Large Eddy Simulations (LES) of a novel type of wing/body junction called the anti-fairing are performed in the current thesis to study the complex turbulent flow physics involved in the junction area and also to obtain a clear understanding of the drag reduction capabilities of the anti-fairing. In regards to that, two separate LES are performed: one for the baseline case with a Rood wing/flat plate combination and another with the Rood wing/anti-fairing combination. A detailed comparative study is performed between the two cases to observe important differences in junction flow characteristics. Both the simulations are performed on a 25 million immersed boundary Cartesian mesh by solving the incompressible Navier-Stokes equations using the in-house finite volume LES solver called INCA. Results from the LES study confirms the existence of the propulsive pressure mechanism of drag reduction for the anti-fairing case, previously proposed by Belligoli et al. However, the results also show that there exists a secondary drag reduction mechanism caused by a combination of increase in approach boundary layer momentum thickness and dampening of the turbulence associated with the horseshoe vortex (HSV) upstream of the wing. This secondary mechanism has been found to be caused by the convex dent present at the start of the anti-fairing geometry. The total drag reduction for the anti-fairing case comes out to be 1.8%. A new parameter called junction drag is defined which accounts for the drag only due to the presence of a junction. The reduction in junction drag obtained for the anti-fairing case is about 6.8%. Apart from the LES analysis, a RANS analysis has also been performed to further investigate the drag reduction capabilities of anti-fairing for different approach boundary layer thicknesses and anti-fairing depths. All the RANS analysis have been performed on a 5 million body-fitted mesh by solving the incompressible Navier-Stokes using the open source finite-volume solver OpenFOAM. Results from the RANS analysis indicate that there exists an optimum depth for the anti-fairing which corresponds to the least drag. Furthermore, it is found that the effect of approach boundary layer thickness is mostly on changing the base drag of the case where no anti-fairing is present, rather than actually affecting the performance of the anti-fairing at different depths.

Wild_res have always been a problem; but, with human migration all around the world, this problem has signi_- cantly increased its importance and impact. The mounting challenges facing wild_re management, together with its increasing demand, have necessitated research into technological advancements and methods to increase wild_re management ef_cacy. As Unmanned Aerial Vehicles (UAVs) become more and more widespread, development has skyrocketed and is applied to all kinds of areas, such as surveillance, military, and commercial _lming. Fire surveillance is the area of interest for this project. The main goal of this report is to offer a concise overview of the preliminary design of the _re monitoring swarm system. This report will touch upon the main problems encountered while working on the design and the solutions of these problems. The report ends with some recommendations for the future. Forest _res happen all over Europe; however, the Mediterranean region is most affected by these forest _res. Combined with global warming, the occurrence of forest _res will increase, which will lead to an increase of the annual economic and environmental damage caused by these _res. Both _re _ghters and operational centres have been searching for years to effectively combat forest _res, thereby minimising the damage done by forest _res. Different systems have been used in the past, some as simple as _re lookout towers and some as complex as optical-based smoke detection systems. However, none of these systems has been able to provide real-time data to _re_ghters. This is where this _re monitoring swarm comes into play. The swarm system is composed of a searching and a tracking element. The searching element has 5 Penguin B UAVs and has two operating modes. The _rst mode is detection of _res and con_rming upon detection, while the second mode consists of acting as a mothership for that speci_c _re. The tracking element has 10 Albatross UAVs which can perform three functions, namely high altitude tracking; low altitude tracking; and scouting. Members of the swarm will have a communication system for communication among swarm members and for communication with the operational centres. All UAVs will be launched using a catapult and are capable of a fully autonomous landing...