Productos de investigación

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12585/8849

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2D CFD Modeling of Rapid Water Filling with Air Valves Using OpenFOAM
(2021-11-04) Aguirre-Mendoza, Andres M.; Oyuela, Sebastián; Espinoza Román, Héctor Gabriel; Coronado-Hernández, Oscar E.; Fuertes Miquel, Vicente S.; Paternina-Verona, Duban A.
The rapid filling process in pressurized pipelines has been extensively studied using mathematical models. On the other hand, the application of computational fluid dynamics models has emerged during the last decade, which considers the development of CFD models that simulate the filling of pipes with entrapped air, and without air expulsion. Currently, studies of CFD models representing rapid filling in pipes with entrapped air and with air expulsion are scarce in the literature. In this paper, a two-dimensional model is developed using OpenFOAM software to evaluate the hydraulic performance of the rapid filling process in a hydraulic installation with an air valve, considering different air pocket sizes and pressure impulsion by means of a hydro-pneumatic tank. The two-dimensional CFD model captures the pressure evolution in the air pocket very well with respect to experimental and mathematical model results, and produces improved results with respect to existing mathematical model
3-webs with singularities
(Maik Nauka-Interperiodica Publishing, 2016) Arias Amaya, Fabián; Arteaga Bejarano J.R.; Malakhaltsev M.
A 3-web with singularities is an ordered collection of three one-dimensional distributions L1, L2, L3 on a 2-dimensional manifold M. The subset Σ ⊂ M where these distributions are not pairwise transversal is called the singularity set. Under some conditions on Σ we find the differential invariants of the 3-web with singularities at the points of Σ and give examples of calculation of these invariants. © 2016, Pleiades Publishing, Ltd.
A blockchain solution for operational parameters monitoring platform for DC microgrids
(2020-12-01) Ariza, H.; Martínez-Santos, Juan Carlos; Payares, E.D.; Medina, M.F.; Domínguez Jiménez, Juan Antonio; Campillo Jiménez, Javier Eduardo
Large penetration of renewable distributed energy resources, as well as the effective integration of storage systems and electric vehicles, are some of the required strategies to reduce the impact of the energy sector on greenhouse gas emissions. Microgrids offer an efficient platform to facilitate the integration of these systems, however, the increased complexity this strategy comes with, requires the use of sophisticated, reliable, and secure monitoring and control systems. The outbreak of cryptocurrency technologies has drawn particular attention, especially, the underlying Blockchain technology. The decentralized structure of this technology enables implementing control strategies, parameters monitoring, and business processes in microgrids. The aim of this work is to present the development of a framework to monitor operational parameters from an islanded microgrid. To build the Blockchain network, the Hyperledger-Fabric development platform was used. To simulate the behavior of the microgrid, an object-oriented open-source library using the Modelica modeling language was used to model a DC microgrid. The performance of the architecture was evaluated through operational parameters such as the difficulty and the number of nodes. Results suggest that changes in these factors can affect significantly the transaction time. The proposed architecture can be used as a basis to study Blockchain communication effects in smart grids and their development.
A boundary element method formulation for modal analysis of doubly curved thick shallow shells
(Elsevier Inc., 2016) Useche Vivero, Jairo; Harnish C.
The study of vibrations of shells is an important aspect in the design of thin-walled structures. In general, analytical solutions for the natural frequencies of shells are not possible, and computational techniques are required. In this paper, modal analysis of shallow shells using a new boundary element method formulation is presented. The proposed formulation is based on a direct time-domain integration using the elastostatic fundamental solutions for both in-plane elasticity and shear-deformable plates. We modeled shallow shells by coupling the boundary element formulation of a shear-deformable plate and the two-dimensional plane stress elasticity. Effects of shear deformation and rotatory inertia were included in the formulation. Domain integrals related to inertial terms were treated by the dual reciprocity boundary element method. Numerical examples are presented to demonstrate the efficiency and accuracy of the proposed formulation. © 2015 Elsevier Inc.
A broad diversity survey of Rhizoctonia species from the Brazilian Amazon reveals the prevalence of R. solani AG-1 IA on signal grass and the new record of AG-1 IF on cowpea and soybeans
(2020-03-01) Chavarro Mesa, Edisson; Ceresini, Paulo; Pereira, Danilo; Vicentini, Samara; Tatiane, Silva; Ramos-Molina, Lina; Negrisoli, Matheus; Schurt, Daniel; Vieira-Júnior, José R.
Leaf blight, sheath blight, and web blight are major diseases caused by Rhizoctonia species on both Fabaceae and Poaceae plant hosts in the Brazilian Amazon agroecosystem. To determine the diversity of Rhizoctonia species associated with foliar diseases on fabaceous (cowpea and soybean) and poaceous (rice and signal grass [Urochloa brizantha]) hosts, a broad survey was conducted in Pará, Rondônia, Roraima, and Mato Grosso, in the Amazon, from 2012 to 2013. We extended our survey to Cerrado areas of Mato Grosso, and the lowlands of Paraíba Valley, in São Paulo, where these Rhizoctonia foliar diseases have not been reported so far. Our findings revealed that these diseases are caused by a diversity of Rhizoctonia solani AG‐1 complex. We detected that R. solani AG‐1 IA (sexual phase Thanatephorus cucumeris) was the predominant pathogen associated with signal grass leaf blight and collar rot diseases in the Amazon, especially in Rondônia and northern Mato Grosso. In addition, a subgroup of R. solani (AG‐1 IF), not previously reported in Brazil, was associated with leaf blight on cowpea and soybean, in Roraima. Another subgroup (AG‐1 ID) was also detected in Roraima. In Mato Grosso Cerrados we did not find any of the major Rhizoctonia foliar pathogens. Instead, R. oryzae (Waitea circinata) was the predominant species associated with a collar rot on U. brizantha. In the lowlands of São Paulo, R. oryzae‐sativae (Ceratobasidium oryzae‐sativae) was the predominant pathogen detected causing the rice sheath spot disease.
A case study approach to introduce circular economy in sustainable design education
(Institution of Engineering Designers, The Design Society, 2019) Esparragoza I.; Mesa-Cogollo J.; Bohemia E.; Kovacevic A.; Buck L.; Brisco R.; Evans D.; Grierson H.; Ion W.; Whitfield R.I.
Finding sustainable solutions to worldwide problems has become a critical challenge for engineers. The use of natural resources and the generation of materials now degradable should be controlled when sustainable solutions are pursued. As a result, the notion of reusing materials and products for longer periods is gaining momentum in the design for sustainability, and the circular economy is becoming the new paradigm to be implemented for that purpose. In contrast to the traditional linear economy that is based on making, using and disposing of products, the circular economy is focused on remanufacturing, reusing and recycling products and materials to extend their life. However, the circular economy is not formally introduced in the academia, and future engineers are not getting prepared to incorporate it into the design for sustainability. This work aims to propose a pedagogical approach to introduce the concept of circular economy in engineering design. A case study is presented to compare the design of a product based on the linear economy model (manufacture, use, waste) and the redesign of the product using the circular economy model (remanufacture, reuse, recycle). The comparison will be attained using sustainability performance indicators considered from early design stages. The contrast between the original design based on the linear economy and the re-design using the circular economy allows illustrating the benefits of the circular economy model to enhance the sustainability performance of a product. © 2019 Institution of Engineering Designers, The Design Society. All rights reserved.
A chronological literature review of electric vehicle interactions with power distribution systems
(2020-06-11) Arias-Londoño, Andrés; Montoya, Oscar; Grisales-Noreña L.F.
In the last decade, the deployment of electric vehicles (EVs) has been largely promoted. This development has increased challenges in the power systems in the context of planning and operation due to the massive amount of recharge needed for EVs. Furthermore, EVs may also offer new opportunities and can be used to support the grid to provide auxiliary services. In this regard, and considering the research around EVs and power grids, this paper presents a chronological background review of EVs and their interactions with power systems, particularly electric distribution networks, considering publications from the IEEE Xplore database. The review is extended from 1973 to 2019 and is developed via systematic classification using key categories that describe the types of interactions between EVs and power grids. These interactions are in the framework of the power quality, study of scenarios, electricity markets, demand response, demand management, power system stability, Vehicle-to-Grid (V2G) concept, and optimal location of battery swap and charging stations.
A collaborative EPQ inventory model for a three-echelon supply chain with multiple products considering the effect of marketing effort on demand
(2020-06-01) Salas-Navarro, Katherine; Acevedo Chedid, Jaime; Florez, Whandy F.; Ospina-Mateus, Holman; Cárdenas-Barrón, Leopoldo; Sankar Sana, Shib
This paper presents an inventory model for a three-echelon supply chain with multiple products and multiple members considering the demand as an increasing function of the marketing effort. In the proposed inventory model, a collaborative approach is studied and an analytical method is applied to obtain the optimal production lot size and the optimal marketing effort in order to achieve the maximum profits. Some numerical examples are illustrated to justify the model. Moreover, a sensitivity analysis is well done in order to analysis the effect of the changes of key parameters of inventory model on the the maximum benefits of all members of the chain
A Comparative Study on Power Flow Methods Applied to AC Distribution Networks with Single-Phase Representation
(2021-10-21) Montoya, Oscar Danilo; Molina-Cabrera, Alexander; Hernández, Jesus C.
This paper presents a comparative analysis of six different iterative power flow methods applied to AC distribution networks, which have been recently reported in the scientific literature. These power flow methods are (i) successive approximations, (ii) matricial backward/forward method, (iii) triangular-based approach, (iv) product linearization method, (v) hyperbolic linearization method, and (vi) diagonal approximation method. The first three methods and the last one are formulated without recurring derivatives, and they can be directly formulated in the complex domain; the fourth and fifth methods are based on the linear approximation of the power balance equations that are also formulated in the complex domain. The numerical comparison involves three main aspects: the convergence rate, processing time, and the number of iterations calculated using the classical Newton–Raphson method as the reference case. Numerical results from two test feeders composed of 34 and 85 nodes demonstrate that the derivative-free methods have linear convergence, and the methods that use derivatives in their formulation have quadratic convergence
A Comparative Study on Power Flow Methods for Direct-Current Networks Considering Processing Time and Numerical Convergence Errors
(2020-12-03) Grisales-Noreña, Luis Fernando; Montoya, Oscar Danilo; Gil-González, Walter; Perea-Moreno, Alberto-Jesus; Perea-Moreno, Miguel-Angel
This study analyzes the numerical convergence and processing time required by several classical and new solution methods proposed in the literature to solve the power-flow problem (PF) in direct-current (DC) networks considering radial and mesh topologies. Three classical numerical methods were studied: Gauss–Jacobi, Gauss–Seidel, and Newton–Raphson. In addition, two unconventional methods were selected. They are iterative and allow solving the DC PF in radial and mesh configurations. The first method uses a Taylor series expansion and a set of decoupling equations to linearize around the desired operating point. The second method manipulates the set of non-linear equations of the DC PF to transform it into a conventional fixed-point form. Moreover, this method is used to develop a successive approximation methodology. For the particular case of radial topology, three methods based on triangular matrix formulation, graph theory, and scanning algorithms were analyzed. The main objective of this study was to identify the methods with the best performance in terms of quality of solution (i.e., numerical convergence) and processing time to solve the DC power flow in mesh and radial distribution networks. We aimed at offering to the reader a set of PF methodologies to analyze electrical DC grids. The PF performance of the analyzed solution methods was evaluated through six test feeders; all of them were employed in prior studies for the same application. The simulation results show the adequate performance of the power-flow methods reviewed in this study, and they permit the selection of the best solution method for radial and mesh structures.
A computational model for residual life assessment of dents generated by explosive loads in pipelines
(2003) Useche Vivero, Jairo; Gomez J.; Brebbia C.A.; Carlomagno G.M.; Anagnostopoulos P.
The present work develops a finite elements computational model that describes the process of dynamic deformation in pipelines under explosive loads. The mechanical response of the material is modeled by means of an elastoviscoplastic constitutive law based on the Johnson-Cook equation. The model allows understanding the process of generation of dents through the dynamics phenomena and of the development and distribution of stress and strain. The model also allows studying the distribution and magnitude of residual stress allowing identifying critical areas in the dent. It is validated by means of the correlation of main variables with data obtained in experiments of generation of dents under controlled conditions. The model predicts the experimental results in a high grade allowing corroborating hypothesis of failure and residual life proposals for the pipe impacted.
A computer vision system for detecting motorcycle violations in pedestrian zones
(2024-05-02) Hernández-Díaz, Nicolás; Peñaloza, Yersica C.; Rios, Y. Yuliana; Martínez-Santos, Juan Carlos; Puertas, Edwin
This paper presents a system that relies on computer vision to identify instances of motorcycle violations in crosswalks utilizing CNNs. The system was trained and evaluated on a novel public dataset published by the authors, which contains traffic images classified into four categories: motorcycles in crosswalks, motorcycles outside crosswalks, pedestrians in cross walks, and only motorbike outside. We demonstrate the viability of leveraging deep learning models such as YOLOv8 for this purpose and provide details on the training and performance of the model. This system has the potential to enable intelligent traffic enforcement to mit igate accidents in pedestrian zones; to develop the system, a dataset comprising over 6,000 images was amassed from publicly available traffic cameras and subsequently annotated. Several models, including YOLOv8, SSD, and MobileNet, were trained on this dataset. The YOLOv8 model attained the highest performance with a mean average precision of 84.6% across classes. The study presents the system architecture and training process. Results illus trate the potential of utilizing deep learning to detect traffic violations in pedestrian zones, which can promote intelligent traffic enforcement and improved safety.
A Convex OPF Approximation for DC Networks Considering Voltage-Dependent Load Models
(2020-12-01) Gil-González, Walter; Garcés, A.; Casilimas-Peña, A.; Garrido Arévalo, Víctor Manuel; Montoya, Oscar
This paper addresses the problems of power flow and optimal power flow analysis considering voltage-dependent load models from the convex point of view. First, Taylor series expansion method is employed for linearizing the power flow equations generating a set of affine h yperplanes. S econd, the sequential quadratic programming (SQP) approach is employed for adjusting the linearization point to eliminate the voltage estimation error between the exact and proposed convex models recursively. Two voltage-dependent load models are considered in our power flow a nd o ptimal p ower fl ow pr oposals wh ich based on the exponential and polynomial models. General algebraic modeling system (GAMS) and its nonlinear optimization packages are employed for comparison purposes. Two DC-test systems with 6 and 21 nodes are used to validate the performance of the SQP proposed. The proposed SQP approach is implemented in MATLAB software with quadprog toolbox.
A convex OPF approximation for selecting the best candidate nodes for optimal location of power sources on DC resistive networks
(Elsevier B.V., 2019) Montoya, O.D.
This paper proposes a convex approximation approach for solving the optimal power flow (OPF) problem in direct current (DC) networks with constant power loads by using a sequential quadratic programming approach. A linearization method based on the Taylor series is used for the convexification of the power balance equations. For selecting the best candidate nodes for optimal location of distributed generators (DGs) on a DC network, a relaxation of the binary variables that represent the DGs location is proposed. This relaxation allows identifying the most important nodes for reducing power losses as well as the unimportant nodes. The optimal solution obtained by the proposed convex model is the best possible solution and serves for adjusting combinatorial optimization techniques for recovering the binary characteristics of the decision variables. The solution of the non-convex OPF model is achieved via GAMS software in conjunction with the CONOPT solver; in addition the sequential quadratic programming model is solved via quadprog from MATLAB for reducing the estimation errors in terms of calculation of the power losses. To compare the results of the proposed convex model, three metaheuristic approaches were employed using genetic algorithms, particle swarm optimization, continuous genetic algorithms, and black hole optimizers. © 2019 Karabuk University
A Deep Learning Approach To Cloud And Shadow Detection In Multiresolution, Multitemporal And Multisensor Images
(2024-07-12) Arrechea-Castillo, Darwin Alexis; Solano-Correa, Yady Tatiana; Muñoz-Ordoñez, Julián Fernando; Pencue-Fierro, Edgar Leonairo
Accurate detection of clouds and shadows present in optical imagery is important in remote sensing for ensuring data quality and reliability. This study introduces a deep learning model capable of generating precise cloud and shadows masks for subsequent filtering. Unlike other works in literature, this model operates efficiently across diverse temporalities, sensors, and spatial resolutions, without the need for any relative or absolute transformation of the original data. This versatility, to date unreported in the literature, marks a significant advancement in the field. The model utilizes data from PlanetScope, Landsat and Sentinel-2 sensors and is based on a simplified convolutional neural network (CNN) architecture, LeNet, which facilitates easy training on standard computers with minimal time requirements. Despite its simplicity, the model demonstrates robustness, achieving accuracy metrics over 96% in validation data. These results show the model potential in transforming cloud and shadow detection in remote sensing, combining ease of use with high accuracy.
A density functional theory study of the reconstruction of gold (111) surfaces
(American Chemical Society, 2014) Torres E.; Dilabio G.A.
We studied (p × √3) gold (111) surface reconstructions within the DFT/PW91 approximation. Our findings clearly show that the reconstruction is energetically favorable in unreconstructed surfaces equal to or larger than the unit cell of the final reconstructed surface. Reconstructions in surfaces smaller than ∼2.95 nm in the [11̄0] direction are not more stable than the unreconstructed surface, and this may explain why (p × √3) type reconstructions have not been observed in subnanometer gold particles. We found that reconstructions with (22 × √3) and (23 × √3) unit cells, usually reported in experiments, are isoenergetic. © 2014 American Chemical Society.
A Discrete-Continuous PSO for the Optimal Integration of D-STATCOMs into Electrical Distribution Systems by Considering Annual Power Loss and Investment Costs
(2022-07-14) Grisales-Noreña, Luis Fernando; Montoya, Oscar Danilo; Hernández, Jesus C.; Ramos-Paja, Carlos Andres; Perea-Moreno, Alberto-Jesus
Currently, with the quick increase in global population, the energetic crisis, the environmental problematic, and the development of the power electronic devices generated the need to include new technologies for supporting and potentiating electrical distributions systems; Distribution Static Compensators (D-STATCOMs) are highly used for this task due to the advantages that this technology presents: reduction in power loss, operation costs, and chargeability of branches, among others. The possibility to include this kind of technology within the electrical system has shown the need to develop efficient methodologies from the point of view of quality solution, repeatability and processing times by considering operation and investment costs as well as the technical conditions of the electrical grids under a scenario of variable power demand and then representing the real operation of the electrical grid. With the aim to propose a solution for this requirement, this paper presents a new Discrete-Continuous Particle Swarm Optimization (DCPSO) algorithm to solve the problem of the optimal integration of D-STATCOMs into Electrical Distribution Systems (EDSs). In this case, the objective function is the minimization of annual operating costs by using a weighted mono-objective function composed of the annual power loss and the investment cost and by including all constraints associated with the operation of an EDS in a distributed reactive compensation environmentinside the mathematical formulation. In order to evaluate the effectiveness and robustness of the proposed solution method, this study implemented two tests systems (i.e., 33- and 69-bus), as well as four comparison methods, and different considerations related to the inclusion of D-STATCOMs in the EDSs. Furthermore, for evaluating the repeatability of the solution obtained by each solution methods used, each algorithm was executed 100 times in Matlab software. The results obtained demonstrated that the proposed DCPSO/HSA methodology achieved the best trade-off between solution quality and processing time, with low standard deviation values for EDSs of any size
A discrete-event simulation model with a collaborative and lean logistic approach application to a dairy industry
(2024-09-11) Salas-Navarro, Katherinne; Bustamante-Salazar, Angélica; Romero-Lambrano, Teresa; Ospina Mateus, Holman; Acevedo Chedid, Jaime; Sankar Sana, Shib
The research introduces a discrete-event simulation model that focuses on implementing a collaborative and lean logistic approach to enhance productivity and competitiveness within a supply chain. The model aims to improve processes in the supply chain by establishing more sustainable methods in production, transportation, and marketing activities. Additionally, a discrete-event simulation model has been created to represent a dairy supply chain and assess performance across various areas such as production activities, transportation, distribution, information systems, and indicators. The model utilizes Arena Simulation Software to depict processes, raw materials, suppliers, manufacturers, resources, products, and customers. It has been developed and validated through statistical comparison with real-world data. Furthermore, the current performance analysis has been computed, and scenarios have been defined to enhance infrastructure utilization, production capacity, collaboration, and lean logistic approaches. The study includes a case study of the dairy industry in Colombia to validate the model. The results indicate that collaborating with suppliers and implementing a new production line have significant benefits in strengthening the dairy sector, leading to improved production planning, the adoption of new technologies, increased incomes, and enhanced competitiveness in the industry.
A fixed-point current injection power flow for electric distribution systems using Laurent series
(2022-07-02) Giraldo, Juan S; Montoya, Oscar Danilo; Vergara, Pedro P.; Milano, Federico
his paper proposes a new power flow (PF) formulation for electrical distribution systems using the current injection method and applying the Laurent series expansion. Two solution algorithms are proposed: a Newtonlike iterative procedure and a fixed-point iteration based on the successive approximation method (SAM). The convergence analysis of the SAM is proven via the Banach fixed-point theorem, ensuring numerical stability, the uniqueness of the solution, and independence on the initializing point. Numerical results are obtained for both proposed algorithms and compared to well-known PF formulations considering their rate of convergence, computational time, and numerical stability. Tests are performed for different branch 𝑅��∕𝑋�� ratios, loading conditions, and initialization points in balanced and unbalanced networks with radial and weakly-meshed topologies. Results show that the SAM is computationally more efficient than the compared PFs, being more than ten times faster than the backward–forward sweep algorithm.
A flexible and simplified calibration procedure for fringe projection profilometry
(SPIE, 2019) Vargas R.; Marrugo A.G.; Pineda J.; Romero L.A.; Bodermann B.; Frenner K.
Fringe Projection Profilometry (FPP) is a widely used technique for optical three-dimensional (3D) shape measurement. Among the existing 3D shape measurement techniques, FPP provides a whole-field 3D reconstruction of objects in a non-contact manner, with high resolution, and fast data processing. The key to accurate 3D shape measurement is the proper calibration of the measurement system. Currently, most calibration procedures in FPP rely on phase-coordinate mapping (PCM) or back-projection stereo-vision (SV) methods. The PCM technique consists in mapping experimental metric XYZ coordinates to recovered phase values by fitting a predetermined function. However, it requires accurately placing 2D or 3D targets at different distances and orientations. Conversely, in the SV method, the projector is regarded as an inverse camera, and the system is modeled using triangulation principles. Therefore, the calibration process can be carried out using 2D targets placed in arbitrary positions and orientations, resulting in a more flexible procedure. In this work, we propose a hybrid calibration procedure that combines SV and PCM methods. The procedure is highly flexible, robust to lens distortions, and has a simple relationship between phase and coordinates. Experimental results show that the proposed method has advantages over the conventional SV model since it needs fewer acquired images for the reconstruction process, and due to its low computational complexity the reconstruction time decreases significantly. © 2019 SPIE.

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