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The aviation industry has started environment friendly and also conventional energy independent alternative energy dependent designs to reduce negative impacts on the nature and to maintain its future activities in a clear, renewable and sustainable way. One possible solution proposed is solar energy. Solar-powered aerial vehicles are seen as key solutions to reduce global warming effects. This study aims to simulate a mathematical model of a solar powered DC motor of an UAV on MATLAB/Simulink environment.

Maximum power point tracking (MPPT) is a critical term in photovoltaic (PV) array systems to provide the maximum power output to the related systems under certain conditions. In this paper, one of the popular MPPT techniques, “Incremental Conductance”, is simulated with solar-powered DC motor for an UAV design on MATLAB/Simulink.

The cascade structure (PV cell, MPPT, buck converter and DC motor models) is simulated and tested under various irradiance values, and results are compared to the DC motor technical data. As a result of that, mathematical model simulation results are overlapped with motor technical reference values in spite of irradiance changes.

It is suggested to be used in real time applications for future developments.

Different from other solar-powered DC motor literature works, a solar-powered DC motor mathematical model of an UAV is designed and simulated on MATLAB/Simulink environment. To adjust the maximum power output at the solar cell, incremental conductance MPPT technique is preferred and a buck converter structure is connected between MPPT and DC motor mathematical model. It is suggested to be used in solar-powered UAV designs for future developments.

The current research conducts a comprehensive review on FishBAC (fishbone active camber morphing wing surfaces) for researchers and scientists and sheds light on challenges and opportunities of FishBAC development.

This is a review article and this study reviews previous research on FishBAC.

The current FishBAC applications could be upgraded into more efficient designs in materials, design and mechanisms with more perspectives involved. Then, this promising branch of morphing surface design could be integrated with rotor blades, unmanned aerial vehicle wings, general aviation aircraft surfaces and so on.

This is a review article.

The contributions of the study are summarized as follows: to provide an overview of FishBAC research; to compare various approaches and trends in FishBAC designs; to address the research gap in the roadmap for FishBAC design; and to discuss the challenges and opportunities of FishBAC development.

To the best of the authors’ knowledge, this is the first review on a promising morphing method and an alternative for conventional flaps and ailerons.

Lithium-polymer batteries have common usage in aviation industry especially unmanned aerial vehicles (UAV). Overheating is a serious problem in lithium-polymer batteries. Various cooling methods are performed to keep lithium-polymer batteries in the desired temperature range. The purpose of this paper is to examine pouch type lithium-polymer battery with plate fins by using particle image velocimetry (PIV) and computational fluid dynamics (CFD) for UAV.

Battery models were produced with a 3D printer. The upper surfaces of fabricated battery models were covered with plate fins with different fin heights and fin thicknesses. Velocities were obtained with PIV and CFD. Temperature dissipations were acquired with numerical simulations.

At the end of the study, the second battery model gave the lowest temperature values among the battery models. Temperature values of the seventh battery model were the highest temperatures. Fin cooling reduced the maximum cell temperatures noticeably. Numerical simulations agreed with PIV measurements well.

This paper takes into account two essential tools such as PIV and CFD, for fluid mechanics, which are significant in the aviation industry and engineering life.

The originality of this paper depends on investigation of both PIV and CFD for UAV and developing a cooling method that can be feasible for landing and take-off phases for UAV.

This paper aims to investigate the cycle performance of a small size turbojet engine used in unmanned aerial vehicles at 0–5,000 m altitude and 0–0.8 Mach flight speeds with real component maps.

The engine performance calculations were performed for both on-design and off-design conditions through an in-house code generated for simulating the performance of turbojet engines at different flight regimes. These calculations rely on input parameters in which fuel composition are obtained through laboratory elemental analysis.

Exemplarily, according to comparative results between in-house developed performance code and commercially available software, there is 0.25% of the difference in thrust value at on-design conditions.

Once the on-design performance parameters and fluid properties were determined, the off-design operation calculations were performed based on the compressor and turbine maps and scaling methodology. This method enables predicting component maps and fitting them to real conditions.

A method to be used easily by researchers on turbojet engine performance calculations which best fits to real conditions.

The purpose of this study is to determine the meteorological events that affect flight training to make the training flight more efficient in a flight training organization (FTO) and to examine the effects of these events on FTO.

Within the scope of this study, the flight training given at Eskisehir Technical University Pilotage Department (ESTU-P) is discussed, and the effect of meteorological events on flight training in this FTO is evaluated.

When the two-year (2019–2020) flight training process of ESTU-P is examined, 45% of the flights planned for 2019, 25% of the flights planned for 2020 and 33% of the total flights in the two-year period could not be realized due to meteorological events. It is determined that this result naturally affects the efficiency of the FTO negatively. Meteorological events such as high temperature, fog and snow are among the main meteorological events that cause flight training to be interrupted.

This study will create a framework for FTOs that have been or will be established.

This study aims to investigate the aviation, energetic, exergetic, environmental, sustainability and exergoeconomic performances of a micro turbojet engine used in unmanned aerial vehicles at four different modes.

The engine data were collected from engine test cell. The engine performance calculations were performed for four different operation modes.

According to the results, maximum energy and exergy efficiency were acquired as 19.19% and 18.079% at Mode 4. Total cost rate was calculated as 6.757 $/h at Mode-1, which varied to 10.131 $/h at Mode-4. Exergy cost of engine power was observed as 0.249 $/MJ at Mode-1, which decreased to 0.088 $/MJ at Mode-4 after a careful exergoeconomic analysis.

The novelty of this work is the capability to serve as a guide for similar systems with a detailed approach in the thermodynamic, thermoeconomic and environmental assessments by prioritizing efficiency, fuel consumption and cost formation. This investigation intends to establish a design of the opportunities and benefits that the thermodynamic approach provides to turbojet engine systems.

The use of unmanned aerial vehicles (UAVs) has significantly increased in the past decade and nowadays is being used for various purposes such as image processing, cargo transport, archaeology, agriculture, manufacturing, health care, surveillance and inspections. For this reason, using the appropriate image processing method for the intended use of UAVs increases the study’s success. This study aims to determine the most suitable one among the innovative methods that constitute the image processing system for a UAV to be used for surveillance purposes.

Analytical hierarchy process has been used in the solution of the decision problem to be handled in three stages, namely, platform, architecture and method. The most suitable alternative and the effect weights of these criteria results were determined at each stage.

As a result of this study, Jetson TX2 was determined as the most suitable embedded platform, ResNet is the optimum architecture and Faster R-convolutional neural networks was the best method in the image processing layer for a system that will provide surveillance with image processing method using UAV.

In UAV designs, where multiple hardware and software choices and system combinations exist, multi-criteria decision-making (MCDM) approaches can be used as a system decision mechanism.

The novelty of this work comes from the application of MCDM methods that are used as a multi-layered decision mechanism in UAV design.