Ingeniería y Ciencia, Vol. 16, Núm. 32 (2020)

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https://hdl.handle.net/10784/25537

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Automatic Design of Large-Scale Trusses: A Comparison Between Derivative-Free Algorithms
(Universidad EAFIT, 2020-11-11) Niño-Alvarez, Luis; Guevara-Corzo, Jeffrey; Begambre-Carrillo, Oscar; Universidad Industrial de Santander
The design of steel trusses is a frequent problem in civil engineering, which requires the experience of the design engineer to achieve a structural solution with good performance and that can satisfy the established needs. In recent years, the design of these systems has been supported by the application of various methods of optimization, which allow optimal solutions, meeting the proposed design objectives, automatically and in a shorter time. This research presents the application of a series of multiobjective metaheuristic algorithms for the automatic design of large-scale trusses. The NSGA-II, MOPSO and AMOSA algorithms were applied and the structures reported in the literature were considered to be made up of a high number of elements. The performance of the algorithms was evaluated based on the computational cost, the hypervolume criterion and the behavior that the algorithms have when increasing the amount of iterations per optimization cycle. The search space used in the optimization was discrete, restricted by the W steel profiles available in the Colombian market. The results obtained show that, for the proposed problems, the MOPSO algorithm is the most efficient, followed by the AMOSA and the NSGA-II which showed a higher computational cost. Finally, it is worth mentioning that the calculation times were less than one hour, for trusses close to a thousand elements.
A Computational Architecture for Inference of a Quantized-CNN for Detecting Atrial Fibrillation
(Universidad EAFIT, 2020-11-11) Jaramillo-Rueda, Andrés F; Vargas-Pacheco, Laura Y; Fajardo, Carlos A.; Universidad Industrial de Santander
Atrial Fibrillation is a common cardiac arrhythmia, which is characterized by an abnormal heartbeat rhythm that can be life-threatening. Recently, researchers have proposed several Convolutional Neural Networks (CNNs) to detect Atrial Fibrillation. CNNs have high requirements on computing and memory resources, which usually demand the use of High Performance Computing (eg, GPUs). This high energy demand is a challenge for portable devices. Therefore, efficient hardware implementations are required. We propose a computational architecture for the inference of a Quantized Convolutional Neural Network (Q-CNN) that allows the detection of the Atrial Fibrillation (AF). The architecture exploits data-level parallelism by incorporating SIMD-based vector units, which is optimized in terms of computation and storage and also optimized to perform both the convolutional and fully connected layers. The computational architecture was implemented and tested in a Xilinx Artix-7 FPGA. We present the experimental results regarding the quantization process in a different number of bits, hardware resources, and precision. The results show an accuracy of 94% accuracy for 22-bits. This work aims to be the basis for the future implementation of a portable, low-cost, and high-reliability device for the diagnosis of Atrial Fibrillation.
Cybersecurity for Centralized and Distributed Power Generation at ISAGEN
(Universidad EAFIT, 2020-11-11) Zuluaga, Diego; ISAGEN
This paper presents the answer to the cybersecurity challenges faced by the centralization of the electric power generation control in the second company of this type in Colombia. Likewise, it describes the main cybersecurity practices that were investigated, analyzed and implemented to establish and maintain a safe environment for operations, which allow facing the risks of cyberattacks on this essential service to the society. It presents the methodologies and technical measures that should have been considered in the different stages of the project to prevent cyberattacks from being effective, to identify them in a timely manner and to achieve the resilience of the supervision and control systems that were used and tested in this environment. It also shows how these results were used as a contribution to the evolution of Colombian national electric sector regulations on the subject and how they can serve as a basis for improvements to regulation and cybersecurity for other agents in the electricity sector in the country and the region.This paper presents the answer to the cybersecurity challenges faced by the centralization of the electric power generation control in the second company of this type in Colombia. Likewise, it describes the main cybersecurity practices that were investigated, analyzed and implemented to establish and maintain a safe environment for operations, which allow facing the risks of cyberattacks on this essential service to the society. It presents the methodologies and technical measures that should have been considered in the different stages of the project to prevent cyberattacks from being effective, to identify them in a timely manner and to achieve the resilience of the supervision and control systems that were used and tested in this environment. It also shows how these results were used as a contribution to the evolution of Colombian national electric sector regulations on the subject and how they can serve as a basis for improvements to regulation and cybersecurity for other agents in the electricity sector in the country and the region.
Effect of the Solvents Content on the Mechanical Response and Compactability of Asphalt Mixtures Fabricated Using Castilla’s Paving-Heavy Crude Oils
(Universidad EAFIT, 2020-11-11) Alvarez-Lugo, Allex E; Ovalles, Evelyn; Reyes-Ortiz, Oscar; Universidad Industrial de Santander; Universidad del Magdalena; Universidad Militar Nueva Granada
The paving-heavy crude oils (PHCO) are natural cut-back asphalts composed by a high content of asphalt cement and a portion of solvents. These materials have been used in Colombia since the 90’s to improve low volume traffic roads. The existence of solvents in the PHCO allows mixing it with the aggregates in cold conditions. Then, before compaction, these asphalt mixtures require a curing process (i.e., process of partial loss of solvents from the PHCO) to ensure its proper performance. However, at present there is no consensus on the loss of solvents to specify for the curing process of mixtures fabricated with PHCO. Given this situation, this study assesses the effect of the partial content of solvents on both the mechanical response and compactability of asphalt mixtures produced using PHCO from the Castilla’s oil field (CA); a material extensively used in the East region of Colombia. The study included conducting and analyzing conventional characterization tests of the mixture constituent materials, surface free energy testing on both mastics and the aggregate, mix design, and characterization of both mechanical response and compactability of the mixtures fabricated using the CA and a control asphalt. Corresponding results led to identify and quantify a progressive improvement in both the adhesion quality of the mastic-aggregate interfaces and the mechanical response of the asphalt mixture as a function of the reduction of the solvents. These results suggest the convenience of compacting the asphalt mixtures fabricated using the CA after allowing a loss of 50% of the solvents obtained from the CA via atmospheric distillation at 360°C.
Generalized Bivariate Kummer-Beta Distribution
(Universidad EAFIT, 2020-11-11) Nagar, Daya K; Zarrazola, Edwin; Serna-Morales, Jessica; Universidad de Antioquia; Universidad Nacional de Colombia
A new bivariate beta distribution based on the Humbert’s confluent hypergeometric function of the second kind is introduced. Various representations are derived for its product moments, marginal densities, marginal moments, conditional densities and entropies.
A High-Order HDG Method with Dubiner Basis for Elliptic Flow Problems
(Universidad EAFIT, 2020-11-11) Bastidas, Manuela; Lopez-Rodríguez, Bibiana; Osorio, Mauricio; Hasselt University; Universidad Nacional de Colombia
We propose a standard hybridizable discontinuous Galerkin (HDG) method to solve a classic problem in fluids mechanics: Darcy’s law. This model describes the behavior of a fluid trough a porous medium and it is relevant to the flow patterns on the macro scale. Here we present the theoretical results of existence and uniqueness of the weak and discontinuous solution of the second order elliptic equation, as well as the predicted convergence order of the HDG method. We highlight the use and implementation of Dubiner polynomial basis functions that allow us to develop a general and efficient high order numerical approximation. We also show some numerical examples that validate the theoretical results.
Mathematical Modeling of the Spread of Alcoholism Among Colombian College Students
(Universidad EAFIT, 2020-11-11) Pérez, Edgardo; Universidad del Sinú
In this paper, we present a nonlinear mathematical model, describing the spread of high-risk alcohol consumption behavior among college students in Colombia. We proved the existence and stability of the alcohol-free and drinking state equilibrium by means of Lyapunov function and LaSalle’s invariance principle. Also, we apply optimal control to study the impact of a preventive measure on the spread of drinking behavior among college students. Finally, we use numerical simulations and available data provided by the United Nations Office on Drugs and Crime (UNODC) and the Colombian Ministry of Justice to validate the obtained mathematical model.
A Predictive Model for the Anisotropy Index of Semi-Coke Derived from the Properties of Colombia's Eastern Cordillera Coals
(Universidad EAFIT, 2020-11-11) Romero-Salcedo, Eliana; Manosalva-Sánchez, Sandra; Naranjo-Merchán, Wilson; García-Cabrejo, Oscar; Bermúdez, Mauricio A; Gómez-Neita, Juan; Universidad Pedagógica y Tecnológica de Colombia
This study developed a theoretical model for the determination of the Coke Anisotropy Quotient (CAQ) of semi-coke from the properties of its precursor coal. This is an useful parameter to define the resistance and reactivity of semi-coke in the blast furnace. For 36 semi-coke samples, a textural analysis was performed alongside a fluidity test to determine the real CAQ. The main textures observed were: isotropic and circular for high volatile bituminous coals (HVB); lenticular and fine ribbons for the medium volatile bituminous coals (MVB); and medium and thick ribbons for the low volatile bituminous coals (LVB). The CAQ varied in a range from 1 to 11. A principal component analysis (PCA) and multiple regression allowed to discriminated the importance of certain coal properties, in determining the CAQ to be recognized and to estimate parameters of the mathematical model. The statistical analysis suggested that CAQ can be best predicted from the fluidity, volatile matter, and Ro of the parent coals. The veracity of this model result was then tested using a second dataset from Poland. This work optimizes the usefulness of standard datasets in the prediction of CAQ's offering a means of quality control that could be implemented in Colombian coke production.
Towards Smart-City Implementation for Crisis Management in Fast-Growing and Unplanned Cities: the Colombian Scenario
(Universidad EAFIT, 2020-11-11) Puentes, Michael; Arroyo Delgado, Irene; Carrillo, Oscar; Barrios H, Carlos J; Le Mouel, Frédèric; Universidad Industrial de Santander; Universidad Politécnica de Madrid; Ecole Superieur de Chimie Physique Electronique de Lyon; Institut National des Sciences Appliquées - INSA - CitiLab Lyon/France
Natural or human-made disasters could do huge damage in urban areas and eventually could take lives. It is fundamental to get knowledge of the event’s characteristics to dispose of hasty information to help affected people or to prevent all the citizens from the danger zone, and then it will get time to respond to the crisis. Internet of Things (IoT) has a big impact on this kind of situation because a large amount of data through different devices could provide information about the situation, and about the people that are involved in the crisis. In a disaster, one of the big problems adding to the principal crisis is the disinformation, for that reason is necessary to have available and trusty data in case of disaster, also to know the data that provided the information system. To inform the affected people around the crisis event, there is exist some previous works that have used data from sensors, social networks text, or images, to finally be processed [1],[2],[3],[4],[5],[6],[7],[8]. This paper aims to review study-cases where cities implement crisis management platforms, focus on IoT environment where applications use hybrid data to be processed to help citizens in a crisis situation. Natural or human-made disasters could do huge damage in urban areas and eventually could take lives. It is fundamental to get knowledge of the event’s characteristics to dispose of hasty information to help affected people or to prevent all the citizens from the danger zone, and then it will get time to respond to the crisis. Internet of Things (IoT) has a big impact on this kind of situation because a large amount of data through different devices could provide information about the situation, and about the people that are involved in the crisis. In a disaster, one of the big problems adding to the principal crisis is the disinformation, for that reason is necessary to have available and trusty data in case of disaster, also to know the data that provided the information system. To inform the affected people around the crisis event, there is exist some previous works that have used data from sensors, social networks text, or images, to finally be processed [1],[2],[3],[4],[5],[6],[7],[8]. This paper aims to review study-cases where cities implement crisis management platforms, focus on IoT environment where applications use hybrid data to be processed to help citizens in a crisis situation.

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