Delaunay Graph Based Inverse Distance Weighting for Fast Dynamic Meshing - Volume 21 Issue 5 - Yibin Wang, Ning Qin, Ning Zhao

By using an array of pressure sensors distributed on the surface of an aircraft to measure the pressure of each port, the flush airdata sensing (FADS) system is widely applied in many modern aircraft and unmanned aerial vehicles (UAVs). Normally, the pressure transducers of the FADS system should be mounted on the leading edge of the aircraft, where they are sensitive to changes in pressure. For UAVs, however, the leading edge of the nose and wing may not be available for pressure transducers. In addition, the number of transducers is limited to 8–10, making it difficult to maintain accuracy in the normal method for FADS systems. An FADS system model for an unmanned flying wing was developed, and the pressure transducers were all located outside the regions of the leading edge areas. The locations of the transducers were selected by using the mean impact value (MIV), and ensemble neural networks were developed to predict the airdata with a very limited number of transducers. Furthermore, an error detection method was also developed based on artificial neural networks and random forests. The FADS system model can accurately detect the malfunctioning port and use the correct pressure combination to predict the Mach number, angle of attack, and angle of sideslip with high accuracy.

A novel mesh deformation technique is developed based on the Delaunay graph mapping method and the inverse distance weighting (IDW) interpolation. The algorithm maintains the advantages of the efficiency of Delaunay-graph-mapping mesh deformation while possess the ability for better controlling the near surface mesh quality. The Delaunay graph is used to divide the mesh domain into a number of sub-domains. On each of the sub-domains, the inverse distance weighting interpolation is applied to build a much smaller sized translation matrix between the original mesh and the deformed mesh, resulting a similar efficiency for the mesh deformation as compared to the fast Delaunay graph mapping method. The paper will show how the near-wall mesh quality is controlled and improved by the new method while the computational time is compared with the original Delaunay graph mapping method.

A CFD-based constrained three-component aerodynamic-trim procedure is implemented to investigate the load balance and coupled flowfield response of a simplified shipborne helicopter hovering over a flight deck. During the unsteady CFD calculation, the collective and cyclic pitch controls are updated according to the period-averaged vertical force and the rolling and pitching moments of the helicopter center of gravity. A pre-trim initialization is introduced before the formal-trim process to avoid large pitch corrections from the initial fixed-pitch state. Under a 20 m/s headwind, the initial fixed-pitch case shows a vertical-force deficit and extra rolling and pitching moments. After dynamic trim, the pitch controls converge to ${\theta }_0=8.46°$, $A_1=-2.48°$, and $B_1=1.20°$. Over the final one-revolution interval of approximately t = 31.74–32.00 s, the period-averaged loads are $F_z=112.82 \mathrm{k}\mathrm{N}$, $M_x=-0.06 \mathrm{k}\mathrm{N}·\mathrm{m}$, and $M_y=-0.07 \mathrm{k}\mathrm{N}·\mathrm{m}$. Additional +30° and −30° oblique-wind calculations confirm convergence toward the prescribed three-component load targets under asymmetric inflow conditions. The instantaneous flowfield comparisons suggest local responses in the rotor-inflow and fuselage-pressure regions after trim. Frequency-domain analysis identifies a dominant blade-passing-frequency component together with additional low-frequency content characteristic of the coupled rotor–ship aerodynamic response.