This paper presents the application of an active energy management strategy to a hybrid system consisting of a proton exchange membrane fuel cell (PEMFC), battery, and supercapacitor. The purpose of energy management is to control the battery and supercapacitor states of charge (SOCs) as well as minimizing hydrogen consumption. Energy management should be applied to hybrid systems created in this way to increase efficiency and control working conditions. In this study, optimization of an existing model in the literature with different meta-heuristic methods was further examined and results similar to those in the literature were obtained. Ant lion optimizer (ALO), moth-flame optimization (MFO), dragonfly algorithm (DA), sine cosine algorithm (SCA), multi-verse optimizer (MVO), particle swarm optimization (PSO), and whale optimization algorithm (WOA) meta-heuristic algorithms were applied to control the flow of power between sources. The optimization methods were compared in terms of hydrogen consumption and calculation time. Simulation studies were conducted in Matlab/Simulink R2020b (academic license). The contribution of the study is that the optimization methods of ant lion algorithm, moth-flame algorithm, and sine cosine algorithm were applied to this system for the first time. It was concluded that the most effective method in terms of hydrogen consumption and computational burden was the sine cosine algorithm. In addition, the sine cosine algorithm provided better results than similar meta-heuristic algorithms in the literature in terms of hydrogen consumption. At the same time, meta-heuristic optimization algorithms and equivalent consumption minimization strategy (ECMS) and classical proportional integral (PI) control strategy were compared as a benchmark study as done in the literature, and it was concluded that meta-heuristic algorithms were more effective in terms of hydrogen consumption and computational time.

Nowadays, due to climate change and disappearance of fossil fuels, hybrid electric UAVs using renewable energy sources are being developed. In addition, although research on UAVs with a large wingspan and high weight is common due to their long endurance, research on mini UAVs has remained limited. This study aims to increase the energy capacity of solar-powered mini UAVs and thus extend their endurance by developing a fixed-wing hybrid UAV that can fly with solar energy as much as possible, especially during the cruise phase. In this study, a solar-powered mini VTOL (vertical take-off and landing) UAV with a wingspan of 1.8 m and weight of 3.3 kg is developed and a model of the system consisting of solar cells, a battery, a super capacitor, and a DC/DC converter is created in MATLAB/Simulink software (R2023b). Additionally, state machine control (SMC), a rule-based (RB) energy management strategy (EMS), has been applied to this model. While the power obtained from the sun is divided among the other energy components, the durability of the UAV is increased, and the excess energy is stored as altitude energy to be used when necessary. As a result, in this study, an energy management algorithm including altitude energy has been successfully applied to a solar-powered UAV, achieving an 11.11% energy saving.

In this paper, a new conceptual design methodology for a hybrid propulsion system consisting of the battery and hydrogen fuel cells is presented based on the minimum energy consumption of the UAV. In this context, an optimization problem with non-linear constraints is constituted to determine the wing loading, aspect ratio, stall velocity, endurance velocity, battery power, fuel cell power, maximum lift coefficient, and zero-lift drag coefficient of the UAV. The solution to this optimization problem, based on the UAV’s minimum energy consumption for the endurance and cruising flight modes, is implemented by meta-heuristic algorithms: particle swarm optimization, cuckoo search algorithm, artificial bee colony, and genetic algorithm. The results of these algorithms are compared in terms of energy consumption. This article contributes to the literature on sizing fuel cell-powered small UAVs based on minimum energy consumption and comparing different metaheuristics. According to the results, the lowest power consumption of the UAV is obtained by the particle swarm optimization algorithm as 2018.63 W. Additionally, the weight ratios calculated with the parameters obtained from the sizing optimization for the UAV propulsion system components and flight stages are compared with a benchmark study in the literature. Finally, the payload weight ratio is also increased by 28.5% by sizing optimization.

This study aims to investigate common fastener implementation methods for parts manufactured with Fused Deposition Modeling (FDM). Although fastener applications for FDM manufactured parts are already in use, the effects of these methods on tensile and bending forces have not been examined. Test samples with different design techniques and infill ratios were produced using Polylactic Acid (PLA), and tensile strength and flexural and tightening torque tests were performed. Four of the of the most preferred fastener applications were studied. Two of the applications use a heat-set insert, and the other two applications use square nuts. Test samples were designed for the applications and printed with three different infill ratios. The production times and material consumption for these different applications were explained and evaluated. Different drawbacks and advantages were investigated for different applications. It has been observed that the strength of the basic heat-set inserts depends on the surface adhesion and is less affected by the filling rate. Advanced heat-set inserts adhere better to the surface, so the infill ratio is the determining factor in strength. The embedded nut methods depend on the infill ratio up to a certain load. As the load increases, the influence of wall thickness becomes increasingly evident. These findings not only contribute to enhancing structural integrity but also offer invaluable insights into optimizing connection methods for diverse applications.

As computer capabilities improve, Molecular Dynamics simulations are becoming more important for solving various flow problems. In this study, Couette and Poiseuille flows at different wall temperatures were investigated using a hard-sphere Molecular Dynamics simulation approach. Although a low spacing ratio was used in the simulations, the results are valid for rarefied gas flows when proper scaling based on the Knudsen number was used because only binary collisions with a hard-sphere model were considered. The main focus of this study was the examination of the effects of various wall speeds, pressure gradients, and wall temperatures. A pressure gradient was generated by developing a modified selective periodicity condition in the flow direction. With the combined effect of the pressure gradient and the wall velocities, subsonic, transonic, and supersonic speeds in nanochannels were examined. With the combination of different parameters, 1260 simulation cases were conducted. The results showed that there are temperature and velocity slips that are dependent on not only the temperature and velocity values but also on the magnitudes of a pressure gradient. The pressure gradient also caused nonlinearities in temperature and velocity profiles.