simplifying the diagnostic system, and can be used in many applications where the diagnosis can be made by monitoring the discharge voltage to a defined controlled value. By testing three different sealed, high-temperature lead acid battery models, it has been proved that open-circuit-voltage measurement at 0% state of charge is valid to evaluate health status and is applicable to different manufactures. In addition, the first derivative value calculation of the relaxation voltage over time provides accurate correlation with the state of health of the battery. The method proposed minimizes diagnosis times providing an easier way to implement the method in real systems.
Javier Olarte; Jaione Martínez de Ilarduya; Ekaitz Zulueta; Raquel Ferret; Erol Kurt; Jose Manuel Lopez-Guede. High Temperature VLRA Lead Acid Battery SOH Characterization Based on the Evolution of Open Circuit Voltage at Different States of Charge. JOM 2021, 73, 1251 -1260.
AMA StyleJavier Olarte, Jaione Martínez de Ilarduya, Ekaitz Zulueta, Raquel Ferret, Erol Kurt, Jose Manuel Lopez-Guede. High Temperature VLRA Lead Acid Battery SOH Characterization Based on the Evolution of Open Circuit Voltage at Different States of Charge. JOM. 2021; 73 (5):1251-1260.
Chicago/Turabian StyleJavier Olarte; Jaione Martínez de Ilarduya; Ekaitz Zulueta; Raquel Ferret; Erol Kurt; Jose Manuel Lopez-Guede. 2021. "High Temperature VLRA Lead Acid Battery SOH Characterization Based on the Evolution of Open Circuit Voltage at Different States of Charge." JOM 73, no. 5: 1251-1260.
One of the materials that is used widely for wind turbine blade manufacturing are fiber-reinforced composites. Although glass fiber reinforcement is the most used in wind turbine blades, the use of carbon fiber allows larger blades to be manufactured due to their better mechanical characteristics. Some turbine manufacturers are using carbon fiber in the most critical parts of the blade design. The larger rotors are exposed to complex loading conditions in service. One of the most relevant structures on a wind turbine blade is the spar cap. It is usually manufactured by means of unidirectional laminates, and one of its major failures is the delamination. The determination of material features that influence delamination initiation and advance by appropriate testing is a fundamental topic for the study of composite delamination. The fracture behavior is studied across coupons of carbon fiber reinforcement epoxy laminates. Fifteen different test conditions have been analyzed. Fracture surfaces for different mode ratios have been explored using optical microscope and scanning electron microscope. Experimental results shown in the paper for critical fracture parameters agree with the theoretically expected values. Therefore, this experimental procedure is suitable for wind turbine blade material characterizing at the initial coupon-scale research level.
Ana Boyano; Jose Lopez-Guede; Leyre Torre-Tojal; Unai Fernandez-Gamiz; Ekaitz Zulueta; Faustino Mujika. Delamination Fracture Behavior of Unidirectional Carbon Reinforced Composites Applied to Wind Turbine Blades. Materials 2021, 14, 593 .
AMA StyleAna Boyano, Jose Lopez-Guede, Leyre Torre-Tojal, Unai Fernandez-Gamiz, Ekaitz Zulueta, Faustino Mujika. Delamination Fracture Behavior of Unidirectional Carbon Reinforced Composites Applied to Wind Turbine Blades. Materials. 2021; 14 (3):593.
Chicago/Turabian StyleAna Boyano; Jose Lopez-Guede; Leyre Torre-Tojal; Unai Fernandez-Gamiz; Ekaitz Zulueta; Faustino Mujika. 2021. "Delamination Fracture Behavior of Unidirectional Carbon Reinforced Composites Applied to Wind Turbine Blades." Materials 14, no. 3: 593.
Road landmark inventory is becoming an important data product for the maintenance of transport infrastructures. Several commercial sensors are available which include synchronized optical cameras that allowto build 360° panoramic images of the surroundings of the vehicle used for road inspection. This paper is devoted to the analysis of such panorama images,specifically the area that contains themost relevant information. Road lane landmark detection is posed as a two class classification problem that may be solved bymachine learningapproaches, such as Random Forest (RF) and ensembles of Extreme Learning Machines (V-ELM). Besides model parameter selection, a central problem is the construction of a labeled training and validation datasetto cope with the highly uncontrolled conditions of image capture. Besides, human labor cost makes image data labeling a very expensive process. This paper proposes an open ended Active Learning (AL) approach involving a human oraclein the loop who provides the data labeling and can trigger the AL process when detection quality is degraded by the change in imaging conditions. The paper reports encouraging results over a collection of sample images selected from an industrial road landmark inventory operation. As an additional contribution, this paper assesses the ability of AL to overcomesome of the issues raised by highly class imbalanced datasets.
Jose Manuel Lopez-Guede; Asier Izquierdo; Julian Estevez; Manuel Graña. Active learning for road lane landmark inventory with V-ELM in highly uncontrolled image capture conditions. Neurocomputing 2021, 438, 259 -269.
AMA StyleJose Manuel Lopez-Guede, Asier Izquierdo, Julian Estevez, Manuel Graña. Active learning for road lane landmark inventory with V-ELM in highly uncontrolled image capture conditions. Neurocomputing. 2021; 438 ():259-269.
Chicago/Turabian StyleJose Manuel Lopez-Guede; Asier Izquierdo; Julian Estevez; Manuel Graña. 2021. "Active learning for road lane landmark inventory with V-ELM in highly uncontrolled image capture conditions." Neurocomputing 438, no. : 259-269.
Large-scale energy storage systems (ESS) are nowadays growing in popularity due to the increase in the energy production by renewable energy sources, which in general have a random intermittent nature. Currently, several redox flow batteries have been presented as an alternative of the classical ESS; the scalability, design flexibility and long life cycle of the vanadium redox flow battery (VRFB) have made it to stand out. In a VRFB cell, which consists of two electrodes and an ion exchange membrane, the electrolyte flows through the electrodes where the electrochemical reactions take place. Computational Fluid Dynamics (CFD) simulations are a very powerful tool to develop feasible numerical models to enhance the performance and lifetime of VRFBs. This review aims to present and discuss the numerical models developed in this field and, particularly, to analyze different types of flow fields and patterns that can be found in the literature. The numerical studies presented in this review are a helpful tool to evaluate several key parameters important to optimize the energy systems based on redox flow technologies.
Iñigo Aramendia; Unai Fernandez-Gamiz; Adrian Martinez-San-Vicente; Ekaitz Zulueta; Jose Manuel Lopez-Guede. Vanadium Redox Flow Batteries: A Review Oriented to Fluid-Dynamic Optimization. Energies 2020, 14, 176 .
AMA StyleIñigo Aramendia, Unai Fernandez-Gamiz, Adrian Martinez-San-Vicente, Ekaitz Zulueta, Jose Manuel Lopez-Guede. Vanadium Redox Flow Batteries: A Review Oriented to Fluid-Dynamic Optimization. Energies. 2020; 14 (1):176.
Chicago/Turabian StyleIñigo Aramendia; Unai Fernandez-Gamiz; Adrian Martinez-San-Vicente; Ekaitz Zulueta; Jose Manuel Lopez-Guede. 2020. "Vanadium Redox Flow Batteries: A Review Oriented to Fluid-Dynamic Optimization." Energies 14, no. 1: 176.
Manuel Graña; José Manuel López-Guede; José Antonio Sáez Muñoz; Álvaro Herrero Cosio; Héctor Quintián; Emilio Corchado. Special issue SOCO-CISIS 2018: New trends in soft computing and computational intelligence in security and its application in industrial and environmental problems. Neurocomputing 2020, 452, 414 -415.
AMA StyleManuel Graña, José Manuel López-Guede, José Antonio Sáez Muñoz, Álvaro Herrero Cosio, Héctor Quintián, Emilio Corchado. Special issue SOCO-CISIS 2018: New trends in soft computing and computational intelligence in security and its application in industrial and environmental problems. Neurocomputing. 2020; 452 ():414-415.
Chicago/Turabian StyleManuel Graña; José Manuel López-Guede; José Antonio Sáez Muñoz; Álvaro Herrero Cosio; Héctor Quintián; Emilio Corchado. 2020. "Special issue SOCO-CISIS 2018: New trends in soft computing and computational intelligence in security and its application in industrial and environmental problems." Neurocomputing 452, no. : 414-415.
Autonomous Mobile Robots (AMR) need a positioning function to move into unknown areas. These kinds of vehicles do not use a magnetic tape to guide into warehouses. Therefore, AMR use two different alternative techniques to solve the localization problem. First one is based on absolute positioning, and second one is established on relative localization. The absolute localization uses Simultaneous Localization and Mapping algorithms, in order to obtain a global position. However, the relative localization is based on odometry techniques. With the intention of developing a navigation system for an industrial mobile robot, which is being programmed in a structured text language, a relative localization is done utilizing LiDAR data acquisition. This novel concept analyzes two LiDAR datasets from different periods to calculate the AMR movement, by implementing Point matching and Linear Regression (LR) techniques. To understand the differences between conventional Iterative Closest Point (ICP) and LR a comparison is performed.
Daniel Teso-Fz-Betoño; Ekaitz Zulueta; Ander Sánchez-Chica; Unai Fernandez-Gamiz; Irantzu Uriarte; Jose Manuel Lopez-Guede. A Relative Positioning Development for an Autonomous Mobile Robot with a Linear Regression Technique. Advances in Intelligent Systems and Computing 2020, 627 -635.
AMA StyleDaniel Teso-Fz-Betoño, Ekaitz Zulueta, Ander Sánchez-Chica, Unai Fernandez-Gamiz, Irantzu Uriarte, Jose Manuel Lopez-Guede. A Relative Positioning Development for an Autonomous Mobile Robot with a Linear Regression Technique. Advances in Intelligent Systems and Computing. 2020; ():627-635.
Chicago/Turabian StyleDaniel Teso-Fz-Betoño; Ekaitz Zulueta; Ander Sánchez-Chica; Unai Fernandez-Gamiz; Irantzu Uriarte; Jose Manuel Lopez-Guede. 2020. "A Relative Positioning Development for an Autonomous Mobile Robot with a Linear Regression Technique." Advances in Intelligent Systems and Computing , no. : 627-635.
Road landmark inventory is becoming an important industry for the maintenance of transport infrastructures among others. Several commercial sensors are available witch include LiDAR sensors allowing to capture up to 1.5 million data point per second. We obtain an intensity based image from the LiDAR point cloud intensity. The landmark detection is posed as a two class classification problem that may be solved by some standard approaches, for example, Random Forest (RF). Besides model parameter selection, a central problem is the construction of the labeled dataset due to human labor cost and the highly uncontrolled conditions of the data capture. We propose an open ended Active Learning approach with a human operator in the loop who can start the Active Learning process when detection quality is degraded by the change in data condition in order to achieve adaptation to them. As an additional contribution, we have assessed the ability of Active Learning to overcome the issues raised by highly class imbalanced dataset, reaching a True Pixel Ratio value of 0.98.
Asier Izquierdo; Jose Manuel Lopez-Guede. Active Learning for Road Lane Landmark Inventory with Random Forest in Highly Uncontrolled LiDAR Intensity Based Image. Advances in Intelligent Systems and Computing 2020, 862 -871.
AMA StyleAsier Izquierdo, Jose Manuel Lopez-Guede. Active Learning for Road Lane Landmark Inventory with Random Forest in Highly Uncontrolled LiDAR Intensity Based Image. Advances in Intelligent Systems and Computing. 2020; ():862-871.
Chicago/Turabian StyleAsier Izquierdo; Jose Manuel Lopez-Guede. 2020. "Active Learning for Road Lane Landmark Inventory with Random Forest in Highly Uncontrolled LiDAR Intensity Based Image." Advances in Intelligent Systems and Computing , no. : 862-871.
With the development of artificial intelligence, alternative advanced machine learning approaches have allowed the training of increasingly sophisticated models via the available data. The light detection and ranging (LiDAR) remote sensing technique is being increasingly applied to obtain informative terrain maps, due to its ability to collect large amounts of data with satisfactory accuracy. Forest ecosystem management needs a multi-faceted approach, combining forest mapping and inventory in order to provide comprehensive knowledge on the current state and future trends of forest resources. Estimation of forestry aboveground biomass (AGB) by means of LiDAR data uses high-density point sampling data obtained in dedicated flights, which are often too costly for available research budgets. In this paper, we exploit already existing public low-density LiDAR data obtained for other purposes, such as cartography. This paper focuses on the application of machine-learning-based predictive systems for the extraction of biomass information from low-density LiDAR data (0.5 points/m2) taking into account the Pinus radiata species in the Arratia-Nervión region (Spain).
Leyre Torre-Tojal; Jose Manuel Lopez-Guede. Machine-Learning Techniques Applied to Biomass Estimation Using LiDAR Data. Advances in Intelligent Systems and Computing 2020, 853 -861.
AMA StyleLeyre Torre-Tojal, Jose Manuel Lopez-Guede. Machine-Learning Techniques Applied to Biomass Estimation Using LiDAR Data. Advances in Intelligent Systems and Computing. 2020; ():853-861.
Chicago/Turabian StyleLeyre Torre-Tojal; Jose Manuel Lopez-Guede. 2020. "Machine-Learning Techniques Applied to Biomass Estimation Using LiDAR Data." Advances in Intelligent Systems and Computing , no. : 853-861.
Academic programs are trying to implement edge technologies on their Bachelor’s and Master’s degrees offerings. In this paper authors present the experience of a dedicated electromobility research project and its alternative use for academic purposes. A case study is selected in a university in Chile, where the design of a new laboratory that serves for e-mobility research and for careers activities is described as an example of a long-term academic strategy. The numerous activities derived from a governmental funded academic research represents a parallel opportunity for continuous student education on high tech fields, in such a way that active student participation is highlighted as a successful academic knowledge transfer. In a period of nine months, over nineteen students from Bachelor’s Degree in Electrical Engineering and Bachelor’s Degree in Automotive Engineering have direct participation, through student internships and four final degree projects are being developed.
Felipe A. Nuñez-Donoso; Jose Manuel Lopez-Guede. Electromobility Laboratory: A Contribution for Student Participation in Higher Education. Advances in Intelligent Systems and Computing 2020, 367 -374.
AMA StyleFelipe A. Nuñez-Donoso, Jose Manuel Lopez-Guede. Electromobility Laboratory: A Contribution for Student Participation in Higher Education. Advances in Intelligent Systems and Computing. 2020; ():367-374.
Chicago/Turabian StyleFelipe A. Nuñez-Donoso; Jose Manuel Lopez-Guede. 2020. "Electromobility Laboratory: A Contribution for Student Participation in Higher Education." Advances in Intelligent Systems and Computing , no. : 367-374.
Over the last few years, the advances in size and weight for wind turbines have led to the development of flow control devices. The current work presents an innovative method to model flow control devices based on a cell-set model, such as Gurney flaps (GFs). This model reuses the cells which are around the required geometry and a wall boundary condition is assigned to the generated region. Numerical simulations based on RANS equations and with have been performed. Firstly, a performance study of the cell-set model on GFs was carried out by comparing it with a fully mesh model of a DU91W250 airfoil. A global relative error of 1.13% was calculated. Secondly, optimum GF lengths were determined (from 0% to 2% of c) for a DU97W300 airfoil and an application of them. The results showed that for lower angles of attack (AoAs) larger GFs were needed, and as the AoA increased, the optimum GF length value decreased. For the purpose of studying the effects generated by two flow control devices (vortex generators (VGs) and optimum GF) working together, a triangular VG based on the jBAY model was implemented. Resulting data indicated, as expected, that when both flow control devices were implemented, higher CL and lower CD values appeared.
Alejandro Ballesteros-Coll; Unai Fernandez-Gamiz; Iñigo Aramendia; Ekaitz Zulueta; Jose Lopez-Guede. Computational Methods for Modelling and Optimization of Flow Control Devices. Energies 2020, 13, 3710 .
AMA StyleAlejandro Ballesteros-Coll, Unai Fernandez-Gamiz, Iñigo Aramendia, Ekaitz Zulueta, Jose Lopez-Guede. Computational Methods for Modelling and Optimization of Flow Control Devices. Energies. 2020; 13 (14):3710.
Chicago/Turabian StyleAlejandro Ballesteros-Coll; Unai Fernandez-Gamiz; Iñigo Aramendia; Ekaitz Zulueta; Jose Lopez-Guede. 2020. "Computational Methods for Modelling and Optimization of Flow Control Devices." Energies 13, no. 14: 3710.
An understanding of marine ecosystems and their biodiversity is relevant to sustainable use of the goods and services they offer. Since marine areas host complex ecosystems, it is important to develop spatially widespread monitoring networks capable of providing large amounts of multiparametric information, encompassing both biotic and abiotic variables, and describing the ecological dynamics of the observed species. In this context, imaging devices are valuable tools that complement other biological and oceanographic monitoring devices. Nevertheless, large amounts of images or movies cannot all be manually processed, and autonomous routines for recognizing the relevant content, classification, and tagging are urgently needed. In this work, we propose a pipeline for the analysis of visual data that integrates video/image annotation tools for defining, training, and validation of datasets with video/image enhancement and machine and deep learning approaches. Such a pipeline is required to achieve good performance in the recognition and classification tasks of mobile and sessile megafauna, in order to obtain integrated information on spatial distribution and temporal dynamics. A prototype implementation of the analysis pipeline is provided in the context of deep-sea videos taken by one of the fixed cameras at the LoVe Ocean Observatory network of Lofoten Islands (Norway) at 260 m depth, in the Barents Sea, which has shown good classification results on an independent test dataset with an accuracy value of 76.18% and an area under the curve (AUC) value of 87.59%.
Vanesa Lopez-Vazquez; Jose Manuel Lopez-Guede; Simone Marini; Emanuela Fanelli; Espen Johnsen; Jacopo Aguzzi. Video Image Enhancement and Machine Learning Pipeline for Underwater Animal Detection and Classification at Cabled Observatories. Sensors 2020, 20, 726 .
AMA StyleVanesa Lopez-Vazquez, Jose Manuel Lopez-Guede, Simone Marini, Emanuela Fanelli, Espen Johnsen, Jacopo Aguzzi. Video Image Enhancement and Machine Learning Pipeline for Underwater Animal Detection and Classification at Cabled Observatories. Sensors. 2020; 20 (3):726.
Chicago/Turabian StyleVanesa Lopez-Vazquez; Jose Manuel Lopez-Guede; Simone Marini; Emanuela Fanelli; Espen Johnsen; Jacopo Aguzzi. 2020. "Video Image Enhancement and Machine Learning Pipeline for Underwater Animal Detection and Classification at Cabled Observatories." Sensors 20, no. 3: 726.
Estimation of forestry aboveground biomass (AGB) by means of aerial Light Detection and Ranging (LiDAR) data uses high-density point sampling data obtained in dedicated flights, which are often too costly for available research budgets. In this paper we exploit already existing public low-density LiDAR data obtained for other purposes, such as cartography. The challenge is to show that such low-density data allows accurate biomass estimation. We demonstrate the approach on data available from plantations of Pinus radiata in the Arratia-Nervión region, located in Biscay province located in the North of Spain. We use public data gathered from the low-density (0.5 pulse/m2) LiDAR flight conducted by the Basque Government in 2012 for cartographic production. We propose a linear regression model based on explanatory variables obtained from the LiDAR point cloud data. We calibrate the model using field data from the Fourth National Forest Inventory (NFI4), including the selection of the optimal model variables. The results revealed that the best model depends on two variables extracted from LiDAR data: One directly related with tree height and a second parameter with the canopy density. The model explained 80% of its variability with a standard error of 0.25 ton/ha in logarithmic units. We validate the predictions against the biomass measurements provided by the government institutions, obtaining a difference of 8%. The proposed approach would allow the exploitation of the periodic available low-density LiDAR data, collected with territorial and cartographic purposes, for a more frequent and less expensive control of the forestry biomass.
Leyre-Torre Tojal; Aitor Bastarrika; Brian Barrett; Javier Maria Sanchez Espeso; Jose Manuel Lopez-Guede; Manuel Graña. Prediction of Aboveground Biomass from Low-Density LiDAR Data: Validation over P. radiata Data from a Region North of Spain. Forests 2019, 10, 819 .
AMA StyleLeyre-Torre Tojal, Aitor Bastarrika, Brian Barrett, Javier Maria Sanchez Espeso, Jose Manuel Lopez-Guede, Manuel Graña. Prediction of Aboveground Biomass from Low-Density LiDAR Data: Validation over P. radiata Data from a Region North of Spain. Forests. 2019; 10 (9):819.
Chicago/Turabian StyleLeyre-Torre Tojal; Aitor Bastarrika; Brian Barrett; Javier Maria Sanchez Espeso; Jose Manuel Lopez-Guede; Manuel Graña. 2019. "Prediction of Aboveground Biomass from Low-Density LiDAR Data: Validation over P. radiata Data from a Region North of Spain." Forests 10, no. 9: 819.
In this paper we present a state-of-the-art review about road lane landmark extraction. Automatic lane landmark extraction has been studied during the last decade for different practical applications. The purpose of this paper is to gather and discuss methodologies of road lane landmark extraction based on signals from different sensors in order to automate the extraction of horizontal road surface lane signs and get an accurate map of road lane landmarks. Specific algorithms for each kind of sensors are analyzed, describing their basic ideas, and discussing their pros and cons.
Asier Izquierdo; Jose Manuel Lopez-Guede; Manuel Graña. Road Lane Landmark Extraction: A State-of-the-art Review. Transactions on Petri Nets and Other Models of Concurrency XV 2019, 625 -635.
AMA StyleAsier Izquierdo, Jose Manuel Lopez-Guede, Manuel Graña. Road Lane Landmark Extraction: A State-of-the-art Review. Transactions on Petri Nets and Other Models of Concurrency XV. 2019; ():625-635.
Chicago/Turabian StyleAsier Izquierdo; Jose Manuel Lopez-Guede; Manuel Graña. 2019. "Road Lane Landmark Extraction: A State-of-the-art Review." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 625-635.
In the present study, a new micro-power scaled electromagnetic (EM) harvester is designed and fabricated. The device has an innovative magnetic flux varying mechanism with two cylindrical Nb magnets and a central core moving inside the magnets back and forth. The system harvest electricity from the linear oscillations by the help of a spring attached at the bottom part of the core. The device requires only one spring and a second linear-laminated core closes the flux outside of the magnets in order to lower the reluctance of the system. The device is 6 cm in length and 2.4 cm in width in cylindrical geometry as a compact and stable geometry. The experimental verifications have proven that it can generate up to U = 7.76 mV output voltage depending on the oscillation frequency. The maximal output power has been measured as P= 32 m W for 44 Hz frequency with the resistive load RL = 0.2 Ohm. The power density p = 1.17 m W/cm 3 has been obtained, experimentally.
Erol Kurt; Busra Mutlu; Nicu Bizon; Jose Manuel Lopez Guede. Design and fabrication of a new micro-power scaled electromagnetic harvester. Journal of Energy Systems 2019, 3, 51 -66.
AMA StyleErol Kurt, Busra Mutlu, Nicu Bizon, Jose Manuel Lopez Guede. Design and fabrication of a new micro-power scaled electromagnetic harvester. Journal of Energy Systems. 2019; 3 (2):51-66.
Chicago/Turabian StyleErol Kurt; Busra Mutlu; Nicu Bizon; Jose Manuel Lopez Guede. 2019. "Design and fabrication of a new micro-power scaled electromagnetic harvester." Journal of Energy Systems 3, no. 2: 51-66.