Despite the increasing demand of Unmanned Aerial Vehicles (UAVs) for a wide range of civil applications, there are few methodologies for their initial sizing. Nowadays, classical methods, mainly developed for transport aircraft, have been adapted to UAVs. However, these tools are not always suitable because they do not fully adapt to the plethora of geometrical and propulsive configurations that the UAV sector represents. Therefore, this work provides series of correlations based on off-the-shelf components for the preliminary sizing of propulsion systems for UAVs. This study encompassed electric and fuel-powered propulsion systems, considering that they are the most used in the UAV industry and are the basis of novel architectures such as hybrid propulsion. For these systems, weight correlations were derived, and, depending on data availability, correlations regarding their geometry and energy consumption are also provided. Furthermore, a flowchart for the implementation of the correlations in the UAV design procedure and two practical examples are provided to highlight their usability. To summarize, the main contribution of this work is to provide parametric tools to size rapidly the propulsion system components, which can be embedded in a UAV design and optimization framework. This research complements other correlation studies for UAVs, where the initial sizing of the vehicle is discussed. The present correlations suit multiple UAV categories ranging from micro to Medium-Altitude-Long-Endurance (MALE) UAVs.

The operation of various types of turbomachines is importantly affected by sediment erosion. Francis turbines used for power generation typically suffer said effects due to the fact that they are used in sediment-laden rivers and are usually operated disregarding the long-term effect of the erosion on turbine performance. This investigation seeks to study the erosion rate for the main components of the turbines located at San Francisco hydropower plant in Pastaza, Ecuador. A sediment characterization study was performed in order to determine the properties of the particles present in Pastaza River and accurately predict their effect on the turbine flow passages. A numerical approach combining liquid–solid two-phase flow simulation and an erosion model was used to analyze the erosion rates at different operating conditions and determine wear patterns in the components. As expected, the results indicated that an increase in the erosion rate was obtained for higher intake flows. However, a dramatic increase in the erosion rate was observed when the turbine was operated at near-full-load conditions, specifically when guide vane opening exceeded a 90% aperture.

The present paper focuses on the numerical simulation of unsteady cavitation around a NACA66 hydrofoil to improve the understanding of the cavitation effects on hydraulic machinery. For this aim, the Zwart–Gerber–Belamri cavitation model was updated and uploaded as a library file for OpenFOAM’s solvers using C++ language. Furthermore, the hybrid Reynold average Navier–Stokes (RANS)–large eddy simulation (LES) model $k-\omega$ SST scale adaptive simulation (SAS) was implemented as a turbulence model for the present study of scale adaptive simulation. For validation, numerical results were compared with experimental results obtained by Leroux at the Naval Academy Research Institute in France. In order to highlight the benefits in terms of computational consumption and reproduction of the phenomenon the $k-\omega$ SST SAS model was compared against implicit large eddy simulation (ILES). Results show that the cavitation evolution including the maximum vapor length, the detachment and the oscillation frequency were reproduced satisfactorily using $k-\omega$ SST SAS. Moreover, $k-\omega$ SST SAS results predicted a lower total vapor volume on time than ILES, which is related to observed pulses of pressure coefficient, $C_{\mathrm{p}}$ , and those match fairly well with the experimental results. To summarize, the $k-\omega$ SST SAS model predicts with good accuracy unsteady cavitation behavior around hydrofoils and shows improved versatility over the ILES approach.

Unmanned Aerial Vehicles (UAVs) are versatile, adapting hardware and software for research. They are vital for remote monitoring, especially in challenging settings such as volcano observation with limited access. In response, economical computer vision systems provide a remedy by processing data, boosting UAV autonomy, and assisting in maneuvering. Through the application of these technologies, researchers can effectively monitor remote areas, thus improving surveillance capabilities. Moreover, flight controllers employ onboard tools to gather data, further enhancing UAV navigation during surveillance tasks. For energy efficiency and comprehensive coverage, this paper introduces a budget-friendly prototype aiding UAV navigation, minimizing effects on endurance. The prototype prioritizes improved maneuvering via the integrated landing and obstacle avoidance system (LOAS). Employing open-source software and MAVLink communication, these systems underwent testing on a Pixhawk-equipped quadcopter. Programmed on a Raspberry Pi onboard computer, the prototype includes a distance sensor and basic camera to meet low computational and weight demands.Tests occurred in controlled environments, with systems performing well in 90% of cases. The Pixhawk and Raspberry Pi documented quad actions during evasive and landing maneuvers. Results prove the prototype’s efficacy in refining UAV navigation. Integrating this cost-effective, energy-efficient model holds promise for long-term mission enhancement—cutting costs, expanding terrain coverage, and boosting surveillance capabilities.

The performance of propulsion configurations with boundary layer ingestion (BLI) is affected to a large extent by the level of distortion in the inlet flow field. Through flow methods and parallel compressor have been used in the past to calculate the effects of this aerodynamic integration issue on the fan performance; however high-fidelity through flow methods are computationally expensive, which limits their use at preliminary design stage. On the other hand, parallel compressor has been developed to assess only circumferential distortion. This paper introduces a discretized semi-empirical performance method, which uses empirical correlations for blade and performance calculations. This tool discretizes the inlet region in radial and circumferential directions enabling the assessment of deterioration in fan performance caused by the combined effect of both distortion patterns. This paper initially studies the accuracy and suitability of the semi-empirical discretized method by comparing its predictions with CFD and experimental data for a baseline case working under distorted and undistorted conditions. Then a test case is examined, which corresponds to the propulsor fan of a distributed propulsion system with BLI. The results obtained from the validation study show a good agreement with the experimental and CFD results under design point conditions