Abstract: The main objective of aircraft aerodynamics is to
enhance the aerodynamic characteristics and maneuverability of the
aircraft. This enhancement includes the reduction in drag and stall
phenomenon. The airfoil which contains dimples will have
comparatively less drag than the plain airfoil. Introducing dimples on
the aircraft wing will create turbulence by creating vortices which
delays the boundary layer separation resulting in decrease of pressure
drag and also increase in the angle of stall. In addition, wake
reduction leads to reduction in acoustic emission. The overall
objective of this paper is to improve the aircraft maneuverability by
delaying the flow separation point at stall and thereby reducing the
drag by applying the dimple effect over the aircraft wing. This project
includes both computational and experimental analysis of dimple
effect on aircraft wing, using NACA 0018 airfoil. Dimple shapes of
Semi-sphere, hexagon, cylinder, square are selected for the analysis;
airfoil is tested under the inlet velocity of 30m/s and 60m/s at
different angle of attack (5˚, 10˚, 15˚, 20˚, and 25˚). This analysis
favors the dimple effect by increasing L/D ratio and thereby
providing the maximum aerodynamic efficiency, which provides the
enhanced performance for the aircraft.
Abstract: In this study acoustic emission (AE) signals obtained during deformation and fracture of two types of ferrite-martensite dual phase steels (DPS) specimens have been analyzed in frequency domain. For this reason two low carbon steels with various amounts of carbon were chosen, and intercritically heat treated. In the introduced method, identifying the mechanisms of failure in the various phases of DPS is done. For this aim, AE monitoring has been used during tensile test of several DPS with various volume fraction of the martensite (VM) and attempted to relate the AE signals and failure mechanisms in these steels. Different signals, which referred to 2-3 micro-mechanisms of failure due to amount of carbon and also VM have been seen. By Fast Fourier Transformation (FFT) of signals in distinct locations, an excellent relationship between peak frequencies in these areas and micro-mechanisms of failure were seen. The results were verified by microscopic observations (SEM).