Current environmental policies for the aviation sector motivate the use of cleaner propulsion alternatives in order to reduce their CO2 footprint and noise pollution in the coming years. In this context, hybrid propulsion systems have emerged as a potential solution, as they have demonstrated a good trade-off between performance and low pollutant emissions. The present work carries out a comparison between parallel and series hybrid propulsion systems using heterogeneous and homogeneous distributed propulsion architectures. In order to highlight the opportunities of distributed propulsion systems and validate the methodology developed, a single propulsion hybrid configuration is used as baseline case for this study. For the propulsion system sizing, this work uses a parametric modelling tool, which includes a constraint analysis coupled with a weight estimation module to determine suitable configurations for a environmental monitoring mission. The latter module includes semi-empirical correlations to size the electric and mechanical components for each propulsion setup. From the results, it has been found that for the representative case of monitoring in the Galapagos Islands, which requires an endurance of approximate 7 h, the parallel hybrid system using three distributed propulsors presents the best performance features in terms of fuel savings, showing a 34% reduction compared with the baseline case. To summarize, the main contribution of this study lies on the development of a methodology to set potential hybrid distributed propulsion configurations for UAVs aimed for determined monitoring missions.
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.
-In this paper, a method based on feed-forward backpropagation artificial neural networks is developed to achieve a more accurate prediction of the useful life of the Francis turbines, subject to the monitoring of the condition. Predicting the remaining life of the Francis turbine components is critical to an effective condition-based maintenance to improve reliability and reduce overall maintenance costs. With the correct instrumentation it is possible to periodically measure and calculate the necessary operating parameters and, in the present investigation, having input data, the vibration severity in speed magnitude and the turbine efficiency, there will be trained a feed-forward backpropagation neural network in such a way as to obtain the Weibull failure rate function of the Francis Turbine. A two-element input vector is introduced with 100 samples for each input; the targets (100 samples) of Weibull failure rate function are also introduced. The method developed, for its consistency and effectiveness, can be generalized to systems and rotating equipment.
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.
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