Affiliation:
1. Department of Mechanical Engineering, Istanbul Technical University, 34437 Istanbul, Turkey
2. Aircraft Department, Turkish Aerospace, 06980 Ankara, Turkey
Abstract
Jet fuel in aircraft fuel tanks moves due to acceleration resulting from maneuvers. The movement mentioned here directly impacts the Center of Gravity (CG). The aircraft’s flight mechanics are significantly affected by the deviation of its CG on the aircraft body, and excessive deviation is undesirable. Preventing CG deviation is achieved by designing various baffles within the fuel tank. In this study, design details of the baffles were investigated with the help of an artificial neural network (ANN) model, 1D simulations, and computational fluid dynamics (CFD) calculations. The 1D simulations, which model the fuel movement, were used to understand the general behavior of the fluid in the tank. CFD calculations simulating turbulent fluid flow in three dimensions were used to confirm the results of the 1D simulations and provide more detailed information. A simulation set is created utilizing five parameters: barrier usage, volume fraction, cutout diameter, number of cutouts, and cutout location. Compared to the barrierless design, the barrier usage as a parameter changes either on baffle number 1, 3, and 6, or on baffle number 2, 4, and 7. The fuel volume fraction parameter accounts for 30%, 45%, and 60% of the interior volume. The diameters of the cutout holes vary between 30 mm and 156 mm and are used as categorized among the baffles. Cutout holes are applied on baffles in single, twin, and triplet forms and their locations are subjected to a divergence of either −20 mm or +20 mm from the z-axis. Based on these parameters, the maximum deviation and the retreat time of CG constitute the output parameters. The importance of the input parameters on the outputs was obtained with the help of an ANN algorithm created from the results of all possible combinations of a sufficient number of 1D simulations. To obtain more detailed results and confirm the importance of input parameters on outputs, selected cases were simulated with CFD. As a result of all analyses, it was revealed that barrier usage is the most dominant input parameter on CG deviation followed by volume fraction, cutout hole diameter, cutout divergence, and finally, the number of cutout holes. This study identifies the dominant input parameters to control fuel sloshing, specifically CG deviation and retreat time in the fuel tank, and proposes baffle designs to promote robust flight stability.
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