Context: This research presents two main results: (i) the application of deep learning networks for the classification of transient overvoltage in the frequency domain, and (ii) the physical-mathematical formulation for the coupling of atmospheric electrical discharges in polarized media in the frequency domain. Method: Initially, transient overvoltage records resulting from atmospheric electrical discharges were obtained from simulations in EMTP-ATP software, using the IEEE 13-node distribution network as a reference. Each transient overvoltage was transformed from the time domain to the frequency domain via the Fast Fourier Transform. Subsequently, the neural networks were trained, and their results were compared. For indirect lightning strikes, a complex-variable analysis of permittivity and permeability was performed. These variables were applied to the lightning coupling model in distribution lines or networks. Results: Classification accuracies of 80 and 89.99% were achieved for transient overvoltage using the GoogLeNet and Python-ChatGPT neural networks, respectively. Furthermore, this work presents the coupling expression for atmospheric electrical discharges in polarized media. Conclusions: The classification of transient overvoltage records using deep-layer neural networks and the physical-mathematical expression for lightning coupling in the frequency domain through complex variables allows for a broader understanding of the network response to this type of natural phenomenon.
Voltage stability is a fundamental aspect of power system reliability, which refers to an electrical network’s ability to maintain acceptable voltage levels under normal operating conditions and various types of disturbances
Context: Evaluating third-party logistics (3PL) providers is a complex task since multiple criteria assessed by experts with potentially diverse perspectives are involved, leading to varying scores based on individual prioritizations. This study attempts to evaluate 3PL providers for a mid-sized fishery company in Jakarta, Indonesia, focusing on refrigerated transportation within cold chain logistics. Method: A methodology integrating rough stepwise weight assessment ratio analysis (R-SWARA) and complex proportional assessment (COPRAS) is employed to address expert uncertainty and rank six providers based on seven criteria: security, punctuality, cost, delivery area, customer service, assurance, and logistics experience. R-SWARA assigns weights using rough set intervals, while COPRAS ranks providers. Results: The integrated methods yield Vendor A as the top choice, with a utility degree of 100%, followed by Vendor D and others ranging from 96.7 to 98.4%. These rankings highlight the critical role of punctuality and security in refrigerated transportation, aligning with the fishery industry’s need to ensure product freshness and reliability. A sensitivity analysis that varies the weight of punctuality by ± 20% confirms the ranking’s stability, highlighting the methodology’s robustness. The findings align with prior studies emphasizing performance and quality in logistics, while R-SWARA’s use of intervals offers a novel approach to handling uncertainty. Conclusions: The proposed method recommends Vendor A to ensure timely and secure seafood delivery, with implications for perishable goods logistics. The limitations include a small expert panel and a single-case focus, suggesting the need for future research with larger samples and broader applications. Another limitation of the proposed approach is its reliance on expert judgement for criteria weighting, as well as its sensitivity to the selected criteria and case context. Therefore, the findings should be interpreted as a decision support rather than universal rankings.
Context: In recent times, access to electricity in non-interconnected areas has been a constant challenge. Therefore, this article evaluates the technical feasibility of implementing direct-current (DC) microgrids in these areas, focusing on food conservation. Our evaluation focuses on the region of Chacón Playa (Timbiquí) in the Cauca Pacific, Colombia. Method: This work analyzes the advantages and disadvantages of DC microgrids vs. alternating-current (AC) systems, selecting a radial topology for its simplicity and expandability. A simulation is performed in MATLAB-Simulink with a control system based on the incremental conductance algorithm, which incorporates solar photovoltaic generation, battery backup, power converters, and a load composed of four DC coolers. Results: The results and simulations show that DC microgrids are effective in meeting voltage and current demands in response to changes in solar radiation and power demand. Our findings highlight the ability of DC microgrids to provide a stable and efficient power supply suitable for food conservation in non-interconnected areas. Conclusions: DC microgrids represent a viable solution to cover energy needs in isolated areas. This study supports their implementation as a sustainable and reliable alternative, opening new opportunities for the development of regulatory frameworks that facilitate the expansion of this type of technology in similar regions.
Contexto: Las tasas de siniestralidad en la red vial terciaria de Colombia superan los promedios nacionales, en gran parte debido a la falta de instrumentos para la recolección sistemática de datos y a la limitada participación de las comunidades locales en la identificación de riesgos. Este estudio tuvo como objetivo diseñar una herramienta de diagnóstico de seguridad vial que pueda ser aplicada por la comunidad, adaptada a contextos rurales y validada con actores locales en el departamento del Cauca, Colombia. Método: Se realizó una revisión de literatura para identificar los principales factores de riesgo que afectan la seguridad vial en las vías terciarias de Colombia. Se incorporó la escala KABCO por su simplicidad y su idoneidad para el trabajo colaborativo. A partir de estos insumos, se desarrolló una herramienta de diagnóstico y una guía de usuario. Finalmente, se implementó un estudio piloto mediante talleres participativos, durante los cuales se recolectaron puntos georreferenciados y evaluaciones de riesgo. Resultados: La aplicación piloto de la herramienta permitió identificar y georreferenciar siete puntos críticos a lo largo de un tramo vial en el municipio de Popayán. En estos lugares, la velocidad fue identificada como uno de los factores más influyentes en los siniestros viales reportados por la comunidad. La herramienta demostró claridad y viabilidad de uso por parte de participantes sin formación técnica previa. Conclusiones: La herramienta desarrollada ofrece un método replicable que permite a las comunidades rurales identificar y gestionar los riesgos de seguridad vial, generando datos valiosos para la formulación de planes de mantenimiento y políticas de prevención. Su implementación puede optimizar la asignación de recursos y fortalecer la colaboración entre las comunidades y las autoridades responsables.
Context: Calculating short-circuit currents is key to equipment sizing and protection coordination in electrical power systems. However, methodological differences between ANSI/IEEE C.37 and 141 and IEC 60909 create uncertainty when selecting the most appropriate approach. This study addresses this problem through a comparative analysis based on computer simulations that evaluate both methodologies under equivalent conditions. Method: An industrial system with 44 busbars is modeled in ETAP (version 20.0), considering grid connection, local generation, and rotating loads. Short-circuit currents are calculated while following the procedures of both standards, and five representative fault points are analyzed. The evaluation includes six parameters: symmetrical inrush current, half-cycle closing current, peak fault current, interrupting current, asymmetrical breaking current, and steady-state current. Results: The IEC method yields values between 5and 10% higher than those obtained with ANSI/IEEE in most cases. The greatest differences are observed at busbars near generators and higher-power rotating machines, reaching up to 9.34% in the inrush current. These variations are mainly associated with the treatment of the X/R ratio and the voltage factor c applied in IEC. Conclusions: The IEC 60909 standard offers more conservative estimates for demanding designs, while ANSI/IEEE is useful in preliminary analyses, providing practical criteria for selecting the standard based on system criticality.
Context: In the ship concept design stage, naval architects must estimate the principal attributes of a vessel before the final definition of hull proportions and detailed arrangements. These estimates are essential for assessing feasibility, performance, and operational capability. However, reliable vessel-specific predictive tools are often unavailable for certain vessel categories. Method: A database of 130 American-type semi-industrial purse with RSW systems was employed to develop practical regression-based power-law models for estimating key ship attributes directly from principal hull dimensions. Results: The results show that the main volumetric and power attributes exhibit strong and consistent scaling relationships with the principal dimensions, yielding moderate to high determination coefficients, while the fuel and water capacities report a weak geometric dependence. The proposed regression equations demonstrate improved predictive performance when compared to existing formulations reported in the literature for semi-industrial purse seiners. Conclusions: This work provides a set of vessel-specific, empirically grounded regression tools tailored to American-type semi-industrial purse seiners, which can be directly applied during the ship concept design stage to support rapid and informed decision-making. This study complements previous analyses focused on hull geometric ratios by addressing a distinct and application-oriented design problem that deals with attribute estimation rather than geometric proportion selection.
Context: The need for efficient energy harvesting in photovoltaic (PV) systems requires advanced maximum power point tracking (MPPT) techniques. Traditional methods like perturb and observe (P&O) exhibit limitations under varying conditions, leading to less efficient energy extraction. Method: This study compares a model-predictive controller (MPC) combined with optimization algorithms such as the particle swarm optimizer (PSO), the vortex search algorithm (VSA), and the salp swarm algorithm (SSA) to improve MPPT performance in PV systems. These algorithms are tested under different irradiance conditions to assess their efficiency and adaptability. Results: The results show that PSO, when used with MPC, greatly enhances energy extraction compared to the conventional P&O method. Additionally, VSA and SSA also perform well in adapting to rapid irradiance changes, ensuring an optimal power output. Conclusions: Optimization-based MPPT methods, especially those using PSO, offer significant efficiency improvements for PV systems, making them strong alternatives to traditional techniques.
Solving the power flow problem in transmission networks is crucial for ensuring the reliable and efficient operation of electrical power systems. Power flow analysis allows engineers to determine the voltage, current, and power flows of a network, which is essential for maintaining system stability and avoiding overloads. Accurate power flow solutions aid in identifying potential issues such as voltage drops, line losses, and system inefficiencies, enabling the proactive maintenance and optimization of the grid. This analysis is vital for integrating renewable energy sources, as it ensures an effective power distribution, even when dealing with variable generation. Ultimately, solving the power flow problem enhances the overall resilience, reliability, and economic performance of the transmission network, supporting a stable supply of electricity to consumers.
Context: The cooling performance of a thermal battery plays a critical role in its efficiency, lifespan, and safety. This importance stems from the heat generated during charging and discharging processes. As temperatures rise, key battery characteristics are significantly affected. Method: Using the ANSYS Fluent computational fluid dynamics software, a 2D numerical simulation was conducted to study the cooling of a lithium-ion battery in the presence of nanofluids. The flow of nanofluids was analyzed using the multiphase mixture model. Results: It was found that the coolant inlet velocity significantly impacts the module's temperature distribution and the maximum temperature difference, where the temperature differences almost stabilize for inlet velocities exceeding 0.3 m/s. The effect of using nanofluids was studied with three different types of nanoparticles (alumina, copper, and fullerene) dispersed in water as the base fluid. The results show that the temperature difference in the module varies depending on the nature and volume fraction of the nanoparticles. The incorporation of nanofluids leads to a significant reduction in module temperatures. Fullerene nanoparticles were found to exhibit superior cooling performance compared to other nanoparticle types. On the other hand, a nanoparticle volume fraction exceeding 2% yields a nearly uniform temperature distribution within the module, as well as reduced cell temperatures. Conclusions: Nanofluids have an important effect on battery cooling. Optimizing nanoparticle concentration and flow dynamics can effectively improve thermal management strategies for lithium-ion battery systems.
Context: Industrial growth and various anthropogenic activities have generated multiple pollutants, including heavy metals such as hexavalent chromium, or Cr(VI), which pose a major threat to both humans and the environment, as their characteristics make them persistent, bioaccumulative, and non-biodegradable. Method: In this paper, computer-aided process engineering (CAPE) was used to simulate an industrial-scale adsorption column packed with a biomass based on cocoa husk residues for the removal of Cr(VI) in solution. A parametric sensitivity analysis was conducted, using Aspen Adsorption as a simulation tool to analyze different column configurations. Results: The Freundlich isothermal model, in combination with the linear driving force (LDF) kinetic model, yielded efficient results in removing Cr(VI) via adsorption, with values of up to 97.1%. The best operating conditions included an initial concentration of 5000 mg/L, a bed height of 5 m, and an inlet flow rate of 100 m3/day. Conclusions: This study demonstrates that the use of computational assistance holds great potential for predicting the performance of an adsorption column packed with agro-industrial waste, which constitutes a safe and cost-effective alternative for the design and modeling of industrial-scale columns.
Context: This article examines access to electrification in rural areas within the framework of Sustainable Development Goal 7 (SDG7), which seeks to ensure access to modern, affordable, and sustainable energy for all. It identifies common barriers to energy access in rural communities and highlights the limitations of conventional approaches, emphasizing the need for integrative and participatory decision-making processes in rural electrification projects. Method: This study proposes an integrative decision-making model based on design thinking, the systemic approach, participatory action research (PAR), and the principles of behavioral economics. This model prioritizes community participation and the cultural and contextual appropriateness of electrification solutions, supported by participatory tools such as empathy maps and digital surveys to identify both explicit and latent energy needs and preferences. Results: The results show that integrating participatory and behavioral approaches strengthens community governance, improves the acceptance of electrification systems, and optimizes the use of technical and financial resources. Active community engagement increases trust in energy solutions, while behavioral design strategies promote more efficient energy use without compromising user comfort. Additionally, participatory tools reveal non-obvious energy demands and social barriers often overlooked by purely technical assessments. Conclusions: The findings demonstrate that a successful rural electrification depends not only on technological solutions, but also on inclusive, context-aware decision-making processes. The proposed integrative model contributes to sustainable human development by enhancing the acceptance and long-term sustainability of electrification projects in rural areas.
Electric power networks are interconnected systems entrusted with transforming, transmitting, and distributing electricity from generation points to the end user. Within this architecture, electrical substations perform the intermediate function of voltage transformation and help to ensure power quality through appropriate control and protection systems. Accordingly, they require automation technologies that enable the continuous monitoring, control, and protection of the infrastructure involved in these processes. Although there are international standards for grid-automation processes—most notably IEC 61850 for communications [1]—, current advances in artificial intelligence (AI) open a window of opportunity to enhance control responses to grid fluctuations.
Context: The mining industry is the main culprit behind the generation of acid mine drainage (AMD). During coal extraction processes, sulfide minerals react with groundwater, releasing ions such as Fe2+ and Fe3+, sulfates (SO4-2), and protonic acidity (H+). The low pH of AMD can cause significant environmental damage. AMD remediation is usually achieved using alkaline systems, wherein the AMD passes through limestone to be neutralized. Nevertheless, this process requires prolonged treatment times and constant cleaning steps to remove the coating formed on the limestone, which reduces its effectiveness. Method: This study evaluates a novel oxic-limestone rotational system for the treatment of AMD produced by the coal industry. The AMD collected was characterized in terms of pH, dissolved oxygen, Fe (Fe total, Fe2+, and Fe3+), and . Results: The results demonstrate the optimal efficiency of the proposed system, reducing the treatment time from 120 h in conventional systems to 1.5 h when applying a ratio of 0.25k g of limestone per liter of AMD. Conclusions: The rotational system enables the superficial degradation of the limestone, maintaining an active contact area for longer periods. This allows for optimized AMD remediation efficiency, reducing operating costs and necessitating fewer system cleanup steps.
Context: The high rate of road accidents in Colombia constitutes a serious public health issue. This study seeks to identify spatial patterns in the occurrence of traffic accidents at the departmental level. Based on these data, the aim is to better understand the factors that influence road accidents in order to propose more effective prevention strategies. Method: To this effect, a cluster analysis based on the K-means algorithm and binomial analysis was used. These statistical techniques allowed grouping Colombian departments according to their accident profile, considering variables such as geographical location, incidents, the validity of vehicle documents, and the presence of new road actors. Results: The results of the analysis revealed three groups of departments with different accident rates: high, medium, and low. This classification makes it possible to identify regions with a higher risk of suffering road accidents and determine their associated factors, such as population density and road conditions. This study demonstrates the usefulness of cluster analysis to identify spatial patterns in road accidents at the departmental level. Conclusions: The results obtained contribute to a better understanding of the factors that influence the occurrence of traffic accidents in Colombia, which enables the design of more focused and effective prevention strategies. Future research could delve into the analysis of the socioeconomic and cultural factors associated with road accidents, in addition to exploring the application of predictive models to anticipate the occurrence of accidents.
Context: Energy harvesting has positioned itself an emerging area of research due to recent developments in low-power electronics, the Internet of Things, and artificial intelligence. Various diode-based circuits and alternatives have been proposed in the literature, but the application of CMOS cross-coupled circuits, specifically in piezoelectric energy-harvesting systems, has not been properly explored. Method: An experimental study was conducted in order to assess the performance of a two-stage cross-couple MOS-based voltage multiplier in piezoelectric and solar energy harvesting. A piezoelectric disc was used to evaluate the output. The piezoelectric output was obtained by applying a small pressure to the input, and a 6 V panel was employed in the solar energy setup. Results: The proposed circuit provides a 1.91-fold voltage gain in the piezoelectric energy harvester. Conclusions: The two-stage MOS-based cross-coupled voltage multiplier circuit performs better than the diode-based alternative in the piezoelectric energy harvester. These experimental results show encouraging prospects for green energy, low-power electronics, and Internet of Things applications, among others.
Context: It is estimated that, in Colombia, more than 1300 brick industries consume around 5800 Tcal/year, which are supplied by coal, biomass, wood, and gas combustion. The most commonly used kilns are down-draught, wherein coal combustion is produced on fixed-grate beds, emitting greenhouse gases and other pollutants. As a contribution to solving this problem, this work presents the model of a fixed-bed system with coal volatiles post-combustion. Method: Temperature, time, coal consumption, and combustion products were monitored in a down-draught kiln, in order to determine their mass, energy, and thermal efficiency balances. Coal characterization was performed under ASTM standards, ashes were determined via XRD, XRF, and TGA, and emissions were obtained using a gas analyzer. The thermodynamic model used to design the 3D reactor was based on coal-burning analysis. Results: The process lasted 3166 min, consuming 2150 kg of coal. The combustion gases exhibited a varying composition of CO2, CO, O2, and hydrocarbons. The temperature on the grate reached 900 °C, and we recorded 1000 °C in the dome and 600 °C at the chimney base. The temperature difference between the dome and the chimney base explains the heat transferred for ceramic baking. The calorific value of the char was 19.52% higher than that of the coal used. The composition of the ash showed silicon oxide, mullite, and goethite. The 3D model consists of a grate with preheater ducts for the secondary air post-combustion of the volatiles. Conclusions: The outcome of this research was the 3D model of a fixed-bed grate for coal combustion and volatiles post-combustion. With its implementation, we expect to improve air quality and reduce the effects of the process on human health, as well as its operating costs.
Context: This work presents the development of an agave decorticator with a safe feeding mechanism. Despite advancements in decortication technology, the literature provides few descriptions that could enable the reproduction of these devices, particularly those with safe feeding mechanisms. Therefore, this article presents the design of an agave decortication machine with a novel feeding system that enhances operational safety. This machine is intended for small-scale production in remote locations with limited access to technology and economic resources, and it is amenable to application in developing countries. Method: A mechanical and electronic design methodology was adopted to configure the drum decortication mechanism, the belt drive, the shaft, bearings, the feeding mechanism, and the electronic control and command elements. Structural verification was also carried out through finite element simulations. Theoretical analysis and simulation tools, along with CAD/CAE and electronic design software, were utilized. The construction involved typical workshop machining operations such as turning, drilling, girder cutting, and shield metal arc welding. Results: The machine was successfully constructed. Preliminary tests demonstrated a good performance, with a dry fiber production rate of 31.2 kg/h, which is comparable to traditional hand-fed decorticators. The feeding mechanism operates at a significantly low speed (2.5% of the beater drum's tangential speed), which prevents accidents associated with typical machine configurations. The cost of the equipment is estimated to be 1152 USD, a good value when compared against other similar prototypes in the literature. Conclusions: Our agave decorticator with a safe feeding mechanism was successfully designed, built, and preliminarily tested, demonstrating its potential to enhance process safety and efficiency in remote and developing regions while supporting environmental sustainability, sustainable agriculture, and rural employment opportunities.
Context: This study developed an energy dispatch model (EDM) using the Cauchy-based distribution optimizer (CbDO) for coordinating battery energy storage units (BESUs) and photovoltaic (PV) sources in medium-voltage distribution networks, aiming to minimize energy losses and operating costs while observing to network constraints. Method: The CbDO was implemented in MATLAB and benchmarked against the continuous genetic algorithm (CGA), the parallel particle swarm optimizer, the parallel vortex search algorithm, and a semidefinite programming (SDP) approach. The analyzed scenarios included unitary and variable power factor operation in order to test optimization performance. Results: The CbDO outperformed traditional methods, achieving lower energy losses and CO2 emissions, closely matching the SDP method's results in variable power factor scenarios. The most significant gains were observed when all DERs operated flexibly, validating our proposal's effectiveness in complex non-convex problems. Conclusions: The CbDO is a viable and efficient solution for EDM, providing near-SDP performance with a simpler implementation. BESU integration and flexible power factor operation can notably enhance grid efficiency.
Context: The use of alternative materials in construction requires the implementation of new methods that allow addressing the problems associated with the manufacture of traditional composite materials. In recent years, additive manufacturing techniques have attracted the attention of entrepreneurs and researchers due to its ease in processing complex designs and its low processing times. However, there is little information about the mechanical performance of composites obtained from the processing of biopolymer filaments reinforced with plant fibers. Method: We evaluated the mechanical behavior of 3D-printed biocomposites subjected to axial tension loads. For the experimental design, filaments were constructed using 90% polylactic acid granules and 10% pulverized rattan fibers. The properties of the filaments were analyzed through microscopy, density, thermogravimetry, roughness, and hardness tests. The specimens were printed according to the dimensions specified in ASTM D638, and the effect of infill density and printing orientation on their physical and mechanical properties was analyzed. A statistical analysis was carried out in order to formulate equations allow predicting the behavior of the material based on the printing parameters considered. Results: The obtained filaments were characterized and compared against their unreinforced counterparts. The specimens were printed using the fused deposition method. The effect of the printing parameters on the physical and mechanical properties of the stressed biocomposite was determined, and the impact of the studied variables was analyzed using a central composite design. Conclusions: The surface roughness of the samples increased with the printing orientation and decreased as the infill density increased. Hardness and tensile strength increased significantly with increasing infill density, and they decreased with an increasing printing angle. The probes printed with 80% infill showed a notable increase in rigidity.
