This research aims to present an analysis of the behavior of multiple Remotely Piloted Aircraft Systems (multi-RPAS) flying in formation, a key aspect of advanced aerial mobility in the aerospace industry. This involves the positioning and relative distance in three dimensions (3D) of two RPAS, taking into account their operational requirements and limitations, recognizing the operating states, and addressing potential situations encountered during formation flight. For this study, the “Conformance and Fault Injection—CoFI” methodology is employed. This methodology guides the user towards a comprehensive understanding of the system and enables the creation of a set of finite state machines representing the system’s behavior under study. Consequently, models and requirements for the behavior of multi-RPAS flying in formation are presented. By applying the CoFI methodology to inject faults into the operation and predict behavior in anomalous situations, both normal and abnormal behavior models, as well as the flight behavior requirements of the multi-RPAS formation, are outlined. This analysis is expected to facilitate the identification of formation flight behavior in multi-RPAS, thereby reducing associated operational risks.

La pandemia de la COVID-19 tuvo un impacto negativo en la industria de la aviación comercial, con una notable reducción del tráfico aéreo. Se proyectó que, hacia finales de 2023, el tráfico aéreo experimentaría un incremento anual del 4,4%, lo cual llevó a un aumento en la contaminación sonora, implicando riesgos para la salud humana. En Colombia, la Aeronáutica Civil regula los niveles de ruido de las aeronaves y establece normativas para su reducción. Utilizando tecnología avanzada, se recolectaron datos sobre el tráfico aéreo en Bogotá mediante una antena ADS-B. El logro más significativo del estudio fue la identificación precisa de las zonas de mayor riesgo de contaminación sonora, con base en datos ya existentes: Suba, Engativá, Usaquén, Fontibón, Teusaquillo, Puente Aranda, Kennedy, Bosa y Barrios Unidos, debido a su proximidad a las rutas aéreas y al Aeropuerto Internacional El Dorado, información que permitió crear mapas de calor fundamentales para planificar estrategias de mitigación adecuadas. Se concluye principalmente que la expansión acelerada del tráfico aéreo incrementará notablemente los niveles de ruido, afectando las áreas cercanas al aeropuerto. Se recomienda revisar y ajustar las regulaciones y políticas de tráfico aéreo para minimizar el impacto en el futuro.

This paper presents the design, optimization, and performance evaluation of a Satellite-Based Augmentation System (SBAS) ground segment tailored to Colombia’s air navigation infrastructure, with emphasis on ionospheric anomalies in equatorial latitudes. The configuration comprises six Reference Stations (RIMS), strategically sited via geometric dilution of precision (GDOP) minimization and airspace demand models from ADS-B data. A simulation suite—integrating STK^®, Radio Mobile™, and Stanford-ESA certified monitors—quantifies service volume, link margins, and protection level compliance. Ionospheric threat characterization uses regional scintillation datasets (σln ≈ 0.36, ROTI₉₅ ≈ 85 mm/km), informing GIVE inflation and dual-frequency pseudorange integrity validation. Simulations confirm the system sustains ≥ 99.8% APV-I availability over the CAR/SAM FIR, with Horizontal and Vertical Protection Levels (HPL/VPL) bounded below 28 m and 46 m. Uplink integrity and GEO broadcast continuity are modelled under worst-case masking and multipath, confirming ICAO Annex 10 SARPs compliance. The architecture achieves a high performance-to-cost ratio, enabling nationwide SBAS coverage with a 65% cost reduction versus legacy navaids. The system is forward-compatible with dual-frequency multi-constellation SBAS (DFMC), supporting future APV-II scalability. These results position Colombia as a regional node for GNSS augmentation, fostering safety, efficiency, and procedural harmonization.

This paper describes the application of computational modeling and computer-aided design (CAD) for the conceptual design and structural analysis of the maintenance process of Klimov TV3-117 engines at an approved Maintenance, Repair and Overhaul (MRO) facility in Colombia. The main issue is that these engines are difficult to roll and manipulate due to their weight, which ranges between 250 and 350 kg, which causes time and cost overruns for the operator, and delays in the scheduled maintenance times. The solution proposed by this study is the conceptualization and structural feasibility of a prototype of ground support equipment for handling and maintenance of Turboshaft engines, implementation of which could save up to 100 person-hours, which translates into about USD 10,000, since the current process requires four specialists and two inspectors, whereas the modified process would only require one of each

Flutter constrains the design of modern high-aspect-ratio wings, yet the combined influence of planform geometry, aspect ratio (AR) and structural flexibility is rarely assessed within a single consistent framework. This work presents a unified, physics-based reduced-order comparison of rectangular, trapezoidal and elliptical planforms under both rigid and flexible representations, intended as a screening tool for preliminary design rather than as a quantitatively predictive methodology for specific aircraft. A two-degree-of-freedom plunge–pitch typical section with quasi-steady (Theodorsen-based) aerodynamics is cast in state-space form, and flutter is identified through eigenvalue continuation by combined frequency coalescence and damping sign change. For rectangular and trapezoidal wings, increasing AR or reducing stiffness consistently advances flutter onset: at a fixed AR of 7.1, stiffening alone raises the critical speed by approximately 43 m/s (from 105 to 148 m/s, ≈+41%). In contrast, within the reduced-order model the elliptical planform inverts this trend: with sufficient stiffness, frequency coalescence is suppressed, and from the stiffened baseline (AR ≈ 4.75) raising AR to 5.6 keeps the wing flutter-free across the investigated velocity range, whereas lowering AR to 3.9 reintroduces hard flutter at 155 m/s. These model-based comparative tendencies indicate that AR and structural flexibility are strongly coupled design drivers and that elliptical loading is comparatively flutter-resistant, providing an efficient basis for early-stage configuration screening.

Reliable and up-to-date measurements of public space remain scarce in small and medium-sized towns (SMSTs), where conventional geospatial datasets are often outdated, inconsistent, or inaccessible. This study presents a low-cost and fully reproducible computational pipeline that integrates nadir RGB imagery captured by a DJI Mini 3 UAV with a lightweight instance-segmentation model (Ultralytics YOLOv12-seg) and GIS-based post-processing to derive class-specific surface indicators at the neighborhood scale. The workflow consists of four components: autonomous UAV acquisition over three representative zones of Sesquilé, Colombia; planar mosaic generation and georeferencing using ad hoc ground control points; fine-tuning of a YOLOv12-seg model trained on locally annotated images; and transformation of predicted masks into OSM and GeoPackage geometries for metric analysis. The trained model achieved stable convergence with mask mAP50 ≈ 0.85 and mAP50–95 ≈ 0.70, supported by balanced precision–recall behavior across classes. Spatial outputs exhibit coherent morphological contrasts between the analyzed zones. Buildings occupy 48.17% of the mapped area, vegetation 25.88%, and transport- and plaza-related public space (roadways, sidewalks, and hardscape areas) 25.95%. These proportions capture a clear gradient from a dense urban core to less consolidated peripheral sectors. Results demonstrate that very-high-resolution UAV imagery, combined with open-source deep-learning tools and structured GIS post-processing, can reliably produce operational public-space indicators for SMSTs at low cost. The methodology provides an accessible and scalable framework for evidence-based urban assessment in municipalities with limited technical and financial resources.