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Journal Article

Assessment of Advanced SGS Models for LES Analysis of ICE Wall-Bounded Flows - Part I: Basic Test Case

Large Eddy Simulation (LES) represents nowadays one of the most promising techniques for the evaluation of the dynamics and evolution of turbulent structures characterizing internal combustion engines (ICE). In the present paper, subdivided into two parts, the capabilities of the open-source CFD code OpenFOAM® v2.3.0 are assessed in order to evaluate its suitability for engine cold flow LES analyses. Firstly, the code dissipative attitude is evaluated through an inviscid vortex convection test to ensure that the levels of numerical dissipation are compatible with LES needs. Quality and completeness estimators for LES simulations are then proposed. In particular the Pope M parameter is used as a LES completeness indicator while the LSR parameter provides useful insights far calibrating the grid density. Other parameters such as the two-grid LESIQk index are also discussed.
Technical Paper

CFRP Crash Absorbers in Small UAV: Design and Optimization

The high number of hull losses is a main concern in the UAV field, mostly due to the high cost of on-board equipment. A crashworthiness design can be helpful to control the extent and position of crash impact damage, minimizing equipment losses. However, the wide use of composite materials has recently put the accent on the lack of data about the behavior of these structures under operative loads, such as the crash conditions. This paper presents the outcome of a set of tests carried out to achieve a controlled crush of UAV structures, and to maximize the Specific Energy Absorption. In this work, a small-scale experimental test able to characterize the energy absorption of a Carbon-fiber-reinforced polymer under compression was developed introducing self-supporting sinusoidal shape specimens, which avoid the need for complex anti-buckling devices.
Technical Paper

Image Processing Based Air Vehicles Classification for UAV Sense and Avoid Systems

The maturity reached in the development of Unmanned Air Vehicles (UAVs) systems is making them more and more attractive for a vast number of civil missions. Clearly, the introduction of UAVs in the civil airspace requiring practical and effective regulation is one of the most critical issues being currently discussed. As several civil air authorities report in their regulations “Sense and Avoid” or “Detect and Avoid” capabilities are critical to the successful integration of UAV into the civil airspace. One possible approach to achieve this capability, specifically for operations beyond the Line-of-Sight, would be to equip air vehicles with a vision-based system using cameras to monitor the surrounding air space and to classify other air vehicles flying in close proximity. This paper presents an image-based application for the supervised classification of air vehicles.