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Diseño de una máquina hidráulica semi-automática para la producción de ladrillos king kong en el sector Fila Alta – Jaén - Cajamarca
(Universidad Nacional de Jaén, 2026-01-22) Pérez Rojas,Sergio; Huatangare Rojas,Janner Joiser; Olivera Aldana,Mario Félix; Llauce Santamaría,Rosario Yaqueliny
La investigación tuvo como objetivo diseñar una máquina hidráulica semi-automática para la producción de ladrillos King Kong en el sector Fila Alta- Provincia de Jaén. La motivación surgió por la necesidad de implementar tecnología accesible que mejore la productividad de ladrillos, actividad fundamental para el desarrollo de la construcción en el sector. La metodología fue de tipo aplicada, de enfoque cuantitativo y con diseño no experimental, limitándose a la fase de diseño. Para el desarrollo del trabajo se aplicó conocimientos y principios de ingeniería mecánica e hidráulica, y software de diseño CAD y FluidSim para su representación y validación. Los resultados de diseño técnico fueron la elaboración de planos estructurales, selección de materiales y un análisis económico preliminar con un VAN de S/. 24,858.21 y un TIR de 47% indicando una recuperación de la inversión en un periodo de 1 año y 10 meses. Concluyéndose que el diseño de la máquina hidráulica semi-automática resultó factible tanto desde un punto de vista técnico como económico.
Diseño de prototipo de turbina eólica de eje vertical para energizar sistema de sensores remotos del Centro Vulcanológico Nacional-IGP
(Universidad Nacional de Jaén, 2026-01-22) Altamirano Silva,Darwin Jesús; Vásquez Mejía,Emerson Junior; Pinedo Nava,Henry Oswaldo
El Centro Vulcanológico Nacional del Perú enfrenta limitaciones energéticas en sus estaciones de monitoreo debido a la dependencia exclusiva de sistemas fotovoltaicos, cuya eficiencia se ve afectada por la acumulación de ceniza, polvo y humedad. Ante esta problemática, se desarrolló el diseño, fabricación y evaluación de un prototipo de turbina eólica de eje vertical tipo Savonius como fuente complementaria al sistema fotovoltaico existente. El diseño se realizó mediante herramientas CAD y CAE, obteniéndose una turbina de 1.30 m de altura y 0.52 m de diámetro, optimizada estructuralmente para operar en condiciones de viento variable. Las simulaciones CFD confirmaron un flujo aerodinámico estable con velocidades entre 0 y 10 m/s, mientras que las pruebas experimentales mostraron potencias máximas en el segundo y tercer día con 11.84 W y 11.30 W respectivamente, con una energía acumulada de hasta 8.0958 Watt-hora/día y un promedio general de 7.21 Watts-hora/día. Los resultados demostraron la viabilidad técnica y funcional del sistema para cubrir parcialmente la demanda energética de 15 Watt-hora de los sensores de monitoreo. Se concluye que la implementación de la turbina eólica complementará eficazmente el sistema solar, mejorando la autonomía y resiliencia energética de las estaciones, y asegurando un monitoreo volcánico continuo y confiable.
Impact of forest fire severity on soil physical and chemical properties in pine and scrub forests in high Andean zones of Peru
(Agriculture, 2024-12-27) Ocaña Zúñiga,Candy Lisbeth
Agroforestry systems can influence the occurrence and abundance of pests and diseases because integrating crops with trees or other vegetation can create diverse microclimates that may either enhance or inhibit their development. This study analyzes the severity of coffee rust in two agroforestry systems in the provinces of Jaén and San Ignacio in the department of Cajamarca (Peru). This research used a quantitative descriptive approach, and 319 photographs were collected with a professional camera during field trips. The photographs were segmented, classified and analyzed using the deep learning MobileNet and VGG16 transfer learning models with two methods for measuring rust severity from SENASA Peru and SENASICA Mexico. The results reported that grade 1 is the most prevalent rust severity according to the SENASA methodology (1 to 5% of the leaf affected) and SENASICA Mexico (0 to 2% of the leaf affected). Moreover, the proposed MobileNet model presented the best classification accuracy rate of 94% over 50 epochs. This research demonstrates the capacity of machine learning algorithms in disease diagnosis, which could be an alternative to help experts quantify the severity of coffee rust in coffee trees and broadens the field of research for future low-cost computational tools for disease recognition and classification
Current and Future Spatial Distribution of the Aedes aegypti in Peru Based on Topoclimatic Analysis and Climate Change Scenarios
(Insects, 2025-05-02) Ocaña Zúñiga,Candy Lisbeth
Dengue, a febrile disease that has caused epidemics and deaths in South America, especially Peru, is vectored by the Aedes aegypti mosquito. Despite the seriousness of dengue fever, and the expanding range of Ae. aegypti, future distributions of the vector and disease in the context of climate change have not yet been clearly determined. Expanding on previous findings, our study employed bioclimatic and topographic variables to model both the present and future distribution of the Ae. aegypti mosquito using the Maximum Entropy algorithm (MaxEnt). The results indicate that 10.23% (132,053.96 km2) and 23.65% (305,253.82 km2) of Peru’s surface area possess regions with high and moderate distribution probabilities, respectively, predominantly located in the departments of San Martín, Piura, Loreto, Lambayeque, Cajamarca, Amazonas, and Cusco. Moreover, based on projected future climate scenarios, it is anticipated that areas with a high probability of Ae. aegypti distribution will undergo expansion; specifically, the extent of these areas is estimated to increase by 4.47% and 2.99% by the years 2070 and 2100, respectively, under SSP2-4.5 in the HadGEM-GC31-LL model. Given the increasing dengue epidemic in Peru in recent years, our study seeks to identify tools for effectively addressing this pressing public health concern. Consequently, this research serves as a foundational framework for assessing areas with the highest likelihood of Ae. aegypti distribution in response to projected climate change in the second half of the 21st century.
Geospatial Landslide Risk Mapping Using AHP and GIS: A Case Study of the Utcubamba River Basin, Peru
(Applied Sciences, 2025-08-28) Ocaña Zúñiga,Candy Lisbeth
This study examines the use of a spatial multi-criteria approach based on GIS and AHP techniques to model landslide risk in the Utcubamba river basin, Peru. The methodology
consisted of selecting twelve triggering variables: slope angle, geology, precipitation, distance to faults, drainage density, TWI, relative relief, profile curve, land use, elevation,
distance to roads, and distance to population centers. These variables were then analyzed using the AHP method and then integrated into a GIS environment, where the weighted
linear combination (WLC) method was used to map landslide risk. The risk was categorized into five classes, ranging from very low (1) to very high (5). The main results indicate that
32.81% of the area analyzed in the Utcubamba river basin presents a high and very high risk of landslides. The high-risk areas are mainly located in the southern part of the basin and
coincide with areas with steep slopes, high rainfall, and proximity to population centers or communication routes. The model generated was highly accurate (AUC of 0.82), confirming
that the integration of the AHP method with GIS allows for the precise identification of critical areas, which is useful for territorial planning, the prioritization of interventions, and
emergency management, making it a reliable and replicable methodology in other parts of Peru.